diff --git a/baselines/add_prohibited_processes_to_es.json b/baselines/add_prohibited_processes_to_es.json index ee79213c42..c8986fd0c8 100644 --- a/baselines/add_prohibited_processes_to_es.json +++ b/baselines/add_prohibited_processes_to_es.json @@ -1,46 +1,46 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain | fillnull value=false is_required is_secure | fillnull value=true is_prohibited | outputlookup interesting_processes_lookup | stats count" - } - }, - "creation_date": "2017-06-27", - "data_metadata": { - "data_models": [], - "data_source": [ - "Splunk Enterprise" - ], - "providing_technologies": [ - "Splunk Enterprise Security" - ] - }, - "description": "This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints.", - "eli5": "This search outputs the interesting processes lookup table and filters out all processes in the table that haven't already been inserted by ESCU. It then appends to those results all the processes currently identified by ESCU that should be prohibited. Next, it fills in the required fields with processes identified by ESCU, and then writes the results back to the interesting process lookup table. This is done so any new processes identified that should be prohibited will be added to the lookup table without creating any duplicate entries.", - "how_to_implement": "This search should be run on each new install of ESCU.", - "id": "251930a5-1451-4428-bb13-eed5775be0ce", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain | fillnull value=false is_required is_secure | fillnull value=true is_prohibited | outputlookup interesting_processes_lookup | stats count" + } + }, + "creation_date": "2017-06-27", + "data_metadata": { + "data_models": [], + "data_source": [ + "Splunk Enterprise" ], - "modification_date": "2017-09-15", - "name": "Add Prohibited Processes to Enterprise Security", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Enterprise Security" + ] + }, + "description": "This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints.", + "eli5": "This search outputs the interesting processes lookup table and filters out all processes in the table that haven't already been inserted by ESCU. It then appends to those results all the processes currently identified by ESCU that should be prohibited. Next, it fills in the required fields with processes identified by ESCU, and then writes the results back to the interesting process lookup table. This is done so any new processes identified that should be prohibited will be added to the lookup table without creating any duplicate entries.", + "how_to_implement": "This search should be run on each new install of ESCU.", + "id": "251930a5-1451-4428-bb13-eed5775be0ce", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-15", + "name": "Add Prohibited Processes to Enterprise Security", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/approved_aws_service_accounts.json b/baselines/approved_aws_service_accounts.json index a98a8efb28..e953c0c583 100644 --- a/baselines/approved_aws_service_accounts.json +++ b/baselines/approved_aws_service_accounts.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail errorCode=success | rename userName as identity | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count by identity | table identity | outputlookup aws_service_accounts | stats count" - } - }, - "creation_date": "2018-03-12", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into aws_service_accounts.csv lookup file.", - "eli5": "We first look for all successful CloudTrail API activity caused by types of user accounts and then remove all the events caused by users in the Identity table. This generates a list of accounts--typically service accounts--configured in your AWS environment. We output this list of service accounts to aws_service_accounts.csv.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in aws_service_accounts.csv, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate.", - "id": "fc0edc95-ff2b-48b1-5f6f-63ga3789fd43", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail errorCode=success | rename userName as identity | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count by identity | table identity | outputlookup aws_service_accounts | stats count" + } + }, + "creation_date": "2018-03-12", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-12-03", - "name": "Create a list of approved AWS service accounts", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file.", + "eli5": "We first look for all successful CloudTrail API activity caused by types of user accounts and then remove all the events caused by users in the Identity table. This generates a list of accounts--typically service accounts--configured in your AWS environment. We output this list of service accounts to `aws_service_accounts.csv`.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in `aws_service_accounts.csv`, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate.", + "id": "fc0edc95-ff2b-48b1-5f6f-63ga3789fd43", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-12-03", + "name": "Create a list of approved AWS service accounts", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/baselines/assets_sorted_by_category.json b/baselines/assets_sorted_by_category.json index 00052bb67e..7b1005a87c 100644 --- a/baselines/assets_sorted_by_category.json +++ b/baselines/assets_sorted_by_category.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| from datamodel Identity_Management.All_Assets | stats count values(nt_host) by category | sort -count" - } - }, - "creation_date": "2017-06-11", - "data_metadata": { - "data_models": [ - "Identity_Management" - ], - "data_source": [ - "Splunk Enterprise Security" - ], - "providing_technologies": [ - "Splunk Enterprise Security" - ] - }, - "description": "This search shows you every asset category you have and the assets that belong to those categories.", - "eli5": "This search gives you the number and the names of the hosts of each host in your environment by category. It will then sort them by the count.", - "how_to_implement": "To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated.", - "id": "dcfd6b40-42f9-469d-a433-2e53f7489ff9", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| from datamodel Identity_Management.All_Assets | stats count values(nt_host) by category | sort -count" + } + }, + "creation_date": "2017-06-11", + "data_metadata": { + "data_models": [ + "Identity_Management" ], - "modification_date": "2017-09-13", - "name": "Count of assets by category", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_source": [ + "Splunk Enterprise Security" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Enterprise Security" + ] + }, + "description": "This search shows you every asset category you have and the assets that belong to those categories.", + "eli5": "This search gives you the number and the names of the hosts of each host in your environment by category. It will then sort them by the count.", + "how_to_implement": "To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated.", + "id": "dcfd6b40-42f9-469d-a433-2e53f7489ff9", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-13", + "name": "Count of assets by category", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/baseline_api_calls_per_user_arn.json b/baselines/baseline_api_calls_per_user_arn.json index b4e8f4edb7..152fe0892f 100644 --- a/baselines/baseline_api_calls_per_user_arn.json +++ b/baselines/baseline_api_calls_per_user_arn.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-90d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventType=AwsApiCall | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count" - } - }, - "creation_date": "2018-04-09", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly.", - "eli5": "This search returns all log events that are API calls, pulls out the ARN that initiated each call, and collects them in one-hour groupings. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points each ARN had. This table is then stored in a lookup file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", - "id": "fc0edc96-ff2b-48b0-9f6f-63da3783fd63", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-90d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventType=AwsApiCall | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count" + } + }, + "creation_date": "2018-04-09", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-04-09", - "name": "Baseline of API Calls per User ARN", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly.", + "eli5": "This search returns all log events that are API calls, pulls out the ARN that initiated each call, and collects them in one-hour groupings. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points each ARN had. This table is then stored in a lookup file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", + "id": "fc0edc96-ff2b-48b0-9f6f-63da3783fd63", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-04-09", + "name": "Baseline of API Calls per User ARN", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/baseline_aws_regions.json b/baselines/baseline_aws_regions.json index 94969d273b..b4a5004258 100644 --- a/baselines/baseline_aws_regions.json +++ b/baselines/baseline_aws_regions.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | stats count" - } - }, - "creation_date": "2018-01-08", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days", - "eli5": "In this support search, we create a table of the first time (earliest) and most recent time (latest) that this region has been seen in our dataset, grouped by the value awsRegion. We only look for those events where an instance has been started. All of these entries will be added to the previously_seen_aws_regions.csv lookup file, which will act like a baseline for detections. Please validate the entries of region names in the lookup file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd63", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | stats count" + } + }, + "creation_date": "2018-01-08", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-01-08", - "name": "Previously Seen AWS Regions", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days", + "eli5": "In this support search, we create a table of the first time (earliest) and most recent time (latest) that this region has been seen in our dataset, grouped by the value `awsRegion`. We only look for those events where an instance has been started. All of these entries will be added to the `previously_seen_aws_regions.csv` lookup file, which will act like a baseline for detections. Please validate the entries of region names in the lookup file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd63", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-01-08", + "name": "Previously Seen AWS Regions", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/baseline_blocked_vpc_traffic.json b/baselines/baseline_blocked_vpc_traffic.json index 993b00f884..95529d8e88 100644 --- a/baselines/baseline_blocked_vpc_traffic.json +++ b/baselines/baseline_blocked_vpc_traffic.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | stats count as numberOfBlockedConnections by _time, src_ip | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) as latestCount, avg(numberOfBlockedConnections) as avgBlockedConnections, stdev(numberOfBlockedConnections) as stdevBlockedConnections by src_ip | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | stats count" - } - }, - "creation_date": "2018-04-26", - "data_metadata": { - "data_source": [ - "AWS VPC Flow Logs" - ], - "data_sourcetypes": [ - "aws:cloudwatchlogs:vpcflow" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly.", - "eli5": "Use this search to create a baseline of blocked outbound network connections by each source IP in your AWS environment. This search returns all log events that correspond to a blocked outbound network connection, extracts the source IP from where the outbound connection was initiated, and collects the events in one-hour groupings. Next, it calculates the number of outbound connections blocked per hour. For each source IP, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points each source IP had. This table is then stored in a lookup file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your VPC flow logs..", - "id": "fc0edd96-ff2b-48b0-9f1f-63da3782fd63", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | stats count as numberOfBlockedConnections by _time, src_ip | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) as latestCount, avg(numberOfBlockedConnections) as avgBlockedConnections, stdev(numberOfBlockedConnections) as stdevBlockedConnections by src_ip | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | stats count" + } + }, + "creation_date": "2018-04-26", + "data_metadata": { + "data_source": [ + "AWS VPC Flow Logs" ], - "modification_date": "2018-05-07", - "name": "Baseline of blocked outbound traffic from AWS", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_sourcetypes": [ + "aws:cloudwatchlogs:vpcflow" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly.", + "eli5": "Use this search to create a baseline of blocked outbound network connections by each source IP in your AWS environment. This search returns all log events that correspond to a blocked outbound network connection, extracts the source IP from where the outbound connection was initiated, and collects the events in one-hour groupings. Next, it calculates the number of outbound connections blocked per hour. For each source IP, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points each source IP had. This table is then stored in a lookup file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`.", + "id": "fc0edd96-ff2b-48b0-9f1f-63da3782fd63", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-05-07", + "name": "Baseline of blocked outbound traffic from AWS", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/baseline_network_acl_modifications.json b/baselines/baseline_network_acl_modifications.json index cb80dffc6d..91537ce651 100644 --- a/baselines/baseline_network_acl_modifications.json +++ b/baselines/baseline_network_acl_modifications.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail `NetworkACLEvents` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats count" - } - }, - "creation_date": "2018-05-21", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly.", - "eli5": "Use this search to create a baseline for API calls related to network ACLs for the users who initiated this activity. It returns all logged API calls for network activity, pulls out the ARN that initiated each call, and collects the eventNames in one-hour groupings. Next, it calculates the number of API calls made per ARN per-hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro NetworkACLEvents.", - "id": "fc0edd96-ff2b-4810-9f1f-63da3783fd63", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail `NetworkACLEvents` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats count" + } + }, + "creation_date": "2018-05-21", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-05-21", - "name": "Baseline of Network ACL Activity by ARN", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly.", + "eli5": "Use this search to create a baseline for API calls related to network ACLs for the users who initiated this activity. It returns all logged API calls for network activity, pulls out the ARN that initiated each call, and collects the `eventNames` in one-hour groupings. Next, it calculates the number of API calls made per ARN per-hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `NetworkACLEvents`.", + "id": "fc0edd96-ff2b-4810-9f1f-63da3783fd63", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-05-21", + "name": "Baseline of Network ACL Activity by ARN", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/baseline_s3_deletion_by_arn.json b/baselines/baseline_s3_deletion_by_arn.json index 04e2fb067c..abe331b629 100644 --- a/baselines/baseline_s3_deletion_by_arn.json +++ b/baselines/baseline_s3_deletion_by_arn.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-90d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=DeleteBucket | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count" - } - }, - "creation_date": "2018-07-17", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly.", - "eli5": "Use this search to create a baseline for API calls related to deleting an S3 bucket, grouped by the users who initiated this activity. It returns all logged API calls for S3 bucket-deletion activity and then pulls out the ARN that initiated each call. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", - "id": "fc0edd96-ff2b-48b0-9f1f-63eq3783fd63", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-90d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=DeleteBucket | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count" + } + }, + "creation_date": "2018-07-17", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-07-17", - "name": "Baseline of S3 Bucket deletion activity by ARN", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly.", + "eli5": "Use this search to create a baseline for API calls related to deleting an S3 bucket, grouped by the users who initiated this activity. It returns all logged API calls for S3 bucket-deletion activity and then pulls out the ARN that initiated each call. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", + "id": "fc0edd96-ff2b-48b0-9f1f-63eq3783fd63", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-07-17", + "name": "Baseline of S3 Bucket deletion activity by ARN", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/baseline_security_group_activity_by_arn.json b/baselines/baseline_security_group_activity_by_arn.json index 216d1bb484..31b26e38fc 100644 --- a/baselines/baseline_security_group_activity_by_arn.json +++ b/baselines/baseline_security_group_activity_by_arn.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-90d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail `securityGroupAPIs` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | stats count" - } - }, - "creation_date": "2018-04-17", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly.", - "eli5": "Use this search to create a baseline for API calls related to security groups by the users who initiated this activity. It returns all logged API calls for all security-group-related activity, pulls out the ARN that initiated each call, and collects the eventNames in one-hour groupings. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro securityGroupAPIs.", - "id": "fc0edd96-ff2b-48b0-9f1f-63da3783fd63", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-90d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail `securityGroupAPIs` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | stats count" + } + }, + "creation_date": "2018-04-17", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-04-17", - "name": "Baseline of Security Group Activity by ARN", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly.", + "eli5": "Use this search to create a baseline for API calls related to security groups by the users who initiated this activity. It returns all logged API calls for all security-group-related activity, pulls out the ARN that initiated each call, and collects the `eventNames` in one-hour groupings. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `securityGroupAPIs`.", + "id": "fc0edd96-ff2b-48b0-9f1f-63da3783fd63", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-04-17", + "name": "Baseline of Security Group Activity by ARN", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/brand_abuse_dnstwist_domains.json b/baselines/brand_abuse_dnstwist_domains.json index 1b75237220..5f241aaa71 100644 --- a/baselines/brand_abuse_dnstwist_domains.json +++ b/baselines/brand_abuse_dnstwist_domains.json @@ -1,45 +1,45 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domain_abuse=\"true\" | table domain, domain_abuse | outputlookup brandMonitoring_lookup | stats count" - } - }, - "creation_date": "2017-06-01", - "data_metadata": { - "data_source": [ - "Splunk Enterprise Security Content Update" - ], - "providing_technologies": [ - "Splunk Enterprise" - ] - }, - "description": "This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches.", - "eli5": "This search starts with the dnstwist command consuming domains from a file called domains.csv in the DA-ESS-SOC/lookups directory. This search then adds a domain\\_abuse=true term to each permutation, removes all the valid domain names and stores all that information into a lookup file that is used in the associated detection search. Alternatively domain dnstwist permutations can be calculated from domains in the `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` lookups located in **Splunk\\_SA\\_CIM** using argument `populate_from_cim=true`. Also an individual domain can be passed using argument `domain=`", - "how_to_implement": "To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\\_SA\\_CIM**.", - "id": "19f7d2ec-6028-4d01-bcdb-bda9a034c17f", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domain_abuse=\"true\" | table domain, domain_abuse | outputlookup brandMonitoring_lookup | stats count" + } + }, + "creation_date": "2017-06-01", + "data_metadata": { + "data_source": [ + "Splunk Enterprise Security Content Update" ], - "modification_date": "2018-10-08", - "name": "DNSTwist Domain Names", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Enterprise" + ] + }, + "description": "This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches.", + "eli5": "This search starts with the dnstwist command consuming domains from a file called domains.csv in the DA-ESS-SOC/lookups directory. This search then adds a domain\\_abuse=true term to each permutation, removes all the valid domain names and stores all that information into a lookup file that is used in the associated detection search. Alternatively domain dnstwist permutations can be calculated from domains in the `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` lookups located in **Splunk\\_SA\\_CIM** using argument `populate_from_cim=true`. Also an individual domain can be passed using argument `domain=`", + "how_to_implement": "To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\\_SA\\_CIM**.", + "id": "19f7d2ec-6028-4d01-bcdb-bda9a034c17f", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "modification_date": "2018-10-08", + "name": "DNSTwist Domain Names", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/baselines/discover_dns_records.json b/baselines/discover_dns_records.json index 47d35cdb66..12d187b4f7 100644 --- a/baselines/discover_dns_records.json +++ b/baselines/discover_dns_records.json @@ -1,53 +1,53 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "0 0 1 * *", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| inputlookup cim_corporate_email_domains.csv | inputlookup append=T cim_corporate_web_domains.csv | inputlookup append=T cim_cloud_domains.csv | eval domain = trim(replace(domain, \"\\*\", \"\")) | join domain [|tstats summariesonly=true count values(DNS.record_type) as type, values(DNS.answer) as answer from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!=\"unknown\" DNS.answer!=\"\" by DNS.query | rename DNS.query as query | where query!=\"unknown\" | rex field=query \"(?\\w+\\.\\w+?)(?:$|/)\"] | makemv delim=\" \" answer | makemv delim=\" \" type | sort -count | table count,domain,type,query,answer | outputlookup createinapp=true discovered_dns_records.csv" - } - }, - "creation_date": "2019-02-14", - "data_metadata": { - "data_models": [ - "Network_Resolution" - ], - "data_source": [ - "Network Communication" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup", - "eli5": "Discover the DNS records and their answers for domains owned by the company using network traffic events. The discovered events are exported as a lookup named `discovered_dns_records.csv`", - "entities": [ - "query", - "answer" + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "0 0 1 * *", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| inputlookup cim_corporate_email_domains.csv | inputlookup append=T cim_corporate_web_domains.csv | inputlookup append=T cim_cloud_domains.csv | eval domain = trim(replace(domain, \"\\*\", \"\")) | join domain [|tstats summariesonly=true count values(DNS.record_type) as type, values(DNS.answer) as answer from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!=\"unknown\" DNS.answer!=\"\" by DNS.query | rename DNS.query as query | where query!=\"unknown\" | rex field=query \"(?\\w+\\.\\w+?)(?:$|/)\"] | makemv delim=\" \" answer | makemv delim=\" \" type | sort -count | table count,domain,type,query,answer | outputlookup createinapp=true discovered_dns_records.csv" + } + }, + "creation_date": "2019-02-14", + "data_metadata": { + "data_models": [ + "Network_Resolution" ], - "how_to_implement": "To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation", - "id": "c096f721-8842-42ce-bfc7-74bd8c72b7c3", - "known_false_positives": "Please vet the lookup created by this baseline search ", - "maintainers": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } + "data_source": [ + "Network Communication" ], - "modification_date": "2019-02-14", - "name": "Discover DNS records", - "original_authors": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup", + "eli5": "Discover the DNS records and their answers for domains owned by the company using network traffic events. The discovered events are exported as a lookup named `discovered_dns_records.csv`", + "entities": [ + "query", + "answer" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation", + "id": "c096f721-8842-42ce-bfc7-74bd8c72b7c3", + "known_false_positives": "Please vet the lookup created by this baseline search ", + "maintainers": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "modification_date": "2019-02-14", + "name": "Discover DNS records", + "original_authors": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/identify_ports_on_network.json b/baselines/identify_ports_on_network.json index 56d0b8c175..28e036380b 100644 --- a/baselines/identify_ports_on_network.json +++ b/baselines/identify_ports_on_network.json @@ -1,49 +1,49 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count dc(All_Traffic.src) as numberOfUniqueHosts from datamodel=Network_Traffic by All_Traffic.dest_port | `drop_dm_object_name(\"All_Traffic\")` | sort - count" - } - }, - "creation_date": "2017-06-24", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communication" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them.", - "eli5": "For each port being accessed on the network, this search gives the total number of connections observed, and the number of unique IP addresses making those connections.", - "how_to_implement": "To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model.", - "id": "9f3bae5a-9fe3-49df-8c84-5edc51d84b7f", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count dc(All_Traffic.src) as numberOfUniqueHosts from datamodel=Network_Traffic by All_Traffic.dest_port | `drop_dm_object_name(\"All_Traffic\")` | sort - count" + } + }, + "creation_date": "2017-06-24", + "data_metadata": { + "data_models": [ + "Network_Traffic" ], - "modification_date": "2017-09-13", - "name": "Count of Unique IPs Connecting to Ports", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_source": [ + "Network Communication" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them.", + "eli5": "For each port being accessed on the network, this search gives the total number of connections observed, and the number of unique IP addresses making those connections.", + "how_to_implement": "To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model.", + "id": "9f3bae5a-9fe3-49df-8c84-5edc51d84b7f", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-13", + "name": "Count of Unique IPs Connecting to Ports", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/identify_systems_creating_rdp_traffic.json b/baselines/identify_systems_creating_rdp_traffic.json index a7f5931478..408597e6e8 100644 --- a/baselines/identify_systems_creating_rdp_traffic.json +++ b/baselines/identify_systems_creating_rdp_traffic.json @@ -1,49 +1,49 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.src | `drop_dm_object_name(\"All_Traffic\")` | sort - count" - } - }, - "creation_date": "2017-04-24", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communication" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "This search counts the numbers of times the system has generated remote desktop traffic.", - "eli5": "This search counts the numbers of times the system has tried to connect to another system on TCP/3389, the default port used for RDP traffic.", - "how_to_implement": "To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model.", - "id": "5cdda34f-4caf-4128-a713-0837fc48b67a", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.src | `drop_dm_object_name(\"All_Traffic\")` | sort - count" + } + }, + "creation_date": "2017-04-24", + "data_metadata": { + "data_models": [ + "Network_Traffic" ], - "modification_date": "2017-09-15", - "name": "Identify Systems Creating Remote Desktop Traffic", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_source": [ + "Network Communication" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search counts the numbers of times the system has generated remote desktop traffic.", + "eli5": "This search counts the numbers of times the system has tried to connect to another system on TCP/3389, the default port used for RDP traffic.", + "how_to_implement": "To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model.", + "id": "5cdda34f-4caf-4128-a713-0837fc48b67a", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-15", + "name": "Identify Systems Creating Remote Desktop Traffic", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/identify_systems_receiving_rdp_traffic.json b/baselines/identify_systems_receiving_rdp_traffic.json index f495c1e698..89ff03a0a2 100644 --- a/baselines/identify_systems_receiving_rdp_traffic.json +++ b/baselines/identify_systems_receiving_rdp_traffic.json @@ -1,49 +1,49 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.dest | `drop_dm_object_name(\"All_Traffic\")` | sort - count" - } - }, - "creation_date": "2017-04-24", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communication" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "This search counts the numbers of times the system has created remote desktop traffic", - "eli5": "This search counts the numbers of times the system has received a connection to TCP/ 3389, the default port used for RDP traffic.", - "how_to_implement": "To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it.", - "id": "baaeea15-fe8a-4090-92c2-5b60943bb608", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.dest | `drop_dm_object_name(\"All_Traffic\")` | sort - count" + } + }, + "creation_date": "2017-04-24", + "data_metadata": { + "data_models": [ + "Network_Traffic" ], - "modification_date": "2017-09-15", - "name": "Identify Systems Receiving Remote Desktop Traffic", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_source": [ + "Network Communication" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search counts the numbers of times the system has created remote desktop traffic", + "eli5": "This search counts the numbers of times the system has received a connection to TCP/ 3389, the default port used for RDP traffic.", + "how_to_implement": "To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it.", + "id": "baaeea15-fe8a-4090-92c2-5b60943bb608", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-15", + "name": "Identify Systems Receiving Remote Desktop Traffic", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/identify_systems_using_remote_desktop.json b/baselines/identify_systems_using_remote_desktop.json index 1f02ce6af1..ea84998bbb 100644 --- a/baselines/identify_systems_using_remote_desktop.json +++ b/baselines/identify_systems_using_remote_desktop.json @@ -1,52 +1,52 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count from datamodel=Endpoint.Processes where Processes.process_name=\"*mstsc.exe*\" by Processes.dest Processes.process_name | `drop_dm_object_name(Processes)` | sort - count" - } - }, - "creation_date": "2017-04-18", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] - }, - "description": "This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system.", - "eli5": "This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. It does this by looking for the process name in the Endpoint data model.", - "how_to_implement": "To successfully implement this search you must be ingesting endpoint data that records process activity.", - "id": "063dfe9f-b1d7-4254-a16d-1e2e7eadd6a8", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count from datamodel=Endpoint.Processes where Processes.process_name=\"*mstsc.exe*\" by Processes.dest Processes.process_name | `drop_dm_object_name(Processes)` | sort - count" + } + }, + "creation_date": "2017-04-18", + "data_metadata": { + "data_models": [ + "Endpoint" ], - "modification_date": "2019-04-01", - "name": "Identify Systems Using Remote Desktop", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_source": [ + "Endpoint Intel" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system.", + "eli5": "This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. It does this by looking for the process name in the Endpoint data model.", + "how_to_implement": "To successfully implement this search you must be ingesting endpoint data that records process activity.", + "id": "063dfe9f-b1d7-4254-a16d-1e2e7eadd6a8", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2019-04-01", + "name": "Identify Systems Using Remote Desktop", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/monitor_successful_backups.json b/baselines/monitor_successful_backups.json index 9036498df4..f5fd1907d2 100644 --- a/baselines/monitor_successful_backups.json +++ b/baselines/monitor_successful_backups.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=\"netbackup_logs\" \"Disk/Partition backup completed successfully.\" | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE" - } - }, - "creation_date": "2017-08-24", - "data_metadata": { - "data_source": [ - "Backup Logs" - ], - "data_sourcetypes": [ - "netbackup_logs" - ], - "providing_technologies": [ - "Netbackup" - ] - }, - "description": "This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate.", - "eli5": "This search gives you the count and the hostname of all the systems that had a successful backup each day.", - "how_to_implement": "To successfully implement this search you must be ingesting your backup logs.", - "id": "b4d0dfb2-2195-4f6e-93a3-48468ed9734e", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=\"netbackup_logs\" \"Disk/Partition backup completed successfully.\" | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE" + } + }, + "creation_date": "2017-08-24", + "data_metadata": { + "data_source": [ + "Backup Logs" ], - "modification_date": "2017-09-12", - "name": "Monitor Successful Backups", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_sourcetypes": [ + "netbackup_logs" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Netbackup" + ] + }, + "description": "This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate.", + "eli5": "This search gives you the count and the hostname of all the systems that had a successful backup each day.", + "how_to_implement": "To successfully implement this search you must be ingesting your backup logs.", + "id": "b4d0dfb2-2195-4f6e-93a3-48468ed9734e", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-12", + "name": "Monitor Successful Backups", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/monitor_successful_windows_updates.json b/baselines/monitor_successful_windows_updates.json index 98d54572af..b785afd6df 100644 --- a/baselines/monitor_successful_windows_updates.json +++ b/baselines/monitor_successful_windows_updates.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product=\"Microsoft Windows\" AND Updates.status=installed by _time span=1d" - } - }, - "creation_date": "2017-08-24", - "data_metadata": { - "data_models": [ - "Updates" - ], - "data_source": [ - "Windows Updates" - ], - "providing_technologies": [ - "Microsoft Windows" - ] - }, - "description": "This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned.", - "eli5": "This search gives you the count and name of all the systems that had a successful update applied each day", - "how_to_implement": "You must be ingesting your Windows Update Logs", - "id": "6a80535c-86a6-4b54-894c-4b446d0c701d", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product=\"Microsoft Windows\" AND Updates.status=installed by _time span=1d" + } + }, + "creation_date": "2017-08-24", + "data_metadata": { + "data_models": [ + "Updates" ], - "modification_date": "2017-09-14", - "name": "Windows Updates Install Successes", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_source": [ + "Windows Updates" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned.", + "eli5": "This search gives you the count and name of all the systems that had a successful update applied each day", + "how_to_implement": "You must be ingesting your Windows Update Logs", + "id": "6a80535c-86a6-4b54-894c-4b446d0c701d", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-14", + "name": "Windows Updates Install Successes", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/monitor_unsuccessful_backups.json b/baselines/monitor_unsuccessful_backups.json index a011d43e28..d10a0684de 100644 --- a/baselines/monitor_unsuccessful_backups.json +++ b/baselines/monitor_unsuccessful_backups.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=\"netbackup_logs\" \"An error occurred, failed to backup.\" | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE" - } - }, - "creation_date": "2017-08-24", - "data_metadata": { - "data_source": [ - "Backup Logs" - ], - "data_sourcetypes": [ - "netbackup_logs" - ], - "providing_technologies": [ - "Netbackup" - ] - }, - "description": "This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate.", - "eli5": "This search gives you the count and hostname of all the systems that had a backup failure each day", - "how_to_implement": "To successfully implement this search you must be ingesting your backup logs.", - "id": "b2178fed-592f-492b-b851-74161678aa56", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=\"netbackup_logs\" \"An error occurred, failed to backup.\" | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE" + } + }, + "creation_date": "2017-08-24", + "data_metadata": { + "data_source": [ + "Backup Logs" ], - "modification_date": "2017-09-12", - "name": "Monitor Unsuccessful Backups", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_sourcetypes": [ + "netbackup_logs" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Netbackup" + ] + }, + "description": "This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate.", + "eli5": "This search gives you the count and hostname of all the systems that had a backup failure each day", + "how_to_implement": "To successfully implement this search you must be ingesting your backup logs.", + "id": "b2178fed-592f-492b-b851-74161678aa56", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-12", + "name": "Monitor Unsuccessful Backups", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/monitor_unsuccessful_windows_updates.json b/baselines/monitor_unsuccessful_windows_updates.json index f4ef93b159..3f13b9535c 100644 --- a/baselines/monitor_unsuccessful_windows_updates.json +++ b/baselines/monitor_unsuccessful_windows_updates.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product=\"Microsoft Windows\" AND Updates.status=failure by _time span=1d" - } - }, - "creation_date": "2017-08-24", - "data_metadata": { - "data_models": [ - "Updates" - ], - "data_source": [ - "Windows Updates" - ], - "providing_technologies": [ - "Microsoft Windows" - ] - }, - "description": "This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned.", - "eli5": "This search gives you the count of the number of systems that attempted and failed to install a Windows update each day.", - "how_to_implement": "You must be ingesting your Windows Update Logs", - "id": "6a4dbd1b-4502-4a11-943a-82b5ae7a42d7", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product=\"Microsoft Windows\" AND Updates.status=failure by _time span=1d" + } + }, + "creation_date": "2017-08-24", + "data_metadata": { + "data_models": [ + "Updates" ], - "modification_date": "2017-09-14", - "name": "Windows Updates Install Failures", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_source": [ + "Windows Updates" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned.", + "eli5": "This search gives you the count of the number of systems that attempted and failed to install a Windows update each day.", + "how_to_implement": "You must be ingesting your Windows Update Logs", + "id": "6a4dbd1b-4502-4a11-943a-82b5ae7a42d7", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-14", + "name": "Windows Updates Install Failures", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/previously_seen_aws_cross_account_activity.json b/baselines/previously_seen_aws_cross_account_activity.json index f59869c9bd..3458c0c83e 100644 --- a/baselines/previously_seen_aws_cross_account_activity.json +++ b/baselines/previously_seen_aws_cross_account_activity.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats count" - } - }, - "creation_date": "2018-06-04", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for AssumeRole events where the requesting account differs from the requested account, then writes these relationships to a lookup file.", - "eli5": "In this support search, we look for AssumeRole events where the requesting account is different from the requested account. The first and last times these events are seen are written to a lookup file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in previously_seen_aws_cross_account_activity.csv, a lookup file created by this support search.", - "id": "1cc22b09-c867-416e-a511-cb36ac44aee2", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats count" + } + }, + "creation_date": "2018-06-04", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-06-04", - "name": "Previously Seen AWS Cross Account Activity", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file.", + "eli5": "In this support search, we look for **AssumeRole** events where the requesting account is different from the requested account. The first and last times these events are seen are written to a lookup file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search.", + "id": "1cc22b09-c867-416e-a511-cb36ac44aee2", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-06-04", + "name": "Previously Seen AWS Cross Account Activity", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/previously_seen_aws_users.json b/baselines/previously_seen_aws_users.json index 331060b9a4..cd5ee90271 100644 --- a/baselines/previously_seen_aws_users.json +++ b/baselines/previously_seen_aws_users.json @@ -1,62 +1,62 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "0 0 1 * *", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE \"\",src,City),Region=if(Region LIKE \"\",src,Region) | stats earliest(_time) as earliest latest(_time) as latest by user src City Region Country | outputlookup previously_seen_users_console_logins.csv | stats count" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "0 0 1 * *", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE \"\",src,City),Region=if(Region LIKE \"\",src,Region) | stats earliest(_time) as earliest latest(_time) as latest by user src City Region Country | outputlookup previously_seen_users_console_logins.csv | stats count" + } + }, + "creation_date": "2018-02-23", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days.", + "eli5": "In this support search, we look for console login events by a particular user and create an initial baseline cache for the previous 30 days, including the earliest and latest times, City, Region, and Country a particular user ARN is seen in our dataset, grouped by the ARN value. In cases where City and Region cannot be determined, the source IP address is substituted for these values.", + "entities": [ + "user", + "src" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search.", + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", + "known_false_positives": "n/a", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" }, - "creation_date": "2018-02-23", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "modification_date": "2018-04-30", + "name": "Previously seen users in CloudTrail", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" }, - "description": "This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days.", - "eli5": "In this support search, we look for console login events by a particular user and create an initial baseline cache for the previous 30 days, including the earliest and latest times, City, Region, and Country a particular user ARN is seen in our dataset, grouped by the ARN value. In cases where City and Region cannot be determined, the source IP address is substituted for these values.", - "entities": [ - "user", - "src" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in previously_seen_users_console_logins.csv, which is a lookup file created as a result of running this support search.", - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", - "known_false_positives": "n/a", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" - } - ], - "modification_date": "2018-04-30", - "name": "Previously seen users in CloudTrail", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.1" -} \ No newline at end of file + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.1" +} diff --git a/baselines/previously_seen_cmd_arguments.json b/baselines/previously_seen_cmd_arguments.json index b01249c289..d41c14a3af 100644 --- a/baselines/previously_seen_cmd_arguments.json +++ b/baselines/previously_seen_cmd_arguments.json @@ -1,52 +1,52 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = \"* /c *\" by Processes.process | `drop_dm_object_name(Processes)`" - } - }, - "creation_date": "2018-04-09", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] - }, - "description": "This search looks for command-line arguments where cmd.exe /c is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days.", - "eli5": "In this support search, we look for command-line arguments using the parameter /c to execute processes and create an initial baseline cache for the previous 30 days. This will include the earliest and latest times a particular command-line argument is seen in our dataset, grouped by the command-line value.", - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd23", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = \"* /c *\" by Processes.process | `drop_dm_object_name(Processes)`" + } + }, + "creation_date": "2018-04-09", + "data_metadata": { + "data_models": [ + "Endpoint" ], - "modification_date": "2019-03-01", - "name": "Previously seen command line arguments", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_source": [ + "Endpoint Intel" ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days.", + "eli5": "In this support search, we look for command-line arguments using the parameter `/c` to execute processes and create an initial baseline cache for the previous 30 days. This will include the earliest and latest times a particular command-line argument is seen in our dataset, grouped by the command-line value.", + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd23", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2019-03-01", + "name": "Previously seen command line arguments", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/baselines/previously_seen_ec2_amis.json b/baselines/previously_seen_ec2_amis.json index 7e91953e47..0dfafcb99a 100644 --- a/baselines/previously_seen_ec2_amis.json +++ b/baselines/previously_seen_ec2_amis.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-90d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) as earliest latest(_time) as latest by amiID | outputlookup previously_seen_ec2_amis.csv | stats count" - } - }, - "creation_date": "2018-03-12", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search builds a table of previously seen AMIs used to launch EC2 instances", - "eli5": "In this support search, we create a table of the earliest and latest time that a specific AMI ID has been seen. This table is then outputted to a csv file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", - "id": "bb1bd99d-1e93-45f1-9571-cfed42d372b9", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-90d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) as earliest latest(_time) as latest by amiID | outputlookup previously_seen_ec2_amis.csv | stats count" + } + }, + "creation_date": "2018-03-12", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-03-12", - "name": "Previously Seen EC2 AMIs", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search builds a table of previously seen AMIs used to launch EC2 instances", + "eli5": "In this support search, we create a table of the earliest and latest time that a specific AMI ID has been seen. This table is then outputted to a csv file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", + "id": "bb1bd99d-1e93-45f1-9571-cfed42d372b9", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-12", + "name": "Previously Seen EC2 AMIs", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/previously_seen_ec2_instance_types.json b/baselines/previously_seen_ec2_instance_types.json index 7b81c1fc86..97ef6f5439 100644 --- a/baselines/previously_seen_ec2_instance_types.json +++ b/baselines/previously_seen_ec2_instance_types.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-90d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename requestParameters.instanceType as instanceType | fillnull value=\"m1.small\" instanceType | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | stats count" - } - }, - "creation_date": "2018-03-08", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search builds a table of previously seen EC2 instance types", - "eli5": "In this support search, we create a table of the earliest and latest time that a specific EC2 instance type has been seen. The instanceType request field is not required and defaults to m1.small, so any time this field is null, the search defaults the field to m1.small. This table is then outputted to a csv file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", - "id": "b8f029f2-65a6-4d76-be98-dad1c9d59c45", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-90d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename requestParameters.instanceType as instanceType | fillnull value=\"m1.small\" instanceType | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | stats count" + } + }, + "creation_date": "2018-03-08", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-03-08", - "name": "Previously Seen EC2 Instance Types", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search builds a table of previously seen EC2 instance types", + "eli5": "In this support search, we create a table of the earliest and latest time that a specific EC2 instance type has been seen. The instanceType request field is not required and defaults to m1.small, so any time this field is null, the search defaults the field to m1.small. This table is then outputted to a csv file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", + "id": "b8f029f2-65a6-4d76-be98-dad1c9d59c45", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-08", + "name": "Previously Seen EC2 Instance Types", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/previously_seen_ec2_launches_by_user.json b/baselines/previously_seen_ec2_launches_by_user.json index dbbe50409f..115dea3185 100644 --- a/baselines/previously_seen_ec2_launches_by_user.json +++ b/baselines/previously_seen_ec2_launches_by_user.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-90d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count" - } - }, - "creation_date": "2018-03-15", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search builds a table of previously seen ARNs that have launched a EC2 instance.", - "eli5": "In this support search, we create a table of the earliest and latest times that an ARN has launched a EC2 instance. This table is then outputted to a csv file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", - "id": "6c767ac0-0906-4355-9a83-927f5ee7bdad", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-90d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count" + } + }, + "creation_date": "2018-03-15", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-03-15", - "name": "Previously Seen EC2 Launches By User", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search builds a table of previously seen ARNs that have launched a EC2 instance.", + "eli5": "In this support search, we create a table of the earliest and latest times that an ARN has launched a EC2 instance. This table is then outputted to a csv file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs.", + "id": "6c767ac0-0906-4355-9a83-927f5ee7bdad", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-15", + "name": "Previously Seen EC2 Launches By User", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/previously_seen_ec2_modifications.json b/baselines/previously_seen_ec2_modifications.json index 3b5e0cee3e..413308c04d 100644 --- a/baselines/previously_seen_ec2_modifications.json +++ b/baselines/previously_seen_ec2_modifications.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-90d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail `ec2ModificationAPIs` errorCode=success | spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats count" - } - }, - "creation_date": "2018-04-05", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search builds a table of previously seen ARNs that have launched a EC2 instance.", - "eli5": "In this support search, we create a table of the earliest and latest times that an ARN has modified a EC2 instance. The list of APIs that modify an EC2 are defined in the ec2ModificationAPIs macro for ease of use. This table is then outputted to a file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro ec2ModificationAPIs.", - "id": "4d69091b-d975-4267-85df-888bd41034eb", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-90d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail `ec2ModificationAPIs` errorCode=success | spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats count" + } + }, + "creation_date": "2018-04-05", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-04-05", - "name": "Previously Seen EC2 Modifications By User", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search builds a table of previously seen ARNs that have launched a EC2 instance.", + "eli5": "In this support search, we create a table of the earliest and latest times that an ARN has modified a EC2 instance. The list of APIs that modify an EC2 are defined in the `ec2ModificationAPIs` macro for ease of use. This table is then outputted to a file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2ModificationAPIs`.", + "id": "4d69091b-d975-4267-85df-888bd41034eb", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-04-05", + "name": "Previously Seen EC2 Modifications By User", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/previously_seen_provisioning_activity_src.json b/baselines/previously_seen_provisioning_activity_src.json index 2ab698c066..5d52ac7b7f 100644 --- a/baselines/previously_seen_provisioning_activity_src.json +++ b/baselines/previously_seen_provisioning_activity_src.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-90d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats count" - } - }, - "creation_date": "2018-03-16", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something.", - "eli5": "This search includes any event name that begins with \"run\" or \"create,\" and then determines the first and last time these events were seen for each IP address that initiated the action. The search then consults a GeoIP database to determine the physical location of this IP address. This table outputs to a file.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-90d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats count" + } + }, + "creation_date": "2018-03-16", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-03-16", - "name": "Previously Seen AWS Provisioning Activity Sources", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something.", + "eli5": "This search includes any event name that begins with \"run\" or \"create,\" and then determines the first and last time these events were seen for each IP address that initiated the action. The search then consults a **GeoIP** database to determine the physical location of this IP address. This table outputs to a file.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-16", + "name": "Previously Seen AWS Provisioning Activity Sources", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/previously_seen_s3_remote_ip.json b/baselines/previously_seen_s3_remote_ip.json index c5b2ffc404..bb0034dcaf 100644 --- a/baselines/previously_seen_s3_remote_ip.json +++ b/baselines/previously_seen_s3_remote_ip.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:s3:accesslogs http_status=200 | stats earliest(_time) as earliest latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip | stats count" - } - }, - "creation_date": "2018-06-28", - "data_metadata": { - "data_source": [ - "AWS S3 Access logs" - ], - "data_sourcetypes": [ - "aws:s3:accesslogs" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is \"200\"", - "eli5": "In this support search, we are looking for successful S3 bucket-access attempts made from remote IPs. The intent is to create an initial baseline cache of remote IP addresses per bucket name for the previous 30 days--including the earliest and latest times seen in our dataset--grouped by the value of remote IP and the name of the S3 bucket.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in previously_seen_S3_access_from_remote_ip.csv, which is a lookup file created as a result of running this support search.", - "id": "fc0edc15-fq2c-48b0-9f6f-63qa1281fd03", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:s3:accesslogs http_status=200 | stats earliest(_time) as earliest latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip | stats count" + } + }, + "creation_date": "2018-06-28", + "data_metadata": { + "data_source": [ + "AWS S3 Access logs" ], - "modification_date": "2018-06-28", - "name": "Previously seen S3 bucket access by remote IP", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_sourcetypes": [ + "aws:s3:accesslogs" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is \"200\"", + "eli5": "In this support search, we are looking for successful S3 bucket-access attempts made from remote IPs. The intent is to create an initial baseline cache of remote IP addresses per bucket name for the previous 30 days--including the earliest and latest times seen in our dataset--grouped by the value of remote IP and the name of the S3 bucket.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search.", + "id": "fc0edc15-fq2c-48b0-9f6f-63qa1281fd03", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-06-28", + "name": "Previously seen S3 bucket access by remote IP", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/previously_seen_user_roles.json b/baselines/previously_seen_user_roles.json index 8005ce8033..e68c7af412 100644 --- a/baselines/previously_seen_user_roles.json +++ b/baselines/previously_seen_user_roles.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles | stats count" - } - }, - "creation_date": "2018-04-01", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role.", - "eli5": "In this support search, we are looking for successful API calls made by user roles within your AWS infrastructure. The intent is to create an initial baseline cache of names of the API calls per security role for the previous 30 days--including the earliest and latest times seen in our dataset--grouped by the value of user role and the name of the API call. It is also worth noting that the role of a particular user is parsed as \"userName\" in the CloudTrail logs.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in previously_seen_api_calls_from_user_roles.csv, which is a lookup file created as a result of running this support search.", - "id": "fc0edc95-fq2c-48b0-9f6f-63da3289fd03", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles | stats count" + } + }, + "creation_date": "2018-04-01", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2018-04-16", - "name": "Previously seen API call per user roles in CloudTrail", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role.", + "eli5": "In this support search, we are looking for successful API calls made by user roles within your AWS infrastructure. The intent is to create an initial baseline cache of names of the API calls per security role for the previous 30 days--including the earliest and latest times seen in our dataset--grouped by the value of user role and the name of the API call. It is also worth noting that the role of a particular user is parsed as \"userName\" in the CloudTrail logs.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search.", + "id": "fc0edc95-fq2c-48b0-9f6f-63da3289fd03", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-04-16", + "name": "Previously seen API call per user roles in CloudTrail", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/previously_seen_windows_service_starts.json b/baselines/previously_seen_windows_service_starts.json index db4da1795e..7c200a56b5 100644 --- a/baselines/previously_seen_windows_service_starts.json +++ b/baselines/previously_seen_windows_service_starts.json @@ -1,48 +1,48 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "eventtype=wineventlog_system signature_id=7036 | rex field=Message \"The (?[\\w\\s-]*) service entered the (?\\w*) state\" | where action=\"running\" | stats earliest(_time) as firstTime, latest(_time) as lastTime by serviceName | outputlookup previously_seen_running_windows_services | stats count" - } - }, - "creation_date": "2018-07-20", - "data_metadata": { - "data_eventtypes": [ - "wineventlog_system" - ], - "data_source": [ - "Windows Event Logs" - ], - "providing_technologies": [ - "Microsoft Windows" - ] - }, - "description": "This collects the services that have been started across your entire enterprise.", - "eli5": "In this support search, we look for Windows system-event code that indicates a status change of a Windows service. It extracts both the name of the service and the action taken by the service from the logs. It keeps only services that have entered the running state. Finally, it finds the first time the service has been seen running across the enterprise and writes that file to a lookup table.", - "how_to_implement": "While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully.", - "id": "64ce0ade-cb01-4678-bddd-d31c0b175394", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "eventtype=wineventlog_system signature_id=7036 | rex field=Message \"The (?[\\w\\s-]*) service entered the (?\\w*) state\" | where action=\"running\" | stats earliest(_time) as firstTime, latest(_time) as lastTime by serviceName | outputlookup previously_seen_running_windows_services | stats count" + } + }, + "creation_date": "2018-07-20", + "data_metadata": { + "data_eventtypes": [ + "wineventlog_system" ], - "modification_date": "2019-02-27", - "name": "Previously Seen Running Windows Services", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_source": [ + "Windows Event Logs" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This collects the services that have been started across your entire enterprise.", + "eli5": "In this support search, we look for Windows system-event code that indicates a status change of a Windows service. It extracts both the name of the service and the action taken by the service from the logs. It keeps only services that have entered the running state. Finally, it finds the first time the service has been seen running across the enterprise and writes that file to a lookup table.", + "how_to_implement": "While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully.", + "id": "64ce0ade-cb01-4678-bddd-d31c0b175394", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2019-02-27", + "name": "Previously Seen Running Windows Services", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/systems_ready_for_spectre_meltdown_patch.json b/baselines/systems_ready_for_spectre_meltdown_patch.json index 4117e97030..196af25042 100644 --- a/baselines/systems_ready_for_spectre_meltdown_patch.json +++ b/baselines/systems_ready_for_spectre_meltdown_patch.json @@ -1,52 +1,52 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-1d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path=\"HKLM\\Software\\Microsoft\\Windows\\CurrentVersion\\QualityCompat*\") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `ctime(lastTime)` | `ctime(firstTime)` | `drop_dm_object_name(\"All_Changes\")`" - } - }, - "creation_date": "2018-01-08", - "data_metadata": { - "data_models": [ - "Change_Analysis" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] - }, - "description": "Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown.", - "eli5": "This search looks to see if a registry key was created at HKLM\\Software\\Microsoft\\Windows\\CurrentVersion\\QualityCompat. It will tell you when it was created and, if possible, what process created it.", - "how_to_implement": "You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.", - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd61", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-1d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path=\"HKLM\\Software\\Microsoft\\Windows\\CurrentVersion\\QualityCompat*\") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `ctime(lastTime)` | `ctime(firstTime)` | `drop_dm_object_name(\"All_Changes\")`" + } + }, + "creation_date": "2018-01-08", + "data_metadata": { + "data_models": [ + "Change_Analysis" ], - "modification_date": "2018-01-08", - "name": "Systems Ready for Spectre-Meltdown Windows Patch", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "data_source": [ + "Endpoint Intel" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown.", + "eli5": "This search looks to see if a registry key was created at `HKLM\\Software\\Microsoft\\Windows\\CurrentVersion\\QualityCompat`. It will tell you when it was created and, if possible, what process created it.", + "how_to_implement": "You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.", + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd61", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-01-08", + "name": "Systems Ready for Spectre-Meltdown Windows Patch", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/train_dns_query_length.json b/baselines/train_dns_query_length.json index 77a4444c91..1c044535c2 100644 --- a/baselines/train_dns_query_length.json +++ b/baselines/train_dns_query_length.json @@ -1,49 +1,49 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-31d@d", - "latest_time": "-1d@d" - }, - "search": "| tstats `summariesonly` count from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(\"DNS\")` | eval query_length = len(query) | fit DensityFunction query_length by record_type into dns_query_pdfmodel" - } - }, - "creation_date": "2019-05-08", - "data_metadata": { - "data_models": [ - "Network_Resolution" - ], - "data_source": [ - "DNS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query.", - "eli5": "Create a machine-learning (ML) model to characterize the length of DNS requests seen in your environment to help identify unusually long ones that may be indicative of attacker infrastrucutre or the use of DNS as a command-and-control channel in your environment.", - "how_to_implement": "To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", - "id": "c914844c-0ff5-4efc-8d44-c063443129ba", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-31d@d", + "latest_time": "-1d@d" + }, + "search": "| tstats `summariesonly` count from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(\"DNS\")` | eval query_length = len(query) | fit DensityFunction query_length by record_type into dns_query_pdfmodel" + } + }, + "creation_date": "2019-05-08", + "data_metadata": { + "data_models": [ + "Network_Resolution" ], - "modification_date": "2019-05-08", - "name": "Baseline of DNS Query Length - MLTK", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + "data_source": [ + "DNS" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query.", + "eli5": "Create a machine-learning (ML) model to characterize the length of DNS requests seen in your environment to help identify unusually long ones that may be indicative of attacker infrastrucutre or the use of DNS as a command-and-control channel in your environment.", + "how_to_implement": "To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", + "id": "c914844c-0ff5-4efc-8d44-c063443129ba", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2019-05-08", + "name": "Baseline of DNS Query Length - MLTK", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/train_smb_traffic_spike.json b/baselines/train_smb_traffic_spike.json index e18a07e23d..8b2dc1692c 100644 --- a/baselines/train_smb_traffic_spike.json +++ b/baselines/train_smb_traffic_spike.json @@ -1,49 +1,49 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-31d@d", - "latest_time": "-1d@d" - }, - "search": "| tstats `summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=10m, All_Traffic.src | eval HourOfDay=strftime(_time, \"%H\") | eval DayOfWeek=strftime(_time, \"%A\") | `drop_dm_object_name(\"All_Traffic\")` | fit DensityFunction count by \"HourOfDay,DayOfWeek\" into smb_pdfmodel" - } - }, - "creation_date": "2019-05-08", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communications" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week.", - "eli5": "Create a machine-learning (ML) model to characterize the number of SMB connections observed in your environment. This may help identify spikes in SMB traffic that may be indicative of attackers scanning or attempting to propagate to other systems in your environment. By default, this model is built over 30 days of data and profiles the number of SMB connections in your environment by the hour of day/day of week that the connections occur.", - "how_to_implement": "You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding \"src\" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", - "id": "df98763b-0b08-4281-8ef9-08db7ac572a9", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-31d@d", + "latest_time": "-1d@d" + }, + "search": "| tstats `summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=10m, All_Traffic.src | eval HourOfDay=strftime(_time, \"%H\") | eval DayOfWeek=strftime(_time, \"%A\") | `drop_dm_object_name(\"All_Traffic\")` | fit DensityFunction count by \"HourOfDay,DayOfWeek\" into smb_pdfmodel" + } + }, + "creation_date": "2019-05-08", + "data_metadata": { + "data_models": [ + "Network_Traffic" ], - "modification_date": "2019-05-08", - "name": "Baseline of SMB Traffic - MLTK", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + "data_source": [ + "Network Communications" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week.", + "eli5": "Create a machine-learning (ML) model to characterize the number of SMB connections observed in your environment. This may help identify spikes in SMB traffic that may be indicative of attackers scanning or attempting to propagate to other systems in your environment. By default, this model is built over 30 days of data and profiles the number of SMB connections in your environment by the hour of day/day of week that the connections occur.", + "how_to_implement": "You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding \"src\" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", + "id": "df98763b-0b08-4281-8ef9-08db7ac572a9", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2019-05-08", + "name": "Baseline of SMB Traffic - MLTK", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/train_unusually_long_commandlines.json b/baselines/train_unusually_long_commandlines.json index 45daaf545e..06bc4112e8 100644 --- a/baselines/train_unusually_long_commandlines.json +++ b/baselines/train_unusually_long_commandlines.json @@ -1,52 +1,52 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "", - "earliest_time": "-31d@d", - "latest_time": "-1d@d" - }, - "search": "| tstats `summariesonly` count min(_time) as start_time max(_time) as end_time FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | search user!=unknown | `ctime(start_time)`| `ctime(end_time)`| eval processlen=len(process) | fit DensityFunction processlen by user into cmdline_pdfmodel" - } - }, - "creation_date": "2019-05-08", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] - }, - "description": "This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line.", - "eli5": "Create a machine-learning (ML) model to characterize the length of the command lines used in your environment. This can help you identify unusually long ones that may indicate that attackers are executing commands on yout systems.", - "how_to_implement": "You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", - "id": "d2a4d85b-fc6a-47a0-82f6-bc1ec2ebc459", - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "", + "earliest_time": "-31d@d", + "latest_time": "-1d@d" + }, + "search": "| tstats `summariesonly` count min(_time) as start_time max(_time) as end_time FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | search user!=unknown | `ctime(start_time)`| `ctime(end_time)`| eval processlen=len(process) | fit DensityFunction processlen by user into cmdline_pdfmodel" + } + }, + "creation_date": "2019-05-08", + "data_metadata": { + "data_models": [ + "Endpoint" ], - "modification_date": "2019-05-08", - "name": "Baseline of Command Line Length - MLTK", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + "data_source": [ + "Endpoint Intel" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line.", + "eli5": "Create a machine-learning (ML) model to characterize the length of the command lines used in your environment. This can help you identify unusually long ones that may indicate that attackers are executing commands on yout systems.", + "how_to_implement": "You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", + "id": "d2a4d85b-fc6a-47a0-82f6-bc1ec2ebc459", + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2019-05-08", + "name": "Baseline of Command Line Length - MLTK", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/baselines/update_previously_seen_aws_users.json b/baselines/update_previously_seen_aws_users.json index cd9315f411..6e1b833fed 100644 --- a/baselines/update_previously_seen_aws_users.json +++ b/baselines/update_previously_seen_aws_users.json @@ -1,52 +1,52 @@ { - "baseline": { - "splunk": { - "schedule": { - "cron_schedule": "0 0 1 * *", - "earliest_time": "-60m@m", - "latest_time": "m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE \"\",src,City),Region=if(Region LIKE \"\",src,Region) | stats earliest(_time) AS earliest latest(_time) AS latest by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user src City Region Country | outputlookup previously_seen_users_console_logins.csv" - } - }, - "creation_date": "2019-04-25", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour.", - "eli5": "In this support search, we look for console login events by a particular user to update the baseline cache of users/arns making the accesses, including the earliest and latest times, City, Region, and Country a particular user ARN is seen in our dataset, grouped by the ARN value. In cases where City and Region cannot be determined, the source IP address is substituted for these values.", - "entities": [ - "user", - "src" + "baseline": { + "splunk": { + "schedule": { + "cron_schedule": "0 0 1 * *", + "earliest_time": "-60m@m", + "latest_time": "m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE \"\",src,City),Region=if(Region LIKE \"\",src,Region) | stats earliest(_time) AS earliest latest(_time) AS latest by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user src City Region Country | outputlookup previously_seen_users_console_logins.csv" + } + }, + "creation_date": "2019-04-25", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in previously_seen_users_console_logins.csv, which is a lookup file created as a result of running this support search.", - "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", - "known_false_positives": "n/a", - "maintainers": [ - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "modification_date": "2018-04-30", - "name": "Update previously seen users in CloudTrail", - "original_authors": [ - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour.", + "eli5": "In this support search, we look for console login events by a particular user to update the baseline cache of users/arns making the accesses, including the earliest and latest times, City, Region, and Country a particular user ARN is seen in our dataset, grouped by the ARN value. In cases where City and Region cannot be determined, the source IP address is substituted for these values.", + "entities": [ + "user", + "src" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search.", + "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", + "known_false_positives": "n/a", + "maintainers": [ + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "modification_date": "2018-04-30", + "name": "Update previously seen users in CloudTrail", + "original_authors": [ + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/abnormally_high_instance_termination.json b/detections/abnormally_high_instance_termination.json index 6513b0c4b7..3291e964f8 100644 --- a/detections/abnormally_high_instance_termination.json +++ b/detections/abnormally_high_instance_termination.json @@ -42,7 +42,7 @@ } } }, - "eli5": "In this search, we query CloudTrail logs to look for events where an instance is successfully terminated by a particular user. Since we want to detect a high number of instances terminated within a short period, we create event buckets for 10-minute windows. We then calculate the total number of instances terminated by a particular user, as well as the average- and standard-deviation values. Assign a threshold_value in the search. Try starting with 3 (but it will likely need to be tweaked for your environment). The eval function will set the outlier to 1 if the number of instances is greater than the average number of instances terminated, added to the multiplied value of threshold and standard deviation. We then filter out outliers with a value of 1 and show only those instance-termination events that happened within the previous 10 minutes.", + "eli5": "In this search, we query CloudTrail logs to look for events where an instance is successfully terminated by a particular user. Since we want to detect a high number of instances terminated within a short period, we create event buckets for 10-minute windows. We then calculate the total number of instances terminated by a particular user, as well as the average- and standard-deviation values. Assign a `threshold_value` in the search. Try starting with 3 (but it will likely need to be tweaked for your environment). The `eval` function will set the outlier to 1 if the number of instances is greater than the average number of instances terminated, added to the multiplied value of threshold and standard deviation. We then filter out outliers with a value of 1 and show only those instance-termination events that happened within the previous 10 minutes.", "entities": [ "userName" ], diff --git a/detections/abnormally_high_instances_launched.json b/detections/abnormally_high_instances_launched.json index 25cd90cab4..f54eec86ff 100644 --- a/detections/abnormally_high_instances_launched.json +++ b/detections/abnormally_high_instances_launched.json @@ -42,7 +42,7 @@ } } }, - "eli5": "In this search, we query CloudTrail logs to look for events where an instance is successfully launched by a particular user. Since we want to detect a high number of instances launched within a short period, we create event buckets for 10-minute windows. We then calculate the total number of instances launched by a particular user, as well as the average and standard deviation values. Assign a threshold_value in the search. Start with 3 (but it will likely need to be tweaked for your environment). The eval function will set the outlier 1 if the number of instances is greater than the average number of instances terminated, added to the multiplied value of threshold and standard deviation. For your reference, we then keep only the outliers and calculate the number of standard deviations away the value is from the average.", + "eli5": "In this search, we query CloudTrail logs to look for events where an instance is successfully launched by a particular user. Since we want to detect a high number of instances launched within a short period, we create event buckets for 10-minute windows. We then calculate the total number of instances launched by a particular user, as well as the average and standard deviation values. Assign a `threshold_value` in the search. Start with 3 (but it will likely need to be tweaked for your environment). The `eval` function will set the outlier 1 if the number of instances is greater than the average number of instances terminated, added to the multiplied value of threshold and standard deviation. For your reference, we then keep only the outliers and calculate the number of standard deviations away the value is from the average.", "entities": [ "userName" ], diff --git a/detections/add_to_untrust_cert_store.json b/detections/add_to_untrust_cert_store.json index 51cabae0aa..2f238ee0cb 100644 --- a/detections/add_to_untrust_cert_store.json +++ b/detections/add_to_untrust_cert_store.json @@ -1,139 +1,139 @@ { - "asset_type": "Endpoint", - "confidence": "high", - "creation_date": "2018-04-09", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "high", + "creation_date": "2018-04-09", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "Attempt to add a certificate to the untrusted certificate store", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process_name", + "rule_description": "Attempt to add a certificate to the untrusted certificate store", + "rule_title": "Attempt To Add Certificate to Untrusted Store" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`|`ctime(lastTime)`", + "suppress": { + "suppress_fields": "process, dest", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "Attackers will often attempt to disable security tools in order to evade detection. It is also possible for end users to attempt to disable anti-virus or other security tools to circumvent restrictions they encounter while trying to execute other programs. One way malware may accomplish this is by adding the legitimate certificate used to sign the security software to the untrusted certificate store. This will cause the system to no longer trust the software signed with this certificate and disallow it from executing. This search simply looks for the execution of **certutil.exe** with the parameters `-addcert` and `disallowed`, which add a certification to the \"untrusted\" certificate store.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "6bc5243e-ef36-45dc-9b12-f4a6be131159", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "Attempt to add a certificate to the untrusted certificate store", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process_name", - "rule_description": "Attempt to add a certificate to the untrusted certificate store", - "rule_title": "Attempt To Add Certificate to Untrusted Store" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`|`ctime(lastTime)`", - "suppress": { - "suppress_fields": "process, dest", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "Attackers will often attempt to disable security tools in order to evade detection. It is also possible for end users to attempt to disable anti-virus or other security tools to circumvent restrictions they encounter while trying to execute other programs. One way malware may accomplish this is by adding the legitimate certificate used to sign the security software to the untrusted certificate store. This will cause the system to no longer trust the software signed with this certificate and disallow it from executing. This search simply looks for the execution of certutil.exe with the parameters -addcert and disallowed, which add a certification to the \"untrusted\" certificate store.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "6bc5243e-ef36-45dc-9b12-f4a6be131159", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 5", - "CIS 8" - ], - "kill_chain_phases": [ - "Installation", - "Actions on Objectives" - ], - "mitre_attack": [ - "Defense Evasion", - "Disabling Security Tools" - ], - "nist": [ - "PR.PT", - "DE.CM", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-15", - "name": "Attempt To Add Certificate To Untrusted Store", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 5", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "4.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Installation", + "Actions on Objectives" + ], + "mitre_attack": [ + "Defense Evasion", + "Disabling Security Tools" + ], + "nist": [ + "PR.PT", + "DE.CM", + "PR.IP" + ] + }, + "modification_date": "2018-11-15", + "name": "Attempt To Add Certificate To Untrusted Store", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "4.0" +} diff --git a/detections/api_acitivity_from_previously_unseen_user_role.json b/detections/api_acitivity_from_previously_unseen_user_role.json index b283b34b4b..d4ca26413e 100644 --- a/detections/api_acitivity_from_previously_unseen_user_role.json +++ b/detections/api_acitivity_from_previously_unseen_user_role.json @@ -20,7 +20,7 @@ "AWS" ] }, - "description": "This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is AssumedRole.", + "description": "This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`.", "detect": { "splunk": { "correlation_rule": { @@ -49,7 +49,7 @@ } } }, - "eli5": "The subsearch will execute first and return the user roles and names of the API calls completed within the last hour, where the type of user identity is AssumedRole. It then appends the historical data to those results in the lookup file. Next, it recalculates the earliest and latest fields for each user role, as well as the name of the API call, and returns only those roles and API calls that have first been seen in the past hour. This is combined with the main search to return the values of API calls, name of the user role, and the earliest and latest time of this activity. It is worth noting that the name of the role of a particular user is parsed as \"userName\" in the CloudTrail logs.", + "eli5": "The subsearch will execute first and return the user roles and names of the API calls completed within the last hour, where the type of user identity is `AssumedRole`. It then appends the historical data to those results in the lookup file. Next, it recalculates the `earliest` and `latest` fields for each user role, as well as the name of the API call, and returns only those roles and API calls that have first been seen in the past hour. This is combined with the main search to return the values of API calls, name of the user role, and the earliest and latest time of this activity. It is worth noting that the name of the role of a particular user is parsed as \"userName\" in the CloudTrail logs.", "entities": [ "user" ], diff --git a/detections/attrib_to_hide_files.json b/detections/attrib_to_hide_files.json index e767915586..0fd76de1a7 100644 --- a/detections/attrib_to_hide_files.json +++ b/detections/attrib_to_hide_files.json @@ -1,134 +1,134 @@ { - "asset_type": "", - "confidence": "medium", - "creation_date": "2017-10-23", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "", + "confidence": "medium", + "creation_date": "2017-10-23", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process", + "rule_description": "Attrib.exe is often used by attackers to hide malware files and directories in windows environments. This rule detects command-line arguments used to hide a file/directory", + "rule_title": "Suspicious usage of attrib.exe on $dest$ " + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "30 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`|`ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest, process", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search is looking to detect command-line execution with of attrib.exe binary with the +h flag set. The +h flag is used to hide a file.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "c77162d3-f93c-45cc-80c8-22f6b5264g9f", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process", - "rule_description": "Attrib.exe is often used by attackers to hide malware files and directories in windows environments. This rule detects command-line arguments used to hide a file/directory", - "rule_title": "Suspicious usage of attrib.exe on $dest$ " - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "30 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`|`ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest, process", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search is looking to detect command-line execution with of attrib.exe binary with the +h flag set. The +h flag is used to hide a file.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "c77162d3-f93c-45cc-80c8-22f6b5264g9f", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Some applications and users may legitimately use attrib.exe to interact with the files. ", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Defense Evasion", - "Persistence" - ], - "nist": [ - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-15", - "name": "Hiding Files And Directories With Attrib.exe", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Some applications and users may legitimately use attrib.exe to interact with the files. ", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Defense Evasion", + "Persistence" + ], + "nist": [ + "DE.CM" + ] + }, + "modification_date": "2018-11-15", + "name": "Hiding Files And Directories With Attrib.exe", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/aws_activity_from_non_approved_accounts.json b/detections/aws_activity_from_non_approved_accounts.json index a5eaf6746d..f55261d0fe 100644 --- a/detections/aws_activity_from_non_approved_accounts.json +++ b/detections/aws_activity_from_non_approved_accounts.json @@ -20,7 +20,7 @@ "AWS" ] }, - "description": "This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or aws_service_accounts.csv. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users.", + "description": "This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users.", "detect": { "splunk": { "correlation_rule": { @@ -49,11 +49,11 @@ } } }, - "eli5": "In this search, we are looking for successful API calls via CloudTrail. We filter out events triggered by known users listed in the identity_lookup_expanded lookup file and the service accounts. Once filtered out, we output a table with the event names and count, as well as the first and last time a specific user or service is detected.", + "eli5": "In this search, we are looking for successful API calls via CloudTrail. We filter out events triggered by known users listed in the `identity_lookup_expanded` lookup file and the service accounts. Once filtered out, we output a table with the event names and count, as well as the first and last time a specific user or service is detected.", "entities": [ "user" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also populate the identity_lookup_expanded lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called \"Create a list of approved AWS service accounts\": run it once every 30 days to create and validate a list of service accounts.

This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):

  • Label: AWS Event Name, Field: eventName
  • Label: First Time, Field: firstTime
  • Label: Last Time, Field: lastTime


Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also populate the `identity_lookup_expanded` lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called \"Create a list of approved AWS service accounts\": run it once every 30 days to create and validate a list of service accounts.\n\nThis search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n\n
  • **Label:** AWS Event Name, **Field:** eventName
  • **Label:** First Time, **Field:** firstTime
  • **Label:** Last Time, **Field:** lastTime
\n\nDetailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", "id": "ada0f478-84a8-4641-a3f1-d82362d4bd55", "investigations": [ { @@ -72,7 +72,7 @@ "type": "splunk" } ], - "known_false_positives": "It's likely that you'll find activity detected by users/service accounts that are not listed in the identity_lookup_expanded or aws_service_accounts.csv file. If the user is a legitimate service account, update the aws_service_accounts.csv table with that entry.", + "known_false_positives": "It's likely that you'll find activity detected by users/service accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` file. If the user is a legitimate service account, update the `aws_service_accounts.csv` table with that entry.", "maintainers": [ { "company": "Splunk", diff --git a/detections/aws_activity_in_new_region.json b/detections/aws_activity_in_new_region.json index fa80cbce40..e749dee9cc 100644 --- a/detections/aws_activity_in_new_region.json +++ b/detections/aws_activity_in_new_region.json @@ -49,7 +49,7 @@ } } }, - "eli5": "In this search, we query CloudTrail logs to look for events that indicate that an instance was started in a particular region. Using the previously_seen_aws_regions.csv lookup file created using the support search, we compare the region where this instance was started to all previously observed regions. The eval and if functions determine that the earliest times seen for this region and instance were within the last day. If a new region is detected, it will alert you with \"Instance Started in a New Region\". However, this region will be added to the list of previously_seen_aws_regions.csv. Please maintain previously_seen_aws_regions.csv", + "eli5": "In this search, we query CloudTrail logs to look for events that indicate that an instance was started in a particular region. Using the `previously_seen_aws_regions.csv` lookup file created using the support search, we compare the region where this instance was started to all previously observed regions. The `eval` and `if` functions determine that the earliest times seen for this region and instance were within the last day. If a new region is detected, it will alert you with \"Instance Started in a New Region\". However, this region will be added to the list of `previously_seen_aws_regions.csv`. Please maintain `previously_seen_aws_regions.csv`", "entities": [ "awsRegion" ], diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_city.json b/detections/aws_cloud_provisioning_from_previously_unseen_city.json index a388fa2af0..9deb91defc 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_city.json +++ b/detections/aws_cloud_provisioning_from_previously_unseen_city.json @@ -1,100 +1,100 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", - "name": "Previously Seen AWS Provisioning Activity Sources", - "type": "splunk" - } + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", + "name": "Previously Seen AWS Provisioning Activity Sources", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-03-16", + "data_metadata": { + "data_source": [ + "AWS CloudTrail" ], - "confidence": "medium", - "creation_date": "2018-03-16", - "data_metadata": { - "data_source": [ - "AWS CloudTrail" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with \"Run\" or \"Create.\" ", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src_ip, city", - "rule_description": "Your AWS infrastructure was provisioned from a city, $city$, which has never before been seen provisioning your infrastructure.", - "rule_title": "AWS Provision Activity From $city$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newCity=1 | table City] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, City, eventName, errorCode", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "14400s" - } - } - } - }, - "eli5": "The subsearch returns all events with event names that start with \"Run\" or \"Create,\" and then does a GeoIP lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the firstTime and lastTime field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the firstTime and lastTime for each city. It returns only those events from cities that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action.", - "entities": [ - "dest" + "data_sourcetypes": [ + "aws:cloudtrail" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen AWS Provisioning Activity Sources\" support search once to create a history of previously seen locations that have provisioned AWS resources.", - "id": "344a1778-0b25-490c-adb1-de8beddf59cd", - "investigations": [ - { - "id": "446ec87a-85c6-40d4-b060-bea4498281d6", - "name": "Get All AWS Activity From IP Address", - "type": "splunk" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with \"Run\" or \"Create.\" ", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src_ip, city", + "rule_description": "Your AWS infrastructure was provisioned from a city, $city$, which has never before been seen provisioning your infrastructure.", + "rule_title": "AWS Provision Activity From $city$" }, - { - "id": "0abeeb40-1255-4b68-91d1-7a7eb410c4b8", - "name": "Get All AWS Activity From City", - "type": "splunk" + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 30 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newCity=1 | table City] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, City, eventName, errorCode", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "14400s" } - ], - "known_false_positives": "This is a strictly behavioral search, so we define \"false positive\" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no \"false positives\" in a traditional sense, there is definitely lots of noise.

This search will fire any time a new city is seen in the GeoIP database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your city, there should be few false positives. If you are located in countries where the free version of MaxMind GeoIP that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 1" - ], - "nist": [ - "ID.AM" - ] + } + } + }, + "eli5": "The subsearch returns all events with event names that start with \"Run\" or \"Create,\" and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from cities that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action.", + "entities": [ + "dest" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen AWS Provisioning Activity Sources\" support search once to create a history of previously seen locations that have provisioned AWS resources.", + "id": "344a1778-0b25-490c-adb1-de8beddf59cd", + "investigations": [ + { + "id": "446ec87a-85c6-40d4-b060-bea4498281d6", + "name": "Get All AWS Activity From IP Address", + "type": "splunk" }, - "modification_date": "2018-03-16", - "name": "AWS Cloud Provisioning From Previously Unseen City", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "0abeeb40-1255-4b68-91d1-7a7eb410c4b8", + "name": "Get All AWS Activity From City", + "type": "splunk" + } + ], + "known_false_positives": "This is a strictly behavioral search, so we define \"false positive\" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no \"false positives\" in a traditional sense, there is definitely lots of noise.\n\n This search will fire any time a new city is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your city, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 1" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "nist": [ + "ID.AM" + ] + }, + "modification_date": "2018-03-16", + "name": "AWS Cloud Provisioning From Previously Unseen City", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_country.json b/detections/aws_cloud_provisioning_from_previously_unseen_country.json index 850675af29..75adecf7b2 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_country.json +++ b/detections/aws_cloud_provisioning_from_previously_unseen_country.json @@ -1,100 +1,100 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", - "name": "Previously Seen AWS Provisioning Activity Sources", - "type": "splunk" - } + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", + "name": "Previously Seen AWS Provisioning Activity Sources", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-03-16", + "data_metadata": { + "data_source": [ + "AWS CloudTrail" ], - "confidence": "medium", - "creation_date": "2018-03-16", - "data_metadata": { - "data_source": [ - "AWS CloudTrail" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with \"Run\" or \"Create.\" ", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src_ip, country", - "rule_description": "Your AWS infrastructure was provisioned from a country, $country$, which has never before been seen provisioning your infrastructure.", - "rule_title": "AWS Provision Activity From $country$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Country | eval newCountry=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newCountry=1 | table Country] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Country, eventName, errorCode", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "14400s" - } - } - } - }, - "eli5": "The subsearch returns all events with event names that start with \"Run\" or \"Create,\" and then does a GeoIP lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the firstTime and lastTime field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the firstTime and lastTime for each country. It returns only those events from countries that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action.", - "entities": [ - "dest" + "data_sourcetypes": [ + "aws:cloudtrail" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen AWS Provisioning Activity Sources\" support search once to create a history of previously seen locations that have provisioned AWS resources.", - "id": "ceb8d3d8-06cb-49eb-beaf-829526e33ff0", - "investigations": [ - { - "id": "446ec87a-85c6-40d4-b060-bea4498281d6", - "name": "Get All AWS Activity From IP Address", - "type": "splunk" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with \"Run\" or \"Create.\" ", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src_ip, country", + "rule_description": "Your AWS infrastructure was provisioned from a country, $country$, which has never before been seen provisioning your infrastructure.", + "rule_title": "AWS Provision Activity From $country$" }, - { - "id": "e763cdb9-00da-41e0-9bda-444debc9501a", - "name": "Get All AWS Activity From Country", - "type": "splunk" + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 30 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Country | eval newCountry=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newCountry=1 | table Country] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Country, eventName, errorCode", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "14400s" } - ], - "known_false_positives": "This is a strictly behavioral search, so we define \"false positive\" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no \"false positives\" in a traditional sense, there is definitely lots of noise.

This search will fire any time a new country is seen in the GeoIP database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of MaxMind GeoIP that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 1" - ], - "nist": [ - "ID.AM" - ] + } + } + }, + "eli5": "The subsearch returns all events with event names that start with \"Run\" or \"Create,\" and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each country. It returns only those events from countries that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action.", + "entities": [ + "dest" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen AWS Provisioning Activity Sources\" support search once to create a history of previously seen locations that have provisioned AWS resources.", + "id": "ceb8d3d8-06cb-49eb-beaf-829526e33ff0", + "investigations": [ + { + "id": "446ec87a-85c6-40d4-b060-bea4498281d6", + "name": "Get All AWS Activity From IP Address", + "type": "splunk" }, - "modification_date": "2018-03-16", - "name": "AWS Cloud Provisioning From Previously Unseen Country", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "e763cdb9-00da-41e0-9bda-444debc9501a", + "name": "Get All AWS Activity From Country", + "type": "splunk" + } + ], + "known_false_positives": "This is a strictly behavioral search, so we define \"false positive\" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no \"false positives\" in a traditional sense, there is definitely lots of noise.\n\n This search will fire any time a new country is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 1" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "nist": [ + "ID.AM" + ] + }, + "modification_date": "2018-03-16", + "name": "AWS Cloud Provisioning From Previously Unseen Country", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_ip.json b/detections/aws_cloud_provisioning_from_previously_unseen_ip.json index 5d8efd82d9..af35ffbc4e 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_ip.json +++ b/detections/aws_cloud_provisioning_from_previously_unseen_ip.json @@ -1,95 +1,95 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", - "name": "Previously Seen AWS Provisioning Activity Sources", - "type": "splunk" - } + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", + "name": "Previously Seen AWS Provisioning Activity Sources", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-03-16", + "data_metadata": { + "data_source": [ + "AWS CloudTrail" ], - "confidence": "medium", - "creation_date": "2018-03-16", - "data_metadata": { - "data_source": [ - "AWS CloudTrail" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with \"Run\" or \"Create.\" ", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src_ip", - "rule_description": "Your AWS infrastructure was provisioned from an IP, $src_ip$, which has never before been seen provisioning your infrastructure.", - "rule_title": "AWS Provision Activity From $src_ip$" - }, - "risk": { - "risk_object": "src_ip", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress | eval newIP=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newIP=1 | table sourceIPAddress] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, eventName, errorCode", - "suppress": { - "suppress_fields": "src_ip", - "suppress_period": "14400s" - } - } - } - }, - "eli5": "The subsearch returns all events with event names that start with \"Run\" or \"Create,\" and then does a GeoIP lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the firstTime and lastTime field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the firstTime and lastTime for each city. It returns only those events from IP addresses that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action.", - "entities": [ - "src_ip" + "data_sourcetypes": [ + "aws:cloudtrail" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen AWS Provisioning Activity Sources\" support search once to create a history of previously seen locations that have provisioned AWS resources.", - "id": "42e15012-ac14-4801-94f4-f1acbe64880b", - "investigations": [ - { - "id": "446ec87a-85c6-40d4-b060-bea4498281d6", - "name": "Get All AWS Activity From IP Address", - "type": "splunk" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with \"Run\" or \"Create.\" ", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src_ip", + "rule_description": "Your AWS infrastructure was provisioned from an IP, $src_ip$, which has never before been seen provisioning your infrastructure.", + "rule_title": "AWS Provision Activity From $src_ip$" + }, + "risk": { + "risk_object": "src_ip", + "risk_object_type": [ + "system" + ], + "risk_score": 30 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress | eval newIP=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newIP=1 | table sourceIPAddress] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, eventName, errorCode", + "suppress": { + "suppress_fields": "src_ip", + "suppress_period": "14400s" } + } + } + }, + "eli5": "The subsearch returns all events with event names that start with \"Run\" or \"Create,\" and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from IP addresses that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action.", + "entities": [ + "src_ip" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen AWS Provisioning Activity Sources\" support search once to create a history of previously seen locations that have provisioned AWS resources.", + "id": "42e15012-ac14-4801-94f4-f1acbe64880b", + "investigations": [ + { + "id": "446ec87a-85c6-40d4-b060-bea4498281d6", + "name": "Get All AWS Activity From IP Address", + "type": "splunk" + } + ], + "known_false_positives": "This is a strictly behavioral search, so we define \"false positive\" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no \"false positives\" in a traditional sense, there is definitely lots of noise.\n\n This search will fire any time a new IP address is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 1" ], - "known_false_positives": "This is a strictly behavioral search, so we define \"false positive\" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no \"false positives\" in a traditional sense, there is definitely lots of noise.

This search will fire any time a new IP address is seen in the GeoIP database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of MaxMind GeoIP that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 1" - ], - "nist": [ - "ID.AM" - ] - }, - "modification_date": "2018-03-16", - "name": "AWS Cloud Provisioning From Previously Unseen IP Address", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "nist": [ + "ID.AM" + ] + }, + "modification_date": "2018-03-16", + "name": "AWS Cloud Provisioning From Previously Unseen IP Address", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_region.json b/detections/aws_cloud_provisioning_from_previously_unseen_region.json index f8570bb801..2d71b216e6 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_region.json +++ b/detections/aws_cloud_provisioning_from_previously_unseen_region.json @@ -1,100 +1,100 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", - "name": "Previously Seen AWS Provisioning Activity Sources", - "type": "splunk" - } + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee", + "name": "Previously Seen AWS Provisioning Activity Sources", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-03-16", + "data_metadata": { + "data_source": [ + "AWS CloudTrail" ], - "confidence": "medium", - "creation_date": "2018-03-16", - "data_metadata": { - "data_source": [ - "AWS CloudTrail" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with \"Run\" or \"Create.\"", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src_ip, Region", - "rule_description": "Your AWS infrastructure was provisioned from a region, $Region$, which has never before been seen provisioning your infrastructure.", - "rule_title": "AWS Provision Activity From $region$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Region | eval newRegion=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newRegion=1 | table Region] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Region, eventName, errorCode", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "14400s" - } - } - } - }, - "eli5": "The subsearch returns all events with event names that start with \"Run\" or \"Create,\" and then does a GeoIP lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the firstTime and lastTime field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the firstTime and lastTime for each city. It returns only those events from regions that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action.", - "entities": [ - "dest" + "data_sourcetypes": [ + "aws:cloudtrail" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen AWS Provisioning Activity Sources\" support search once to create a history of previously seen locations that have provisioned AWS resources.", - "id": "7971d3df-da82-4648-a6e5-b5637bea5253", - "investigations": [ - { - "id": "446ec87a-85c6-40d4-b060-bea4498281d6", - "name": "Get All AWS Activity From IP Address", - "type": "splunk" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with \"Run\" or \"Create.\"", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src_ip, Region", + "rule_description": "Your AWS infrastructure was provisioned from a region, $Region$, which has never before been seen provisioning your infrastructure.", + "rule_title": "AWS Provision Activity From $region$" }, - { - "id": "5b794bef-1743-4f6f-804a-43915a2702ff", - "name": "Get All AWS Activity From Region", - "type": "splunk" + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 30 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Region | eval newRegion=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newRegion=1 | table Region] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Region, eventName, errorCode", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "14400s" } - ], - "known_false_positives": "This is a strictly behavioral search, so we define \"false positive\" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no \"false positives\" in a traditional sense, there is definitely lots of noise.

This search will fire any time a new region is seen in the GeoIP database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your region, there should be few false positives. If you are located in regions where the free version of MaxMind GeoIP that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 1" - ], - "nist": [ - "ID.AM" - ] + } + } + }, + "eli5": "The subsearch returns all events with event names that start with \"Run\" or \"Create,\" and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from regions that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action.", + "entities": [ + "dest" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen AWS Provisioning Activity Sources\" support search once to create a history of previously seen locations that have provisioned AWS resources.", + "id": "7971d3df-da82-4648-a6e5-b5637bea5253", + "investigations": [ + { + "id": "446ec87a-85c6-40d4-b060-bea4498281d6", + "name": "Get All AWS Activity From IP Address", + "type": "splunk" }, - "modification_date": "2018-03-16", - "name": "AWS Cloud Provisioning From Previously Unseen Region", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "5b794bef-1743-4f6f-804a-43915a2702ff", + "name": "Get All AWS Activity From Region", + "type": "splunk" + } + ], + "known_false_positives": "This is a strictly behavioral search, so we define \"false positive\" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no \"false positives\" in a traditional sense, there is definitely lots of noise.\n\n This search will fire any time a new region is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your region, there should be few false positives. If you are located in regions where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 1" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "nist": [ + "ID.AM" + ] + }, + "modification_date": "2018-03-16", + "name": "AWS Cloud Provisioning From Previously Unseen Region", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/aws_cross_account_activity_from_new_account.json b/detections/aws_cross_account_activity_from_new_account.json index b74cf16912..0008ee459e 100644 --- a/detections/aws_cross_account_activity_from_new_account.json +++ b/detections/aws_cross_account_activity_from_new_account.json @@ -1,113 +1,113 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "1cc22b09-c867-416e-a511-cb36ac44aee2", - "name": "Previously Seen AWS Cross Account Activity", - "type": "splunk" - } + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "1cc22b09-c867-416e-a511-cb36ac44aee2", + "name": "Previously Seen AWS Cross Account Activity", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-02-01", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "confidence": "medium", - "creation_date": "2018-02-01", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for AssumeRole events where an IAM role in a different account is requested for the first time.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "requestingAccountId, requestedAccountId, src_user, dest_user", - "rule_description": "Access to $dest_user$ was requested for the first time by $src_user$", - "rule_title": "AWS Account $dest_user$ access by $src_user$" - }, - "risk": { - "risk_object": "dest_user", - "risk_object_type": [ - "user" - ], - "risk_score": 20 - }, - "schedule": { - "cron_schedule": "5 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId != requestedAccountId | inputlookup append=t previously_seen_aws_cross_account_activity | multireport [| stats min(eval(coalesce(firstTime, strptime(_time,\"%Y-%m-%d %H:%M:%S\")))) as firstTime max(eval(coalesce(strptime(_time,\"%Y-%m-%d %H:%M:%S\"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, strptime(_time,\"%Y-%m-%d %H:%M:%S\")))) as firstTime, max(eval(coalesce(strptime(_time,\"%Y-%m-%d %H:%M:%S\"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | where firstTime >= relative_time(now(), \"-70m@m\") AND isnotnull(_time) | spath output=accessKeyId path=responseElements.credentials.accessKeyId | spath output=requestingARN path=resources{}.ARN | stats values(awsRegion) as awsRegion values(firstTime) as firstTime values(lastTime) as lastTime values(sharedEventID) as sharedEventID, values(requestingARN) as src_user, values(responseElements.assumedRoleUser.arn) as dest_user by _time, requestingAccountId, requestedAccountId, accessKeyId] | table _time, firstTime, lastTime, src_user, requestingAccountId, dest_user, requestedAccountId, awsRegion, accessKeyId, sharedEventID", - "suppress": { - "suppress_fields": "requestingAccountId, requestedAccountId", - "suppress_period": "14400s" - } - } - } - }, - "eli5": "This search
  1. Retrieves the AssumeRole event
  2. Verifies that the log entry contains a value for the account ID of the requesting account
  3. Ensures that the requesting account ID does not match the account ID of the requested account
  4. Pulls in the previously seen requesting and requested account IDs
  5. Splits up and executes multiple search paths at the same.
  6. The first path determines the firstTime and lastTime entries for the cache file
  7. Outputs the data to the cache file.
  8. Creates a conditional statement that is always false (both because we don't want these values to exit the search pipeline and because we think we're clever).
The second pipeline adds the firstTime and lastTime entries to search results. Next, it filters out any account pairs that haven't been seen for the first time within the last hour. The isnotnull(_time) will remove the entries from the cache file.

The search finishes by gathering the data that it will display to the user.", - "entities": [ - "dest_user" + "data_sourcetypes": [ + "aws:cloudtrail" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the Previously Seen AWS Cross Account Activity support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search.", - "id": "64fbbddf-fabf-4edf-80b3-0cc36ef37727", - "investigations": [ - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for AssumeRole events where an IAM role in a different account is requested for the first time.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "requestingAccountId, requestedAccountId, src_user, dest_user", + "rule_description": "Access to $dest_user$ was requested for the first time by $src_user$", + "rule_title": "AWS Account $dest_user$ access by $src_user$" }, - { - "id": "703b65a4-a0ae-4171-965d-45507506c64f", - "name": "AWS Investigate User Activities By AccessKeyId", - "type": "splunk" + "risk": { + "risk_object": "dest_user", + "risk_object_type": [ + "user" + ], + "risk_score": 20 }, - { - "id": "b0d2e6a8-75fa-4b1b-9486-3d32acadf891", - "name": "AWS Investigate User Activities By Source User", - "type": "splunk" + "schedule": { + "cron_schedule": "5 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId != requestedAccountId | inputlookup append=t previously_seen_aws_cross_account_activity | multireport [| stats min(eval(coalesce(firstTime, strptime(_time,\"%Y-%m-%d %H:%M:%S\")))) as firstTime max(eval(coalesce(strptime(_time,\"%Y-%m-%d %H:%M:%S\"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, strptime(_time,\"%Y-%m-%d %H:%M:%S\")))) as firstTime, max(eval(coalesce(strptime(_time,\"%Y-%m-%d %H:%M:%S\"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | where firstTime >= relative_time(now(), \"-70m@m\") AND isnotnull(_time) | spath output=accessKeyId path=responseElements.credentials.accessKeyId | spath output=requestingARN path=resources{}.ARN | stats values(awsRegion) as awsRegion values(firstTime) as firstTime values(lastTime) as lastTime values(sharedEventID) as sharedEventID, values(requestingARN) as src_user, values(responseElements.assumedRoleUser.arn) as dest_user by _time, requestingAccountId, requestedAccountId, accessKeyId] | table _time, firstTime, lastTime, src_user, requestingAccountId, dest_user, requestedAccountId, awsRegion, accessKeyId, sharedEventID", + "suppress": { + "suppress_fields": "requestingAccountId, requestedAccountId", + "suppress_period": "14400s" } - ], - "known_false_positives": "Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 16" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Credential Access" - ], - "nist": [ - "PR.AC", - "PR.DS", - "DE.AE" - ] + } + } + }, + "eli5": "This search\n\n1. Retrieves the **AssumeRole** event
  • Verifies that the log entry contains a value for the account ID of the requesting account
  • Ensures that the requesting account ID does not match the account ID of the requested account
  • Pulls in the previously seen requesting and requested account IDs
  • Splits up and executes multiple search paths at the same.
  • The first path determines the **firstTime** and **lastTime** entries for the cache file
  • Outputs the data to the cache file.
  • Creates a conditional statement that is always false (both because we don't want these values to exit the search pipeline and because we think we're clever).
    • The second pipeline adds the **firstTime** and **lastTime** entries to search results. Next, it filters out any account pairs that haven't been seen for the first time within the last hour. The `isnotnull(_time)` will remove the entries from the cache file.\n\nThe search finishes by gathering the data that it will display to the user.", + "entities": [ + "dest_user" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search.", + "id": "64fbbddf-fabf-4edf-80b3-0cc36ef37727", + "investigations": [ + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "modification_date": "2018-11-02", - "name": "AWS Cross Account Activity From Previously Unseen Account", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "703b65a4-a0ae-4171-965d-45507506c64f", + "name": "AWS Investigate User Activities By AccessKeyId", + "type": "splunk" + }, + { + "id": "b0d2e6a8-75fa-4b1b-9486-3d32acadf891", + "name": "AWS Investigate User Activities By Source User", + "type": "splunk" + } + ], + "known_false_positives": "Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 16" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Credential Access" + ], + "nist": [ + "PR.AC", + "PR.DS", + "DE.AE" + ] + }, + "modification_date": "2018-11-02", + "name": "AWS Cross Account Activity From Previously Unseen Account", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/aws_spike_acl_activity.json b/detections/aws_spike_acl_activity.json index ac18bd0fa7..f32cf49a3f 100644 --- a/detections/aws_spike_acl_activity.json +++ b/detections/aws_spike_acl_activity.json @@ -49,11 +49,11 @@ } } }, - "eli5": "This search and its corresponding subsearch run through the following series of steps:
    1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls specifically for creating/modifying/replacing network Access Control Lists (ACLs).
    2. Kick off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.
    3. Count the number of API calls per Amazon Resource Name (ARN).
    4. Load the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.
    5. Drop the count from the latest hour, since it is not necessary, and merge the rest of the data with the results of the stats command.
    6. Rename apiCalls as latestCount.
    7. Calculate the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. They do the same for the standard deviation--weighting the past more heavily than the current.
    8. Update the cache file with the latest results.
    9. Set the minimum threshold for the number of data points and set the number of standard deviations away from the mean it must be to be considered a spike.
    10. Make a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.
    11. Filter out anything that it determines is not a spike and return the list of ARNs to the main search.
    The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average.", + "eli5": "This search and its corresponding subsearch run through the following series of steps: \n\n1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls specifically for creating/modifying/replacing network Access Control Lists (ACLs).
  • Kick off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.
  • Count the number of API calls per Amazon Resource Name (ARN).
  • Load the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.
  • Drop the count from the latest hour, since it is not necessary, and merge the rest of the data with the results of the stats command.
  • Rename `apiCalls` as `latestCount`.
  • Calculate the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. They do the same for the standard deviation--weighting the past more heavily than the current.
  • Update the cache file with the latest results.
  • Set the minimum threshold for the number of data points and set the number of standard deviations away from the mean it must be to be considered a spike.
  • Make a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.
  • Filter out anything that it determines is not a spike and return the list of ARNs to the main search.
    • The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average.", "entities": [ "user" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify dataPointThreshold and deviationThreshold to better fit your environment. The dataPointThreshold variable is the minimum number of data points required to have a statistically significant amount of data to determine. The deviationThreshold variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the \"Baseline of Network ACL Activity by ARN\" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro NetworkACLEvents.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the \"Baseline of Network ACL Activity by ARN\" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `NetworkACLEvents`.", "id": "ada0f478-84a8-4641-a1f1-e32372d4bd53", "investigations": [ { @@ -87,7 +87,7 @@ "type": "splunk" } ], - "known_false_positives": "The false-positive rate may vary based on the values ofdataPointThreshold and deviationThreshold. Please modify this according the your environment.", + "known_false_positives": "The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment.", "maintainers": [ { "company": "Splunk", diff --git a/detections/children_of_spoolsv.json b/detections/children_of_spoolsv.json index 1744898e52..6734b1332e 100644 --- a/detections/children_of_spoolsv.json +++ b/detections/children_of_spoolsv.json @@ -1,137 +1,137 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-11-26", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-11-26", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, process_name, parent_process_name", + "rule_description": "A child process of spoolsv.exe was detected on $dest$.", + "rule_title": "Spoolsv.exe spawned a child process on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 60 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.process_name) as process_name values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=spoolsv.exe AND Processes.process_name!=regsvr32.exe by Processes.dest Processes.parent_process Processes.user | `drop_dm_object_name(Processes)` | `ctime(firstTime)` | `ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest, parent_process_name", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search looks for child processes of spoolsv.exe, which is associated with the Print Spooler service on Windows. Children of this process typically run under the SYSTEM context. This search should address the POC developed for the Windows local-privilege-escalation exploit announced in September of 2018. The associated vulnerability was assigned CVE-2018-8440. More information is available at https://doublepulsar.com/task-scheduler-alpc-exploit-high-level-analysis-ff08cda6ad4f.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "aa0c4aeb-5b18-41c4-8c07-f1442d7599df", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, process_name, parent_process_name", - "rule_description": "A child process of spoolsv.exe was detected on $dest$.", - "rule_title": "Spoolsv.exe spawned a child process on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 60 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.process_name) as process_name values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=spoolsv.exe AND Processes.process_name!=regsvr32.exe by Processes.dest Processes.parent_process Processes.user | `drop_dm_object_name(Processes)` | `ctime(firstTime)` | `ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest, parent_process_name", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search looks for child processes of spoolsv.exe, which is associated with the Print Spooler service on Windows. Children of this process typically run under the SYSTEM context. This search should address the POC developed for the Windows local-privilege-escalation exploit announced in September of 2018. The associated vulnerability was assigned CVE-2018-8440. More information is available at https://doublepulsar.com/task-scheduler-alpc-exploit-high-level-analysis-ff08cda6ad4f.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "aa0c4aeb-5b18-41c4-8c07-f1442d7599df", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 5", - "CIS 8" - ], - "kill_chain_phases": [ - "Exploitation" - ], - "mitre_attack": [ - "Privilege Escalation", - "Exploitation for Privilege Escalation" - ], - "nist": [ - "PR.AC", - "PR.PT", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-12-03", - "name": "Child Processes of Spoolsv.exe", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 5", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Exploitation" + ], + "mitre_attack": [ + "Privilege Escalation", + "Exploitation for Privilege Escalation" + ], + "nist": [ + "PR.AC", + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2018-12-03", + "name": "Child Processes of Spoolsv.exe", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/clients_connecting_to_multiple_dns_servers.json b/detections/clients_connecting_to_multiple_dns_servers.json index bb40ff5942..2c03d63101 100644 --- a/detections/clients_connecting_to_multiple_dns_servers.json +++ b/detections/clients_connecting_to_multiple_dns_servers.json @@ -1,105 +1,105 @@ { - "asset_type": "Endpoint", - "baselines": [], - "confidence": "medium", - "creation_date": "2016-09-13", - "data_metadata": { - "data_models": [ - "Network_Resolution" - ], - "data_source": [ - "DNS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src, dest", - "rule_description": "This search allows you to identify the endpoints that have connected to more than five DNS servers over the time frame specified in the search.", - "rule_title": "Client $src$ Connecting to Multiple DNS Servers" - }, - "risk": { - "risk_object": "src", - "risk_object_type": [ - "system" - ], - "risk_score": 80 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count, values(DNS.dest) AS dest dc(DNS.dest) as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY by DNS.src | `drop_dm_object_name(\"Network_Resolution\")` |where dest_count > 5", - "suppress": { - "suppress_fields": "src", - "suppress_period": "86400s" - } - } - } - }, - "eli5": "DNS Queries with multiple DNS servers from a single client is unusual and may be indicative of malicious activity. This search works by performing a count by the source of the distinct destinations for the DNS traffic. The search uses the Network_Resolution data model.", - "entities": [ - "dest", - "src" + "asset_type": "Endpoint", + "baselines": [], + "confidence": "medium", + "creation_date": "2016-09-13", + "data_metadata": { + "data_models": [ + "Network_Resolution" ], - "how_to_implement": "This search requires that DNS data is being ingested and populating the Network_Resolution data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.

    This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):

    • Label: Distinct DNS Connections, Field: dest_count


    Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", - "id": "74ec6f18-604b-4202-a567-86b2066be3ce", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", - "name": "Get DNS Server History for a host", - "type": "splunk" - } + "data_source": [ + "DNS" ], - "known_false_positives": "It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src, dest", + "rule_description": "This search allows you to identify the endpoints that have connected to more than five DNS servers over the time frame specified in the search.", + "rule_title": "Client $src$ Connecting to Multiple DNS Servers" + }, + "risk": { + "risk_object": "src", + "risk_object_type": [ + "system" + ], + "risk_score": 80 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count, values(DNS.dest) AS dest dc(DNS.dest) as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY by DNS.src | `drop_dm_object_name(\"Network_Resolution\")` |where dest_count > 5", + "suppress": { + "suppress_fields": "src", + "suppress_period": "86400s" } + } + } + }, + "eli5": "DNS Queries with multiple DNS servers from a single client is unusual and may be indicative of malicious activity. This search works by performing a count by the source of the distinct destinations for the DNS traffic. The search uses the `Network_Resolution` data model.", + "entities": [ + "dest", + "src" + ], + "how_to_implement": "This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\n\nThis search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n\n
    • **Label:** Distinct DNS Connections, **Field:** dest_count
    \n\nDetailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "id": "74ec6f18-604b-4202-a567-86b2066be3ce", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", + "name": "Get DNS Server History for a host", + "type": "splunk" + } + ], + "known_false_positives": "It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 9", + "CIS 12", + "CIS 13" ], - "mappings": { - "cis20": [ - "CIS 9", - "CIS 12", - "CIS 13" - ], - "kill_chain_phases": [ - "Command and Control" - ], - "mitre_attack": [ - "Command and Control", - "Exfiltration", - "Exfiltration Over Alternative Protocol", - "Commonly Used Port", - "Standard Application Layer Protocol" - ], - "nist": [ - "PR.PT", - "DE.AE", - "PR.DS" - ] - }, - "modification_date": "2017-09-18", - "name": "Clients Connecting to Multiple DNS Servers", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "kill_chain_phases": [ + "Command and Control" ], - "responses": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "mitre_attack": [ + "Command and Control", + "Exfiltration", + "Exfiltration Over Alternative Protocol", + "Commonly Used Port", + "Standard Application Layer Protocol" + ], + "nist": [ + "PR.PT", + "DE.AE", + "PR.DS" + ] + }, + "modification_date": "2017-09-18", + "name": "Clients Connecting to Multiple DNS Servers", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "responses": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/common_ransomware_extensions.json b/detections/common_ransomware_extensions.json index 689024d540..d9d3723838 100644 --- a/detections/common_ransomware_extensions.json +++ b/detections/common_ransomware_extensions.json @@ -1,140 +1,140 @@ { - "asset_type": "Endpoint", - "confidence": "high", - "creation_date": "2017-08-21", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon" - ] + "asset_type": "Endpoint", + "confidence": "high", + "creation_date": "2017-08-21", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon" + ] + }, + "description": "The search looks for file modifications with extensions commonly used by Ransomware", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, file_name", + "rule_description": "A file modification was detected on $dest$ with an extension commonly used by ransomware.", + "rule_title": "Ransomware Extension detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 80 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `ctime(lastTime)` | `ctime(firstTime)`| rex field=file_name \"(?\\.[^\\.]+)$\" | `ransomware_extensions`", + "suppress": { + "suppress_fields": "dest,file_name", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "This search looks at file modifications across your hosts and identifies files with extensions that are commonly associated with the encrypted files generated by ransomware.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\n\nThis search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n\n
    • **Label:** Name, **Field:** Name
    • **Label:** File Extension, **Field:** file_extension\n\nDetailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "id": "a9e5c5db-db11-43ca-86a8-c852d1b2c0ec", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "The search looks for file modifications with extensions commonly used by Ransomware", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, file_name", - "rule_description": "A file modification was detected on $dest$ with an extension commonly used by ransomware.", - "rule_title": "Ransomware Extension detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 80 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `ctime(lastTime)` | `ctime(firstTime)`| rex field=file_name \"(?\\.[^\\.]+)$\" | `ransomware_extensions`", - "suppress": { - "suppress_fields": "dest,file_name", - "suppress_period": "14400s" - } - } - } + { + "id": "d98675ed-da43-4a7e-96a7-eeca3232ba8e", + "name": "Get Update Logs For Endpoint", + "type": "splunk" }, - "eli5": "This search looks at file modifications across your hosts and identifies files with extensions that are commonly associated with the encrypted files generated by ransomware.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.

      This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):

      • Label: Name, Field: Name
      • Label: File Extension, Field: file_extension

        Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", - "id": "a9e5c5db-db11-43ca-86a8-c852d1b2c0ec", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "d98675ed-da43-4a7e-96a7-eeca3232ba8e", - "name": "Get Update Logs For Endpoint", - "type": "splunk" - }, - { - "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", - "name": "Get Vulnerability Logs For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d44", - "name": "Get Backup Logs For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", - "name": "Investigate Web Activity From Host", - "type": "splunk" - } - ], - "known_false_positives": "It is possible for a legitimate file with these extensions to be created. If this is a true ransomware attack, there will be a large number of files created with these extensions.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - }, - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", + "name": "Get Vulnerability Logs For Endpoint", + "type": "splunk" }, - "modification_date": "2018-11-15", - "name": "Common Ransomware Extensions", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d44", + "name": "Get Backup Logs For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", + "name": "Investigate Web Activity From Host", + "type": "splunk" + } + ], + "known_false_positives": "It is possible for a legitimate file with these extensions to be created. If this is a true ransomware attack, there will be a large number of files created with these extensions.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + }, + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2018-11-15", + "name": "Common Ransomware Extensions", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" } diff --git a/detections/create_hidden_shares.json b/detections/create_hidden_shares.json index e45fcf5716..a500d51314 100644 --- a/detections/create_hidden_shares.json +++ b/detections/create_hidden_shares.json @@ -1,136 +1,136 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-06-14", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-06-14", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for the creation or deletion of hidden shares using net.exe.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest,process_name", + "rule_description": "Net.exe was used to create or delete hidden network shares by $user$ on $dest$", + "rule_title": "Hidden File shares created/deleted on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "5 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)` | search (process=*share* OR process=*delete*)| regex process=\"\\S+[$]\"", + "suppress": { + "suppress_fields": "dest,process_name", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "Net.exe is a built-in command-line tool on Windows that can be used to create, delete, and manage shared resources on the computer, both locally and remotely. Though this tool is used by Microsoft administrators to manage the network shares, attackers also leverage it to create and delete hidden file shares by appending \"$\" after the name of the share. To look for hidden shares, use a regular expression to look for a `(name_file_share)$`. In this search, we are looking for the command-line execution of net.exe with command-line parameters such as `net`, `share`, or `delete` that may correspond to the creation of hidden shares", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "qw9919ed-fe5f-492c-b139-151bb162140e", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for the creation or deletion of hidden shares using net.exe.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest,process_name", - "rule_description": "Net.exe was used to create or delete hidden network shares by $user$ on $dest$", - "rule_title": "Hidden File shares created/deleted on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "5 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)` | search (process=*share* OR process=*delete*)| regex process=\"\\S+[$]\"", - "suppress": { - "suppress_fields": "dest,process_name", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "Net.exe is a built-in command-line tool on Windows that can be used to create, delete, and manage shared resources on the computer, both locally and remotely. Though this tool is used by Microsoft administrators to manage the network shares, attackers also leverage it to create and delete hidden file shares by appending \"$\" after the name of the share. To look for hidden shares, use a regular expression to look for a (name_file_share)$. In this search, we are looking for the command-line execution of net.exe with command-line parameters such as net, share, or delete that may correspond to the creation of hidden shares", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "qw9919ed-fe5f-492c-b139-151bb162140e", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Command-Line Interface", - "Persistence" - ], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-15", - "name": "Create or delete hidden shares using net.exe", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "3.0" + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Command-Line Interface", + "Persistence" + ], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2018-11-15", + "name": "Create or delete hidden shares using net.exe", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "3.0" } diff --git a/detections/create_local_admin_via_net.json b/detections/create_local_admin_via_net.json index a1278603eb..4aa06c2b82 100644 --- a/detections/create_local_admin_via_net.json +++ b/detections/create_local_admin_via_net.json @@ -1,136 +1,136 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-03-28", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-03-28", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for the creation of local administrator accounts using net.exe.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest", + "rule_description": "Net.exe was used to create local administrator accounts on $dest$.", + "rule_title": "Local administrator account created on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 8 * * *", + "earliest_time": "-1440m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)` | search (process=*localgroup* OR process=*/add* OR process=*user*)", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "Net.exe is a built-in Windows command-line tool that can be used to add, display, or modify user accounts. While Microsoft administrators use this tool to manage user groups, threat actors often leverage it to create local admin accounts to maintain persistence. In this search, we are looking for the execution of process net.exe with command-line parameters such as `localgroup`, `add`, or `user` that may correspond to the creation of local admin accounts or setting user/group properties.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "b89919ed-fe5f-492c-b139-151bb162040e", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for the creation of local administrator accounts using net.exe.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest", - "rule_description": "Net.exe was used to create local administrator accounts on $dest$.", - "rule_title": "Local administrator account created on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 8 * * *", - "earliest_time": "-1440m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)` | search (process=*localgroup* OR process=*/add* OR process=*user*)", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "Net.exe is a built-in Windows command-line tool that can be used to add, display, or modify user accounts. While Microsoft administrators use this tool to manage user groups, threat actors often leverage it to create local admin accounts to maintain persistence. In this search, we are looking for the execution of process net.exe with command-line parameters such as localgroup, add, or user that may correspond to the creation of local admin accounts or setting user/group properties.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "b89919ed-fe5f-492c-b139-151bb162040e", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Administrators often leverage net.exe to create admin accounts.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Command-Line Interface", - "Persistence" - ], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-15", - "name": "Create local admin accounts using net.exe", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Administrators often leverage net.exe to create admin accounts.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Command-Line Interface", + "Persistence" + ], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2018-11-15", + "name": "Create local admin accounts using net.exe", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" } diff --git a/detections/dns_amplification_any_query.json b/detections/dns_amplification_any_query.json index 99fad150b3..c4d77c961b 100644 --- a/detections/dns_amplification_any_query.json +++ b/detections/dns_amplification_any_query.json @@ -1,110 +1,110 @@ { - "asset_type": "DNS Servers", - "confidence": "high", - "creation_date": "2016-08-24", - "data_metadata": { - "data_models": [ - "Network_Resolution" - ], - "data_source": [ - "DNS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest", - "rule_description": "The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries.", - "rule_title": "Large Volume of DNS ANY Queries" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 60 - }, - "schedule": { - "cron_schedule": "*/5 * * * *", - "earliest_time": "-15m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count from datamodel=Network_Resolution where nodename=DNS \"DNS.message_type\"=\"QUERY\" \"DNS.record_type\"=\"ANY\" by \"DNS.dest\" | `drop_dm_object_name(\"DNS\")` | where count>200", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "7200s" - } - } - } - }, - "eli5": "This search counts the number of DNS ANY queries received in 5 minutes, and generates a Notable Event if the count exceeds a predefined threshold. The search returns the count, the first time, and the last time a DNS packet was observed with the ANY flag set.", - "entities": [ - "dest" + "asset_type": "DNS Servers", + "confidence": "high", + "creation_date": "2016-08-24", + "data_metadata": { + "data_models": [ + "Network_Resolution" ], - "how_to_implement": "To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model.", - "id": "8fa891f7-a533-4b3c-af85-5aa2e7c1f1eb", - "investigations": [ - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" + "data_source": [ + "DNS" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest", + "rule_description": "The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries.", + "rule_title": "Large Volume of DNS ANY Queries" }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 60 }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" + "schedule": { + "cron_schedule": "*/5 * * * *", + "earliest_time": "-15m@m", + "latest_time": "-10m@m" }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" + "search": "| tstats `summariesonly` count from datamodel=Network_Resolution where nodename=DNS \"DNS.message_type\"=\"QUERY\" \"DNS.record_type\"=\"ANY\" by \"DNS.dest\" | `drop_dm_object_name(\"DNS\")` | where count>200", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "7200s" } - ], - "known_false_positives": "Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 11", - "CIS 12" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "nist": [ - "PR.PT", - "DE.AE", - "PR.IP" - ] + } + } + }, + "eli5": "This search counts the number of DNS ANY queries received in 5 minutes, and generates a Notable Event if the count exceeds a predefined threshold. The search returns the count, the first time, and the last time a DNS packet was observed with the ANY flag set.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model.", + "id": "8fa891f7-a533-4b3c-af85-5aa2e7c1f1eb", + "investigations": [ + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "modification_date": "2017-09-20", - "name": "Large Volume of DNS ANY Queries", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + } + ], + "known_false_positives": "Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 11", + "CIS 12" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "nist": [ + "PR.PT", + "DE.AE", + "PR.IP" + ] + }, + "modification_date": "2017-09-20", + "name": "Large Volume of DNS ANY Queries", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/dns_evilginx_subdomains.json b/detections/dns_evilginx_subdomains.json index 273f42b274..ce1b9b29a4 100644 --- a/detections/dns_evilginx_subdomains.json +++ b/detections/dns_evilginx_subdomains.json @@ -48,7 +48,7 @@ "entities": [ "src" ], - "how_to_implement": "You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app.

        Splunk>Phantom Playbook Integration

        If Splunk>Phantom is also configured in your environment, a Playbook called `Lets Encrypt Domain Investigate` can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk https://splunkbase.splunk.com/app/3411/, add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active.
        (Playbook link:https://my.phantom.us/4.2/playbook/lets-encrypt-domain-investigate/).

        ", + "how_to_implement": "You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \n\n **Splunk>Phantom Playbook Integration**\n\nIf Splunk>Phantom is also configured in your environment, a Playbook called `Lets Encrypt Domain Investigate` can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \n\n(Playbook link:`https://my.phantom.us/4.2/playbook/lets-encrypt-domain-investigate/`).\n\n", "id": "24dd17b1-e2fb-4c31-878c-d4f226595bfa", "investigations": [ { diff --git a/detections/dns_query_length_mltk.json b/detections/dns_query_length_mltk.json index f777b615f4..29fcc5f4bb 100644 --- a/detections/dns_query_length_mltk.json +++ b/detections/dns_query_length_mltk.json @@ -1,157 +1,157 @@ { - "asset_type": "Endpoint", - "baselines": [ - { - "id": "c914844c-0ff5-4efc-8d44-c063443129ba", - "name": "Baseline of DNS Query Length - MLTK", - "type": "splunk" - } + "asset_type": "Endpoint", + "baselines": [ + { + "id": "c914844c-0ff5-4efc-8d44-c063443129ba", + "name": "Baseline of DNS Query Length - MLTK", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2019-05-08", + "data_metadata": { + "data_models": [ + "Network_Resolution" ], - "confidence": "medium", - "creation_date": "2019-05-08", - "data_metadata": { - "data_models": [ - "Network_Resolution" - ], - "data_source": [ - "DNS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] + "data_source": [ + "DNS" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src", + "rule_description": "Identify DNS traffic with unusual query lengths by record type", + "rule_title": "DNS query length outliers" + }, + "risk": { + "risk_object": "src", + "risk_object_type": [ + "system" + ], + "risk_score": 40 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as start_time max(_time) as end_time values(DNS.src) as src values(DNS.dest) as dest from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(DNS)` | `ctime(firstTime)` | `ctime(lastTime)` | eval query_length = len(query) | apply dns_query_pdfmodel threshold=0.01 | rename \"IsOutlier(query_length)\" as isOutlier | search isOutlier > 0 | sort -query_length | table start_time end_time query record_type count src dest query_length", + "suppress": { + "suppress_fields": "query", + "suppress_period": "43200s" + } + } + } + }, + "eli5": "Attackers often use random, long domain names for components of their attack infrastructure. This search leverages the probability distribution function algorithm provided by the Machine Learning Toolkit (MLTK) to identify outliers in the length of the DNS query for each record type observed. The companion search \"Baseline of DNS Query Length - MLTK\" creates a machine-learning (ML) model built over the historical data used by this search. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", + "entities": [ + "src" + ], + "how_to_implement": "To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search \"Baseline of DNS Query Length - MLTK\" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\n\nThis search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n\n
        • **Label:** DNS Query, **Field:** query
        • **Label:** DNS Query Length, **Field:** query_length
        • **Label:** Number of events, **Field:** count
        \n\nDetailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "id": "85fbcfe8-9718-4911-adf6-7000d077a3a9", + "investigations": [ + { + "id": "910e6512-edc9-4f93-ba24-5b786f47a672", + "name": "Get Process Responsible For The DNS Traffic", + "type": "splunk" }, - "description": "This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src", - "rule_description": "Identify DNS traffic with unusual query lengths by record type", - "rule_title": "DNS query length outliers" - }, - "risk": { - "risk_object": "src", - "risk_object_type": [ - "system" - ], - "risk_score": 40 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as start_time max(_time) as end_time values(DNS.src) as src values(DNS.dest) as dest from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(DNS)` | `ctime(firstTime)` | `ctime(lastTime)` | eval query_length = len(query) | apply dns_query_pdfmodel threshold=0.01 | rename \"IsOutlier(query_length)\" as isOutlier | search isOutlier > 0 | sort -query_length | table start_time end_time query record_type count src dest query_length", - "suppress": { - "suppress_fields": "query", - "suppress_period": "43200s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "Attackers often use random, long domain names for components of their attack infrastructure. This search leverages the probability distribution function algorithm provided by the Machine Learning Toolkit (MLTK) to identify outliers in the length of the DNS query for each record type observed. The companion search \"Baseline of DNS Query Length - MLTK\" creates a machine-learning (ML) model built over the historical data used by this search. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", - "entities": [ - "src" - ], - "how_to_implement": "To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search \"Baseline of DNS Query Length - MLTK\" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.

        This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):

        • Label: DNS Query, Field: query
        • Label: DNS Query Length, Field: query_length
        • Label: Number of events, Field: count


        Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", - "id": "85fbcfe8-9718-4911-adf6-7000d077a3a9", - "investigations": [ - { - "id": "910e6512-edc9-4f93-ba24-5b786f47a672", - "name": "Get Process Responsible For The DNS Traffic", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd73", - "name": "Get DNS traffic ratio", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", - "name": "Get DNS Server History for a host", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "If you are seeing more results than desired, you may consider reducing the value for threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 8", - "CIS 12" - ], - "kill_chain_phases": [ - "Command and Control" - ], - "mitre_attack": [ - "Command and Control", - "Exfiltration", - "Commonly Used Port" - ], - "nist": [ - "PR.PT", - "DE.AE", - "DE.CM" - ] + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd73", + "name": "Get DNS traffic ratio", + "type": "splunk" }, - "modification_date": "2019-05-08", - "name": "DNS Query Length Outliers - MLTK", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", + "name": "Get DNS Server History for a host", + "type": "splunk" + }, + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "If you are seeing more results than desired, you may consider reducing the value for threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 8", + "CIS 12" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Command and Control" + ], + "mitre_attack": [ + "Command and Control", + "Exfiltration", + "Commonly Used Port" + ], + "nist": [ + "PR.PT", + "DE.AE", + "DE.CM" + ] + }, + "modification_date": "2019-05-08", + "name": "DNS Query Length Outliers - MLTK", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/dns_record_changed.json b/detections/dns_record_changed.json index 698309a528..6691a3fb9e 100644 --- a/detections/dns_record_changed.json +++ b/detections/dns_record_changed.json @@ -1,118 +1,118 @@ { - "asset_type": "Endpoint", - "baselines": [ - { - "id": "c096f721-8842-42ce-bfc7-74bd8c72b7c3", - "name": "Discover DNS records", - "type": "splunk" - } + "asset_type": "Endpoint", + "baselines": [ + { + "id": "c096f721-8842-42ce-bfc7-74bd8c72b7c3", + "name": "Discover DNS records", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2019-02-14", + "data_metadata": { + "data_models": [ + "Network_Resolution" ], - "confidence": "medium", - "creation_date": "2019-02-14", - "data_metadata": { - "data_models": [ - "Network_Resolution" - ], - "data_source": [ - "DNS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src", - "rule_description": "The table represents a list of DNS records and their responses for corporate domains that have recently changed", - "rule_title": "DNS record changed" - }, - "risk": { - "risk_object": "src", - "risk_object_type": [ - "system" - ], - "risk_score": 40 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| inputlookup discovered_dns_records.csv | rename answer as discovered_answer | join domain[|tstats summariesonly=true count values(DNS.record_type) as type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!=\"unknown\" DNS.answer!=\"\" by DNS.query | rename DNS.query as query | where query!=\"unknown\" | rex field=query \"(?\\w+\\.\\w+?)(?:$|/)\"] | makemv delim=\" \" answer | makemv delim=\" \" type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer | makemv current_answer | mvexpand current_answer | makemv discovered_answer | eval n=mvfind(discovered_answer, current_answer) | where isnull(n)", - "suppress": { - "suppress_fields": "src", - "suppress_period": "28800s" - } - } - } - }, - "eli5": "Using a lookup `discover_dns_records` generated by support search \"Discover DNS records\" we check previous network traffic and make sure the responses have not changed.", - "entities": [ - "src", - "dest" + "data_source": [ + "DNS" ], - "how_to_implement": "To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search \"Discover DNS record\".

        Splunk>Phantom Playbook Integration

        If Splunk>Phantom is also configured in your environment, a Playbook called \"DNS Hijack Enrichment\" can be configured to run when any results are found by this detection search. The playbook takes in the DNS record changed and uses Geoip, whois, Censys and PassiveTotal to detect if DNS issuers changed. To use this integration, install the Phantom App for Splunk https://splunkbase.splunk.com/app/3411/, add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active.
        (Playbook Link:https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/).

        ", - "id": "44d3a43e-dcd5-49f7-8356-5209bb369065", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", - "name": "Get DNS Server History for a host", - "type": "splunk" + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src", + "rule_description": "The table represents a list of DNS records and their responses for corporate domains that have recently changed", + "rule_title": "DNS record changed" }, - { - "id": "c096f721-8842-42ce-bfc7-74bd9a72c712", - "name": "DNS Hijack Enrichment", - "type": "phantom" + "risk": { + "risk_object": "src", + "risk_object_type": [ + "system" + ], + "risk_score": 40 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| inputlookup discovered_dns_records.csv | rename answer as discovered_answer | join domain[|tstats summariesonly=true count values(DNS.record_type) as type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!=\"unknown\" DNS.answer!=\"\" by DNS.query | rename DNS.query as query | where query!=\"unknown\" | rex field=query \"(?\\w+\\.\\w+?)(?:$|/)\"] | makemv delim=\" \" answer | makemv delim=\" \" type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer | makemv current_answer | mvexpand current_answer | makemv discovered_answer | eval n=mvfind(discovered_answer, current_answer) | where isnull(n)", + "suppress": { + "suppress_fields": "src", + "suppress_period": "28800s" } - ], - "known_false_positives": "Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate.", - "maintainers": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } - ], - "mappings": { - "cis20": [ - "CIS 1", - "CIS 3", - "CIS 8", - "CIS 12" - ], - "kill_chain_phases": [ - "Command and Control" - ], - "mitre_attack": [ - "Exfiltration", - "Command and Control", - "Defense Evasion", - "Commonly Used Port" - ], - "nist": [ - "ID.AM", - "PR.DS", - "PR.IP", - "DE.AE", - "DE.CM" - ] + } + } + }, + "eli5": "Using a lookup `discover_dns_records` generated by support search \"Discover DNS records\" we check previous network traffic and make sure the responses have not changed.", + "entities": [ + "src", + "dest" + ], + "how_to_implement": "To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search \"Discover DNS record\". \n\n **Splunk>Phantom Playbook Integration**\n\nIf Splunk>Phantom is also configured in your environment, a Playbook called \"DNS Hijack Enrichment\" can be configured to run when any results are found by this detection search. The playbook takes in the DNS record changed and uses Geoip, whois, Censys and PassiveTotal to detect if DNS issuers changed. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \n\n(Playbook Link:`https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/`).\n\n", + "id": "44d3a43e-dcd5-49f7-8356-5209bb369065", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", + "name": "Get DNS Server History for a host", + "type": "splunk" }, - "modification_date": "2019-02-14", - "name": "DNS record changed", - "original_authors": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } + { + "id": "c096f721-8842-42ce-bfc7-74bd9a72c712", + "name": "DNS Hijack Enrichment", + "type": "phantom" + } + ], + "known_false_positives": "Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate.", + "maintainers": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "mappings": { + "cis20": [ + "CIS 1", + "CIS 3", + "CIS 8", + "CIS 12" ], - "responses": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Command and Control" + ], + "mitre_attack": [ + "Exfiltration", + "Command and Control", + "Defense Evasion", + "Commonly Used Port" + ], + "nist": [ + "ID.AM", + "PR.DS", + "PR.IP", + "DE.AE", + "DE.CM" + ] + }, + "modification_date": "2019-02-14", + "name": "DNS record changed", + "original_authors": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "responses": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/dyn_dns_queries.json b/detections/dyn_dns_queries.json index 7a59241280..8e3a5ea7a2 100644 --- a/detections/dyn_dns_queries.json +++ b/detections/dyn_dns_queries.json @@ -1,106 +1,106 @@ { - "asset_type": "Endpoint", - "baselines": [], - "confidence": "medium", - "creation_date": "2017-11-17", - "data_metadata": { - "data_models": [ - "Network_Resolution" - ], - "data_source": [ - "DNS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "answer, src, query", - "rule_description": "The search has detected a host making outbound queries to Dynamic DNS providers", - "rule_title": "Host $src$ detected to make a query to a Dynamic DNS provider" - }, - "risk": { - "risk_object": "src", - "risk_object_type": [ - "system" - ], - "risk_score": 20 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(DNS.answer) as answer min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name(\"DNS\")` | `ctime(firstTime)` | `dynamic_dns_providers`", - "suppress": { - "suppress_fields": "src, query", - "suppress_period": "86400s" - } - } - } - }, - "eli5": "The search leverages an accelerated Network_Resolution data model to count and list the values of resolved domains for each DNS query. It checks the results against the list of Dynamic DNS providers in the lookup dynamic_dns_providers by each host (DNS.src).", - "entities": [ - "dest", - "query" + "asset_type": "Endpoint", + "baselines": [], + "confidence": "medium", + "creation_date": "2017-11-17", + "data_metadata": { + "data_models": [ + "Network_Resolution" ], - "how_to_implement": "First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the Network_Resolution data model. This search also leverages a lookup file, dynamic_dns_providers_default.csv, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of dynamic_dns_providers_local.csv.

        This search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):

        • Label: DNS Query, Field: query
        • Label: DNS Answer, Field: answer
        • Label: IsDynamicDNS, Field: isDynDNS


        Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", - "id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", - "name": "Get DNS Server History for a host", - "type": "splunk" - } + "data_source": [ + "DNS" ], - "known_false_positives": "Some users and applications may leverage Dynamic DNS to reach out to some domains on the Internet since dynamic DNS by itself is not malicious, however this activity must be verified.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "answer, src, query", + "rule_description": "The search has detected a host making outbound queries to Dynamic DNS providers", + "rule_title": "Host $src$ detected to make a query to a Dynamic DNS provider" + }, + "risk": { + "risk_object": "src", + "risk_object_type": [ + "system" + ], + "risk_score": 20 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(DNS.answer) as answer min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name(\"DNS\")` | `ctime(firstTime)` | `dynamic_dns_providers`", + "suppress": { + "suppress_fields": "src, query", + "suppress_period": "86400s" } + } + } + }, + "eli5": "The search leverages an accelerated `Network_Resolution` data model to count and list the values of resolved domains for each DNS query. It checks the results against the list of Dynamic DNS providers in the lookup `dynamic_dns_providers` by each host (DNS.src).", + "entities": [ + "dest", + "query" + ], + "how_to_implement": "First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\n\nThis search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n\n
        • **Label:** DNS Query, **Field:** query
        • **Label:** DNS Answer, **Field:** answer
        • **Label:** IsDynamicDNS, **Field:** isDynDNS
        \n\nDetailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", + "name": "Get DNS Server History for a host", + "type": "splunk" + } + ], + "known_false_positives": "Some users and applications may leverage Dynamic DNS to reach out to some domains on the Internet since dynamic DNS by itself is not malicious, however this activity must be verified.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8", + "CIS 12", + "CIS 13" ], - "mappings": { - "cis20": [ - "CIS 8", - "CIS 12", - "CIS 13" - ], - "kill_chain_phases": [ - "Command and Control", - "Actions on Objectives" - ], - "mitre_attack": [ - "Exfiltration", - "Exfiltration Over Command and Control Channel", - "Defense Evasion", - "Commonly Used Port" - ], - "nist": [ - "PR.DS", - "PR.PT", - "DE.AE", - "DE.CM" - ] - }, - "modification_date": "2017-09-18", - "name": "Detect hosts connecting to dynamic domain providers", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "kill_chain_phases": [ + "Command and Control", + "Actions on Objectives" ], - "responses": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "mitre_attack": [ + "Exfiltration", + "Exfiltration Over Command and Control Channel", + "Defense Evasion", + "Commonly Used Port" + ], + "nist": [ + "PR.DS", + "PR.PT", + "DE.AE", + "DE.CM" + ] + }, + "modification_date": "2017-09-18", + "name": "Detect hosts connecting to dynamic domain providers", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "responses": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/dyn_dns_web_traffic.json b/detections/dyn_dns_web_traffic.json index 0bdcea3246..613aa24625 100644 --- a/detections/dyn_dns_web_traffic.json +++ b/detections/dyn_dns_web_traffic.json @@ -1,148 +1,148 @@ { - "asset_type": "Endpoint", - "confidence": "high", - "creation_date": "2018-09-06", - "data_metadata": { - "data_models": [ - "Web" - ], - "data_source": [ - "Web Traffic" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro", - "Bluecoat", - "Palo Alto Firewall" - ] + "asset_type": "Endpoint", + "confidence": "high", + "creation_date": "2018-09-06", + "data_metadata": { + "data_models": [ + "Web" + ], + "data_source": [ + "Web Traffic" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro", + "Bluecoat", + "Palo Alto Firewall" + ] + }, + "description": "This search looks for web connections to dynamic DNS providers.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src, url, dest", + "rule_description": "The host $src$ has been detected making a web request to $url$, which is a listed as a dynamic DNS provider.", + "rule_title": "Dynamic DNS web traffic detected on $src$." + }, + "risk": { + "risk_object": "src", + "risk_object_type": [ + "system" + ], + "risk_score": 40 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats summariesonly=true allow_old_summaries=true count values(Web.url) as url min(_time) as firstTime from datamodel=Web where Web.status=200 by Web.src Web.dest Web.status | `drop_dm_object_name(\"Web\")` | `ctime(firstTime)` | `dynamic_dns_web_traffic`", + "suppress": { + "suppress_fields": "src, url , dest", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search looks for hosts in your environment that may be communicating with a dynamic DNS provider. It checks each URL an endpoint is connecting to against a list of dynamic DNS providers. It returns the source and destination IP address of the web request, the URL requested, and the first time the event occurred.", + "entities": [ + "src" + ], + "how_to_implement": "This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\n\nThis search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n\n
        • **Label:** IsDynamicDNS, **Field:** isDynDNS
        \n\nDetailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "id": "134da869-e264-4a8f-8d7e-fcd01c18f301", + "investigations": [ + { + "id": "910e6512-edc9-4f93-ba24-5b786f47a672", + "name": "Get Process Responsible For The DNS Traffic", + "type": "splunk" }, - "description": "This search looks for web connections to dynamic DNS providers.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src, url, dest", - "rule_description": "The host $src$ has been detected making a web request to $url$, which is a listed as a dynamic DNS provider.", - "rule_title": "Dynamic DNS web traffic detected on $src$." - }, - "risk": { - "risk_object": "src", - "risk_object_type": [ - "system" - ], - "risk_score": 40 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats summariesonly=true allow_old_summaries=true count values(Web.url) as url min(_time) as firstTime from datamodel=Web where Web.status=200 by Web.src Web.dest Web.status | `drop_dm_object_name(\"Web\")` | `ctime(firstTime)` | `dynamic_dns_web_traffic`", - "suppress": { - "suppress_fields": "src, url , dest", - "suppress_period": "86400s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "This search looks for hosts in your environment that may be communicating with a dynamic DNS provider. It checks each URL an endpoint is connecting to against a list of dynamic DNS providers. It returns the source and destination IP address of the web request, the URL requested, and the first time the event occurred.", - "entities": [ - "src" - ], - "how_to_implement": "This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, dynamic_dns_providers_default.csv, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.

        This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):

        • Label: IsDynamicDNS, Field: isDynDNS


        Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", - "id": "134da869-e264-4a8f-8d7e-fcd01c18f301", - "investigations": [ - { - "id": "910e6512-edc9-4f93-ba24-5b786f47a672", - "name": "Get Process Responsible For The DNS Traffic", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd73", - "name": "Get DNS traffic ratio", - "type": "splunk" - }, - { - "id": "2f5b960b-71df-49c0-affc-74992ce60e45", - "name": "Investigate Web Activity From src_ip", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", - "name": "Get DNS Server History for a host", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "It is possible that list of dynamic DNS providers is outdated and/or that the URL being requested is legitimate.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 7", - "CIS 8" - ], - "kill_chain_phases": [ - "Command and Control", - "Actions on Objectives" - ], - "mitre_attack": [ - "Command and Control", - "Web Service", - "Exfiltration Over Command and Control Channel", - "Defense Evasion" - ], - "nist": [ - "PR.IP", - "DE.DP" - ] + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd73", + "name": "Get DNS traffic ratio", + "type": "splunk" }, - "modification_date": "2018-09-06", - "name": "Detect web traffic to dynamic domain providers", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "2f5b960b-71df-49c0-affc-74992ce60e45", + "name": "Investigate Web Activity From src_ip", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", + "name": "Get DNS Server History for a host", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "It is possible that list of dynamic DNS providers is outdated and/or that the URL being requested is legitimate.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 7", + "CIS 8" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Command and Control", + "Actions on Objectives" + ], + "mitre_attack": [ + "Command and Control", + "Web Service", + "Exfiltration Over Command and Control Channel", + "Defense Evasion" + ], + "nist": [ + "PR.IP", + "DE.DP" + ] + }, + "modification_date": "2018-09-06", + "name": "Detect web traffic to dynamic domain providers", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/ec2_instance_created_by_previously_unseen_user.json b/detections/ec2_instance_created_by_previously_unseen_user.json index afe9b09423..86f18fe649 100644 --- a/detections/ec2_instance_created_by_previously_unseen_user.json +++ b/detections/ec2_instance_created_by_previously_unseen_user.json @@ -1,125 +1,125 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "6c767ac0-0906-4355-9a83-927f5ee7bdad", - "name": "Previously Seen EC2 Launches By User", - "type": "splunk" - } + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "6c767ac0-0906-4355-9a83-927f5ee7bdad", + "name": "Previously Seen EC2 Launches By User", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-03-15", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "confidence": "medium", - "creation_date": "2018-03-15", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for EC2 instances being created by users who have not created them before.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "user, dest", + "rule_description": "The EC2 instance $dest$ was created by $user$. This user has never created an EC2 instance before.", + "rule_title": "EC2 Instance Created By Previously Unseen User $user$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 30 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_launches_by_user.csv | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | eval newUser=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newUser=1 | `ctime(firstTime)` | `ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as user | table _time, user, dest, instanceType", + "suppress": { + "suppress_fields": "user, dest", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "The subsearch returns the ARNs of all successful EC2 instance launches within the last hour and then appends the historical data in the lookup file to those results. It then recalculates the `firstTime` and `lastTime` field for each ARN and returns only those ARNs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance id of those systems.", + "entities": [ + "dest" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen EC2 Launches By User\" support search once to create a history of previously seen ARNs.", + "id": "22773e84-bac0-4595-b086-20d3f735b4f1", + "investigations": [ + { + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", + "name": "AWS Investigate User Activities By ARN", + "type": "splunk" }, - "description": "This search looks for EC2 instances being created by users who have not created them before.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "user, dest", - "rule_description": "The EC2 instance $dest$ was created by $user$. This user has never created an EC2 instance before.", - "rule_title": "EC2 Instance Created By Previously Unseen User $user$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_launches_by_user.csv | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | eval newUser=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newUser=1 | `ctime(firstTime)` | `ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as user | table _time, user, dest, instanceType", - "suppress": { - "suppress_fields": "user, dest", - "suppress_period": "14400s" - } - } - } + { + "id": "0e40fe83-3edb-4d86-8206-8fed36529ca6", + "name": "Get EC2 Launch Details", + "type": "splunk" }, - "eli5": "The subsearch returns the ARNs of all successful EC2 instance launches within the last hour and then appends the historical data in the lookup file to those results. It then recalculates the firstTime and lastTime field for each ARN and returns only those ARNs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance id of those systems.", - "entities": [ - "dest" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen EC2 Launches By User\" support search once to create a history of previously seen ARNs.", - "id": "22773e84-bac0-4595-b086-20d3f735b4f1", - "investigations": [ - { - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", - "name": "AWS Investigate User Activities By ARN", - "type": "splunk" - }, - { - "id": "0e40fe83-3edb-4d86-8206-8fed36529ca6", - "name": "Get EC2 Launch Details", - "type": "splunk" - }, - { - "id": "f3db4d1b-5f33-4b01-c541-c7ah9514c242", - "name": "Get EC2 Instance Details by instanceId", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - }, - { - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd11", - "name": "Investigate AWS activities via region name", - "type": "splunk" - } - ], - "known_false_positives": "It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 1" - ], - "nist": [ - "ID.AM" - ] + { + "id": "f3db4d1b-5f33-4b01-c541-c7ah9514c242", + "name": "Get EC2 Instance Details by instanceId", + "type": "splunk" }, - "modification_date": "2018-03-12", - "name": "EC2 Instance Started With Previously Unseen User", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + }, + { + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd11", + "name": "Investigate AWS activities via region name", + "type": "splunk" + } + ], + "known_false_positives": "It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 1" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "nist": [ + "ID.AM" + ] + }, + "modification_date": "2018-03-12", + "name": "EC2 Instance Started With Previously Unseen User", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/ec2_instance_modified_by_previously_unseen_user.json b/detections/ec2_instance_modified_by_previously_unseen_user.json index 746a3c0efe..cfcc91872d 100644 --- a/detections/ec2_instance_modified_by_previously_unseen_user.json +++ b/detections/ec2_instance_modified_by_previously_unseen_user.json @@ -1,105 +1,105 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "4d69091b-d975-4267-85df-888bd41034eb", - "name": "Previously Seen EC2 Modifications By User", - "type": "splunk" - } + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "4d69091b-d975-4267-85df-888bd41034eb", + "name": "Previously Seen EC2 Modifications By User", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-04-09", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "confidence": "medium", - "creation_date": "2018-04-09", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for EC2 instances being modified by users who have not previously modified them.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "user, dest", - "rule_description": "The EC2 instance $dest$ was modified by $user$. This user has never modified an EC2 instance before.", - "rule_title": "EC2 Instance Modified By Previously Unseen User $user$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail `ec2ModificationAPIs` [search sourcetype=aws:cloudtrail `ec2ModificationAPIs` errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_modifications_by_user | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | eval newUser=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newUser=1 | `ctime(firstTime)` | `ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=dest responseElements.instancesSet.items{}.instanceId | spath output=user userIdentity.arn | table _time, user, dest", - "suppress": { - "suppress_fields": "user, dest", - "suppress_period": "14400s" - } - } - } - }, - "eli5": "The subsearch returns the ARNs of all successful EC2 instance modifications within the last hour and then appends the historical data in the lookup file to those results. EC2 modification APIs are defined by the macro ec2ModificationAPIs. The search then recalculates the firstTime and lastTime field for each ARN and returns only those ARNs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance ID of those systems.", - "entities": [ - "dest" + "data_sourcetypes": [ + "aws:cloudtrail" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen EC2 Launches By User\" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro ec2ModificationAPIs.", - "id": "56f91724-cf3f-4666-84e1-e3712fb41e76", - "investigations": [ - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for EC2 instances being modified by users who have not previously modified them.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "user, dest", + "rule_description": "The EC2 instance $dest$ was modified by $user$. This user has never modified an EC2 instance before.", + "rule_title": "EC2 Instance Modified By Previously Unseen User $user$" }, - { - "id": "f3db4d1b-5f33-4b01-c541-c7ah9514c242", - "name": "Get EC2 Instance Details by instanceId", - "type": "splunk" + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 30 }, - { - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", - "name": "AWS Investigate User Activities By ARN", - "type": "splunk" + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail `ec2ModificationAPIs` [search sourcetype=aws:cloudtrail `ec2ModificationAPIs` errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_modifications_by_user | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | eval newUser=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newUser=1 | `ctime(firstTime)` | `ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=dest responseElements.instancesSet.items{}.instanceId | spath output=user userIdentity.arn | table _time, user, dest", + "suppress": { + "suppress_fields": "user, dest", + "suppress_period": "14400s" } - ], - "known_false_positives": "It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 1" - ], - "nist": [ - "ID.AM" - ] + } + } + }, + "eli5": "The subsearch returns the ARNs of all successful EC2 instance modifications within the last hour and then appends the historical data in the lookup file to those results. EC2 modification APIs are defined by the macro `ec2ModificationAPIs`. The search then recalculates the `firstTime` and `lastTime` field for each ARN and returns only those ARNs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance ID of those systems.", + "entities": [ + "dest" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the \"Previously Seen EC2 Launches By User\" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2ModificationAPIs`.", + "id": "56f91724-cf3f-4666-84e1-e3712fb41e76", + "investigations": [ + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "modification_date": "2018-04-09", - "name": "EC2 Instance Modified With Previously Unseen User", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "f3db4d1b-5f33-4b01-c541-c7ah9514c242", + "name": "Get EC2 Instance Details by instanceId", + "type": "splunk" + }, + { + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", + "name": "AWS Investigate User Activities By ARN", + "type": "splunk" + } + ], + "known_false_positives": "It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 1" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "nist": [ + "ID.AM" + ] + }, + "modification_date": "2018-04-09", + "name": "EC2 Instance Modified With Previously Unseen User", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/email_attachments_with_spaces.json b/detections/email_attachments_with_spaces.json index 444b8dc95c..f31054c595 100644 --- a/detections/email_attachments_with_spaces.json +++ b/detections/email_attachments_with_spaces.json @@ -1,93 +1,93 @@ { - "asset_type": "Endpoint", - "channel": "ESCU", - "confidence": "high", - "creation_date": "2017-04-21", - "data_metadata": { - "data_models": [ - "Email" - ], - "data_source": [ - "Email" - ], - "providing_technologies": [ - "Microsoft Exchange" - ] - }, - "description": "Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src_user, file_name", - "rule_description": "The sender $src_user$ has sent an email with a suspicious amount of spaces in the file name: $file_name$", - "rule_title": "Suspicious Email Attachment from $src_user$" - }, - "risk": { - "risk_object": "src_user", - "risk_object_type": [ - "user" - ], - "risk_score": 60 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(All_Email.recipient) as recipient_address min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name=\"*\" by All_Email.src_user, All_Email.file_name All_Email.message_id | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(\"All_Email\")` | eval space_ratio = (mvcount(split(file_name,\" \"))-1)/len(file_name) | search space_ratio >= 0.1 | rex field=recipient_address \"(?.*)@\"", - "suppress": { - "suppress_fields": "src_user", - "suppress_period": "86400s" - } - } - } - }, - "eli5": "This search looks at any emails with file attachment names that contain many spaces, relative to the length of the file name. Specifically, it checks to see whether spaces make up more than 10% of the number of characters in the file name. This percentage can be tuned for each environment. The search will output the message ID of the email, the count, the sender and recipient addresses, the first and last time this event was seen, and the space ratio of the file attachment name.", - "entities": [ - "src", - "message_id" + "asset_type": "Endpoint", + "channel": "ESCU", + "confidence": "high", + "creation_date": "2017-04-21", + "data_metadata": { + "data_models": [ + "Email" ], - "how_to_implement": "You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment.

        Splunk Phantom Playbook Integration

        If Splunk Phantom is also configured in your environment, a playbook called \"Suspicious Email Attachment Investigate and Delete\" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk https://splunkbase.splunk.com/app/3411/ and add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox.", - "id": "56e877a6-1455-4479-ada6-0550dc1e22f8", - "investigations": [ - { - "id": "3096f721-8842-42ce-2fc7-742d8372b712", - "name": "Suspicious Email Attachment Investigate and Delete", - "type": "phantom" - } + "data_source": [ + "Email" ], - "known_false_positives": "None at this time", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "providing_technologies": [ + "Microsoft Exchange" + ] + }, + "description": "Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src_user, file_name", + "rule_description": "The sender $src_user$ has sent an email with a suspicious amount of spaces in the file name: $file_name$", + "rule_title": "Suspicious Email Attachment from $src_user$" + }, + "risk": { + "risk_object": "src_user", + "risk_object_type": [ + "user" + ], + "risk_score": 60 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(All_Email.recipient) as recipient_address min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name=\"*\" by All_Email.src_user, All_Email.file_name All_Email.message_id | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(\"All_Email\")` | eval space_ratio = (mvcount(split(file_name,\" \"))-1)/len(file_name) | search space_ratio >= 0.1 | rex field=recipient_address \"(?.*)@\"", + "suppress": { + "suppress_fields": "src_user", + "suppress_period": "86400s" } + } + } + }, + "eli5": "This search looks at any emails with file attachment names that contain many spaces, relative to the length of the file name. Specifically, it checks to see whether spaces make up more than 10% of the number of characters in the file name. This percentage can be tuned for each environment. The search will output the message ID of the email, the count, the sender and recipient addresses, the first and last time this event was seen, and the space ratio of the file attachment name.", + "entities": [ + "src", + "message_id" + ], + "how_to_implement": "You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \n\n **Splunk Phantom Playbook Integration**\n\nIf Splunk Phantom is also configured in your environment, a playbook called \"Suspicious Email Attachment Investigate and Delete\" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/` and add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox.", + "id": "56e877a6-1455-4479-ada6-0550dc1e22f8", + "investigations": [ + { + "id": "3096f721-8842-42ce-2fc7-742d8372b712", + "name": "Suspicious Email Attachment Investigate and Delete", + "type": "phantom" + } + ], + "known_false_positives": "None at this time", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 7" ], - "mappings": { - "cis20": [ - "CIS 7" - ], - "kill_chain_phases": [ - "Delivery" - ], - "mitre_attack": [], - "nist": [ - "PR.IP" - ] - }, - "modification_date": "2017-09-19", - "name": "Email Attachments With Lots Of Spaces", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "kill_chain_phases": [ + "Delivery" ], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "mitre_attack": [], + "nist": [ + "PR.IP" + ] + }, + "modification_date": "2017-09-19", + "name": "Email Attachments With Lots Of Spaces", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/email_files_not_in_outlook_directory.json b/detections/email_files_not_in_outlook_directory.json index ad8575702e..5759354797 100644 --- a/detections/email_files_not_in_outlook_directory.json +++ b/detections/email_files_not_in_outlook_directory.json @@ -1,131 +1,131 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2017-12-13", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2017-12-13", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, file_path, action, file_name", + "rule_description": "The system $dest$ has email files outside of the normal Outlook directory ", + "rule_title": "Email files created or modified on $dest$ that are not in the normal Outlook directory" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where (Filesystem.file_name=*.dll OR Filesystem.file_name=*.ost) Filesystem.file_path != \"C:\\\\Users\\\\*\\\\My Documents\\\\Outlook Files\\\\*\" by Filesystem.action Filesystem.process_id Filesystem.file_name Filesystem.dest | `drop_dm_object_name(\"Filesystem\")` | `ctime(firstTime)` | `ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest, file_path", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "In this search, we are looking for activities consistent with an adversary collecting email data from local machines. The search will detect email files (files with .pst or .ost extensions) created in directories other than the standard Outlook directory (c:\\users\\username\\My Documents\\Outlook Files\\.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes.", + "id": "ee18ed37-0802-4268-9435-b3b91aaa18xx", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, file_path, action, file_name", - "rule_description": "The system $dest$ has email files outside of the normal Outlook directory ", - "rule_title": "Email files created or modified on $dest$ that are not in the normal Outlook directory" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where (Filesystem.file_name=*.dll OR Filesystem.file_name=*.ost) Filesystem.file_path != \"C:\\\\Users\\\\*\\\\My Documents\\\\Outlook Files\\\\*\" by Filesystem.action Filesystem.process_id Filesystem.file_name Filesystem.dest | `drop_dm_object_name(\"Filesystem\")` | `ctime(firstTime)` | `ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest, file_path", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "In this search, we are looking for activities consistent with an adversary collecting email data from local machines. The search will detect email files (files with .pst or .ost extensions) created in directories other than the standard Outlook directory (c:\\users\\username\\My Documents\\Outlook Files\\.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes.", - "id": "ee18ed37-0802-4268-9435-b3b91aaa18xx", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Collection", - "Email Collection" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-02", - "name": "Email files written outside of the Outlook directory", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Collection", + "Email Collection" + ] + }, + "modification_date": "2018-11-02", + "name": "Email files written outside of the Outlook directory", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/excessive_lockouts_from_endpoint.json b/detections/excessive_lockouts_from_endpoint.json index 8ed1fbdffc..d52f1cbcfb 100644 --- a/detections/excessive_lockouts_from_endpoint.json +++ b/detections/excessive_lockouts_from_endpoint.json @@ -1,97 +1,97 @@ { - "asset_type": "Windows", - "confidence": "low", - "creation_date": "2017-08-17", - "data_metadata": { - "data_models": [ - "Change" - ], - "data_source": [ - "Windows Event Logs" - ], - "providing_technologies": [ - "Microsoft Windows" - ] - }, - "description": "This search identifies endpoints that have caused a relatively high number of account lockouts in a short period.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest", - "rule_description": "The system $dest$ has generated a high number of account lockouts.", - "rule_title": "$dest$ has generated a high number of account lockouts" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 40 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-4h@h", - "latest_time": "-5m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result=\"lockout\" by All_Changes.dest All_Changes.result |`drop_dm_object_name(\"All_Changes\")` |`drop_dm_object_name(\"Account_Management\")`| `ctime(firstTime)` | `ctime(lastTime)` | search count > 5", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "86400s" - } - } - } - }, - "eli5": "This search queries the `Change.All_Changes` datamodel under the nodename is `Account_Management` , where the result is \"lockout\", which indicates that an account has been locked out. It then counts the number of times an endpoint has caused an account lockout within a four hour window and displays those hosts with a count greater than or equal to five.", - "entities": [ - "dest" + "asset_type": "Windows", + "confidence": "low", + "creation_date": "2017-08-17", + "data_metadata": { + "data_models": [ + "Change" ], - "how_to_implement": "You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment.

        Splunk>Phantom Playbook Integration

        If Splunk>Phantom is also configured in your environment, a Playbook called \"Excessive Account Lockouts Enrichment and Response\" can be configured to run when any results are found by this detection search. The Playbook executes the Contextual and Investigative searches in this Story, conducts additional information gathering on Windows endpoints, and takes a response action to shut down the affected endpoint. To use this integration, install the Phantom App for Splunk https://splunkbase.splunk.com/app/3411/, add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active.
        (Playbook Link:https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/).

        ", - "id": "c026e3dd-7e18-4abb-8f41-929e836efe74", - "investigations": [ - { - "id": "ab62b5c1-95d4-4e71-8fd7-53a55db33da4", - "name": "Excessive Account Lockouts Enrichment And Response", - "type": "phantom" - } + "data_source": [ + "Windows Event Logs" ], - "known_false_positives": "It's possible that a widely used system, such as a kiosk, could cause a large number of account lockouts.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search identifies endpoints that have caused a relatively high number of account lockouts in a short period.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest", + "rule_description": "The system $dest$ has generated a high number of account lockouts.", + "rule_title": "$dest$ has generated a high number of account lockouts" }, - { - "company": "Splunk", - "email": "proyer@splunk.com", - "name": "Philip Royer" + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 40 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-4h@h", + "latest_time": "-5m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result=\"lockout\" by All_Changes.dest All_Changes.result |`drop_dm_object_name(\"All_Changes\")` |`drop_dm_object_name(\"Account_Management\")`| `ctime(firstTime)` | `ctime(lastTime)` | search count > 5", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "86400s" } - ], - "mappings": { - "cis20": [ - "CIS 16" - ], - "mitre_attack": [ - "Initial Access", - "Valid Accounts" - ], - "nist": [ - "PR.IP" - ] + } + } + }, + "eli5": "This search queries the `Change.All_Changes` datamodel under the nodename is `Account_Management` , where the result is \"lockout\", which indicates that an account has been locked out. It then counts the number of times an endpoint has caused an account lockout within a four hour window and displays those hosts with a count greater than or equal to five.", + "entities": [ + "dest" + ], + "how_to_implement": "You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \n\n **Splunk>Phantom Playbook Integration**\n\nIf Splunk>Phantom is also configured in your environment, a Playbook called \"Excessive Account Lockouts Enrichment and Response\" can be configured to run when any results are found by this detection search. The Playbook executes the Contextual and Investigative searches in this Story, conducts additional information gathering on Windows endpoints, and takes a response action to shut down the affected endpoint. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \n\n(Playbook Link:`https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/`).\n\n", + "id": "c026e3dd-7e18-4abb-8f41-929e836efe74", + "investigations": [ + { + "id": "ab62b5c1-95d4-4e71-8fd7-53a55db33da4", + "name": "Excessive Account Lockouts Enrichment And Response", + "type": "phantom" + } + ], + "known_false_positives": "It's possible that a widely used system, such as a kiosk, could cause a large number of account lockouts.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" }, - "modification_date": "2019-04-18", - "name": "Detect Excessive Account Lockouts From Endpoint", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "company": "Splunk", + "email": "proyer@splunk.com", + "name": "Philip Royer" + } + ], + "mappings": { + "cis20": [ + "CIS 16" ], - "responses": [], - "security_domain": "access", - "spec_version": 2, - "type": "splunk", - "version": "3.0" + "mitre_attack": [ + "Initial Access", + "Valid Accounts" + ], + "nist": [ + "PR.IP" + ] + }, + "modification_date": "2019-04-18", + "name": "Detect Excessive Account Lockouts From Endpoint", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "responses": [], + "security_domain": "access", + "spec_version": 2, + "type": "splunk", + "version": "3.0" } diff --git a/detections/first_time_seen_cmd_line.json b/detections/first_time_seen_cmd_line.json index 8249f9334d..03fe67c1cb 100644 --- a/detections/first_time_seen_cmd_line.json +++ b/detections/first_time_seen_cmd_line.json @@ -1,152 +1,152 @@ { - "asset_type": "Endpoint", - "baselines": [ - { - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd23", - "name": "Previously seen command line arguments", - "type": "splunk" - } + "asset_type": "Endpoint", + "baselines": [ + { + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd23", + "name": "Previously seen command line arguments", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-04-09", + "data_metadata": { + "data_models": [ + "Endpoint" ], - "confidence": "medium", - "creation_date": "2018-04-09", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process", + "rule_description": "The system $dest$ executed a command-line argument, $process$, that has not previously been seen.", + "rule_title": "First-time seen command-line argument was detected on $dest$." + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "30 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = \"* /c *\" by Processes.process Processes.process_name Processes.parent_process_name Processes.dest| `drop_dm_object_name(Processes)`| `ctime(firstTime)` | `ctime(lastTime)` | search [| tstats `summariesonly` earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = \"* /c *\" by Processes.process | `drop_dm_object_name(Processes)` | inputlookup append=t previously_seen_cmd_line_arguments | stats min(firstTime) as firstTime, max(lastTime) as lastTime by process | outputlookup previously_seen_cmd_line_arguments | eval newCmdLineArgument=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newCmdLineArgument=1 | `ctime(firstTime)` | `ctime(lastTime)` | table process]", + "suppress": { + "suppress_fields": "dest, process", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "The subsearch returns all events where `cmd.exe` was used with a `/c` parameter in the command-line arguments to execute other commands/programs. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for command-line execution and outputs this data to the lookup file to update the local cache. It returns only those events that have first been seen in the past one hour. This is combined with the main search to return the time, user, destination, process, parent process, and value of the command-line argument.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the \"process\" field in the Endpoint data model. Please make sure you run the support search \"Previously seen command line arguments,\"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function.", + "id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for command-line arguments that use a /c parameter to execute a command that has not previously been seen.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process", - "rule_description": "The system $dest$ executed a command-line argument, $process$, that has not previously been seen.", - "rule_title": "First-time seen command-line argument was detected on $dest$." - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "30 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = \"* /c *\" by Processes.process Processes.process_name Processes.parent_process_name Processes.dest| `drop_dm_object_name(Processes)`| `ctime(firstTime)` | `ctime(lastTime)` | search [| tstats `summariesonly` earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = \"* /c *\" by Processes.process | `drop_dm_object_name(Processes)` | inputlookup append=t previously_seen_cmd_line_arguments | stats min(firstTime) as firstTime, max(lastTime) as lastTime by process | outputlookup previously_seen_cmd_line_arguments | eval newCmdLineArgument=if(firstTime >= relative_time(now(), \"-70m@m\"), 1, 0) | where newCmdLineArgument=1 | `ctime(firstTime)` | `ctime(lastTime)` | table process]", - "suppress": { - "suppress_fields": "dest, process", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "The subsearch returns all events where cmd.exe was used with a /c parameter in the command-line arguments to execute other commands/programs. It appends the historical data to those results in the lookup file. Next, it recalculates the firstTime and lastTime field for command-line execution and outputs this data to the lookup file to update the local cache. It returns only those events that have first been seen in the past one hour. This is combined with the main search to return the time, user, destination, process, parent process, and value of the command-line argument.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the \"process\" field in the Endpoint data model. Please make sure you run the support search \"Previously seen command line arguments,\"—which creates a lookup file called previously_seen_cmd_line_arguments.csv—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function.", - "id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", - "name": "Investigate Web Activity From Host", - "type": "splunk" - } - ], - "known_false_positives": "Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 8" - ], - "kill_chain_phases": [ - "Command and Control", - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Scripting", - "Persistence", - "Command-Line Interface" - ], - "nist": [ - "PR.PT", - "DE.CM", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2019-03-04", - "name": "First time seen command line argument", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", + "name": "Investigate Web Activity From Host", + "type": "splunk" + } + ], + "known_false_positives": "Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "3.0" + "kill_chain_phases": [ + "Command and Control", + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Scripting", + "Persistence", + "Command-Line Interface" + ], + "nist": [ + "PR.PT", + "DE.CM", + "PR.IP" + ] + }, + "modification_date": "2019-03-04", + "name": "First time seen command line argument", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "3.0" } diff --git a/detections/first_time_seen_running_windows_service.json b/detections/first_time_seen_running_windows_service.json index 21a6c2026f..87f1db8496 100644 --- a/detections/first_time_seen_running_windows_service.json +++ b/detections/first_time_seen_running_windows_service.json @@ -1,132 +1,132 @@ { - "asset_type": "Endpoint", - "baselines": [ - { - "id": "64ce0ade-cb01-4678-bddd-d31c0b175394", - "name": "Previously Seen Running Windows Services", - "type": "splunk" - } + "asset_type": "Endpoint", + "baselines": [ + { + "id": "64ce0ade-cb01-4678-bddd-d31c0b175394", + "name": "Previously Seen Running Windows Services", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-07-22", + "data_metadata": { + "data_eventtypes": [ + "wineventlog_system" ], - "confidence": "medium", - "creation_date": "2018-07-22", - "data_metadata": { - "data_eventtypes": [ - "wineventlog_system" - ], - "data_source": [ - "Windows Event Logs" - ], - "providing_technologies": [ - "Microsoft Windows" - ] + "data_source": [ + "Windows Event Logs" + ], + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search looks for the first time a Windows service is seen running in your environment.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "serviceName", + "rule_description": "The service $serviceName$ is running on $dest$. This is the first time this service has been run on any system.", + "rule_title": "First Time Seen Windows Service $serviceName$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 40 + }, + "schedule": { + "cron_schedule": "30 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "eventtype=wineventlog_system signature_id=7036 | rex field=Message \"The (?[\\w\\s-]*) service entered the (?\\w*) state\" | where action=\"running\" | inputlookup append=t previously_seen_running_windows_services | multireport [| stats earliest(eval(coalesce(_time, firstTime))) as firstTime, latest(eval(coalesce(_time, lastTime))) as lastTime by serviceName | outputlookup previously_seen_running_windows_services | where fact=fiction] [| eventstats earliest(eval(coalesce(_time, firstTime))) as firstTime, latest(eval(coalesce(_time, lastTime))) as lastTime by serviceName | where firstTime >= relative_time(now(), \"-60m@m\") AND isnotnull(_time) | stats values(dest) as dest by _time, serviceName] | table _time, serviceName, dest", + "suppress": { + "suppress_fields": "serviceName, dest", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search looks for a change in the status of a Windows service and extracts the name of the service and the action taken by the service. Then the cache file of previously seen Windows services is added to the search. At this point, the search takes two different paths: the first updates the cache file with the latest information and the second searches for services that have never before been seen. It returns the time, the Windows host name, and the service name.", + "entities": [ + "dest" + ], + "how_to_implement": "While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services.", + "id": "823136f2-d755-4b6d-ae04-372b486a5808", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for the first time a Windows service is seen running in your environment.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "serviceName", - "rule_description": "The service $serviceName$ is running on $dest$. This is the first time this service has been run on any system.", - "rule_title": "First Time Seen Windows Service $serviceName$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 40 - }, - "schedule": { - "cron_schedule": "30 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "eventtype=wineventlog_system signature_id=7036 | rex field=Message \"The (?[\\w\\s-]*) service entered the (?\\w*) state\" | where action=\"running\" | inputlookup append=t previously_seen_running_windows_services | multireport [| stats earliest(eval(coalesce(_time, firstTime))) as firstTime, latest(eval(coalesce(_time, lastTime))) as lastTime by serviceName | outputlookup previously_seen_running_windows_services | where fact=fiction] [| eventstats earliest(eval(coalesce(_time, firstTime))) as firstTime, latest(eval(coalesce(_time, lastTime))) as lastTime by serviceName | where firstTime >= relative_time(now(), \"-60m@m\") AND isnotnull(_time) | stats values(dest) as dest by _time, serviceName] | table _time, serviceName, dest", - "suppress": { - "suppress_fields": "serviceName, dest", - "suppress_period": "86400s" - } - } - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "eli5": "This search looks for a change in the status of a Windows service and extracts the name of the service and the action taken by the service. Then the cache file of previously seen Windows services is added to the search. At this point, the search takes two different paths: the first updates the cache file with the latest information and the second searches for services that have never before been seen. It returns the time, the Windows host name, and the service name.", - "entities": [ - "dest" - ], - "how_to_implement": "While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, Previously Seen Running Windows Services, should be run before this search to create the baseline of known Windows services.", - "id": "823136f2-d755-4b6d-ae04-372b486a5808", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 2", - "CIS 9" - ], - "kill_chain_phases": [ - "Installation", - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "New Service" - ], - "nist": [ - "ID.AM", - "PR.DS", - "PR.AC", - "DE.AE" - ] + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "modification_date": "2019-02-27", - "name": "First Time Seen Running Windows Service", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 2", + "CIS 9" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Installation", + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "New Service" + ], + "nist": [ + "ID.AM", + "PR.DS", + "PR.AC", + "DE.AE" + ] + }, + "modification_date": "2019-02-27", + "name": "First Time Seen Running Windows Service", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/large_icmp_outbound.json b/detections/large_icmp_outbound.json index badde96d2c..508fe23ed7 100644 --- a/detections/large_icmp_outbound.json +++ b/detections/large_icmp_outbound.json @@ -1,128 +1,128 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-06-01", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communications" - ], - "providing_technologies": [ - "Bro", - "Splunk Stream", - "Palo Alto Firewall" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-06-01", + "data_metadata": { + "data_models": [ + "Network_Traffic" + ], + "data_source": [ + "Network Communications" + ], + "providing_technologies": [ + "Bro", + "Splunk Stream", + "Palo Alto Firewall" + ] + }, + "description": "This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src_ip, dest_ip", + "rule_description": "Large outbound ICMP packet detected.", + "rule_title": "Large ICMP packet from $src_ip$ to $dest_ip$ detected" + }, + "risk": { + "risk_object": "src_ip", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count earliest(_time) as earliest latest(_time) as latest values(All_Traffic.action) values(All_Traffic.bytes) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.protocol=icmp OR All_Traffic.transport=icmp) All_Traffic.bytes > 1000 by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name(\"All_Traffic\")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | convert ctime(earliest) ctime(latest)", + "suppress": { + "suppress_fields": "src_ip", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "This search works by looking at fields in the Network_Traffic data model, which is populated by various firewalls and passive networking monitoring technologies. Specifically, the search looks for ICMP packets larger than 1,000 bytes with a destination that is external to your organization.", + "entities": [ + "src_ip" + ], + "how_to_implement": "In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model", + "id": "e9c102de-4d43-42a7-b1c8-8062ea297419", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src_ip, dest_ip", - "rule_description": "Large outbound ICMP packet detected.", - "rule_title": "Large ICMP packet from $src_ip$ to $dest_ip$ detected" - }, - "risk": { - "risk_object": "src_ip", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count earliest(_time) as earliest latest(_time) as latest values(All_Traffic.action) values(All_Traffic.bytes) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.protocol=icmp OR All_Traffic.transport=icmp) All_Traffic.bytes > 1000 by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name(\"All_Traffic\")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | convert ctime(earliest) ctime(latest)", - "suppress": { - "suppress_fields": "src_ip", - "suppress_period": "28800s" - } - } - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "eli5": "This search works by looking at fields in the Network_Traffic data model, which is populated by various firewalls and passive networking monitoring technologies. Specifically, the search looks for ICMP packets larger than 1,000 bytes with a destination that is external to your organization.", - "entities": [ - "src_ip" - ], - "how_to_implement": "In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named internal to the CIDRs that host the company's assets in the assets_by_cidr.csv lookup file, which is located in $SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model", - "id": "e9c102de-4d43-42a7-b1c8-8062ea297419", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 9", - "CIS 12" - ], - "kill_chain_phases": [ - "Command and Control" - ], - "mitre_attack": [ - "Command and Control", - "Standard Non-Application Layer Protocol" - ], - "nist": [ - "DE.AE" - ] + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" }, - "modification_date": "2018-06-01", - "name": "Detect Large Outbound ICMP Packets", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 9", + "CIS 12" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "2.0" + "kill_chain_phases": [ + "Command and Control" + ], + "mitre_attack": [ + "Command and Control", + "Standard Non-Application Layer Protocol" + ], + "nist": [ + "DE.AE" + ] + }, + "modification_date": "2018-06-01", + "name": "Detect Large Outbound ICMP Packets", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "2.0" } diff --git a/detections/local_admin_account_creation.json b/detections/local_admin_account_creation.json index e9d679f09f..1e857827d7 100644 --- a/detections/local_admin_account_creation.json +++ b/detections/local_admin_account_creation.json @@ -1,133 +1,133 @@ { - "asset_type": "Windows", - "confidence": "medium", - "creation_date": "2018-03-26", - "data_metadata": { - "data_eventtypes": [ - "wineventlog_security" - ], - "data_source": [ - "Windows Event Logs" - ], - "providing_technologies": [ - "Microsoft Windows" - ] + "asset_type": "Windows", + "confidence": "medium", + "creation_date": "2018-03-26", + "data_metadata": { + "data_eventtypes": [ + "wineventlog_security" + ], + "data_source": [ + "Windows Event Logs" + ], + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search looks for newly created accounts that have been elevated to local administrators.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "user,src_user, dest", + "rule_description": "The new user account $user$ was created on $dest$ by $src_user$.", + "rule_title": "New local admin account $user$ created by $src_user$." + }, + "risk": { + "risk_object": "user", + "risk_object_type": [ + "system" + ], + "risk_score": 40 + }, + "schedule": { + "cron_schedule": "0 9 * * *", + "earliest_time": "-1440m@m", + "latest_time": "-10m@m" + }, + "search": "eventtype = wineventlog_security signature_id=4720 OR (signature_id=4732 Group_Name= Administrators) | transaction Security_ID maxspan=180m | search signature_id=4720 signature_id=4732 | table _time user dest signature_id Security_ID Group_Name src_user Message", + "suppress": { + "suppress_fields": "user", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search looks for Windows Event Code 4720 (account creation) and 4732 (account added to a security-enabled local group), where the group name is \"Administrators\", and determines whether they are generated for the same user's Security ID within three hours of each other. It will return the user account that was added, the Security ID, the group name to which the user was added, the account name of the user who initiated the action, and the subsequent message returned.", + "entities": [ + "user" + ], + "how_to_implement": "You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is \"Administrators\" to be able to look for the right group membership changes.\n\nThis search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n\n
        • **Label:** Security ID, **Field:** Security_ID
        • **Label:** Group Name, **Field:** Group_Name
        • **Label:** Message, **Field:** Message
        \n\nDetailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "id": "b25f6f62-0712-43c1-b203-083231ffd97d", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for newly created accounts that have been elevated to local administrators.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "user,src_user, dest", - "rule_description": "The new user account $user$ was created on $dest$ by $src_user$.", - "rule_title": "New local admin account $user$ created by $src_user$." - }, - "risk": { - "risk_object": "user", - "risk_object_type": [ - "system" - ], - "risk_score": 40 - }, - "schedule": { - "cron_schedule": "0 9 * * *", - "earliest_time": "-1440m@m", - "latest_time": "-10m@m" - }, - "search": "eventtype = wineventlog_security signature_id=4720 OR (signature_id=4732 Group_Name= Administrators) | transaction Security_ID maxspan=180m | search signature_id=4720 signature_id=4732 | table _time user dest signature_id Security_ID Group_Name src_user Message", - "suppress": { - "suppress_fields": "user", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search looks for Windows Event Code 4720 (account creation) and 4732 (account added to a security-enabled local group), where the group name is \"Administrators\", and determines whether they are generated for the same user's Security ID within three hours of each other. It will return the user account that was added, the Security ID, the group name to which the user was added, the account name of the user who initiated the action, and the subsequent message returned.", - "entities": [ - "user" - ], - "how_to_implement": "You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is \"Administrators\" to be able to look for the right group membership changes.

        This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):

        • Label: Security ID, Field: Security_ID
        • Label: Group Name, Field: Group_Name
        • Label: Message, Field: Message


        Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", - "id": "b25f6f62-0712-43c1-b203-083231ffd97d", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "The activity may be legitimate. For this reason, it's best to verify the account with an administrator and ask whether there was a valid service request for the account creation. If your local administrator group name is not \"Administrators\", this search may generate an excessive number of false positives", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 16" - ], - "kill_chain_phases": [ - "Actions on Objectives", - "Command and Control" - ], - "mitre_attack": [ - "Valid Accounts", - "Defense Evasion", - "Persistence" - ], - "nist": [ - "PR.AC", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2019-02-28", - "name": "Detect New Local Admin account", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "The activity may be legitimate. For this reason, it's best to verify the account with an administrator and ask whether there was a valid service request for the account creation. If your local administrator group name is not \"Administrators\", this search may generate an excessive number of false positives", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 16" ], - "references": [], - "security_domain": "access", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Actions on Objectives", + "Command and Control" + ], + "mitre_attack": [ + "Valid Accounts", + "Defense Evasion", + "Persistence" + ], + "nist": [ + "PR.AC", + "DE.CM" + ] + }, + "modification_date": "2019-02-28", + "name": "Detect New Local Admin account", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "access", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/malicious_application_shimming_via_registry.json b/detections/malicious_application_shimming_via_registry.json index 89381be5d2..d4210ecbf2 100644 --- a/detections/malicious_application_shimming_via_registry.json +++ b/detections/malicious_application_shimming_via_registry.json @@ -1,138 +1,138 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2017-08-27", - "data_metadata": { - "data_models": [ - "Change_Analysis" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2017-08-27", + "data_metadata": { + "data_models": [ + "Change_Analysis" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon" + ] + }, + "description": "This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user", + "rule_description": "A registry key that is used for persistence on Windows was modified on $dest$ by $user$", + "rule_title": "Registry Key Associated With SHIM databases on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 30 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path=\"*CurrentVersion\\\\AppCompatFlags\\\\Custom*\" OR All_Changes.object_path=\"*CurrentVersion\\\\AppCompatFlags\\\\InstalledSDB*\") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `drop_dm_object_name(\"All_Changes\")`", + "suppress": { + "suppress_fields": "dest,object_path", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "In this search, we look for modifications to registry keys used for shim databases on Microsoft platforms via the object_category and object_path field in the Change_Analysis data model and give you the destination, command used to initiate the change, the user who conducted this activity, the resource affected(object), and the whole path of the object. An application compatibility shim is a small library that transparently intercepts an API (via hooking), changes the parameters passed, handles the operation itself, or redirects the operation elsewhere, such as additional code stored on a system. This capability can be also leveraged by attackers to create and store malicious files in a shim database as observed in CARBANAK backdoor.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry.", + "id": "f5f6af30-7aa7-4295-bfe9-07fe87c01bbb", + "investigations": [ + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", + "name": "Get Registry Activities", + "type": "splunk" }, - "description": "This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user", - "rule_description": "A registry key that is used for persistence on Windows was modified on $dest$ by $user$", - "rule_title": "Registry Key Associated With SHIM databases on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path=\"*CurrentVersion\\\\AppCompatFlags\\\\Custom*\" OR All_Changes.object_path=\"*CurrentVersion\\\\AppCompatFlags\\\\InstalledSDB*\") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `drop_dm_object_name(\"All_Changes\")`", - "suppress": { - "suppress_fields": "dest,object_path", - "suppress_period": "86400s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "In this search, we look for modifications to registry keys used for shim databases on Microsoft platforms via the object_category and object_path field in the Change_Analysis data model and give you the destination, command used to initiate the change, the user who conducted this activity, the resource affected(object), and the whole path of the object. An application compatibility shim is a small library that transparently intercepts an API (via hooking), changes the parameters passed, handles the operation itself, or redirects the operation elsewhere, such as additional code stored on a system. This capability can be also leveraged by attackers to create and store malicious files in a shim database as observed in CARBANAK backdoor.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry.", - "id": "f5f6af30-7aa7-4295-bfe9-07fe87c01bbb", - "investigations": [ - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", - "name": "Get Registry Activities", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Persistence", - "Application Shimming" - ], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "modification_date": "2017-09-15", - "name": "Registry Keys for Creating SHIM Databases", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Persistence", + "Application Shimming" + ], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2017-09-15", + "name": "Registry Keys for Creating SHIM Databases", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/malicious_powershell_process_execpolicy.json b/detections/malicious_powershell_process_execpolicy.json index 02a5ec6184..9f10edd2fb 100644 --- a/detections/malicious_powershell_process_execpolicy.json +++ b/detections/malicious_powershell_process_execpolicy.json @@ -1,140 +1,140 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-03-19", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-03-19", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process_name", + "rule_description": "The system $dest$ executed a PowerShell process with parameters to bypass the local execution policy.", + "rule_title": "PowerShell process with -executionpolicy bypass detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "50 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)`| search process=* -ex* OR process=* bypass *", + "suppress": { + "suppress_fields": "dest, process_name", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "This search looks for PowerShell processes that were launched using a parameter designed to bypass the local PowerShell execution policy. By default, the policy is set to \"Restricted,\" which disables the execution of PowerShell scripts. In environments that make heavy use of PowerShell, the policy can be set to allow only scripts signed by a trusted publisher. Malicious PowerShell use almost always includes the parameter `-ExecutionPolicy bypass`. PowerShell is very liberal when it comes to interpreting command-line parameters passed to it. For example, the parameter we look for, `-ExecutionPolicy`, can be abbreviated to `-Execution`, `-Exec`, or even `-ex`. As such, we look for `* -ex*`, which should catch all variations of this parameter, followed by the keyword `bypass`. This search will return the host, the user the process ran under, the process and its command-line arguments, the number of times it has seen this process, and the first and last times it saw this process.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "9be56c82-b1cc-4318-87eb-d138afaaca39", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process_name", - "rule_description": "The system $dest$ executed a PowerShell process with parameters to bypass the local execution policy.", - "rule_title": "PowerShell process with -executionpolicy bypass detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "50 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)`| search process=* -ex* OR process=* bypass *", - "suppress": { - "suppress_fields": "dest, process_name", - "suppress_period": "14400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search looks for PowerShell processes that were launched using a parameter designed to bypass the local PowerShell execution policy. By default, the policy is set to \"Restricted,\" which disables the execution of PowerShell scripts. In environments that make heavy use of PowerShell, the policy can be set to allow only scripts signed by a trusted publisher. Malicious PowerShell use almost always includes the parameter -ExecutionPolicy bypass. PowerShell is very liberal when it comes to interpreting command-line parameters passed to it. For example, the parameter we look for, -ExecutionPolicy, can be abbreviated to -Execution, -Exec, or even -ex. As such, we look for * -ex*, which should catch all variations of this parameter, followed by the keyword bypass. This search will return the host, the user the process ran under, the process and its command-line arguments, the number of times it has seen this process, and the first and last times it saw this process.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "9be56c82-b1cc-4318-87eb-d138afaaca39", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 7", - "CIS 8" - ], - "kill_chain_phases": [ - "Command and Control", - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "PowerShell", - "Scripting" - ], - "nist": [ - "PR.PT", - "DE.CM", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-12-03", - "name": "Malicious PowerShell Process - Execution Policy Bypass", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 7", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "3.0" + "kill_chain_phases": [ + "Command and Control", + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "PowerShell", + "Scripting" + ], + "nist": [ + "PR.PT", + "DE.CM", + "PR.IP" + ] + }, + "modification_date": "2018-12-03", + "name": "Malicious PowerShell Process - Execution Policy Bypass", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "3.0" } diff --git a/detections/malicious_powershell_process_multiple_suspicious_arguments.json b/detections/malicious_powershell_process_multiple_suspicious_arguments.json index 33b97262e4..2946f94f54 100644 --- a/detections/malicious_powershell_process_multiple_suspicious_arguments.json +++ b/detections/malicious_powershell_process_multiple_suspicious_arguments.json @@ -1,135 +1,135 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2016-09-18", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2016-09-18", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process, process_name", + "rule_description": "The system $dest$ executed a PowerShell that had an encoded command on the command-line, attempted to bypass local execution policy, and prevented the display of an interactive prompt to the user.", + "rule_title": "PowerShell process with multiple suspicious command-line arguments detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 60 + }, + "schedule": { + "cron_schedule": "50 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)`| search (process=*-EncodedCommand* OR process=*-enc*) process=*-Exec* AND process=*-NonI*", + "suppress": { + "suppress_fields": "dest, process_name", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "This search looks for PowerShell processes that have a number of suspicious flags on the command-line. It is looking for flags are passing encoded commands on the command-line. The flags `-EncodedCommand` and `-enc` are two different possible flags that can be used to pass base64 encoded commands to PowerShell. The `*-Exec*` flag looks to see it the default execution policy of PowerShell is being overridden, while the `*-NonI*` flag tells the PowerShell process that this will be a noninteractive process, so the user doesn't know about the process. This search will return the host, the user the process ran under, the process and it's command-line arguments, the number of times it's seen this process, and the first and last times it saw this process.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "2cdb91d2-542c-497f-b252-be495e71f38c", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process, process_name", - "rule_description": "The system $dest$ executed a PowerShell that had an encoded command on the command-line, attempted to bypass local execution policy, and prevented the display of an interactive prompt to the user.", - "rule_title": "PowerShell process with multiple suspicious command-line arguments detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 60 - }, - "schedule": { - "cron_schedule": "50 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)`| search (process=*-EncodedCommand* OR process=*-enc*) process=*-Exec* AND process=*-NonI*", - "suppress": { - "suppress_fields": "dest, process_name", - "suppress_period": "14400s" - } - } - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "eli5": "This search looks for PowerShell processes that have a number of suspicious flags on the command-line. It is looking for flags are passing encoded commands on the command-line. The flags -EncodedCommand and -enc are two different possible flags that can be used to pass base64 encoded commands to PowerShell. The *-Exec* flag looks to see it the default execution policy of PowerShell is being overridden, while the *-NonI* flag tells the PowerShell process that this will be a noninteractive process, so the user doesn't know about the process. This search will return the host, the user the process ran under, the process and it's command-line arguments, the number of times it's seen this process, and the first and last times it saw this process.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "2cdb91d2-542c-497f-b252-be495e71f38c", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Legitimate process can have this combination of command-line options, but it's not common.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 7", - "CIS 8" - ], - "kill_chain_phases": [ - "Command and Control", - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "PowerShell", - "Scripting" - ], - "nist": [ - "PR.PT", - "DE.CM", - "PR.IP" - ] + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" }, - "modification_date": "2018-12-03", - "name": "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Legitimate process can have this combination of command-line options, but it's not common.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 7", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "3.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Command and Control", + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "PowerShell", + "Scripting" + ], + "nist": [ + "PR.PT", + "DE.CM", + "PR.IP" + ] + }, + "modification_date": "2018-12-03", + "name": "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "3.0" +} diff --git a/detections/malicious_powershell_process_obfuscation_techniques.json b/detections/malicious_powershell_process_obfuscation_techniques.json index e945326d16..26bbc30a59 100644 --- a/detections/malicious_powershell_process_obfuscation_techniques.json +++ b/detections/malicious_powershell_process_obfuscation_techniques.json @@ -1,135 +1,135 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2017-04-25", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2017-04-25", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process_name, process", + "rule_description": "The system $dest$ executed a PowerShell process that has evidence of obfuscation on the command-line", + "rule_title": "PowerShell process with an obfuscation techniques detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 60 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)`| eval num_obfuscation = (mvcount(split(process, \"`\"))-1) + (mvcount(split(process, \"^\"))-1) | search num_obfuscation > 0", + "suppress": { + "suppress_fields": "dest,process_name,process", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "This search looks for PowerShell processes that are passing command-line arguments with unusual characters (backticks and carets) that are PowerShell specific escape characters. Attackers use this obfuscation technique since it does not affect the functionality of PowerShell and it will bypass standard security controls that look for straight up malicious strings and commands. The search counts the occurrence of these obfuscation characters and lists out destination IPs running these PowerShell commands.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "cde75cf6-3c7a-4dd6-af01-27cdb4511fd4", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process_name, process", - "rule_description": "The system $dest$ executed a PowerShell process that has evidence of obfuscation on the command-line", - "rule_title": "PowerShell process with an obfuscation techniques detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 60 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)`| eval num_obfuscation = (mvcount(split(process, \"`\"))-1) + (mvcount(split(process, \"^\"))-1) | search num_obfuscation > 0", - "suppress": { - "suppress_fields": "dest,process_name,process", - "suppress_period": "14400s" - } - } - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "eli5": "This search looks for PowerShell processes that are passing command-line arguments with unusual characters (backticks and carets) that are PowerShell specific escape characters. Attackers use this obfuscation technique since it does not affect the functionality of PowerShell and it will bypass standard security controls that look for straight up malicious strings and commands. The search counts the occurrence of these obfuscation characters and lists out destination IPs running these PowerShell commands.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "cde75cf6-3c7a-4dd6-af01-27cdb4511fd4", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "These characters might be legitimately on the command-line, but it is not common.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 7", - "CIS 8" - ], - "kill_chain_phases": [ - "Command and Control", - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "PowerShell", - "Scripting" - ], - "nist": [ - "PR.PT", - "DE.CM", - "PR.IP" - ] + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" }, - "modification_date": "2018-12-03", - "name": "Malicious PowerShell Process With Obfuscation Techniques", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "These characters might be legitimately on the command-line, but it is not common.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 7", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Command and Control", + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "PowerShell", + "Scripting" + ], + "nist": [ + "PR.PT", + "DE.CM", + "PR.IP" + ] + }, + "modification_date": "2018-12-03", + "name": "Malicious PowerShell Process With Obfuscation Techniques", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/netbackup_failed_backup.json b/detections/netbackup_failed_backup.json index fe51bd2b80..8930b4f6f0 100644 --- a/detections/netbackup_failed_backup.json +++ b/detections/netbackup_failed_backup.json @@ -1,115 +1,115 @@ { - "asset_type": "Endpoint", - "baselines": [ - { - "id": "b2178fed-592f-492b-b851-74161678aa56", - "name": "Monitor Unsuccessful Backups", - "type": "splunk" - }, - { - "id": "b4d0dfb2-2195-4f6e-93a3-48468ed9734e", - "name": "Monitor Successful Backups", - "type": "splunk" - } - ], - "confidence": "high", - "creation_date": "2017-06-15", - "data_metadata": { - "data_source": [ - "Backup Systems" - ], - "data_sourcetypes": [ - "netbackup_logs" - ], - "providing_technologies": [ - "Netbackup" - ] + "asset_type": "Endpoint", + "baselines": [ + { + "id": "b2178fed-592f-492b-b851-74161678aa56", + "name": "Monitor Unsuccessful Backups", + "type": "splunk" }, - "description": "This search gives you the hosts where a backup was attempted and then failed.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest", - "rule_description": "The system $dest$ attempted a backup but encountered an error.", - "rule_title": "Failed backup attempt by $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 10 - }, - "schedule": { - "cron_schedule": "0 7 * * *", - "earliest_time": "-24h@h", - "latest_time": "-10m@m" - }, - "search": "sourcetype=\"netbackup_logs\" | stats latest(_time) as latestTime by COMPUTERNAME, MESSAGE | search MESSAGE=\"An error occurred, failed to backup.\" | `ctime(latestTime)` | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, signature", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "86400s" - } - } + { + "id": "b4d0dfb2-2195-4f6e-93a3-48468ed9734e", + "name": "Monitor Successful Backups", + "type": "splunk" + } + ], + "confidence": "high", + "creation_date": "2017-06-15", + "data_metadata": { + "data_source": [ + "Backup Systems" + ], + "data_sourcetypes": [ + "netbackup_logs" + ], + "providing_technologies": [ + "Netbackup" + ] + }, + "description": "This search gives you the hosts where a backup was attempted and then failed.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest", + "rule_description": "The system $dest$ attempted a backup but encountered an error.", + "rule_title": "Failed backup attempt by $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 10 + }, + "schedule": { + "cron_schedule": "0 7 * * *", + "earliest_time": "-24h@h", + "latest_time": "-10m@m" + }, + "search": "sourcetype=\"netbackup_logs\" | stats latest(_time) as latestTime by COMPUTERNAME, MESSAGE | search MESSAGE=\"An error occurred, failed to backup.\" | `ctime(latestTime)` | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, signature", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "86400s" } + } + } + }, + "eli5": "This search looks across the most recent backup events for each host, and returns those messages that indicate there was a backup failure.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution.", + "id": "a34aae96-ccf8-4aaa-952c-3ea21444444f", + "investigations": [ + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "eli5": "This search looks across the most recent backup events for each host, and returns those messages that indicate there was a backup failure.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution.", - "id": "a34aae96-ccf8-4aaa-952c-3ea21444444f", - "investigations": [ - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-aaaa-4bb2-8140-e756cc06fd72", - "name": "All backup logs for host", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - } - ], - "known_false_positives": "None identified", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 10" - ], - "nist": [ - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" }, - "modification_date": "2017-09-12", - "name": "Unsuccessful Netbackup backups", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "bc91a8cf-aaaa-4bb2-8140-e756cc06fd72", + "name": "All backup logs for host", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + } + ], + "known_false_positives": "None identified", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 10" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "nist": [ + "PR.IP" + ] + }, + "modification_date": "2017-09-12", + "name": "Unsuccessful Netbackup backups", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/netsh_launching_process.json b/detections/netsh_launching_process.json index 6b52e9258a..a1e69d9ea4 100644 --- a/detections/netsh_launching_process.json +++ b/detections/netsh_launching_process.json @@ -1,136 +1,136 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-01-04", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-01-04", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, process, parent_process", + "rule_description": "A process, $process$, is spawned by netsh.exe. It is highly unlikely for netsh to have any child processes.", + "rule_title": "Process spawned by netsh.exe detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.process) min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process=\"C:\\Windows\\System32\\netsh.exe\" by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`|`ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest, process", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search looks for all processes with the parent process \"c:\\Windows\\System32\\netsh.exe\" and returns the process, the command line used to execute it, the host name, and the user context under which it ran.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.", + "id": "b89919ed-fe5f-492c-b139-95dbb162041e", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, process, parent_process", - "rule_description": "A process, $process$, is spawned by netsh.exe. It is highly unlikely for netsh to have any child processes.", - "rule_title": "Process spawned by netsh.exe detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.process) min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process=\"C:\\Windows\\System32\\netsh.exe\" by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`|`ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest, process", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search looks for all processes with the parent process \"c:\\Windows\\System32\\netsh.exe\" and returns the process, the command line used to execute it, the host name, and the user context under which it ran.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.", - "id": "b89919ed-fe5f-492c-b139-95dbb162041e", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", - "name": "Investigate Web Activity From Host", - "type": "splunk" - } - ], - "known_false_positives": "It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Command-Line Interface", - "Persistence" - ], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-02", - "name": "Processes created by netsh", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", + "name": "Investigate Web Activity From Host", + "type": "splunk" + } + ], + "known_false_positives": "It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Command-Line Interface", + "Persistence" + ], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2018-11-02", + "name": "Processes created by netsh", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/new_aws_console_login_by_user.json b/detections/new_aws_console_login_by_user.json index 4d354dc5c6..8422e87ee6 100644 --- a/detections/new_aws_console_login_by_user.json +++ b/detections/new_aws_console_login_by_user.json @@ -1,111 +1,111 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", - "name": "Previously seen users in CloudTrail", - "type": "splunk" + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", + "name": "Previously seen users in CloudTrail", + "type": "splunk" + }, + { + "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", + "name": "Update previously seen users in CloudTrail", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-02-26", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "user", + "rule_description": "A new user has logged into the AWS console", + "rule_title": "AWS Console Login by New User" }, - { - "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", - "name": "Update previously seen users in CloudTrail", - "type": "splunk" - } - ], - "confidence": "medium", - "creation_date": "2018-02-26", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "user", - "rule_description": "A new user has logged into the AWS console", - "rule_title": "AWS Console Login by New User" - }, - "risk": { - "risk_object": "user", - "risk_object_type": [ - "user" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "5 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn as user |stats earliest(_time) as earliest latest(_time) as latest by user | inputlookup append=t previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user | eval userStatus=if(earliest >= relative_time(now(), \"-70m@m\"), \"First Time Logging into AWS Console\",\"Previously Seen User\") | convert ctime(earliest) ctime(latest) | where userStatus =\"First Time Logging into AWS Console\" ", - "suppress": { - "suppress_fields": "user", - "suppress_period": "86400s" - } - } - } - }, - "eli5": "In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console and group the events using ARN value. Using the previously_seen_users_console_logins.csv lookup file created using the support search, we compare the ARN to all the previously seen users logging into the AWS console. The eval and if functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour.", - "entities": [ - "user" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the \"Previously seen users in CloudTrail\" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run \"Update previously seen users in CloudTrail\" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines.", - "id": "ada0f478-84a8-4641-a3f3-d82362dffd75", - "investigations": [ - { - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", - "name": "AWS Investigate User Activities By ARN", - "type": "splunk" - } - ], - "known_false_positives": "When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "risk": { + "risk_object": "user", + "risk_object_type": [ + "user" + ], + "risk_score": 30 }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" + "schedule": { + "cron_schedule": "5 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn as user |stats earliest(_time) as earliest latest(_time) as latest by user | inputlookup append=t previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user | eval userStatus=if(earliest >= relative_time(now(), \"-70m@m\"), \"First Time Logging into AWS Console\",\"Previously Seen User\") | convert ctime(earliest) ctime(latest) | where userStatus =\"First Time Logging into AWS Console\" ", + "suppress": { + "suppress_fields": "user", + "suppress_period": "86400s" } - ], - "mappings": { - "cis20": [ - "CIS 16" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Credential Access" - ], - "nist": [ - "DE.DP", - "DE.AE" - ] + } + } + }, + "eli5": "In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen users logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour.", + "entities": [ + "user" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the \"Previously seen users in CloudTrail\" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run \"Update previously seen users in CloudTrail\" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines.", + "id": "ada0f478-84a8-4641-a3f3-d82362dffd75", + "investigations": [ + { + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", + "name": "AWS Investigate User Activities By ARN", + "type": "splunk" + } + ], + "known_false_positives": "When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" }, - "modification_date": "2018-04-30", - "name": "Detect new user AWS Console Login", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "mappings": { + "cis20": [ + "CIS 16" ], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Credential Access" + ], + "nist": [ + "DE.DP", + "DE.AE" + ] + }, + "modification_date": "2018-04-30", + "name": "Detect new user AWS Console Login", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/new_aws_console_login_city_by_user.json b/detections/new_aws_console_login_city_by_user.json index a97dce855e..f49dc97349 100644 --- a/detections/new_aws_console_login_city_by_user.json +++ b/detections/new_aws_console_login_city_by_user.json @@ -1,117 +1,117 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", - "name": "Previously seen users in CloudTrail", - "type": "splunk" - }, - { - "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", - "name": "Update previously seen users in CloudTrail", - "type": "splunk" - } - ], - "confidence": "medium", - "creation_date": "2018-04-24", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", + "name": "Previously seen users in CloudTrail", + "type": "splunk" }, - "description": "This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "user", - "rule_description": "A user has logged into the AWS console from a new city.", - "rule_title": "AWS Console Login by User from New City" - }, - "risk": { - "risk_object": "user", - "risk_object_type": [ - "user" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "5 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user City | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(earliest >= relative_time(now(), \"@d\"), \"New City\",\"Previously Seen City\") | eval UserData=if(earliestseen >= relative_time(now(), \"@d\") OR isnull(earliestseen), \"New User\",\"Old User\") | where userStatus=\"New City\" AND UserData=\"Old User\" | convert ctime(earliest) ctime(latest) ctime(earliestseen) | table user City userStatus earliest latest earliestseen", - "suppress": { - "suppress_fields": "user", - "suppress_period": "86400s" - } - } - } - }, - "eli5": "In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new city and group the events using ARN value. Using the previously_seen_users_console_logins.csv lookup file created using the support search, we compare the ARN to all the previously seen ARN and city combinations logging into the AWS console. The eval and if functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour.", - "entities": [ - "user" + { + "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", + "name": "Update previously seen users in CloudTrail", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-04-24", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the \"Previously seen users in CloudTrail\" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run \"Update previously seen users in CloudTrail\" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines.", - "id": "121b0b11-f8ac-4ed6-a132-3800ca4fc07a", - "investigations": [ - { - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", - "name": "AWS Investigate User Activities By ARN", - "type": "splunk" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "known_false_positives": "When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "user", + "rule_description": "A user has logged into the AWS console from a new city.", + "rule_title": "AWS Console Login by User from New City" }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" - } - ], - "mappings": { - "cis20": [ - "CIS 16" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Credential Access" - ], - "nist": [ - "DE.DP", - "DE.AE" - ] - }, - "modification_date": "2018-04-30", - "name": "Detect AWS Console Login by User from New City", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "risk": { + "risk_object": "user", + "risk_object_type": [ + "user" + ], + "risk_score": 30 }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" + "schedule": { + "cron_schedule": "5 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user City | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(earliest >= relative_time(now(), \"@d\"), \"New City\",\"Previously Seen City\") | eval UserData=if(earliestseen >= relative_time(now(), \"@d\") OR isnull(earliestseen), \"New User\",\"Old User\") | where userStatus=\"New City\" AND UserData=\"Old User\" | convert ctime(earliest) ctime(latest) ctime(earliestseen) | table user City userStatus earliest latest earliestseen", + "suppress": { + "suppress_fields": "user", + "suppress_period": "86400s" } + } + } + }, + "eli5": "In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new city and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen ARN and city combinations logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour.", + "entities": [ + "user" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the \"Previously seen users in CloudTrail\" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run \"Update previously seen users in CloudTrail\" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines.", + "id": "121b0b11-f8ac-4ed6-a132-3800ca4fc07a", + "investigations": [ + { + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", + "name": "AWS Investigate User Activities By ARN", + "type": "splunk" + } + ], + "known_false_positives": "When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + }, + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "mappings": { + "cis20": [ + "CIS 16" ], - "responses": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Credential Access" + ], + "nist": [ + "DE.DP", + "DE.AE" + ] + }, + "modification_date": "2018-04-30", + "name": "Detect AWS Console Login by User from New City", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + }, + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "responses": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/new_aws_console_login_country_by_user.json b/detections/new_aws_console_login_country_by_user.json index dfcbcc3e88..1533a8dd76 100644 --- a/detections/new_aws_console_login_country_by_user.json +++ b/detections/new_aws_console_login_country_by_user.json @@ -1,116 +1,116 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", - "name": "Previously seen users in CloudTrail", - "type": "splunk" - }, - { - "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", - "name": "Update previously seen users in CloudTrail", - "type": "splunk" - } - ], - "confidence": "medium", - "creation_date": "2018-04-24", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", + "name": "Previously seen users in CloudTrail", + "type": "splunk" }, - "description": "This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "user", - "rule_description": "A user has logged into the AWS console from a new country.", - "rule_title": "AWS Console Login by User from New Country" - }, - "risk": { - "risk_object": "user", - "risk_object_type": [ - "user" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "5 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user Country | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(earliest >= relative_time(now(), \"@d\"), \"New Country\",\"Previously Seen Country\") | eval UserData=if(earliestseen >= relative_time(now(), \"@d\") OR isnull(earliestseen), \"New User\",\"Old User\") | where userStatus=\"New Country\" AND UserData=\"Old User\" | convert ctime(earliest) ctime(latest) ctime(earliestseen) | table user Country userStatus earliest latest earliestseen", - "suppress": { - "suppress_fields": "user", - "suppress_period": "86400s" - } - } - } - }, - "eli5": "In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new country and group the events using ARN value. Using the previously_seen_users_console_logins.csv lookup file created using the support search, we compare the ARN to all the previously seen ARN and country combinations logging into the AWS console. The eval and if functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour.", - "entities": [ - "user" + { + "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", + "name": "Update previously seen users in CloudTrail", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-04-24", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the \"Previously seen users in CloudTrail\" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run \"Update previously seen users in CloudTrail\" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines.", - "id": "67bd3def-c41c-4bf6-837b-ae196b4257c6", - "investigations": [ - { - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", - "name": "AWS Investigate User Activities By ARN", - "type": "splunk" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "known_false_positives": "When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "user", + "rule_description": "A user has logged into the AWS console from a new country.", + "rule_title": "AWS Console Login by User from New Country" }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" - } - ], - "mappings": { - "cis20": [ - "CIS 16" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Credential Access" - ], - "nist": [ - "DE.DP", - "DE.AE" - ] - }, - "modification_date": "2018-04-30", - "name": "Detect AWS Console Login by User from New Country", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "risk": { + "risk_object": "user", + "risk_object_type": [ + "user" + ], + "risk_score": 30 }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" + "schedule": { + "cron_schedule": "5 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user Country | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(earliest >= relative_time(now(), \"@d\"), \"New Country\",\"Previously Seen Country\") | eval UserData=if(earliestseen >= relative_time(now(), \"@d\") OR isnull(earliestseen), \"New User\",\"Old User\") | where userStatus=\"New Country\" AND UserData=\"Old User\" | convert ctime(earliest) ctime(latest) ctime(earliestseen) | table user Country userStatus earliest latest earliestseen", + "suppress": { + "suppress_fields": "user", + "suppress_period": "86400s" } + } + } + }, + "eli5": "In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new country and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen ARN and country combinations logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour.", + "entities": [ + "user" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the \"Previously seen users in CloudTrail\" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run \"Update previously seen users in CloudTrail\" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines.", + "id": "67bd3def-c41c-4bf6-837b-ae196b4257c6", + "investigations": [ + { + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", + "name": "AWS Investigate User Activities By ARN", + "type": "splunk" + } + ], + "known_false_positives": "When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + }, + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "mappings": { + "cis20": [ + "CIS 16" ], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Credential Access" + ], + "nist": [ + "DE.DP", + "DE.AE" + ] + }, + "modification_date": "2018-04-30", + "name": "Detect AWS Console Login by User from New Country", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + }, + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/new_aws_console_login_region_by_user.json b/detections/new_aws_console_login_region_by_user.json index 0bebee4910..415d443a17 100644 --- a/detections/new_aws_console_login_region_by_user.json +++ b/detections/new_aws_console_login_region_by_user.json @@ -1,117 +1,117 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", - "name": "Previously seen users in CloudTrail", - "type": "splunk" - }, - { - "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", - "name": "Update previously seen users in CloudTrail", - "type": "splunk" - } - ], - "confidence": "medium", - "creation_date": "2018-04-24", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd03", + "name": "Previously seen users in CloudTrail", + "type": "splunk" }, - "description": "This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "user", - "rule_description": "A user has logged into the AWS console from a new region.", - "rule_title": "AWS Console Login by User from New Region" - }, - "risk": { - "risk_object": "user", - "risk_object_type": [ - "user" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "5 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user Region | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(earliest >= relative_time(now(), \"@d\"), \"New Region\",\"Previously Seen Region\") | eval UserData=if(earliestseen >= relative_time(now(), \"@d\") OR isnull(earliestseen), \"New User\",\"Old User\") | where userStatus=\"New Region\" AND UserData=\"Old User\" | convert ctime(earliest) ctime(latest) ctime(earliestseen) | table user Region userStatus earliest latest earliestseen", - "suppress": { - "suppress_fields": "user", - "suppress_period": "86400s" - } - } - } - }, - "eli5": "In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new region and group the events using ARN value. Using the previously_seen_users_console_logins.csv lookup file created using the support search, we compare the ARN to all the previously seen ARN and region combinations logging into the AWS console. The eval and if functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour.", - "entities": [ - "user" + { + "id": "06c036e6-d6d7-4daa-bd76-411c3d356031", + "name": "Update previously seen users in CloudTrail", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-04-24", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the \"Previously seen users in CloudTrail\" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run \"Update previously seen users in CloudTrail\" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines.", - "id": "9f31aa8e-e37c-46bc-bce1-8b3be646d026", - "investigations": [ - { - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", - "name": "AWS Investigate User Activities By ARN", - "type": "splunk" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "known_false_positives": "When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "user", + "rule_description": "A user has logged into the AWS console from a new region.", + "rule_title": "AWS Console Login by User from New Region" }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" - } - ], - "mappings": { - "cis20": [ - "CIS 16" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Credential Access" - ], - "nist": [ - "DE.DP", - "DE.AE" - ] - }, - "modification_date": "2018-04-30", - "name": "Detect AWS Console Login by User from New Region", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "risk": { + "risk_object": "user", + "risk_object_type": [ + "user" + ], + "risk_score": 30 }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" + "schedule": { + "cron_schedule": "5 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) as earliest max(latest) as latest by user Region | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(earliest) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(earliest >= relative_time(now(), \"@d\"), \"New Region\",\"Previously Seen Region\") | eval UserData=if(earliestseen >= relative_time(now(), \"@d\") OR isnull(earliestseen), \"New User\",\"Old User\") | where userStatus=\"New Region\" AND UserData=\"Old User\" | convert ctime(earliest) ctime(latest) ctime(earliestseen) | table user Region userStatus earliest latest earliestseen", + "suppress": { + "suppress_fields": "user", + "suppress_period": "86400s" } + } + } + }, + "eli5": "In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new region and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen ARN and region combinations logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour.", + "entities": [ + "user" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the \"Previously seen users in CloudTrail\" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run \"Update previously seen users in CloudTrail\" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines.", + "id": "9f31aa8e-e37c-46bc-bce1-8b3be646d026", + "investigations": [ + { + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", + "name": "AWS Investigate User Activities By ARN", + "type": "splunk" + } + ], + "known_false_positives": "When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + }, + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "mappings": { + "cis20": [ + "CIS 16" ], - "responses": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Credential Access" + ], + "nist": [ + "DE.DP", + "DE.AE" + ] + }, + "modification_date": "2018-04-30", + "name": "Detect AWS Console Login by User from New Region", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + }, + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "responses": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/new_connections_to_routers.json b/detections/new_connections_to_routers.json index c537003156..9560cfde37 100644 --- a/detections/new_connections_to_routers.json +++ b/detections/new_connections_to_routers.json @@ -1,119 +1,119 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2017-07-18", - "data_metadata": { - "data_models": [ - "Authentication" - ], - "data_source": [ - "Network Equipment" - ], - "providing_technologies": [ - "Active Directory", - "Palo Alto Firewall" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2017-07-18", + "data_metadata": { + "data_models": [ + "Authentication" + ], + "data_source": [ + "Network Equipment" + ], + "providing_technologies": [ + "Active Directory", + "Palo Alto Firewall" + ] + }, + "description": "The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user", + "rule_description": "This search detects new connections made to the router devices at $dest$", + "rule_title": "Detected a New Router Login" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 20 + }, + "schedule": { + "cron_schedule": "0 0 * * *", + "earliest_time": "-30d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count earliest(_time) as earliest latest(_time) as latest from datamodel=Authentication where Authentication.dest_category=router by Authentication.dest Authentication.user| eval isOutlier=if(earliest >= relative_time(now(), \"-30d@d\"), 1, 0) | where isOutlier=1| `ctime(earliest)`| `ctime(latest)` | `drop_dm_object_name(\"Authentication\")`", + "suppress": { + "suppress_fields": "dest,user", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "Attackers will often attempt to compromise network devices such as routers for a variety of nefarious purposes, including modifying VPN settings or re-routing network traffic. Typically, only a relatively small number of user accounts log into these devices on a regular basis. This search identifies 'new' connections to your routers by checking to see if a similar login was made in the last 30 days. Routers are identified by checking the IP address against those categorized as a \"router\" in the ES assets and identity framework.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must ensure the network router devices are categorized as \"router\" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure.", + "id": "104658f4-afdc-499e-9719-17243rr826f1", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user", - "rule_description": "This search detects new connections made to the router devices at $dest$", - "rule_title": "Detected a New Router Login" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 20 - }, - "schedule": { - "cron_schedule": "0 0 * * *", - "earliest_time": "-30d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count earliest(_time) as earliest latest(_time) as latest from datamodel=Authentication where Authentication.dest_category=router by Authentication.dest Authentication.user| eval isOutlier=if(earliest >= relative_time(now(), \"-30d@d\"), 1, 0) | where isOutlier=1| `ctime(earliest)`| `ctime(latest)` | `drop_dm_object_name(\"Authentication\")`", - "suppress": { - "suppress_fields": "dest,user", - "suppress_period": "86400s" - } - } - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "eli5": "Attackers will often attempt to compromise network devices such as routers for a variety of nefarious purposes, including modifying VPN settings or re-routing network traffic. Typically, only a relatively small number of user accounts log into these devices on a regular basis. This search identifies 'new' connections to your routers by checking to see if a similar login was made in the last 30 days. Routers are identified by checking the IP address against those categorized as a \"router\" in the ES assets and identity framework.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must ensure the network router devices are categorized as \"router\" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure.", - "id": "104658f4-afdc-499e-9719-17243rr826f1", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Legitimate router connections may appear as new connections", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 11" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "nist": [ - "PR.PT", - "PR.AC", - "PR.IP" - ] + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "modification_date": "2017-09-12", - "name": "Detect New Login Attempts to Routers", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Legitimate router connections may appear as new connections", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 11" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "nist": [ + "PR.PT", + "PR.AC", + "PR.IP" + ] + }, + "modification_date": "2017-09-12", + "name": "Detect New Login Attempts to Routers", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/outbound_smb_connections.json b/detections/outbound_smb_connections.json index 2c1dc9e076..81f609cfee 100644 --- a/detections/outbound_smb_connections.json +++ b/detections/outbound_smb_connections.json @@ -1,133 +1,133 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-03-20", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communications" - ], - "providing_technologies": [ - "Bro", - "Splunk Stream" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-03-20", + "data_metadata": { + "data_models": [ + "Network_Traffic" + ], + "data_source": [ + "Network Communications" + ], + "providing_technologies": [ + "Bro", + "Splunk Stream" + ] + }, + "description": "This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src_ip, dest_ip", + "rule_description": "Outbound SMB network traffic detected.", + "rule_title": "Outbound SMB traffic from $src_ip$ to $dest_ip$ detected" + }, + "risk": { + "risk_object": "src_ip", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count earliest(_time) as earliest latest(_time) as latest values(All_Traffic.action) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb) by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name(\"All_Traffic\")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | convert ctime(earliest) ctime(latest)", + "suppress": { + "suppress_fields": "src_ip", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "In this search, we are looking for the network connections that were not blocked by the firewall and that are destined for destination port 139 or 445. We then filter out events that have Classless Inter-Domain Routing (CIDR) blocks categorized as internal in the `assets_by_cidr.csv` lookup file which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. Since we are only looking for outbound traffic from the hosts made to the Internet, we filter out traffic whose destination IP address is private.", + "entities": [ + "src_ip" + ], + "how_to_implement": "In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model", + "id": "7f5fb3e1-4209-414-90db-0ec21b936378", + "investigations": [ + { + "id": "9925d08f-561e-4faa-8912-e3888a842341", + "name": "Get Process Information For Port Activity", + "type": "splunk" }, - "description": "This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src_ip, dest_ip", - "rule_description": "Outbound SMB network traffic detected.", - "rule_title": "Outbound SMB traffic from $src_ip$ to $dest_ip$ detected" - }, - "risk": { - "risk_object": "src_ip", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count earliest(_time) as earliest latest(_time) as latest values(All_Traffic.action) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb) by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name(\"All_Traffic\")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | convert ctime(earliest) ctime(latest)", - "suppress": { - "suppress_fields": "src_ip", - "suppress_period": "28800s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "In this search, we are looking for the network connections that were not blocked by the firewall and that are destined for destination port 139 or 445. We then filter out events that have Classless Inter-Domain Routing (CIDR) blocks categorized as internal in the assets_by_cidr.csv lookup file which is located in $SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/. Since we are only looking for outbound traffic from the hosts made to the Internet, we filter out traffic whose destination IP address is private.", - "entities": [ - "src_ip" - ], - "how_to_implement": "In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named internal to the CIDRs that host the company's assets in assets_by_cidr.csv lookup file, which is located in $SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model", - "id": "7f5fb3e1-4209-414-90db-0ec21b936378", - "investigations": [ - { - "id": "9925d08f-561e-4faa-8912-e3888a842341", - "name": "Get Process Information For Port Activity", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as internal in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 12" - ], - "kill_chain_phases": [ - "Actions on Objectives", - "Command and Control" - ], - "mitre_attack": [ - "Commonly Used Port", - "Credential Access", - "Lateral Movement" - ], - "nist": [ - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-03-20", - "name": "Detect Outbound SMB Traffic", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 12" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Actions on Objectives", + "Command and Control" + ], + "mitre_attack": [ + "Commonly Used Port", + "Credential Access", + "Lateral Movement" + ], + "nist": [ + "DE.CM" + ] + }, + "modification_date": "2018-03-20", + "name": "Detect Outbound SMB Traffic", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/overwrite_accessibility_binaries.json b/detections/overwrite_accessibility_binaries.json index a407190557..f49169855b 100644 --- a/detections/overwrite_accessibility_binaries.json +++ b/detections/overwrite_accessibility_binaries.json @@ -1,133 +1,133 @@ { - "asset_type": "Endpoint", - "confidence": "high", - "creation_date": "2017-12-07", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon" - ] + "asset_type": "Endpoint", + "confidence": "high", + "creation_date": "2017-12-07", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon" + ] + }, + "description": "Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, file_name", + "rule_description": "A file, $file_name$, was created in the default shim database directory on $dest.", + "rule_title": "Modification to accessibility binary, $file_path$, was detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 40 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where (Filesystem.file_path=*\\Windows\\System32\\sethc.exe* OR Filesystem.file_path=*\\Windows\\System32\\utilman.exe* OR Filesystem.file_path=*\\Windows\\System32\\osk.exe* OR Filesystem.file_path=*\\Windows\\System32\\Magnify.exe* OR Filesystem.file_path=*\\Windows\\System32\\Narrator.exe* OR Filesystem.file_path=*\\Windows\\System32\\DisplaySwitch.exe* OR Filesystem.file_path=*\\Windows\\System32\\AtBroker.exe*) by Filesystem.file_name Filesystem.dest | `drop_dm_object_name(Filesystem)` | `ctime(lastTime)` | `ctime(firstTime)`", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "This search returns all the different accessibility binaries that have been modified for each Windows host.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.", + "id": "13c2f6c3-10c5-4deb-9ba1-7c4460ebe4ae", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, file_name", - "rule_description": "A file, $file_name$, was created in the default shim database directory on $dest.", - "rule_title": "Modification to accessibility binary, $file_path$, was detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 40 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where (Filesystem.file_path=*\\Windows\\System32\\sethc.exe* OR Filesystem.file_path=*\\Windows\\System32\\utilman.exe* OR Filesystem.file_path=*\\Windows\\System32\\osk.exe* OR Filesystem.file_path=*\\Windows\\System32\\Magnify.exe* OR Filesystem.file_path=*\\Windows\\System32\\Narrator.exe* OR Filesystem.file_path=*\\Windows\\System32\\DisplaySwitch.exe* OR Filesystem.file_path=*\\Windows\\System32\\AtBroker.exe*) by Filesystem.file_name Filesystem.dest | `drop_dm_object_name(Filesystem)` | `ctime(lastTime)` | `ctime(firstTime)`", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "14400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search returns all the different accessibility binaries that have been modified for each Windows host.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.", - "id": "13c2f6c3-10c5-4deb-9ba1-7c4460ebe4ae", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Persistence", - "Accessibility Features" - ], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-15", - "name": "Overwriting Accessibility Binaries", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Persistence", + "Accessibility Features" + ], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2018-11-15", + "name": "Overwriting Accessibility Binaries", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/password_sharing.json b/detections/password_sharing.json index d32ef10c95..e30d216668 100644 --- a/detections/password_sharing.json +++ b/detections/password_sharing.json @@ -1,110 +1,110 @@ { - "asset_type": "account", - "confidence": "medium", - "creation_date": "2018-07-12", - "data_metadata": { - "data_source": [ - "Network Communications" - ], - "data_sourcetypes": [ - "stream:http" - ], - "providing_technologies": [ - "Splunk Stream", - "Palo Alto Firewall", - "Bro" - ] - }, - "description": "This search is used to identify user accounts that share a common password.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "user", - "rule_description": "This search is used to identify user accounts, $user$, that share common passwords", - "rule_title": "Web Fraud Detection: Password Sharing Across Accounts" - }, - "risk": { - "risk_object": "user", - "risk_object_type": [ - "other" - ], - "risk_score": 10 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=stream:http http_content_type=text* uri=/magento2/customer/account/loginPost* | rex field=form_data \"login\\[username\\]=(?[^&|^$]+)\" | rex field=form_data \"login\\[password\\]=(?[^&|^$]+)\" | stats dc(Username) as UniqueUsernames values(Username) as user list(src_ip) as src_ip by Password|where UniqueUsernames>5", - "suppress": { - "suppress_fields": "user", - "suppress_period": "3600s" - } - } - } - }, - "eli5": "A common password across user accounts generally indicates that the users are choosing poor passwords or that a fraudster has a common password across multiple accounts embedded within a script. The search will extract the username and password information from the form_data field, then calculate the number and values for usernames that have the same passwords. Finally, it outputs the values where the unique usernames sharing passwords are greater than 5", - "entities": [ - "user" + "asset_type": "account", + "confidence": "medium", + "creation_date": "2018-07-12", + "data_metadata": { + "data_source": [ + "Network Communications" ], - "how_to_implement": "We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream.", - "id": "31337a1a-53b9-4e05-96e9-55c934cb71d3", - "investigations": [ - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" + "data_sourcetypes": [ + "stream:http" + ], + "providing_technologies": [ + "Splunk Stream", + "Palo Alto Firewall", + "Bro" + ] + }, + "description": "This search is used to identify user accounts that share a common password.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "user", + "rule_description": "This search is used to identify user accounts, $user$, that share common passwords", + "rule_title": "Web Fraud Detection: Password Sharing Across Accounts" }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" + "risk": { + "risk_object": "user", + "risk_object_type": [ + "other" + ], + "risk_score": 10 }, - { - "id": "bc91a8cf-35e7-4bb2-1120-e756cc06fd89", - "name": "Get Web Session Information via session_id", - "type": "splunk" + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" }, - { - "id": "5df39b3f-447d-4869-b673-8f45ad4616fe", - "name": "Get Emails From Specific Sender", - "type": "splunk" + "search": "sourcetype=stream:http http_content_type=text* uri=/magento2/customer/account/loginPost* | rex field=form_data \"login\\[username\\]=(?[^&|^$]+)\" | rex field=form_data \"login\\[password\\]=(?[^&|^$]+)\" | stats dc(Username) as UniqueUsernames values(Username) as user list(src_ip) as src_ip by Password|where UniqueUsernames>5", + "suppress": { + "suppress_fields": "user", + "suppress_period": "3600s" } - ], - "known_false_positives": "As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior.", - "maintainers": [ - { - "company": "Splunk", - "email": "Mayhem@splunk.com", - "name": "Jim Apger" - } - ], - "mappings": { - "cis20": [ - "CIS 16" - ], - "nist": [ - "DE.DP" - ] + } + } + }, + "eli5": "A common password across user accounts generally indicates that the users are choosing poor passwords or that a fraudster has a common password across multiple accounts embedded within a script. The search will extract the username and password information from the form_data field, then calculate the number and values for usernames that have the same passwords. Finally, it outputs the values where the unique usernames sharing passwords are greater than 5", + "entities": [ + "user" + ], + "how_to_implement": "We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream.", + "id": "31337a1a-53b9-4e05-96e9-55c934cb71d3", + "investigations": [ + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "modification_date": "2018-10-08", - "name": "Web Fraud - Password Sharing Across Accounts", - "original_authors": [ - { - "company": "Splunk", - "email": "Mayhem@splunk.com", - "name": "Jim Apger" - } + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-1120-e756cc06fd89", + "name": "Get Web Session Information via session_id", + "type": "splunk" + }, + { + "id": "5df39b3f-447d-4869-b673-8f45ad4616fe", + "name": "Get Emails From Specific Sender", + "type": "splunk" + } + ], + "known_false_positives": "As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior.", + "maintainers": [ + { + "company": "Splunk", + "email": "Mayhem@splunk.com", + "name": "Jim Apger" + } + ], + "mappings": { + "cis20": [ + "CIS 16" ], - "references": [ - "https://en.wikipedia.org/wiki/Session_ID", - "https://en.wikipedia.org/wiki/Session_(computer_science)", - "https://en.wikipedia.org/wiki/HTTP_cookie", - "https://splunkbase.splunk.com/app/1809/" - ], - "security_domain": "threat", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "nist": [ + "DE.DP" + ] + }, + "modification_date": "2018-10-08", + "name": "Web Fraud - Password Sharing Across Accounts", + "original_authors": [ + { + "company": "Splunk", + "email": "Mayhem@splunk.com", + "name": "Jim Apger" + } + ], + "references": [ + "https://en.wikipedia.org/wiki/Session_ID", + "https://en.wikipedia.org/wiki/Session_(computer_science)", + "https://en.wikipedia.org/wiki/HTTP_cookie", + "https://splunkbase.splunk.com/app/1809/" + ], + "security_domain": "threat", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/path_interception_program.exe.json b/detections/path_interception_program.exe.json index fcae8c01b0..a7ed8778ed 100644 --- a/detections/path_interception_program.exe.json +++ b/detections/path_interception_program.exe.json @@ -1,134 +1,134 @@ { - "asset_type": "", - "confidence": "medium", - "creation_date": "2017-11-16", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Tanium", - "Ziften" - ] + "asset_type": "", + "confidence": "medium", + "creation_date": "2017-11-16", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Tanium", + "Ziften" + ] + }, + "description": "The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, file_path, file_name", + "rule_description": "A potentially malicious file program.exe was detected on the C: drive. The creation of this file is often associated with a motive to perform a path interception attack. ", + "rule_title": "Path Interception attempt discovered $dest$ via creation of program.exe" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "30 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where Filesystem.file_path=\"C:\\\\program.exe\" by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `ctime(lastTime)` | `ctime(firstTime)`", + "suppress": { + "suppress_fields": "dest, file_path, file_name", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search queries the Endpoint file-system data model node to list out all the values of destination machines, as well as the values of file hashes and file paths that have the file \"program.exe\" in the C: drive. Path interception occurs when an executable is placed in a specific path so that it is executed by an application instead of by the intended target. In this case, applications vulnerable to path interception (because of unquoted service paths with spaces in Windows registry) allow attackers to execute maliciously crafted program.exes.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes.", + "id": "c77162d3-f93c-45cc-80c8-22f6v5264g9f", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, file_path, file_name", - "rule_description": "A potentially malicious file program.exe was detected on the C: drive. The creation of this file is often associated with a motive to perform a path interception attack. ", - "rule_title": "Path Interception attempt discovered $dest$ via creation of program.exe" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "30 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where Filesystem.file_path=\"C:\\\\program.exe\" by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `ctime(lastTime)` | `ctime(firstTime)`", - "suppress": { - "suppress_fields": "dest, file_path, file_name", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search queries the Endpoint file-system data model node to list out all the values of destination machines, as well as the values of file hashes and file paths that have the file \"program.exe\" in the C: drive. Path interception occurs when an executable is placed in a specific path so that it is executed by an application instead of by the intended target. In this case, applications vulnerable to path interception (because of unquoted service paths with spaces in Windows registry) allow attackers to execute maliciously crafted program.exes.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes.", - "id": "c77162d3-f93c-45cc-80c8-22f6v5264g9f", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Privilege Escalation", - "Persistence" - ], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-15", - "name": "Detect Path Interception By Creation Of program.exe", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Privilege Escalation", + "Persistence" + ], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2018-11-15", + "name": "Detect Path Interception By Creation Of program.exe", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/port_monitor_via_registry.json b/detections/port_monitor_via_registry.json index 465764b675..2b306e7513 100644 --- a/detections/port_monitor_via_registry.json +++ b/detections/port_monitor_via_registry.json @@ -1,141 +1,141 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2017-12-01", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2017-12-01", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon" + ] + }, + "description": "This search looks for registry activity associated with modifications to the registry key `HKLM\\SYSTEM\\CurrentControlSet\\Control\\Print\\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, registry_path", + "rule_description": "A registry key associated with adding print monitors can potentially be misused by giving it a path of a malicious .dll in the registry.", + "rule_title": "Registry Key changes for Print Monitors detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 30 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.action=modified AND Registry.registry_path=\"*CurrentControlSet\\\\Control\\\\Print\\\\Monitors*\" by Registry.dest, Registry.registry_key_name Registry.status Registry.user Registry.registry_path Registry.action | `drop_dm_object_name(Registry)`", + "suppress": { + "suppress_fields": "dest, registry_path", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "In this search, we look for modifications to registry keys used for adding print-monitor entries on Microsoft platforms via the `registry_path` field in the endpoint data model. It then provides the destination, command used to initiate the change, the user who conducted this activity, the resource affected (registry_key_name), and the entire path of the registry.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications.", + "id": "f5f6af30-7ba7-4295-bfe9-07de87c01bbc", + "investigations": [ + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", + "name": "Get Registry Activities", + "type": "splunk" }, - "description": "This search looks for registry activity associated with modifications to the registry key HKLM\\SYSTEM\\CurrentControlSet\\Control\\Print\\Monitors. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, registry_path", - "rule_description": "A registry key associated with adding print monitors can potentially be misused by giving it a path of a malicious .dll in the registry.", - "rule_title": "Registry Key changes for Print Monitors detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.action=modified AND Registry.registry_path=\"*CurrentControlSet\\\\Control\\\\Print\\\\Monitors*\" by Registry.dest, Registry.registry_key_name Registry.status Registry.user Registry.registry_path Registry.action | `drop_dm_object_name(Registry)`", - "suppress": { - "suppress_fields": "dest, registry_path", - "suppress_period": "86400s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "In this search, we look for modifications to registry keys used for adding print-monitor entries on Microsoft platforms via the registry_path field in the endpoint data model. It then provides the destination, command used to initiate the change, the user who conducted this activity, the resource affected (registry_key_name), and the entire path of the registry.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications.", - "id": "f5f6af30-7ba7-4295-bfe9-07de87c01bbc", - "investigations": [ - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", - "name": "Get Registry Activities", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "You will encounter noise from legitimate print-monitor registry entries.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8", - "CIS 5" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Persistence", - "Privilege Escalation", - "Local Port Monitor" - ], - "nist": [ - "PR.PT", - "DE.CM", - "PR.AC" - ] + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "modification_date": "2018-11-02", - "name": "Monitor Registry Keys for Print Monitors", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "You will encounter noise from legitimate print-monitor registry entries.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8", + "CIS 5" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Persistence", + "Privilege Escalation", + "Local Port Monitor" + ], + "nist": [ + "PR.PT", + "DE.CM", + "PR.AC" + ] + }, + "modification_date": "2018-11-02", + "name": "Monitor Registry Keys for Print Monitors", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/process_with_double_extension.json b/detections/process_with_double_extension.json index 62effcf4da..6e39968e6f 100644 --- a/detections/process_with_double_extension.json +++ b/detections/process_with_double_extension.json @@ -1,138 +1,138 @@ { - "asset_type": "Endpoint", - "confidence": "high", - "creation_date": "2018-01-26", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "high", + "creation_date": "2018-01-26", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the \"real\" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, process", + "rule_description": "The system $dest$ executed a file with a double extension.", + "rule_title": "Process With Multiple Extensions Launched on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 60 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = *.doc.exe OR Processes.process = *.htm.exe OR Processes.process = *.html.exe OR Processes.process = *.txt.exe OR Processes.process = *.pdf.exe OR Processes.process = *.doc.exe by Processes.dest Processes.user Processes.process Processes.parent_process | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(Processes)`", + "suppress": { + "suppress_fields": "dest, process", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "This search uses the \"Application State\" data model to look for process names with specific combinations of double extensions. Relatively straightforward, the search looks for strings in the \"process\" field that match what you're looking for.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node.", + "id": "b06a555e-dce0-417d-a2eb-28a5d8d66ef7", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the \"real\" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, process", - "rule_description": "The system $dest$ executed a file with a double extension.", - "rule_title": "Process With Multiple Extensions Launched on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 60 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = *.doc.exe OR Processes.process = *.htm.exe OR Processes.process = *.html.exe OR Processes.process = *.txt.exe OR Processes.process = *.pdf.exe OR Processes.process = *.doc.exe by Processes.dest Processes.user Processes.process Processes.parent_process | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(Processes)`", - "suppress": { - "suppress_fields": "dest, process", - "suppress_period": "28800s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search uses the \"Application State\" data model to look for process names with specific combinations of double extensions. Relatively straightforward, the search looks for strings in the \"process\" field that match what you're looking for.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node.", - "id": "b06a555e-dce0-417d-a2eb-28a5d8d66ef7", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "None identified.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Persistence", - "Change Default File Association" - ], - "nist": [ - "DE.CM", - "PR.PT", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-02", - "name": "Execution of File with Multiple Extensions", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "None identified.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Persistence", + "Change Default File Association" + ], + "nist": [ + "DE.CM", + "PR.PT", + "PR.IP" + ] + }, + "modification_date": "2018-11-02", + "name": "Execution of File with Multiple Extensions", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/process_with_spaces_before_extension.json b/detections/process_with_spaces_before_extension.json index b37aaa643f..5761d64a6e 100644 --- a/detections/process_with_spaces_before_extension.json +++ b/detections/process_with_spaces_before_extension.json @@ -1,138 +1,138 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-01-26", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-01-26", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest", + "rule_description": "The system $dest$ executed a file with spaces before its extension.", + "rule_title": "Process $process$ with spaces before extension Launched on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 60 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.process_path) as process_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = \"* .*\" by Processes.dest Processes.user Processes.process Processes.process_name | `ctime(firstTime)`| `ctime(lastTime)` | `drop_dm_object_name(Processes)`", + "suppress": { + "suppress_fields": "dest,process", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "This search uses the endpoint data model to look for process names with at least five spaces between the file name and its extension.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.", + "id": "ab0353e6-a956-420b-b724-a8b4846d5d5a", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest", - "rule_description": "The system $dest$ executed a file with spaces before its extension.", - "rule_title": "Process $process$ with spaces before extension Launched on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 60 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.process_path) as process_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = \"* .*\" by Processes.dest Processes.user Processes.process Processes.process_name | `ctime(firstTime)`| `ctime(lastTime)` | `drop_dm_object_name(Processes)`", - "suppress": { - "suppress_fields": "dest,process", - "suppress_period": "28800s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search uses the endpoint data model to look for process names with at least five spaces between the file name and its extension.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.", - "id": "ab0353e6-a956-420b-b724-a8b4846d5d5a", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "None identified.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Persistence", - "Change Default File Association" - ], - "nist": [ - "DE.CM", - "PR.PT", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-01-26", - "name": "Execution of File With Spaces Before Extension", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "None identified.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Persistence", + "Change Default File Association" + ], + "nist": [ + "DE.CM", + "PR.PT", + "PR.IP" + ] + }, + "modification_date": "2018-01-26", + "name": "Execution of File With Spaces Before Extension", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/prohibited_apps_spawning_cmdprompt.json b/detections/prohibited_apps_spawning_cmdprompt.json index 1e6a0edb9a..17893a4928 100644 --- a/detections/prohibited_apps_spawning_cmdprompt.json +++ b/detections/prohibited_apps_spawning_cmdprompt.json @@ -1,157 +1,157 @@ { - "asset_type": "Endpoint", - "baselines": [ - { - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd23", - "name": "Previously seen command line arguments", - "type": "splunk" - }, - { - "id": "d2a4d85b-fc6a-47a0-82f6-bc1ec2ebc459", - "name": "Baseline of Command Line Length - MLTK", - "type": "splunk" - } - ], - "confidence": "medium", - "creation_date": "2017-10-07", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "baselines": [ + { + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd23", + "name": "Previously seen command line arguments", + "type": "splunk" }, - "description": "This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, process, parent_process", - "rule_description": "A prohibited application from prohibited_apps_launching_cmd.csv was leveraged to launch cmd.exe", - "rule_title": "Prohibited application($parent_process$) used to launch cmd.exe on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 80 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.user) as user values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe by Processes.parent_process_name Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)` |search [`prohibited_apps_launching_cmd`]", - "suppress": { - "suppress_fields": "dest, parent_process", - "suppress_period": "86400s" - } - } + { + "id": "d2a4d85b-fc6a-47a0-82f6-bc1ec2ebc459", + "name": "Baseline of Command Line Length - MLTK", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2017-10-07", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, process, parent_process", + "rule_description": "A prohibited application from prohibited_apps_launching_cmd.csv was leveraged to launch cmd.exe", + "rule_title": "Prohibited application($parent_process$) used to launch cmd.exe on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 80 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.user) as user values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe by Processes.parent_process_name Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)` |search [`prohibited_apps_launching_cmd`]", + "suppress": { + "suppress_fields": "dest, parent_process", + "suppress_period": "86400s" } + } + } + }, + "eli5": "Obtaining access to the Command-Line Interface (CLI) is typically a primary attacker goal. Once an attacker has obtained the ability to execute code on a target system, they will often further manipulate the system via commands passed to the CLI. It is also unusual for many applications to spawn a command shell during normal operation, while it is often observed if an application has been compromised in some way. As such, it is often beneficial to look for cmd.exe being executed by processes that are often targeted for exploitation, or that would not spawn cmd.exe in any other circumstances. A lookup file is provided to easily modify the processes that are being watched for execution of cmd.exe.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment.", + "id": "dcfd6b40-42f9-469d-a433-2e53f7486664", + "investigations": [ + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", + "name": "Get Registry Activities", + "type": "splunk" }, - "eli5": "Obtaining access to the Command-Line Interface (CLI) is typically a primary attacker goal. Once an attacker has obtained the ability to execute code on a target system, they will often further manipulate the system via commands passed to the CLI. It is also unusual for many applications to spawn a command shell during normal operation, while it is often observed if an application has been compromised in some way. As such, it is often beneficial to look for cmd.exe being executed by processes that are often targeted for exploitation, or that would not spawn cmd.exe in any other circumstances. A lookup file is provided to easily modify the processes that are being watched for execution of cmd.exe.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, prohibited_apps_launching_cmd.csv, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment.", - "id": "dcfd6b40-42f9-469d-a433-2e53f7486664", - "investigations": [ - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", - "name": "Get Registry Activities", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", - "name": "Investigate Web Activity From Host", - "type": "splunk" - } - ], - "known_false_positives": "There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Exploitation" - ], - "mitre_attack": [ - "Execution", - "Command-Line Interface" - ], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "modification_date": "2018-11-15", - "name": "Detect Prohibited Applications Spawning cmd.exe", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", + "name": "Investigate Web Activity From Host", + "type": "splunk" + } + ], + "known_false_positives": "There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Exploitation" + ], + "mitre_attack": [ + "Execution", + "Command-Line Interface" + ], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2018-11-15", + "name": "Detect Prohibited Applications Spawning cmd.exe", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/prohibited_software_on_endpoint.json b/detections/prohibited_software_on_endpoint.json index 9e3efe37a4..415a86b21d 100644 --- a/detections/prohibited_software_on_endpoint.json +++ b/detections/prohibited_software_on_endpoint.json @@ -1,158 +1,158 @@ { - "asset_type": "Endpoint", - "baselines": [ - { - "id": "251930a5-1451-4428-bb13-eed5775be0ce", - "name": "Add Prohibited Processes to Enterprise Security", - "type": "splunk" - } + "asset_type": "Endpoint", + "baselines": [ + { + "id": "251930a5-1451-4428-bb13-eed5775be0ce", + "name": "Add Prohibited Processes to Enterprise Security", + "type": "splunk" + } + ], + "confidence": "high", + "creation_date": "2017-06-26", + "data_metadata": { + "data_models": [ + "Endpoint" ], - "confidence": "high", - "creation_date": "2017-06-26", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for applications on the endpoint that you have marked as prohibited.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, process, user", + "rule_description": "Prohibited software $process_name$ has been detected on $dest$.", + "rule_title": "Prohibited Software Detected On $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process | `ctime(firstTime)`| `ctime(lastTime)` | `drop_dm_object_name(Processes)` | `prohibited_softwares`", + "suppress": { + "suppress_fields": "dest,user", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search returns the number of times, as well as the first and last time, every process has run for each endpoint and user. It then displays only those processes that you have marked as \"prohibited\" in the Enterprise Security \"Interesting Processes\" table.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or populated via Windows event logs, after enabling process tracking in your Windows audit settings. In addition, you must also have processes marked as \"prohibited\" in the Enterprise Security `interesting processes` table. To include the processes marked as \"prohibited\", which is included with ES Content Updates, run the included search `Support - Add Prohibited Processes to ES`.", + "id": "a51bfe1a-94f0-48cc-b4e4-b6ae50145893", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for applications on the endpoint that you have marked as prohibited.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, process, user", - "rule_description": "Prohibited software $process_name$ has been detected on $dest$.", - "rule_title": "Prohibited Software Detected On $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process | `ctime(firstTime)`| `ctime(lastTime)` | `drop_dm_object_name(Processes)` | `prohibited_softwares`", - "suppress": { - "suppress_fields": "dest,user", - "suppress_period": "86400s" - } - } - } + { + "id": "d98675ed-da43-4a7e-96a7-eeca3232ba8e", + "name": "Get Update Logs For Endpoint", + "type": "splunk" }, - "eli5": "This search returns the number of times, as well as the first and last time, every process has run for each endpoint and user. It then displays only those processes that you have marked as \"prohibited\" in the Enterprise Security \"Interesting Processes\" table.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or populated via Windows event logs, after enabling process tracking in your Windows audit settings. In addition, you must also have processes marked as \"prohibited\" in the Enterprise Security interesting processes table. To include the processes marked as \"prohibited\", which is included with ES Content Updates, run the included search Support - Add Prohibited Processes to ES.", - "id": "a51bfe1a-94f0-48cc-b4e4-b6ae50145893", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "d98675ed-da43-4a7e-96a7-eeca3232ba8e", - "name": "Get Update Logs For Endpoint", - "type": "splunk" - }, - { - "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", - "name": "Get Vulnerability Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", - "name": "Investigate Web Activity From Host", - "type": "splunk" - } - ], - "known_false_positives": "None identified", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 2" - ], - "kill_chain_phases": [ - "Installation", - "Command and Control", - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution" - ], - "nist": [ - "ID.AM", - "PR.DS" - ] + { + "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", + "name": "Get Vulnerability Logs For Endpoint", + "type": "splunk" }, - "modification_date": "2010-11-02", - "name": "Prohibited Software On Endpoint", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", + "name": "Investigate Web Activity From Host", + "type": "splunk" + } + ], + "known_false_positives": "None identified", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 2" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Installation", + "Command and Control", + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution" + ], + "nist": [ + "ID.AM", + "PR.DS" + ] + }, + "modification_date": "2010-11-02", + "name": "Prohibited Software On Endpoint", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/protocols_authenticating_in_cleartext.json b/detections/protocols_authenticating_in_cleartext.json index f140444635..faefc75934 100644 --- a/detections/protocols_authenticating_in_cleartext.json +++ b/detections/protocols_authenticating_in_cleartext.json @@ -1,127 +1,127 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2017-08-03", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communications" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2017-08-03", + "data_metadata": { + "data_models": [ + "Network_Traffic" + ], + "data_source": [ + "Network Communications" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src, dest, user", + "rule_description": "This search looks for the use of cleartext protocols that are known to pass authentication information in the clear. The cleartext credentials are typically passed at the beginning of the session.", + "rule_title": "Possible credential leak over cleartext protocol" + }, + "risk": { + "risk_object": "user", + "risk_object_type": [ + "user" + ], + "risk_score": 60 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.protocol=\"tcp\" AND (All_Traffic.dest_port=\"23\" OR All_Traffic.dest_port=\"143\" OR All_Traffic.dest_port=\"110\" OR (All_Traffic.dest_port=\"21\" AND All_Traffic.user != \"anonymous\")) groupby All_Traffic.user All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(\"All_Traffic\")`", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search is checking for traffic on well-known ports that are associated with protocols that pass authentication in cleartext.", + "entities": [ + "user" + ], + "how_to_implement": "This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model.", + "id": "6923cd64-17a0-453c-b945-81ac2d8c6db9", + "investigations": [ + { + "id": "9925d08f-561e-4faa-8912-e3888a842341", + "name": "Get Process Information For Port Activity", + "type": "splunk" }, - "description": "This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src, dest, user", - "rule_description": "This search looks for the use of cleartext protocols that are known to pass authentication information in the clear. The cleartext credentials are typically passed at the beginning of the session.", - "rule_title": "Possible credential leak over cleartext protocol" - }, - "risk": { - "risk_object": "user", - "risk_object_type": [ - "user" - ], - "risk_score": 60 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.protocol=\"tcp\" AND (All_Traffic.dest_port=\"23\" OR All_Traffic.dest_port=\"143\" OR All_Traffic.dest_port=\"110\" OR (All_Traffic.dest_port=\"21\" AND All_Traffic.user != \"anonymous\")) groupby All_Traffic.user All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(\"All_Traffic\")`", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "86400s" - } - } - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "eli5": "This search is checking for traffic on well-known ports that are associated with protocols that pass authentication in cleartext.", - "entities": [ - "user" - ], - "how_to_implement": "This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model.", - "id": "6923cd64-17a0-453c-b945-81ac2d8c6db9", - "investigations": [ - { - "id": "9925d08f-561e-4faa-8912-e3888a842341", - "name": "Get Process Information For Port Activity", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Some networks may use kerberized FTP or telnet servers, however, this is rare.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 9", - "CIS 14" - ], - "kill_chain_phases": [ - "Reconnaissance", - "Actions on Objectives" - ], - "mitre_attack": [ - "Credential Access", - "Lateral Movement", - "Collection" - ], - "nist": [ - "PR.PT", - "DE.AE", - "PR.AC", - "PR.DS" - ] + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "modification_date": "2017-09-15", - "name": "Protocols passing authentication in cleartext", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Some networks may use kerberized FTP or telnet servers, however, this is rare.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 9", + "CIS 14" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Reconnaissance", + "Actions on Objectives" + ], + "mitre_attack": [ + "Credential Access", + "Lateral Movement", + "Collection" + ], + "nist": [ + "PR.PT", + "DE.AE", + "PR.AC", + "PR.DS" + ] + }, + "modification_date": "2017-09-15", + "name": "Protocols passing authentication in cleartext", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/psexec_accepteula.json b/detections/psexec_accepteula.json index 8331b0ad06..907fffb6dd 100644 --- a/detections/psexec_accepteula.json +++ b/detections/psexec_accepteula.json @@ -1,131 +1,131 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-03-28", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Sysmon" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-03-28", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Sysmon" + ] + }, + "description": "This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest,process_name", + "rule_description": "The process pssxec.exe was run with the -accepteula flag on $dest$ by $user$.", + "rule_title": "PsExec executed with accepteula flag on $dest$." + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 75 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = PsExec.exe Processes.process = \"*accepteula*\" by Processes.process_name Processes.dest Processes.parent_process_name | `drop_dm_object_name(Processes)`| `ctime(firstTime)`| `ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest, process_name", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "In this search, we are looking for the PsExec process with `accepteula` on the command line.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "b89919ed-fe5f-492c-b139-151xb162040e", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for events where PsExec.exe is run with the accepteula flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument accepteula within the command line.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest,process_name", - "rule_description": "The process pssxec.exe was run with the -accepteula flag on $dest$ by $user$.", - "rule_title": "PsExec executed with accepteula flag on $dest$." - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 75 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = PsExec.exe Processes.process = \"*accepteula*\" by Processes.process_name Processes.dest Processes.parent_process_name | `drop_dm_object_name(Processes)`| `ctime(firstTime)`| `ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest, process_name", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "In this search, we are looking for the PsExec process with accepteula on the command line.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "b89919ed-fe5f-492c-b139-151xb162040e", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Administrators can leverage PsExec for accessing remote systems and might pass accepteula as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Command-Line Interface" - ], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2019-02-26", - "name": "Detect PsExec With accepteula Flag", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Command-Line Interface" + ], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2019-02-26", + "name": "Detect PsExec With accepteula Flag", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" } diff --git a/detections/rare_executables_on_endpoint.json b/detections/rare_executables_on_endpoint.json index e28df4571a..ce779ce933 100644 --- a/detections/rare_executables_on_endpoint.json +++ b/detections/rare_executables_on_endpoint.json @@ -1,144 +1,144 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2016-08-09", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2016-08-09", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, process", + "rule_description": "The process $process$ was detected running on $dest. This process is rare in your environment.", + "rule_title": "Rare Process $process$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 20 + }, + "schedule": { + "cron_schedule": "10 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.dest) as dest values(Processes.user) as user min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.process_name | rename Processes.process_name as process | rex field=user \"(?.*)\\\\\\\\(?.*)\" | `ctime(firstTime)`| `ctime(lastTime)`| search [| tstats count from datamodel=Endpoint.Processes by Processes.process_name | rare Processes.process_name limit=30 | rename Processes.process_name as process| `filter_rare_process_whitelist`| table process ]", + "suppress": { + "suppress_fields": "dest, process", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search first executes the subsearch and counts all of your processes to determine the 10 most rare (the limit set is 10). It then filters out whitelisted processes and outputs the first and last time a rare process was encountered, the destination where the process is running, the count of occurrences, and the users who initiated the processes.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment.", + "id": "44fddcb2-8d3b-454c-874e-7c6de5a4f7ac", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, process", - "rule_description": "The process $process$ was detected running on $dest. This process is rare in your environment.", - "rule_title": "Rare Process $process$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 20 - }, - "schedule": { - "cron_schedule": "10 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.dest) as dest values(Processes.user) as user min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.process_name | rename Processes.process_name as process | rex field=user \"(?.*)\\\\\\\\(?.*)\" | `ctime(firstTime)`| `ctime(lastTime)`| search [| tstats count from datamodel=Endpoint.Processes by Processes.process_name | rare Processes.process_name limit=30 | rename Processes.process_name as process| `filter_rare_process_whitelist`| table process ]", - "suppress": { - "suppress_fields": "dest, process", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search first executes the subsearch and counts all of your processes to determine the 10 most rare (the limit set is 10). It then filters out whitelisted processes and outputs the first and last time a rare process was encountered, the destination where the process is running, the count of occurrences, and the users who initiated the processes.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro filter_rare_process_whitelist searches two lookup files to whitelist your processes. These consist of rare_process_whitelist_default.csv and rare_process_whitelist_local.csv. To add your own processes to the whitelist, add them to rare_process_whitelist_local.csv. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment.", - "id": "44fddcb2-8d3b-454c-874e-7c6de5a4f7ac", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", - "name": "Investigate Web Activity From Host", - "type": "splunk" - } - ], - "known_false_positives": "Some legitimate processes may be only rarely executed in your environment. As these are identified, update rare_process_whitelist_local.csv to filter them out of your search results.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 2", - "CIS 8" - ], - "kill_chain_phases": [ - "Installation", - "Command and Control", - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution" - ], - "nist": [ - "ID.AM", - "PR.PT", - "PR.DS", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-10-30", - "name": "Detect Rare Executables", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", + "name": "Investigate Web Activity From Host", + "type": "splunk" + } + ], + "known_false_positives": "Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 2", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "4.0" + "kill_chain_phases": [ + "Installation", + "Command and Control", + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution" + ], + "nist": [ + "ID.AM", + "PR.PT", + "PR.DS", + "DE.CM" + ] + }, + "modification_date": "2018-10-30", + "name": "Detect Rare Executables", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "4.0" } diff --git a/detections/reg_used_to_hide_files.json b/detections/reg_used_to_hide_files.json index b88f76adc5..e1b9f603c0 100644 --- a/detections/reg_used_to_hide_files.json +++ b/detections/reg_used_to_hide_files.json @@ -1,139 +1,139 @@ { - "asset_type": "", - "confidence": "medium", - "creation_date": "2017-10-27", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "", + "confidence": "medium", + "creation_date": "2017-10-27", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "The search looks for command-line arguments used to hide a file or directory using the reg add command.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, process", + "rule_description": "Regedit.exe is used by attackers to hide malware files/directories in windows environments via registry key settings. This rule detects command-line arguments used to hide a file/directory", + "rule_title": "Regedit.exe used to hide a file/directory on $dest$ " + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = reg.exe Processes.process=\"*add*\" Processes.process=\"*Hidden*\" Processes.process=\"*REG_DWORD*\" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `ctime(firstTime)` |`ctime(lastTime)`| regex process = \"(/d\\s+2)\"", + "suppress": { + "suppress_fields": "dest,process", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "Reg.exe is a binary native to Windows platform used to edit the registry hives of the system. Attackers can leverage this binary to hide files by passing in arguments that are used to hide the files. In the search, we first gather results with keywords, add, Hidden, and REG_DWORD, that will be in the raw event and filter by process and the command-line. We then leverage regular expressions on the command-line field to look for /d value as 2 which is responsible for hiding a file or directory.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "c77162d3-f93c-45cc-80c8-22f6b5264x9f", + "investigations": [ + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", + "name": "Get Registry Activities", + "type": "splunk" }, - "description": "The search looks for command-line arguments used to hide a file or directory using the reg add command.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, process", - "rule_description": "Regedit.exe is used by attackers to hide malware files/directories in windows environments via registry key settings. This rule detects command-line arguments used to hide a file/directory", - "rule_title": "Regedit.exe used to hide a file/directory on $dest$ " - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = reg.exe Processes.process=\"*add*\" Processes.process=\"*Hidden*\" Processes.process=\"*REG_DWORD*\" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `ctime(firstTime)` |`ctime(lastTime)`| regex process = \"(/d\\s+2)\"", - "suppress": { - "suppress_fields": "dest,process", - "suppress_period": "86400s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "Reg.exe is a binary native to Windows platform used to edit the registry hives of the system. Attackers can leverage this binary to hide files by passing in arguments that are used to hide the files. In the search, we first gather results with keywords, add, Hidden, and REG_DWORD, that will be in the raw event and filter by process and the command-line. We then leverage regular expressions on the command-line field to look for /d value as 2 which is responsible for hiding a file or directory.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "c77162d3-f93c-45cc-80c8-22f6b5264x9f", - "investigations": [ - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", - "name": "Get Registry Activities", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "None at the moment", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Defense Evasion", - "Persistence" - ], - "nist": [ - "DE.CM" - ] + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "modification_date": "2019-02-27", - "name": "Reg.exe used to hide files/directories via registry keys", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "None at the moment", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Defense Evasion", + "Persistence" + ], + "nist": [ + "DE.CM" + ] + }, + "modification_date": "2019-02-27", + "name": "Reg.exe used to hide files/directories via registry keys", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/remote_desktop_process_running_on_system.json b/detections/remote_desktop_process_running_on_system.json index 976b142767..88e25c7efb 100644 --- a/detections/remote_desktop_process_running_on_system.json +++ b/detections/remote_desktop_process_running_on_system.json @@ -1,143 +1,143 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2016-09-13", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2016-09-13", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process", + "rule_description": "The system $dest$ is running the remote desktop process, mstsc.exe. This system does not commonly run this application.", + "rule_title": "Remote Desktop Process Running On $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 40 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process=mstsc.exe AND Processes.dest_category!=common_rdp_source by Processes.dest Processes.user Processes.process | `ctime(firstTime)`| `ctime(lastTime)` | `drop_dm_object_name(Processes)`", + "suppress": { + "suppress_fields": "dest,user", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "This search finds systems that do not commonly use remote desktop, but which begin using it. It filters out all systems that have the \"common_rdp_source\" category applied. Categories are applied to systems using the Assets and Identity framework.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search \"Identify Systems Using Remote Desktop\" to identify these systems. After identifying them, you will need to add the \"common_rdp_source\" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`.", + "id": "f5939373-8054-40ad-8c64-cec478a22a4a", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the common_rdp_source category in the Assets and Identity framework.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process", - "rule_description": "The system $dest$ is running the remote desktop process, mstsc.exe. This system does not commonly run this application.", - "rule_title": "Remote Desktop Process Running On $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 40 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process=mstsc.exe AND Processes.dest_category!=common_rdp_source by Processes.dest Processes.user Processes.process | `ctime(firstTime)`| `ctime(lastTime)` | `drop_dm_object_name(Processes)`", - "suppress": { - "suppress_fields": "dest,user", - "suppress_period": "28800s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search finds systems that do not commonly use remote desktop, but which begin using it. It filters out all systems that have the \"common_rdp_source\" category applied. Categories are applied to systems using the Assets and Identity framework.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search \"Identify Systems Using Remote Desktop\" to identify these systems. After identifying them, you will need to add the \"common_rdp_source\" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups.", - "id": "f5939373-8054-40ad-8c64-cec478a22a4a", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Remote Desktop may be used legitimately by users on the network.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - }, - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 9", - "CIS 16" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Lateral Movement", - "Remote Desktop Protocol" - ], - "nist": [ - "DE.AE", - "PR.AC", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-02", - "name": "Remote Desktop Process Running On System", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Remote Desktop may be used legitimately by users on the network.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + }, + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 9", + "CIS 16" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "3.0" + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Lateral Movement", + "Remote Desktop Protocol" + ], + "nist": [ + "DE.AE", + "PR.AC", + "PR.IP" + ] + }, + "modification_date": "2018-11-02", + "name": "Remote Desktop Process Running On System", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "3.0" } diff --git a/detections/remote_registry_modifications.json b/detections/remote_registry_modifications.json index 8e6e63fe0e..97fdcfc1f4 100644 --- a/detections/remote_registry_modifications.json +++ b/detections/remote_registry_modifications.json @@ -1,139 +1,139 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-05-31", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-05-31", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon" + ] + }, + "description": "This search monitors for remote modifications to registry keys.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user", + "rule_description": "A registry key was modified remotely using the machine $dest$ by $user$.", + "rule_title": "Remote Registry Key Modification detection on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 30 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path=\"\\\\\\\\*\" by Registry.dest , Registry.status, Registry.user | `ctime(lastTime)` | `ctime(firstTime)` | `drop_dm_object_name(Registry)`", + "suppress": { + "suppress_fields": "dest, user,registry_path", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "This search looks for modifications made to the Windows registry from remote locations using reg.exe—a tool used to create/update/delete/modify Windows registry keys. It is accomplished through specifying the machine names in the registry path, by entering double backslashes, followed by a computer name. In this search, we look for registry changes where the registry path contains the name of a remote computer. The search returns the number of times the remote server has been accessed, the first and last times the activity occurred, the name of the modified registry path, the host on which the modification took place, and the name of the user that performed the modification.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must populate the `Change_Analysis` data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry.", + "id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", + "investigations": [ + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", + "name": "Get Registry Activities", + "type": "splunk" }, - "description": "This search monitors for remote modifications to registry keys.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user", - "rule_description": "A registry key was modified remotely using the machine $dest$ by $user$.", - "rule_title": "Remote Registry Key Modification detection on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path=\"\\\\\\\\*\" by Registry.dest , Registry.status, Registry.user | `ctime(lastTime)` | `ctime(firstTime)` | `drop_dm_object_name(Registry)`", - "suppress": { - "suppress_fields": "dest, user,registry_path", - "suppress_period": "14400s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "This search looks for modifications made to the Windows registry from remote locations using reg.exe—a tool used to create/update/delete/modify Windows registry keys. It is accomplished through specifying the machine names in the registry path, by entering double backslashes, followed by a computer name. In this search, we look for registry changes where the registry path contains the name of a remote computer. The search returns the number of times the remote server has been accessed, the first and last times the activity occurred, the name of the modified registry path, the host on which the modification took place, and the name of the user that performed the modification.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry.", - "id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", - "investigations": [ - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", - "name": "Get Registry Activities", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Defense Evasion", - "Persistence", - "Lateral Movement" - ], - "nist": [ - "PR.PT", - "DE.CM" - ] + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "modification_date": "2018-05-31", - "name": "Remote Registry Key modifications", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Defense Evasion", + "Persistence", + "Lateral Movement" + ], + "nist": [ + "PR.PT", + "DE.CM" + ] + }, + "modification_date": "2018-05-31", + "name": "Remote Registry Key modifications", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" } diff --git a/detections/remote_wmi_command_attempt.json b/detections/remote_wmi_command_attempt.json index e35395b6e7..e17184ae11 100644 --- a/detections/remote_wmi_command_attempt.json +++ b/detections/remote_wmi_command_attempt.json @@ -1,138 +1,138 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2017-01-13", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2017-01-13", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for wmic.exe being launched with parameters to operate on remote systems.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest,user,process_name", + "rule_description": "This search looks for wmic.exe being launched with parameters to operate on remote systems.", + "rule_title": "Endpoint - Remote WMI command attempt" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 30 + }, + "schedule": { + "cron_schedule": "50 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=wmic.exe AND Processes.process= */node* by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest,user,process_name", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "Many a times, attackers leverage native Windows utilities that are designed to help administrators better manage their systems, infrastructure, and auditing, but are instead leveraged for malicious purposes. In this case, we are looking for instances of wmic.exe being run with various parameters that are not typically used by administrators.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "272df6de-61f1-4784-877c-1fbc3e2d0838", + "investigations": [ + { + "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", + "name": "Get Sysmon WMI Activity for Host", + "type": "splunk" }, - "description": "This search looks for wmic.exe being launched with parameters to operate on remote systems.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest,user,process_name", - "rule_description": "This search looks for wmic.exe being launched with parameters to operate on remote systems.", - "rule_title": "Endpoint - Remote WMI command attempt" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "50 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=wmic.exe AND Processes.process= */node* by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`| `ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest,user,process_name", - "suppress_period": "28800s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "Many a times, attackers leverage native Windows utilities that are designed to help administrators better manage their systems, infrastructure, and auditing, but are instead leveraged for malicious purposes. In this case, we are looking for instances of wmic.exe being run with various parameters that are not typically used by administrators.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "272df6de-61f1-4784-877c-1fbc3e2d0838", - "investigations": [ - { - "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", - "name": "Get Sysmon WMI Activity for Host", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Administrators may use this legitimately to gather info from remote systems.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 5" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Windows Management Instrumentation" - ], - "nist": [ - "PR.PT", - "PR.AT", - "PR.AC", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-12-03", - "name": "Remote WMI Command Attempt", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Administrators may use this legitimately to gather info from remote systems.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 5" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Windows Management Instrumentation" + ], + "nist": [ + "PR.PT", + "PR.AT", + "PR.AC", + "PR.IP" + ] + }, + "modification_date": "2018-12-03", + "name": "Remote WMI Command Attempt", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/s3_access_from_new_ip.json b/detections/s3_access_from_new_ip.json index dc002b4676..63531d88ec 100644 --- a/detections/s3_access_from_new_ip.json +++ b/detections/s3_access_from_new_ip.json @@ -49,7 +49,7 @@ } } }, - "eli5": "Here the subsearch executes first and returns all successful S3 bucket-access attempts (HTTP code \"200\") within the last hour. It groups the results by the earliest and latest times it has seen a remote IP accessing a particular bucket. It appends this information to the historical data from the lookup file and then recalculates the firstTime and lastTime field for each remote IP accessing an S3 bucket. Next, it returns only those remote IP addresses that have first been seen accessing a specific bucket within the past hour. This is combined with the main search to return the time, bucket name, source IP, city, and country operations performed, as well as the requested URI of the resource ", + "eli5": "Here the subsearch executes first and returns all successful S3 bucket-access attempts (HTTP code \"200\") within the last hour. It groups the results by the earliest and latest times it has seen a remote IP accessing a particular bucket. It appends this information to the historical data from the lookup file and then recalculates the `firstTime` and `lastTime` field for each remote IP accessing an S3 bucket. Next, it returns only those remote IP addresses that have first been seen accessing a specific bucket within the past hour. This is combined with the main search to return the time, bucket name, source IP, city, and country operations performed, as well as the requested URI of the resource ", "entities": [ "src_ip" ], diff --git a/detections/shim_database_file_creation.json b/detections/shim_database_file_creation.json index 377e7d71ff..beb8d04009 100644 --- a/detections/shim_database_file_creation.json +++ b/detections/shim_database_file_creation.json @@ -1,137 +1,137 @@ { - "asset_type": "Endpoint", - "confidence": "high", - "creation_date": "2017-10-03", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon" - ] + "asset_type": "Endpoint", + "confidence": "high", + "creation_date": "2017-10-03", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon" + ] + }, + "description": "This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, file_name", + "rule_description": "A file, $file_name$, was created in the default shim database directory on $dest.", + "rule_title": "Shim database file created on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 20 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Filesystem.action) values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path=*Windows\\AppPatch\\Custom* by Filesystem.file_name Filesystem.dest | `ctime(lastTime)` | `ctime(firstTime)` |`drop_dm_object_name(Filesystem)`", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "This search looks for files being created in `Windows\\AppPatch\\Custom and Windows\\AppPatch\\Custom64`, the location where shim databases are installed. It will return all the files created, as well as the time of creation for the first and last file for each endpoint.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.", + "id": "6e4c4588-ba2f-42fa-97e6-9f6f548eaa33", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, file_name", - "rule_description": "A file, $file_name$, was created in the default shim database directory on $dest.", - "rule_title": "Shim database file created on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 20 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Filesystem.action) values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path=*Windows\\AppPatch\\Custom* by Filesystem.file_name Filesystem.dest | `ctime(lastTime)` | `ctime(firstTime)` |`drop_dm_object_name(Filesystem)`", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "14400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search looks for files being created in Windows\\AppPatch\\Custom and Windows\\AppPatch\\Custom64, the location where shim databases are installed. It will return all the files created, as well as the time of creation for the first and last file for each endpoint.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.", - "id": "6e4c4588-ba2f-42fa-97e6-9f6f548eaa33", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - }, - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Persistence", - "Application Shimming" - ], - "nist": [ - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-11-02", - "name": "Shim Database File Creation", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + }, + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Persistence", + "Application Shimming" + ], + "nist": [ + "DE.CM" + ] + }, + "modification_date": "2018-11-02", + "name": "Shim Database File Creation", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/shim_database_installation.json b/detections/shim_database_installation.json index c019208bc1..d90f3b47df 100644 --- a/detections/shim_database_installation.json +++ b/detections/shim_database_installation.json @@ -1,134 +1,134 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2017-10-03", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2017-10-03", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process", + "rule_description": "The system $dest$ had a shim database installed.", + "rule_title": "Shim Database Installation on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 20 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sdbinst.exe Processes.process=\"*-p*\" Processes.process=\"*-q*\" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `ctime(firstTime)` | `ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest,user", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "This search looks for the execution of sdbinst.exe with command-line arguments of -q and -p. The -q option performs a silent installation with no visible window, status, or warning information. The -p option allows the shim database to contain patches. It will return the count, the first time, and the last time these command-line arguments were seen on each endpoint and by each user.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "404620de-46d8-48b6-90cc-8a8d7b0876a3", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process", - "rule_description": "The system $dest$ had a shim database installed.", - "rule_title": "Shim Database Installation on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 20 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sdbinst.exe Processes.process=\"*-p*\" Processes.process=\"*-q*\" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `ctime(firstTime)` | `ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest,user", - "suppress_period": "14400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search looks for the execution of sdbinst.exe with command-line arguments of -q and -p. The -q option performs a silent installation with no visible window, status, or warning information. The -p option allows the shim database to contain patches. It will return the count, the first time, and the last time these command-line arguments were seen on each endpoint and by each user.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "404620de-46d8-48b6-90cc-8a8d7b0876a3", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "None identified", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Persistence", - "Application Shimming" - ], - "nist": [ - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2019-03-01", - "name": "Shim Database Installation With Suspicious Parameters", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "None identified", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Persistence", + "Application Shimming" + ], + "nist": [ + "DE.CM" + ] + }, + "modification_date": "2019-03-01", + "name": "Shim Database Installation With Suspicious Parameters", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/smb_traffic_spike.json b/detections/smb_traffic_spike.json index 566472f22b..e7947808a6 100644 --- a/detections/smb_traffic_spike.json +++ b/detections/smb_traffic_spike.json @@ -1,143 +1,143 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2017-08-20", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communications" - ], - "providing_technologies": [ - "Bro", - "Splunk Stream" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2017-08-20", + "data_metadata": { + "data_models": [ + "Network_Traffic" + ], + "data_source": [ + "Network Communications" + ], + "providing_technologies": [ + "Bro", + "Splunk Stream" + ] + }, + "description": "This search looks for spikes in the number of Server Message Block (SMB) traffic connections.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src", + "rule_description": "There was a spike in SMB traffic from $src$.", + "rule_title": "SMB Traffic Spike from $src$" + }, + "risk": { + "risk_object": "src", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-7d@d", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | `drop_dm_object_name(\"All_Traffic\")` | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time >= relative_time(maxtime, \"-70m@m\"), count, null))) as count avg(eval(if(_time upperBound AND num_data_samples >=50, 1, 0) | where isOutlier=1 | table src count", + "suppress": { + "suppress_fields": "src", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "Server Message Block (SMB) traffic, a protocol used for Windows file sharing-activity, is often leveraged by attackers. One example of SMB abuse was the WannaCry ransomware, which leveraged a vulnerability in the SMB protocol to propagate to other systems. Attackers have also used SMB for lateral movement with a target environment and to test credentials against target systems. While SMB is highly prevalent in Windows environments, a spike in SMB traffic may still be indicative of this type of malicious activity. This search looks for a traffic spike in SMB traffic from a particular system. If such a spike is detected, you may want to investigate the source and analyze the cause of the abnormal traffic.", + "entities": [ + "src" + ], + "how_to_implement": "This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model.", + "id": "7f5fb3e1-4209-4914-90db-0ec21b936378", + "investigations": [ + { + "id": "9925d08f-561e-4faa-8912-e3888a842341", + "name": "Get Process Information For Port Activity", + "type": "splunk" }, - "description": "This search looks for spikes in the number of Server Message Block (SMB) traffic connections.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src", - "rule_description": "There was a spike in SMB traffic from $src$.", - "rule_title": "SMB Traffic Spike from $src$" - }, - "risk": { - "risk_object": "src", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-7d@d", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | `drop_dm_object_name(\"All_Traffic\")` | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time >= relative_time(maxtime, \"-70m@m\"), count, null))) as count avg(eval(if(_time upperBound AND num_data_samples >=50, 1, 0) | where isOutlier=1 | table src count", - "suppress": { - "suppress_fields": "src", - "suppress_period": "28800s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "Server Message Block (SMB) traffic, a protocol used for Windows file sharing-activity, is often leveraged by attackers. One example of SMB abuse was the WannaCry ransomware, which leveraged a vulnerability in the SMB protocol to propagate to other systems. Attackers have also used SMB for lateral movement with a target environment and to test credentials against target systems. While SMB is highly prevalent in Windows environments, a spike in SMB traffic may still be indicative of this type of malicious activity. This search looks for a traffic spike in SMB traffic from a particular system. If such a spike is detected, you may want to investigate the source and analyze the cause of the abnormal traffic.", - "entities": [ - "src" - ], - "how_to_implement": "This search requires you to be ingesting your network traffic logs and populating the Network_Traffic data model.", - "id": "7f5fb3e1-4209-4914-90db-0ec21b936378", - "investigations": [ - { - "id": "9925d08f-561e-4faa-8912-e3888a842341", - "name": "Get Process Information For Port Activity", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", - "name": "Get Vulnerability Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "A file server may experience high-demand loads that could cause this analytic to trigger.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Lateral Movement", - "Execution", - "Command and Control", - "Commonly Used Port" - ], - "nist": [ - "DE.CM" - ] + { + "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", + "name": "Get Vulnerability Logs For Endpoint", + "type": "splunk" }, - "modification_date": "2017-09-10", - "name": "SMB Traffic Spike", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "A file server may experience high-demand loads that could cause this analytic to trigger.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Lateral Movement", + "Execution", + "Command and Control", + "Commonly Used Port" + ], + "nist": [ + "DE.CM" + ] + }, + "modification_date": "2017-09-10", + "name": "SMB Traffic Spike", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/smb_traffic_spike_mltk.json b/detections/smb_traffic_spike_mltk.json index 1c6f2a4122..ec249ef4c7 100644 --- a/detections/smb_traffic_spike_mltk.json +++ b/detections/smb_traffic_spike_mltk.json @@ -1,150 +1,150 @@ { - "asset_type": "Endpoint", - "baselines": [ - { - "id": "df98763b-0b08-4281-8ef9-08db7ac572a9", - "name": "Baseline of SMB Traffic - MLTK", - "type": "splunk" - } + "asset_type": "Endpoint", + "baselines": [ + { + "id": "df98763b-0b08-4281-8ef9-08db7ac572a9", + "name": "Baseline of SMB Traffic - MLTK", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2019-05-08", + "data_metadata": { + "data_models": [ + "Network_Traffic" ], - "confidence": "medium", - "creation_date": "2019-05-08", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communications" - ], - "providing_technologies": [ - "Bro", - "Splunk Stream" - ] + "data_source": [ + "Network Communications" + ], + "providing_technologies": [ + "Bro", + "Splunk Stream" + ] + }, + "description": "This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src", + "rule_description": "There was a spike in SMB traffic from $src$", + "rule_title": "SMB Traffic Spike from $src$" + }, + "risk": { + "risk_object": "src", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(All_Traffic.dest_ip) as dest values(All_Traffic.dest_port) as port from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | eval HourOfDay=strftime(_time, \"%H\") | eval DayOfWeek=strftime(_time, \"%A\") | `drop_dm_object_name(All_Traffic)` | apply smb_pdfmodel threshold=0.001 | rename \"IsOutlier(count)\" as isOutlier | search isOutlier > 0 | sort -count | table _time src dest port count", + "suppress": { + "suppress_fields": "src", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "Attackers often leverage Server Message Block (SMB) traffic, a protocol used for Windows file-sharing activity. A high-profile example of SMB abuse was the WannaCry ransomware, which leveraged a vulnerability in the SMB protocol to propagate to other systems. Attackers have also used SMB for lateral movement with a target environment and to test credentials against target systems. While SMB is highly prevalent in Windows environments, a spike in SMB traffic may still be indicative of this type of malicious activity. This search leverages Splunk's Machine Learning Toolkit (MLTK) to identify spikes in SMB traffic that are unusual for a given hour of day/day of week combination. If such a spike is detected, you may want to investigate the source and analyze the cause of the abnormal traffic. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", + "entities": [ + "src" + ], + "how_to_implement": "To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search \"Baseline of SMB Traffic - MLTK\" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\n\nThis search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): **Label:** Number of events, **Field:** count\n\nDetailed documentation on how to create a new field within Incident Review is found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", + "investigations": [ + { + "id": "9925d08f-561e-4faa-8912-e3888a842341", + "name": "Get Process Information For Port Activity", + "type": "splunk" }, - "description": "This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src", - "rule_description": "There was a spike in SMB traffic from $src$", - "rule_title": "SMB Traffic Spike from $src$" - }, - "risk": { - "risk_object": "src", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(All_Traffic.dest_ip) as dest values(All_Traffic.dest_port) as port from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | eval HourOfDay=strftime(_time, \"%H\") | eval DayOfWeek=strftime(_time, \"%A\") | `drop_dm_object_name(All_Traffic)` | apply smb_pdfmodel threshold=0.001 | rename \"IsOutlier(count)\" as isOutlier | search isOutlier > 0 | sort -count | table _time src dest port count", - "suppress": { - "suppress_fields": "src", - "suppress_period": "28800s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "Attackers often leverage Server Message Block (SMB) traffic, a protocol used for Windows file-sharing activity. A high-profile example of SMB abuse was the WannaCry ransomware, which leveraged a vulnerability in the SMB protocol to propagate to other systems. Attackers have also used SMB for lateral movement with a target environment and to test credentials against target systems. While SMB is highly prevalent in Windows environments, a spike in SMB traffic may still be indicative of this type of malicious activity. This search leverages Splunk's Machine Learning Toolkit (MLTK) to identify spikes in SMB traffic that are unusual for a given hour of day/day of week combination. If such a spike is detected, you may want to investigate the source and analyze the cause of the abnormal traffic. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.", - "entities": [ - "src" - ], - "how_to_implement": "To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search \"Baseline of SMB Traffic - MLTK\" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.

        This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): Label: Number of events, Field: count

        Detailed documentation on how to create a new field within Incident Review is found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", - "id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", - "investigations": [ - { - "id": "9925d08f-561e-4faa-8912-e3888a842341", - "name": "Get Process Information For Port Activity", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", - "name": "Get Vulnerability Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "If you are seeing more results than desired, you may consider reducing the value of the threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Lateral Movement", - "Execution", - "Command and Control", - "Commonly Used Port" - ], - "nist": [ - "DE.CM" - ] + { + "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", + "name": "Get Vulnerability Logs For Endpoint", + "type": "splunk" }, - "modification_date": "2019-05-08", - "name": "SMB Traffic Spike - MLTK", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "If you are seeing more results than desired, you may consider reducing the value of the threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Lateral Movement", + "Execution", + "Command and Control", + "Commonly Used Port" + ], + "nist": [ + "DE.CM" + ] + }, + "modification_date": "2019-05-08", + "name": "SMB Traffic Spike - MLTK", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/sncd_processes.json b/detections/sncd_processes.json index 80629ef058..e732355e24 100644 --- a/detections/sncd_processes.json +++ b/detections/sncd_processes.json @@ -1,126 +1,126 @@ { - "asset_type": "Endpoint", - "confidence": "high", - "creation_date": "2018-11-04", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "high", + "creation_date": "2018-11-04", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for fast execution of processes used for system network configuration discovery on the endpoint.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, process, user", + "rule_description": "Fast execution of processes $related to network system configuration discovery seen on $dest$.", + "rule_title": "Fast execution of processes $process_name$ related to network discovery seen on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.process_name Processes.user _time | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(Processes)` | search `system_network_configuration_discovery_tools` | transaction dest maxpause=5m |where eventcount>=5 | table firstTime lastTime dest user process_name process parent_process eventcount", + "suppress": { + "suppress_fields": "dest,user", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "Attackers have a range of built-in Windows tools they leverage to ascertain the topography of a network from the point of view of a compromised machine. It is uncommon to see these commands execute quickly within short periods of time. This search returns the number of times, as well as the first time and last times, that every process has run for each endpoint. It then executes the macro `system_network_configuration_discovery_tools`, which looks for processes that are typically used for network configuration discovery. Once you have a list of suspicious process launches for each destination, you can leverage the transaction command to see what processes are fired within a five-minute span on an endpoint and detect only those events where the count of these processes is greater than five.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings.", + "id": "a51bfe1a-94f0-48cc-b1e4-16ae10145893", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for fast execution of processes used for system network configuration discovery on the endpoint.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, process, user", - "rule_description": "Fast execution of processes $related to network system configuration discovery seen on $dest$.", - "rule_title": "Fast execution of processes $process_name$ related to network discovery seen on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.process_name Processes.user _time | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(Processes)` | search `system_network_configuration_discovery_tools` | transaction dest maxpause=5m |where eventcount>=5 | table firstTime lastTime dest user process_name process parent_process eventcount", - "suppress": { - "suppress_fields": "dest,user", - "suppress_period": "86400s" - } - } - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "eli5": "Attackers have a range of built-in Windows tools they leverage to ascertain the topography of a network from the point of view of a compromised machine. It is uncommon to see these commands execute quickly within short periods of time. This search returns the number of times, as well as the first time and last times, that every process has run for each endpoint. It then executes the macro system_network_configuration_discovery_tools, which looks for processes that are typically used for network configuration discovery. Once you have a list of suspicious process launches for each destination, you can leverage the transaction command to see what processes are fired within a five-minute span on an endpoint and detect only those events where the count of these processes is greater than five.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings.", - "id": "a51bfe1a-94f0-48cc-b1e4-16ae10145893", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "mappings": { - "cis20": [ - "CIS 2" - ], - "kill_chain_phases": [ - "Installation", - "Command and Control", - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution" - ], - "nist": [ - "ID.AM", - "PR.DS" - ] + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" }, - "modification_date": "2018-11-20", - "name": "Detect processes used for System Network Configuration Discovery", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 2" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Installation", + "Command and Control", + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution" + ], + "nist": [ + "ID.AM", + "PR.DS" + ] + }, + "modification_date": "2018-11-20", + "name": "Detect processes used for System Network Configuration Discovery", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/spectre_meltdown_vulnerabilities.json b/detections/spectre_meltdown_vulnerabilities.json index 45438f988b..ea5cc226ba 100644 --- a/detections/spectre_meltdown_vulnerabilities.json +++ b/detections/spectre_meltdown_vulnerabilities.json @@ -1,124 +1,124 @@ { - "asset_type": "Endpoint", - "baselines": [ - { - "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd61", - "name": "Systems Ready for Spectre-Meltdown Windows Patch", - "type": "splunk" - } + "asset_type": "Endpoint", + "baselines": [ + { + "id": "fc0edc95-ff2b-48b0-9f6f-63da3789fd61", + "name": "Systems Ready for Spectre-Meltdown Windows Patch", + "type": "splunk" + } + ], + "confidence": "high", + "creation_date": "2018-01-07", + "data_metadata": { + "data_models": [ + "Vulnerabilities" ], - "confidence": "high", - "creation_date": "2018-01-07", - "data_metadata": { - "data_models": [ - "Vulnerabilities" - ], - "data_source": [ - "Vulnerability Scanner" - ], - "providing_technologies": [ - "Nessus", - "Qualys" - ] + "data_source": [ + "Vulnerability Scanner" + ], + "providing_technologies": [ + "Nessus", + "Qualys" + ] + }, + "description": "The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest", + "rule_description": "$dest is vulnerable to the Spectre or Meltdown CPU vulnerabilities.", + "rule_title": "$dest is vulnerable to the Spectre or Meltdown CPU vulnerabilities" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 100 + }, + "schedule": { + "cron_schedule": "0 6 * * *", + "earliest_time": "-25h@h", + "latest_time": "-1h@h" + }, + "search": "| tstats `summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Vulnerabilities where Vulnerabilities.cve =\"CVE-2017-5753\" OR Vulnerabilities.cve =\"CVE-2017-5715\" OR Vulnerabilities.cve =\"CVE-2017-5754\" by Vulnerabilities.dest| `ctime(firstTime)` | `ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search looks for the three CVEs associated with the Spectre and Meltdown vulnerabilities.", + "entities": [ + "dest" + ], + "how_to_implement": "The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified.", + "id": "354be8e0-32cd-4da0-8c47-796de13b60ea", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest", - "rule_description": "$dest is vulnerable to the Spectre or Meltdown CPU vulnerabilities.", - "rule_title": "$dest is vulnerable to the Spectre or Meltdown CPU vulnerabilities" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 100 - }, - "schedule": { - "cron_schedule": "0 6 * * *", - "earliest_time": "-25h@h", - "latest_time": "-1h@h" - }, - "search": "| tstats `summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Vulnerabilities where Vulnerabilities.cve =\"CVE-2017-5753\" OR Vulnerabilities.cve =\"CVE-2017-5715\" OR Vulnerabilities.cve =\"CVE-2017-5754\" by Vulnerabilities.dest| `ctime(firstTime)` | `ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "86400s" - } - } - } + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "eli5": "This search looks for the three CVEs associated with the Spectre and Meltdown vulnerabilities.", - "entities": [ - "dest" - ], - "how_to_implement": "The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified.", - "id": "354be8e0-32cd-4da0-8c47-796de13b60ea", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "It is possible that your vulnerability scanner is not detecting that the patches have been applied.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 4" - ], - "nist": [ - "ID.RA", - "RS.MI", - "PR.IP", - "DE.CM" - ] + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "modification_date": "2017-01-07", - "name": "Spectre and Meltdown Vulnerable Systems", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "It is possible that your vulnerability scanner is not detecting that the patches have been applied.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 4" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "nist": [ + "ID.RA", + "RS.MI", + "PR.IP", + "DE.CM" + ] + }, + "modification_date": "2017-01-07", + "name": "Spectre and Meltdown Vulnerable Systems", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/spike_aws_api_call_per_account.json b/detections/spike_aws_api_call_per_account.json index 1a3e931e36..335f596bbc 100644 --- a/detections/spike_aws_api_call_per_account.json +++ b/detections/spike_aws_api_call_per_account.json @@ -1,114 +1,114 @@ { - "asset_type": "AWS Instance", - "baselines": [ - { - "id": "fc0edc96-ff2b-48b0-9f6f-63da3783fd63", - "name": "Baseline of API Calls per User ARN", - "type": "splunk" - } + "asset_type": "AWS Instance", + "baselines": [ + { + "id": "fc0edc96-ff2b-48b0-9f6f-63da3783fd63", + "name": "Baseline of API Calls per User ARN", + "type": "splunk" + } + ], + "confidence": "medium", + "creation_date": "2018-03-12", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "confidence": "medium", - "creation_date": "2018-03-12", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "user", - "rule_description": "A spike in the number of AWS API calls by $user$ was detected.", - "rule_title": "Spike in AWS API activity detected by $user$" - }, - "risk": { - "risk_object": "user", - "risk_object_type": [ - "user" - ], - "risk_score": 30 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=aws:cloudtrail eventType=AwsApiCall [search sourcetype=aws:cloudtrail eventType=AwsApiCall | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup api_call_by_user_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user", - "suppress": { - "suppress_fields": "user", - "suppress_period": "14400s" - } - } - } - }, - "eli5": "This search and its corresponding subsearch run through a series of steps, as per the following:
        1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls.
        2. Kicks off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.
        3. Counts the number of API calls per ARN.
        4. Loads the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.
        5. Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command.
        6. Renames apiCalls as latestCount.
        7. Calculates the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation--weighting the past more heavily than the current.
        8. Updates the cache file with the latest results.
        9. Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.
        10. Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.
        11. Filters out anything that it determines is not a spike and returns the list of ARNs to the main search.
        The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average.", - "entities": [ - "user" + "data_sourcetypes": [ + "aws:cloudtrail" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify dataPointThreshold and deviationThreshold to better fit your environment. The dataPointThreshold variable is the minimum number of data points required to have a statistically significant amount of data to determine. The deviationThreshold variable is the number of standard deviations away from the mean that the value must be to be considered a spike.

        This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):

        • Label: AWS Event Name, Field: eventName
        • Label: Number of API Calls, Field: numberOfApiCalls
        • Label: Unique API Calls, Field: uniqueApisCalled


        Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", - "id": "ada0f478-84a8-4641-a3f1-d32362d4bd55", - "investigations": [ - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "user", + "rule_description": "A spike in the number of AWS API calls by $user$ was detected.", + "rule_title": "Spike in AWS API activity detected by $user$" }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" + "risk": { + "risk_object": "user", + "risk_object_type": [ + "user" + ], + "risk_score": 30 }, - { - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd76", - "name": "Investigate AWS User Activities by user field", - "type": "splunk" + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=aws:cloudtrail eventType=AwsApiCall [search sourcetype=aws:cloudtrail eventType=AwsApiCall | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup api_call_by_user_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user", + "suppress": { + "suppress_fields": "user", + "suppress_period": "14400s" } - ], - "known_false_positives": "", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 16" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Credential Access", - "Execution" - ], - "nist": [ - "DE.DP", - "DE.CM", - "PR.AC" - ] + } + } + }, + "eli5": "This search and its corresponding subsearch run through a series of steps, as per the following: \n\n1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls.
      • Kicks off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.
      • Counts the number of API calls per ARN.
      • Loads the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.
      • Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command.
      • Renames `apiCalls` as `latestCount`.
      • Calculates the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation--weighting the past more heavily than the current.
      • Updates the cache file with the latest results.
      • Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.
      • Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.
      • Filters out anything that it determines is not a spike and returns the list of ARNs to the main search.
        • The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average.", + "entities": [ + "user" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.\n\nThis search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n\n
        • **Label:** AWS Event Name, **Field:** eventName
        • **Label:** Number of API Calls, **Field:** numberOfApiCalls
        • **Label:** Unique API Calls, **Field:** uniqueApisCalled
        \n\nDetailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "id": "ada0f478-84a8-4641-a3f1-d32362d4bd55", + "investigations": [ + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "modification_date": "2018-04-09", - "name": "Detect Spike in AWS API Activity", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd76", + "name": "Investigate AWS User Activities by user field", + "type": "splunk" + } + ], + "known_false_positives": "", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 16" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Credential Access", + "Execution" + ], + "nist": [ + "DE.DP", + "DE.CM", + "PR.AC" + ] + }, + "modification_date": "2018-04-09", + "name": "Detect Spike in AWS API Activity", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" } diff --git a/detections/spike_aws_security_group_activity.json b/detections/spike_aws_security_group_activity.json index d18960dc92..522336e6a5 100644 --- a/detections/spike_aws_security_group_activity.json +++ b/detections/spike_aws_security_group_activity.json @@ -49,11 +49,11 @@ } } }, - "eli5": "This search and its corresponding subsearch run through the following series of steps:
        1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls specifically for security groups.
        2. Kicks off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.
        3. Counts the number of API calls per ARN.
        4. Loads the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.
        5. Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command.
        6. Renames apiCalls as latestCount.
        7. Calculates the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation--weighting the past more heavily than the current.
        8. Updates the cache file with the latest results.
        9. Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.
        10. Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.
        11. Filters out anything that it determines is not a spike and returns the list of ARNs to the main search.
        The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average.", + "eli5": "This search and its corresponding subsearch run through the following series of steps: \n\n1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls specifically for security groups.
      • Kicks off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.
      • Counts the number of API calls per ARN.
      • Loads the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.
      • Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command.
      • Renames `apiCalls` as `latestCount`.
      • Calculates the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation--weighting the past more heavily than the current.
      • Updates the cache file with the latest results.
      • Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.
      • Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.
      • Filters out anything that it determines is not a spike and returns the list of ARNs to the main search.
        • The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average.", "entities": [ "user" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify dataPointThreshold and deviationThreshold to better fit your environment. The dataPointThreshold variable is the minimum number of data points required to have a statistically significant amount of data to determine. The deviationThreshold variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the \"Baseline of Security Group Activity by ARN\" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro securityGroupAPIs.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the \"Baseline of Security Group Activity by ARN\" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `securityGroupAPIs`.", "id": "ada0f478-84a8-4641-a3f1-e32372d4bd53", "investigations": [ { @@ -72,7 +72,7 @@ "type": "splunk" } ], - "known_false_positives": "Based on the values ofdataPointThreshold and deviationThreshold, the false positive rate may vary. Please modify this according the your environment.", + "known_false_positives": "Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment.", "maintainers": [ { "company": "Splunk", diff --git a/detections/spike_s3_deletion.json b/detections/spike_s3_deletion.json index 84e689d490..be7dada673 100644 --- a/detections/spike_s3_deletion.json +++ b/detections/spike_s3_deletion.json @@ -49,11 +49,11 @@ } } }, - "eli5": "This search and its corresponding subsearch run through the following series of steps:
        1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls specifically for deletion of S3 buckets.
        2. Kick off a subsearch that retrieves the same data and pulls out and converts the ARN into a more friendly format.
        3. Count the number of API calls per ARN.
        4. Load the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.
        5. Drop the count from the latest hour, since it is unnecessary, and merge the rest of the data with the results of the stats command.
        6. Rename apiCalls as latestCount.
        7. Calculate the new average value for each ARN with the latest count, weighting the past more heavily than the current hour. It does the same for the standard deviation—weighting the past more heavily than the current.
        8. Update the cache file with the latest results.
        9. Set the minimum threshold for the number of data points and the number of standard deviations away from the mean it must be to be considered a spike.
        10. Make a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and if the count is a sufficient number of standard deviations away from the average.
        11. Filter out anything that it determines is not a spike and returns the list of ARNs to the main search.
        The main search subsequently gets the names of the deleted S3 buckets, the number of unique API calls, and the total number of API calls for each of these user ARNs.", + "eli5": "This search and its corresponding subsearch run through the following series of steps: \n\n1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls specifically for deletion of S3 buckets.
      • Kick off a subsearch that retrieves the same data and pulls out and converts the ARN into a more friendly format.
      • Count the number of API calls per ARN.
      • Load the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.
      • Drop the count from the latest hour, since it is unnecessary, and merge the rest of the data with the results of the `stats` command.
      • Rename `apiCalls` as `latestCount`.
      • Calculate the new average value for each ARN with the latest count, weighting the past more heavily than the current hour. It does the same for the standard deviation—weighting the past more heavily than the current.
      • Update the cache file with the latest results.
      • Set the minimum threshold for the number of data points and the number of standard deviations away from the mean it must be to be considered a spike.
      • Make a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and if the count is a sufficient number of standard deviations away from the average.
      • Filter out anything that it determines is not a spike and returns the list of ARNs to the main search.
        • The main search subsequently gets the names of the deleted S3 buckets, the number of unique API calls, and the total number of API calls for each of these user ARNs.", "entities": [ "user" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify dataPointThreshold and deviationThreshold to better fit your environment. The dataPointThreshold variable is the minimum number of data points required to have a statistically significant amount of data to determine. The deviationThreshold variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the \"Baseline of S3 Bucket deletion activity by ARN\" support search once to create a baseline of previously seen S3 bucket-deletion activity.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the \"Baseline of S3 Bucket deletion activity by ARN\" support search once to create a baseline of previously seen S3 bucket-deletion activity.", "id": "ad12w478-84a8-4641-a3w1-e32372q4bd53", "investigations": [ { @@ -92,7 +92,7 @@ "type": "splunk" } ], - "known_false_positives": "Based on the values ofdataPointThreshold and deviationThreshold, the false positive rate may vary. Please modify this according the your environment.", + "known_false_positives": "Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment.", "maintainers": [ { "company": "Splunk", diff --git a/detections/spike_vpc_blocked_traffic.json b/detections/spike_vpc_blocked_traffic.json index c3706a4fa8..66a82fbd2a 100644 --- a/detections/spike_vpc_blocked_traffic.json +++ b/detections/spike_vpc_blocked_traffic.json @@ -49,11 +49,11 @@ } } }, - "eli5": "This search retrieves all the VPC Flow log entries that have recorded a blocked outbound network connection originating from your AWS environment. Then it kicks off a subsearch, which looks at the same data and performs the following series of steps:
        1. Counts the number of blocked outbound connections by each source IP
        2. Loads the cache file that contains the number of data points, the count from the latest hour, the average blocked connections, and the standard deviation for each source IP.
        3. Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command.
        4. Renames numberOfBlockedConnections as latestCount.
        5. Calculates the new average value for each source IP with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation, weighting the past more heavily than the current.
        6. Updates the cache file with the latest results.
        7. Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.
        8. Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.
        9. Filters out anything that it determines is not a spike and returns the list of source IPs to the main search.
        The main search subsequently gets the list of all destination IPs for which the traffic was blocked, the network interface ID, the number of unique destination IP, and the total number of blocked connections for each of these source IP addresses. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average.", + "eli5": "This search retrieves all the VPC Flow log entries that have recorded a blocked outbound network connection originating from your AWS environment. Then it kicks off a subsearch, which looks at the same data and performs the following series of steps: \n\n1. Counts the number of blocked outbound connections by each source IP
      • Loads the cache file that contains the number of data points, the count from the latest hour, the average blocked connections, and the standard deviation for each source IP.
      • Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command.
      • Renames `numberOfBlockedConnections` as `latestCount`.
      • Calculates the new average value for each source IP with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation, weighting the past more heavily than the current.
      • Updates the cache file with the latest results.
      • Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.
      • Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.
      • Filters out anything that it determines is not a spike and returns the list of source IPs to the main search.
        • The main search subsequently gets the list of all destination IPs for which the traffic was blocked, the network interface ID, the number of unique destination IP, and the total number of blocked connections for each of these source IP addresses. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average.", "entities": [ "src_ip" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow logs. You can modify dataPointThreshold and deviationThreshold to better fit your environment. The dataPointThreshold variable is the number of data points required to meet the definition of \"spike.\" The deviationThreshold variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the \"Baseline of Blocked Outbound Connection\" support search once to create a history of previously seen blocked outbound connections.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of \"spike.\" The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the \"Baseline of Blocked Outbound Connection\" support search once to create a history of previously seen blocked outbound connections.", "id": "ada0f278-84a8-46w1-a3f1-w32372d4bd53", "investigations": [ { @@ -132,7 +132,7 @@ "type": "splunk" } ], - "known_false_positives": "The false-positive rate may vary based on the values ofdataPointThreshold and deviationThreshold. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections.", + "known_false_positives": "The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections.", "maintainers": [ { "company": "Splunk", diff --git a/detections/splunk_information_disclosure.json b/detections/splunk_information_disclosure.json index 77f7701c0c..f71ef4fc7d 100644 --- a/detections/splunk_information_disclosure.json +++ b/detections/splunk_information_disclosure.json @@ -1,122 +1,122 @@ { - "asset_type": "Splunk Server", - "confidence": "medium", - "creation_date": "2018-06-14", - "data_metadata": { - "data_source": [ - "Splunk" - ], - "data_sourcetypes": [ - "splunk_web_access" - ], - "providing_technologies": [ - "Splunk Enterprise" - ] + "asset_type": "Splunk Server", + "confidence": "medium", + "creation_date": "2018-06-14", + "data_metadata": { + "data_source": [ + "Splunk" + ], + "data_sourcetypes": [ + "splunk_web_access" + ], + "providing_technologies": [ + "Splunk Enterprise" + ] + }, + "description": "This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, src_ip", + "rule_description": "The Splunk Server $dest$ had a possible Splunk information-disclosure possibility from $src_ip$", + "rule_title": "Possible Splunk Information Disclosure Exploitation Attempt from $src_ip$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 80 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "index=_internal sourcetype=splunkd_ui_access server-info | search clientip!=127.0.0.1 uri_path=\"*raw/services/server/info/server-info\" | rename clientip as src_ip, splunk_server as dest | stats earliest(_time) as firstTime, latest(_time) as lastTime, values(uri) as uri, values(useragent) as http_user_agent, values(user) as user by src_ip, dest | convert ctime(firstTime) ctime(lastTime)", + "suppress": { + "suppress_fields": "dest, src_ip", + "suppress_period": "14400s" + } + } + } + }, + "eli5": "This search searches Splunk's internal logs for evidence of CVE-2018-11409 exploitation attempts.", + "entities": [ + "dest" + ], + "how_to_implement": "The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives.", + "id": "f6a26b7b-7e80-4963-a9a8-d836e7534ebd", + "investigations": [ + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" }, - "description": "This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, src_ip", - "rule_description": "The Splunk Server $dest$ had a possible Splunk information-disclosure possibility from $src_ip$", - "rule_title": "Possible Splunk Information Disclosure Exploitation Attempt from $src_ip$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 80 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "index=_internal sourcetype=splunkd_ui_access server-info | search clientip!=127.0.0.1 uri_path=\"*raw/services/server/info/server-info\" | rename clientip as src_ip, splunk_server as dest | stats earliest(_time) as firstTime, latest(_time) as lastTime, values(uri) as uri, values(useragent) as http_user_agent, values(user) as user by src_ip, dest | convert ctime(firstTime) ctime(lastTime)", - "suppress": { - "suppress_fields": "dest, src_ip", - "suppress_period": "14400s" - } - } - } + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" }, - "eli5": "This search searches Splunk's internal logs for evidence of CVE-2018-11409 exploitation attempts.", - "entities": [ - "dest" - ], - "how_to_implement": "The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives.", - "id": "f6a26b7b-7e80-4963-a9a8-d836e7534ebd", - "investigations": [ - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "2f5b960b-71df-49c0-affc-74992ce60e45", - "name": "Investigate Web Activity From src_ip", - "type": "splunk" - }, - { - "id": "9df9ca9c-a02b-4f48-9eba-0bac55179050", - "name": "Investigate Network Traffic From src_ip", - "type": "splunk" - } - ], - "known_false_positives": "Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information.", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 4", - "CIS 18" - ], - "kill_chain_phases": [ - "Delivery" - ], - "mitre_attack": [ - "Defense Evasion", - "Exploitation of Vulnerability" - ], - "nist": [ - "ID.RA", - "RS.MI", - "PR.PT", - "PR.AC", - "PR.IP", - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" }, - "modification_date": "2018-06-14", - "name": "Splunk Enterprise Information Disclosure", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + { + "id": "2f5b960b-71df-49c0-affc-74992ce60e45", + "name": "Investigate Web Activity From src_ip", + "type": "splunk" + }, + { + "id": "9df9ca9c-a02b-4f48-9eba-0bac55179050", + "name": "Investigate Network Traffic From src_ip", + "type": "splunk" + } + ], + "known_false_positives": "Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information.", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 4", + "CIS 18" ], - "references": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Delivery" + ], + "mitre_attack": [ + "Defense Evasion", + "Exploitation of Vulnerability" + ], + "nist": [ + "ID.RA", + "RS.MI", + "PR.PT", + "PR.AC", + "PR.IP", + "DE.CM" + ] + }, + "modification_date": "2018-06-14", + "name": "Splunk Enterprise Information Disclosure", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/stop_security_services.json b/detections/stop_security_services.json index 9add64cfdd..f768fad1c7 100644 --- a/detections/stop_security_services.json +++ b/detections/stop_security_services.json @@ -1,139 +1,139 @@ { - "asset_type": "Endpoint", - "confidence": "high", - "creation_date": "2018-04-09", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "high", + "creation_date": "2018-04-09", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for attempts to stop security-related services on the endpoint.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, process, user", + "rule_description": "Attempt to stop a security-related service on $dest$", + "rule_title": "Attempt to Stop Security Service On $dest$" + }, + "risk": { + "risk_object": "src", + "risk_object_type": [ + "system" + ], + "risk_score": 50 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name = net.exe OR Processes.process_name = sc.exe) Processes.process=\"* stop *\" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `ctime(firstTime)` | `ctime(lastTime)` |lookup security_services_lookup service as process OUTPUTNEW category, description | search category=security", + "suppress": { + "suppress_fields": "dest, user", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search looks for the processes **net.exe** and **sc.exe** with a parameter of `\"stop\"`. It then searches a list of security-related services included in a lookup file for matches on the command line. Results are subsequently returned in table format. The included lookup file can be modified to update the services to monitor.", + "entities": [ + "src" + ], + "how_to_implement": "You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service.,", + "id": "c8e349c6-b97c-486e-8949-bd7bcd1f3910", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search looks for attempts to stop security-related services on the endpoint.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, process, user", - "rule_description": "Attempt to stop a security-related service on $dest$", - "rule_title": "Attempt to Stop Security Service On $dest$" - }, - "risk": { - "risk_object": "src", - "risk_object_type": [ - "system" - ], - "risk_score": 50 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name = net.exe OR Processes.process_name = sc.exe) Processes.process=\"* stop *\" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `ctime(firstTime)` | `ctime(lastTime)` |lookup security_services_lookup service as process OUTPUTNEW category, description | search category=security", - "suppress": { - "suppress_fields": "dest, user", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search looks for the processes net.exe and sc.exe with a parameter of \"stop\". It then searches a list of security-related services included in a lookup file for matches on the command line. Results are subsequently returned in table format. The included lookup file can be modified to update the services to monitor.", - "entities": [ - "src" - ], - "how_to_implement": "You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, security_services.csv, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in $SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service.,", - "id": "c8e349c6-b97c-486e-8949-bd7bcd1f3910", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "None identified. Attempts to disable security-related services should be identified and understood.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 5", - "CIS 8" - ], - "kill_chain_phases": [ - "Installation", - "Actions on Objectives" - ], - "mitre_attack": [ - "Defense Evasion", - "Disabling Security Tools" - ], - "nist": [ - "PR.PT", - "DE.CM", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2017-09-15", - "name": "Attempt To Stop Security Service", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "None identified. Attempts to disable security-related services should be identified and understood.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 5", + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Installation", + "Actions on Objectives" + ], + "mitre_attack": [ + "Defense Evasion", + "Disabling Security Tools" + ], + "nist": [ + "PR.PT", + "DE.CM", + "PR.IP" + ] + }, + "modification_date": "2017-09-15", + "name": "Attempt To Stop Security Service", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/suspicious_email_attachments.json b/detections/suspicious_email_attachments.json index 1b64d3da42..5d15ec8d78 100644 --- a/detections/suspicious_email_attachments.json +++ b/detections/suspicious_email_attachments.json @@ -1,99 +1,99 @@ { - "asset_type": "Endpoint", - "channel": "ESCU", - "confidence": "high", - "creation_date": "2017-04-20", - "data_metadata": { - "data_models": [ - "Email" - ], - "data_source": [ - "Email" - ], - "providing_technologies": [ - "Microsoft Exchange" - ] - }, - "description": "This search looks for emails that have attachments with suspicious file extensions.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "src_user, file_name", - "rule_description": "The sender $src_user$ has sent an email with a suspicious file named $file_name$", - "rule_title": "Suspicious Email Attachment from $src_user$" - }, - "risk": { - "risk_object": "src_user", - "risk_object_type": [ - "user" - ], - "risk_score": 60 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name=\"*\" by All_Email.src_user, All_Email.file_name All_Email.message_id | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(\"All_Email\")` | `suspicious_email_attachments`", - "suppress": { - "suppress_fields": "src_user,message_id", - "suppress_period": "86400s" - } - } - } - }, - "eli5": "This search looks at any email messages with attachments and checks the file names of those attachments against an included lookup file to see if it has a suspicious file extension.", - "entities": [ - "src_user", - "message_id" + "asset_type": "Endpoint", + "channel": "ESCU", + "confidence": "high", + "creation_date": "2017-04-20", + "data_metadata": { + "data_models": [ + "Email" ], - "how_to_implement": "You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model.

        Splunk Phantom Playbook Integration

        If Splunk Phantom is also configured in your environment, a Playbook called \"Suspicious Email Attachment Investigate and Delete\" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk https://splunkbase.splunk.com/app/3411/, and add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox.", - "id": "473bd65f-06ca-4dfe-a2b8-ba04ab4a0084", - "investigations": [ - { - "id": "3096f721-8842-42ce-2fc7-742d8372b712", - "name": "Suspicious Email Attachment Investigate and Delete", - "type": "phantom" - } + "data_source": [ + "Email" ], - "known_false_positives": "None identified", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" + "providing_technologies": [ + "Microsoft Exchange" + ] + }, + "description": "This search looks for emails that have attachments with suspicious file extensions.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "src_user, file_name", + "rule_description": "The sender $src_user$ has sent an email with a suspicious file named $file_name$", + "rule_title": "Suspicious Email Attachment from $src_user$" + }, + "risk": { + "risk_object": "src_user", + "risk_object_type": [ + "user" + ], + "risk_score": 60 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name=\"*\" by All_Email.src_user, All_Email.file_name All_Email.message_id | `ctime(firstTime)` | `ctime(lastTime)` | `drop_dm_object_name(\"All_Email\")` | `suspicious_email_attachments`", + "suppress": { + "suppress_fields": "src_user,message_id", + "suppress_period": "86400s" } + } + } + }, + "eli5": "This search looks at any email messages with attachments and checks the file names of those attachments against an included lookup file to see if it has a suspicious file extension.", + "entities": [ + "src_user", + "message_id" + ], + "how_to_implement": "You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \n\n **Splunk Phantom Playbook Integration**\n\nIf Splunk Phantom is also configured in your environment, a Playbook called \"Suspicious Email Attachment Investigate and Delete\" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, and add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox.", + "id": "473bd65f-06ca-4dfe-a2b8-ba04ab4a0084", + "investigations": [ + { + "id": "3096f721-8842-42ce-2fc7-742d8372b712", + "name": "Suspicious Email Attachment Investigate and Delete", + "type": "phantom" + } + ], + "known_false_positives": "None identified", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 7", + "CIS 12" ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 7", - "CIS 12" - ], - "kill_chain_phases": [ - "Delivery" - ], - "mitre_attack": [ - "Execution", - "Defense Evasion" - ], - "nist": [ - "DE.AE", - "PR.IP" - ] - }, - "modification_date": "2019-05-13", - "name": "Suspicious Email Attachment Extensions", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } + "kill_chain_phases": [ + "Delivery" ], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "mitre_attack": [ + "Execution", + "Defense Evasion" + ], + "nist": [ + "DE.AE", + "PR.IP" + ] + }, + "modification_date": "2019-05-13", + "name": "Suspicious Email Attachment Extensions", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/suspicious_write_to_recycler.json b/detections/suspicious_write_to_recycler.json index 57c1fc07a1..b7b0717f0b 100644 --- a/detections/suspicious_write_to_recycler.json +++ b/detections/suspicious_write_to_recycler.json @@ -1,127 +1,127 @@ { - "asset_type": "Windows", - "confidence": "medium", - "creation_date": "2018-01-08", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Sysmon" - ] + "asset_type": "Windows", + "confidence": "medium", + "creation_date": "2018-01-08", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Sysmon" + ] + }, + "description": "This search detects writes to the recycle bin by a process other than explorer.exe.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, file_name, process_name", + "rule_description": "The process $process_name$ on $dest$ wrote $file_name$ to the Recycle Bin.", + "rule_title": "Suspicious process $process_name$ wrote to the Recycle Bin on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 70 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.file_path) as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem where Filesystem.filepath = \"*$Recycle.Bin*\" by Filesystem.process_id Filesystem.dest | `drop_dm_object_name(\"Filesystem\")`| search [| tstats `summariesonly` values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name != \"explorer.exe\" by Processes.process_id Processes.dest| `drop_dm_object_name(\"Processes\")` | table process_id dest]", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search uses data on file writes captured via Sysmon to watch for writes to the Recycle Bin by processes other than explorer.exe. The search looks for event code 11 in the Sysmon events, which indicates a file-creation event. Next, it looks for files created with a path that includes the string \"$Recycle.Bin\" by processes other than explorer.exe, which is the process responsible for copying files to the Recycle Bin on delete. It will report the system where the activity occurred, the path to which the file was written, the process responsible for the write, and the times it first and last saw this activity.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes.", + "id": "b5541828-8ffd-4070-9d95-b3da4de924cb", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search detects writes to the recycle bin by a process other than explorer.exe.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, file_name, process_name", - "rule_description": "The process $process_name$ on $dest$ wrote $file_name$ to the Recycle Bin.", - "rule_title": "Suspicious process $process_name$ wrote to the Recycle Bin on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 70 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.file_path) as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem where Filesystem.filepath = \"*$Recycle.Bin*\" by Filesystem.process_id Filesystem.dest | `drop_dm_object_name(\"Filesystem\")`| search [| tstats `summariesonly` values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name != \"explorer.exe\" by Processes.process_id Processes.dest| `drop_dm_object_name(\"Processes\")` | table process_id dest]", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search uses data on file writes captured via Sysmon to watch for writes to the Recycle Bin by processes other than explorer.exe. The search looks for event code 11 in the Sysmon events, which indicates a file-creation event. Next, it looks for files created with a path that includes the string \"$Recycle.Bin\" by processes other than explorer.exe, which is the process responsible for copying files to the Recycle Bin on delete. It will report the system where the activity occurred, the path to which the file was written, the process responsible for the write, and the times it first and last saw this activity.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes.", - "id": "b5541828-8ffd-4070-9d95-b3da4de924cb", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "mitre_attack": [ - "Collection", - "Data Staged" - ], - "nist": [ - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2019-03-01", - "name": "Suspicious writes to windows Recycle Bin", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "mitre_attack": [ + "Collection", + "Data Staged" + ], + "nist": [ + "DE.CM" + ] + }, + "modification_date": "2019-03-01", + "name": "Suspicious writes to windows Recycle Bin", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/suspicious_write_to_sysvol.json b/detections/suspicious_write_to_sysvol.json index 6968d45904..8ced6316f5 100644 --- a/detections/suspicious_write_to_sysvol.json +++ b/detections/suspicious_write_to_sysvol.json @@ -1,127 +1,127 @@ { - "asset_type": "Windows", - "confidence": "medium", - "creation_date": "2018-01-08", - "data_metadata": { - "data_source": [ - "Endpoint Intel" - ], - "data_sourcetypes": [ - "XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" - ], - "providing_technologies": [ - "Sysmon" - ] + "asset_type": "Windows", + "confidence": "medium", + "creation_date": "2018-01-08", + "data_metadata": { + "data_source": [ + "Endpoint Intel" + ], + "data_sourcetypes": [ + "XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" + ], + "providing_technologies": [ + "Sysmon" + ] + }, + "description": "This search detects writes to the 'System Volume Information' folder by something other than the System process.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, file_name, process", + "rule_description": "The process $process$ on $dest$ wrote $file_name$ to 'System Volume Information'.", + "rule_title": "Suspicious process $process$ wrote to 'System Volume Information' on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 70 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "(sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational OR tag=process) EventCode=11 process_id!=4 file_path=*System\\ Volume\\ Information* | stats count min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path | `ctime(firstTime)`| `ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "86400s" + } + } + } + }, + "eli5": "This search uses data on file writes captured via Sysmon to watch for writes to the \"System Volume Information\" folder by processes other than the system process. The search looks for event code 11 in the Sysmon events, which indicates a file-creation event. It then looks for a file created with a path that includes \"System Volume Information\" and a process ID (PID) other than 4. PID 4 is assigned to the System process on Windows systems. Excluding these writes allows us to filter out legitimate activity. It will report the system where the activity occurred, the path to which the file was written, the process responsible for the write, and the times it first and last saw this activity.", + "entities": [ + "dest" + ], + "how_to_implement": "You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.", + "id": "cd6297cd-2bdd-4aa1-84aa-5d2f84228fac", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "description": "This search detects writes to the 'System Volume Information' folder by something other than the System process.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, file_name, process", - "rule_description": "The process $process$ on $dest$ wrote $file_name$ to 'System Volume Information'.", - "rule_title": "Suspicious process $process$ wrote to 'System Volume Information' on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 70 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "(sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational OR tag=process) EventCode=11 process_id!=4 file_path=*System\\ Volume\\ Information* | stats count min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path | `ctime(firstTime)`| `ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "86400s" - } - } - } + { + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "name": "Get Parent Process Info", + "type": "splunk" }, - "eli5": "This search uses data on file writes captured via Sysmon to watch for writes to the \"System Volume Information\" folder by processes other than the system process. The search looks for event code 11 in the Sysmon events, which indicates a file-creation event. It then looks for a file created with a path that includes \"System Volume Information\" and a process ID (PID) other than 4. PID 4 is assigned to the System process on Windows systems. Excluding these writes allows us to filter out legitimate activity. It will report the system where the activity occurred, the path to which the file was written, the process responsible for the write, and the times it first and last saw this activity.", - "entities": [ - "dest" - ], - "how_to_implement": "You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA.", - "id": "cd6297cd-2bdd-4aa1-84aa-5d2f84228fac", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "name": "Get Parent Process Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 8" - ], - "mitre_attack": [ - "Collection", - "Data Staged" - ], - "nist": [ - "DE.CM" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-01-08", - "name": "Suspicious writes to System Volume Information", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 8" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "mitre_attack": [ + "Collection", + "Data Staged" + ], + "nist": [ + "DE.CM" + ] + }, + "modification_date": "2018-01-08", + "name": "Suspicious writes to System Volume Information", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/unauthorized_dns_servers.json b/detections/unauthorized_dns_servers.json index 32164f2f06..9689db226f 100644 --- a/detections/unauthorized_dns_servers.json +++ b/detections/unauthorized_dns_servers.json @@ -1,107 +1,107 @@ { - "asset_type": "Endpoint", - "baselines": [], - "confidence": "medium", - "creation_date": "2017-07-08", - "data_metadata": { - "data_models": [ - "Network_Resolution" - ], - "data_source": [ - "DNS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, src", - "rule_description": "The table represents a list of unauthorized DNS servers interacting with hosts in your network", - "rule_title": "DNS requests resolved by unauthorized DNS servers" - }, - "risk": { - "risk_object": "src", - "risk_object_type": [ - "system" - ], - "risk_score": 40 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count from datamodel=Network_Resolution where DNS.dest_category != dns_server AND DNS.src_category != dns_server by DNS.src DNS.dest | `drop_dm_object_name(\"DNS\")`", - "suppress": { - "suppress_fields": "dest,src", - "suppress_period": "28800s" - } - } - } - }, - "eli5": "Clients should be resolving their DNS requests via a trusted DNS server. This search will identify DNS queries being sent to unauthorized DNS servers by comparing the destination and source of the traffic with assets marked as DNS servers.", - "entities": [ - "dest", - "src" + "asset_type": "Endpoint", + "baselines": [], + "confidence": "medium", + "creation_date": "2017-07-08", + "data_metadata": { + "data_models": [ + "Network_Resolution" ], - "how_to_implement": "To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security.", - "id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", - "investigations": [ - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", - "name": "Get DNS Server History for a host", - "type": "splunk" - } + "data_source": [ + "DNS" ], - "known_false_positives": "Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate.", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, src", + "rule_description": "The table represents a list of unauthorized DNS servers interacting with hosts in your network", + "rule_title": "DNS requests resolved by unauthorized DNS servers" + }, + "risk": { + "risk_object": "src", + "risk_object_type": [ + "system" + ], + "risk_score": 40 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count from datamodel=Network_Resolution where DNS.dest_category != dns_server AND DNS.src_category != dns_server by DNS.src DNS.dest | `drop_dm_object_name(\"DNS\")`", + "suppress": { + "suppress_fields": "dest,src", + "suppress_period": "28800s" } + } + } + }, + "eli5": "Clients should be resolving their DNS requests via a trusted DNS server. This search will identify DNS queries being sent to unauthorized DNS servers by comparing the destination and source of the traffic with assets marked as DNS servers.", + "entities": [ + "dest", + "src" + ], + "how_to_implement": "To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security.", + "id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", + "investigations": [ + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", + "name": "Get DNS Server History for a host", + "type": "splunk" + } + ], + "known_false_positives": "Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate.", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "mappings": { + "cis20": [ + "CIS 1", + "CIS 3", + "CIS 8", + "CIS 12" ], - "mappings": { - "cis20": [ - "CIS 1", - "CIS 3", - "CIS 8", - "CIS 12" - ], - "kill_chain_phases": [ - "Command and Control" - ], - "mitre_attack": [ - "Exfiltration", - "Command and Control", - "Defense Evasion", - "Commonly Used Port" - ], - "nist": [ - "ID.AM", - "PR.DS", - "PR.IP", - "DE.AE", - "DE.CM" - ] - }, - "modification_date": "2017-09-18", - "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "kill_chain_phases": [ + "Command and Control" ], - "responses": [], - "security_domain": "network", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "mitre_attack": [ + "Exfiltration", + "Command and Control", + "Defense Evasion", + "Commonly Used Port" + ], + "nist": [ + "ID.AM", + "PR.DS", + "PR.IP", + "DE.AE", + "DE.CM" + ] + }, + "modification_date": "2017-09-18", + "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "responses": [], + "security_domain": "network", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/users_without_mfa.json b/detections/users_without_mfa.json index 9d49cc5cba..5240ec1175 100644 --- a/detections/users_without_mfa.json +++ b/detections/users_without_mfa.json @@ -46,7 +46,7 @@ "entities": [ "user" ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Leverage the support search Create a list of approved AWS service accounts: run it once every 30 days to create a list of service accounts and validate them.

        This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):

        • Label: AWS Event Name, Field: eventName
        • Label: AWS User ARN, Field: userIdentity.arn
        • Label: AWS User Type, Field: userIdentity.type


        Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Leverage the support search `Create a list of approved AWS service accounts`: run it once every 30 days to create a list of service accounts and validate them.\n\nThis search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n\n
        • **Label:** AWS Event Name, **Field:** eventName
        • **Label:** AWS User ARN, **Field:** userIdentity.arn
        • **Label:** AWS User Type, **Field:** userIdentity.type
        \n\nDetailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`", "id": "2a9b80d3-6340-4345-w5ad-212bf5d1dac4", "investigations": [ { diff --git a/detections/wmi_perm_event_subscription.json b/detections/wmi_perm_event_subscription.json index 55c27ab0df..912047014f 100644 --- a/detections/wmi_perm_event_subscription.json +++ b/detections/wmi_perm_event_subscription.json @@ -1,136 +1,136 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-10-23", - "data_metadata": { - "data_source": [ - "Microsoft Windows" - ], - "data_sourcetypes": [ - "WinEventLog://Microsoft-Windows-WMI-Activity/Operational" - ], - "providing_technologies": [ - "Microsoft Windows" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-10-23", + "data_metadata": { + "data_source": [ + "Microsoft Windows" + ], + "data_sourcetypes": [ + "WinEventLog://Microsoft-Windows-WMI-Activity/Operational" + ], + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search looks for the creation of WMI permanent event subscriptions.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest", + "rule_description": "This search looks for the creation of a permanent WMI event subscription via Windows event logs.", + "rule_title": "WMI Event Subscription Detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 70 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=\"wineventlog:microsoft-windows-wmi-activity/operational\" EventCode=5861 Binding | rex field=Message \"Consumer =\\s+(?[^;|^$]+)\" | search consumer!=\"NTEventLogEventConsumer=\\\"SCM Event Log Consumer\\\"\" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, consumer, Message | `ctime(firstTime)`| `ctime(lastTime)` | rename ComputerName as dest", + "suppress": { + "suppress_fields": "dest", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI event subscription by watching for Windows event ID 5861.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational].", + "id": "71bfdb13-f200-4c6c-b2c9-a2e07adf437d", + "investigations": [ + { + "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", + "name": "Get Sysmon WMI Activity for Host", + "type": "splunk" }, - "description": "This search looks for the creation of WMI permanent event subscriptions.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest", - "rule_description": "This search looks for the creation of a permanent WMI event subscription via Windows event logs.", - "rule_title": "WMI Event Subscription Detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 70 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=\"wineventlog:microsoft-windows-wmi-activity/operational\" EventCode=5861 Binding | rex field=Message \"Consumer =\\s+(?[^;|^$]+)\" | search consumer!=\"NTEventLogEventConsumer=\\\"SCM Event Log Consumer\\\"\" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, consumer, Message | `ctime(firstTime)`| `ctime(lastTime)` | rename ComputerName as dest", - "suppress": { - "suppress_fields": "dest", - "suppress_period": "28800s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI event subscription by watching for Windows event ID 5861.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational].", - "id": "71bfdb13-f200-4c6c-b2c9-a2e07adf437d", - "investigations": [ - { - "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", - "name": "Get Sysmon WMI Activity for Host", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Although unlikely, administrators may use event subscriptions for legitimate purposes.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 5" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Windows Management Instrumentation", - "Persistence", - "Windows Management Instrumentation Event Subscription" - ], - "nist": [ - "PR.PT", - "PR.AT", - "PR.AC", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-10-23", - "name": "WMI Permanent Event Subscription", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Although unlikely, administrators may use event subscriptions for legitimate purposes.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 5" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Windows Management Instrumentation", + "Persistence", + "Windows Management Instrumentation Event Subscription" + ], + "nist": [ + "PR.PT", + "PR.AT", + "PR.AC", + "PR.IP" + ] + }, + "modification_date": "2018-10-23", + "name": "WMI Permanent Event Subscription", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/wmi_perm_event_subscription_sysmon.json b/detections/wmi_perm_event_subscription_sysmon.json index dd3c3ba324..d8d9289524 100644 --- a/detections/wmi_perm_event_subscription_sysmon.json +++ b/detections/wmi_perm_event_subscription_sysmon.json @@ -1,136 +1,136 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-10-23", - "data_metadata": { - "data_source": [ - "Microsoft Windows" - ], - "data_sourcetypes": [ - "WinEventLog://Microsoft-Windows-WMI-Activity/Operational" - ], - "providing_technologies": [ - "Microsoft Windows" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-10-23", + "data_metadata": { + "data_source": [ + "Microsoft Windows" + ], + "data_sourcetypes": [ + "WinEventLog://Microsoft-Windows-WMI-Activity/Operational" + ], + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search looks for the creation of WMI permanent event subscriptions.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user", + "rule_description": "This search looks for the creation of a permanent WMI event subscription via Sysmon logs.", + "rule_title": "WMI Event Subscription Detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 70 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=\"XmlWinEventLog:Microsoft-Windows-Sysmon/Operational\" EventCode=21 | rename host as dest | table _time, dest, user, Operation, EventType, Query, Consumer, Filter", + "suppress": { + "suppress_fields": "dest,user", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI event subscription by watching for Sysmon event ID 21.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate alerts for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields.", + "id": "ad05aae6-3b2a-4f73-af97-57bd26cee3b9", + "investigations": [ + { + "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", + "name": "Get Sysmon WMI Activity for Host", + "type": "splunk" }, - "description": "This search looks for the creation of WMI permanent event subscriptions.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user", - "rule_description": "This search looks for the creation of a permanent WMI event subscription via Sysmon logs.", - "rule_title": "WMI Event Subscription Detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 70 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=\"XmlWinEventLog:Microsoft-Windows-Sysmon/Operational\" EventCode=21 | rename host as dest | table _time, dest, user, Operation, EventType, Query, Consumer, Filter", - "suppress": { - "suppress_fields": "dest,user", - "suppress_period": "28800s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI event subscription by watching for Sysmon event ID 21.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate alerts for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields.", - "id": "ad05aae6-3b2a-4f73-af97-57bd26cee3b9", - "investigations": [ - { - "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", - "name": "Get Sysmon WMI Activity for Host", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Although unlikely, administrators may use event subscriptions for legitimate purposes.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 5" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Windows Management Instrumentation", - "Persistence", - "Windows Management Instrumentation Event Subscription" - ], - "nist": [ - "PR.PT", - "PR.AT", - "PR.AC", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-10-23", - "name": "WMI Permanent Event Subscription - Sysmon", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Although unlikely, administrators may use event subscriptions for legitimate purposes.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 5" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Windows Management Instrumentation", + "Persistence", + "Windows Management Instrumentation Event Subscription" + ], + "nist": [ + "PR.PT", + "PR.AT", + "PR.AC", + "PR.IP" + ] + }, + "modification_date": "2018-10-23", + "name": "WMI Permanent Event Subscription - Sysmon", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/detections/wmi_script_execution.json b/detections/wmi_script_execution.json index a8517e0a27..f0c83eba3e 100644 --- a/detections/wmi_script_execution.json +++ b/detections/wmi_script_execution.json @@ -1,137 +1,137 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-10-23", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "Sysmon", - "Tanium", - "Ziften" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-10-23", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search looks for scripts launched via WMI.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process", + "rule_description": "This search looks for scrcons.exe, which indicates that a script was launched via WMI.", + "rule_title": "Script execution via WMI on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 70 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = \"scrcons.exe\" by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`| `ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest,process", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "Attackers are increasingly abusing Windows Management Infrastructure for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for scripts launched via WMI, either remotely or locally, by looking for the execution of scrcons.exe, which is the scripting host used by WMI, similar to wscript or cscript.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "aa73f80d-d728-4077-b226-81ea0c8be589", + "investigations": [ + { + "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", + "name": "Get Sysmon WMI Activity for Host", + "type": "splunk" }, - "description": "This search looks for scripts launched via WMI.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process", - "rule_description": "This search looks for scrcons.exe, which indicates that a script was launched via WMI.", - "rule_title": "Script execution via WMI on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 70 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = \"scrcons.exe\" by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`| `ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest,process", - "suppress_period": "28800s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "Attackers are increasingly abusing Windows Management Infrastructure for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for scripts launched via WMI, either remotely or locally, by looking for the execution of scrcons.exe, which is the scripting host used by WMI, similar to wscript or cscript.", - "entities": [ - "dest" - ], - "how_to_implement": "You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "aa73f80d-d728-4077-b226-81ea0c8be589", - "investigations": [ - { - "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", - "name": "Get Sysmon WMI Activity for Host", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Although unlikely, administrators may use wmi to launch scripts for legitimate purposes.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 5" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Windows Management Instrumentation" - ], - "nist": [ - "PR.PT", - "PR.AT", - "PR.AC", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2019-03-01", - "name": "Script Execution via WMI", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Although unlikely, administrators may use wmi to launch scripts for legitimate purposes.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 5" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Windows Management Instrumentation" + ], + "nist": [ + "PR.PT", + "PR.AT", + "PR.AC", + "PR.IP" + ] + }, + "modification_date": "2019-03-01", + "name": "Script Execution via WMI", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/detections/wmi_temp_event_subscription.json b/detections/wmi_temp_event_subscription.json index 5241b74f9f..c2e243db0b 100644 --- a/detections/wmi_temp_event_subscription.json +++ b/detections/wmi_temp_event_subscription.json @@ -1,136 +1,136 @@ { - "asset_type": "Endpoint", - "confidence": "medium", - "creation_date": "2018-10-23", - "data_metadata": { - "data_source": [ - "Microsoft Windows" - ], - "data_sourcetypes": [ - "WinEventLog://Microsoft-Windows-WMI-Activity/Operational" - ], - "providing_technologies": [ - "Microsoft Windows" - ] + "asset_type": "Endpoint", + "confidence": "medium", + "creation_date": "2018-10-23", + "data_metadata": { + "data_source": [ + "Microsoft Windows" + ], + "data_sourcetypes": [ + "WinEventLog://Microsoft-Windows-WMI-Activity/Operational" + ], + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search looks for the creation of WMI temporary event subscriptions.", + "detect": { + "splunk": { + "correlation_rule": { + "notable": { + "nes_fields": "dest, user, process", + "rule_description": "This search looks for the creation of a temporary WMI event subscription via Windows event logs.", + "rule_title": "Temporary WMI Event Subscription Detected on $dest$" + }, + "risk": { + "risk_object": "dest", + "risk_object_type": [ + "system" + ], + "risk_score": 70 + }, + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "sourcetype=\"wineventlog:microsoft-windows-wmi-activity/operational\" EventCode=5860 Temporary | rex field=Message \"NotificationQuery =\\s+(?[^;|^$]+)\" | search query!=\"SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = 'wsmprovhost.exe'\" AND query!=\"SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA 'AntiVirusProduct' OR TargetInstance ISA 'FirewallProduct' OR TargetInstance ISA 'AntiSpywareProduct'\" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, query | `ctime(firstTime)`| `ctime(lastTime)`", + "suppress": { + "suppress_fields": "dest,user", + "suppress_period": "28800s" + } + } + } + }, + "eli5": "Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI temporary event subscription by watching for Windows event ID 5860.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational].", + "id": "38cbd42c-1098-41bb-99cf-9d6d2b296d83", + "investigations": [ + { + "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", + "name": "Get Sysmon WMI Activity for Host", + "type": "splunk" }, - "description": "This search looks for the creation of WMI temporary event subscriptions.", - "detect": { - "splunk": { - "correlation_rule": { - "notable": { - "nes_fields": "dest, user, process", - "rule_description": "This search looks for the creation of a temporary WMI event subscription via Windows event logs.", - "rule_title": "Temporary WMI Event Subscription Detected on $dest$" - }, - "risk": { - "risk_object": "dest", - "risk_object_type": [ - "system" - ], - "risk_score": 70 - }, - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "sourcetype=\"wineventlog:microsoft-windows-wmi-activity/operational\" EventCode=5860 Temporary | rex field=Message \"NotificationQuery =\\s+(?[^;|^$]+)\" | search query!=\"SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = 'wsmprovhost.exe'\" AND query!=\"SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA 'AntiVirusProduct' OR TargetInstance ISA 'FirewallProduct' OR TargetInstance ISA 'AntiSpywareProduct'\" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, query | `ctime(firstTime)`| `ctime(lastTime)`", - "suppress": { - "suppress_fields": "dest,user", - "suppress_period": "28800s" - } - } - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "name": "Get Authentication Logs For Endpoint", + "type": "splunk" }, - "eli5": "Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI temporary event subscription by watching for Windows event ID 5860.", - "entities": [ - "dest" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational].", - "id": "38cbd42c-1098-41bb-99cf-9d6d2b296d83", - "investigations": [ - { - "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", - "name": "Get Sysmon WMI Activity for Host", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "name": "Get Authentication Logs For Endpoint", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "name": "Get Risk Modifiers For User", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "name": "Get Process Info", - "type": "splunk" - }, - { - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "name": "Get Notable History", - "type": "splunk" - }, - { - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "name": "Get Notable Info", - "type": "splunk" - }, - { - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "name": "Get Risk Modifiers For Endpoint", - "type": "splunk" - }, - { - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "name": "Get User Information from Identity Table", - "type": "splunk" - } - ], - "known_false_positives": "Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to create exceptions for other legitimate events.", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "mappings": { - "cis20": [ - "CIS 3", - "CIS 5" - ], - "kill_chain_phases": [ - "Actions on Objectives" - ], - "mitre_attack": [ - "Execution", - "Windows Management Instrumentation", - "Persistence", - "Windows Management Instrumentation Event Subscription" - ], - "nist": [ - "PR.PT", - "PR.AT", - "PR.AC", - "PR.IP" - ] + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "name": "Get Risk Modifiers For User", + "type": "splunk" }, - "modification_date": "2018-10-23", - "name": "WMI Temporary Event Subscription", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "name": "Get Process Info", + "type": "splunk" + }, + { + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "name": "Get Notable History", + "type": "splunk" + }, + { + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "name": "Get Notable Info", + "type": "splunk" + }, + { + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "name": "Get Risk Modifiers For Endpoint", + "type": "splunk" + }, + { + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "name": "Get User Information from Identity Table", + "type": "splunk" + } + ], + "known_false_positives": "Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to create exceptions for other legitimate events.", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "mappings": { + "cis20": [ + "CIS 3", + "CIS 5" ], - "references": [], - "security_domain": "endpoint", - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "kill_chain_phases": [ + "Actions on Objectives" + ], + "mitre_attack": [ + "Execution", + "Windows Management Instrumentation", + "Persistence", + "Windows Management Instrumentation Event Subscription" + ], + "nist": [ + "PR.PT", + "PR.AT", + "PR.AC", + "PR.IP" + ] + }, + "modification_date": "2018-10-23", + "name": "WMI Temporary Event Subscription", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [], + "security_domain": "endpoint", + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/aws_activity_via_region.json b/investigations/aws_activity_via_region.json index 15ffcec49f..f2445ffea9 100644 --- a/investigations/aws_activity_via_region.json +++ b/investigations/aws_activity_via_region.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-02-09", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user", - "entities": [ + "creation_date": "2018-02-09", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user", + "entities": [ + "awsRegion" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd11", + "investigate": { + "splunk": { + "fields_required": [ "awsRegion" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd11", - "investigate": { - "splunk": { - "fields_required": [ - "awsRegion" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "14400", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-02-09", - "name": "Investigate AWS activities via region name", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "14400", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-02-09", + "name": "Investigate AWS activities via region name", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/aws_network_interface_details.json b/investigations/aws_network_interface_details.json index dc822d025d..0a2e5a03bb 100644 --- a/investigations/aws_network_interface_details.json +++ b/investigations/aws_network_interface_details.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-05-07", - "data_metadata": { - "data_source": [ - "AWS Configuration Logs" - ], - "data_sourcetypes": [ - "aws:config" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface.", - "entities": [ + "creation_date": "2018-05-07", + "data_metadata": { + "data_source": [ + "AWS Configuration Logs" + ], + "data_sourcetypes": [ + "aws:config" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface.", + "entities": [ + "resourceId" + ], + "how_to_implement": "In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS configuration inputs", + "id": "f3fb4d1c-5f33-4b01-b541-c3ah9534c241", + "investigate": { + "splunk": { + "fields_required": [ "resourceId" - ], - "how_to_implement": "In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS configuration inputs", - "id": "f3fb4d1c-5f33-4b01-b541-c3ah9534c241", - "investigate": { - "splunk": { - "fields_required": [ - "resourceId" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "86400", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:config resourceId={resourceId} | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-05-07", - "name": "AWS Network Interface details via resourceId", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "86400", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:config resourceId={resourceId} | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-05-07", + "name": "AWS Network Interface details via resourceId", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/aws_s3_bucket_details.json b/investigations/aws_s3_bucket_details.json index 64b7581e74..c95c311871 100644 --- a/investigations/aws_s3_bucket_details.json +++ b/investigations/aws_s3_bucket_details.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-06-26", - "data_metadata": { - "data_source": [ - "AWS Configuration Logs" - ], - "data_sourcetypes": [ - "aws:config" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket.", - "entities": [ + "creation_date": "2018-06-26", + "data_metadata": { + "data_source": [ + "AWS Configuration Logs" + ], + "data_sourcetypes": [ + "aws:config" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket.", + "entities": [ + "bucketName" + ], + "how_to_implement": "To implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later) and configure your AWS inputs.", + "id": "f3fb2q1c-5f33-4b01-b541-c2ah9534c242", + "investigate": { + "splunk": { + "fields_required": [ "bucketName" - ], - "how_to_implement": "To implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later) and configure your AWS inputs.", - "id": "f3fb2q1c-5f33-4b01-b541-c2ah9534c242", - "investigate": { - "splunk": { - "fields_required": [ - "bucketName" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "86400", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-06-26", - "name": "AWS S3 Bucket details via bucketName", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "86400", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-06-26", + "name": "AWS S3 Bucket details via bucketName", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/aws_user_activities_by_user_field.json b/investigations/aws_user_activities_by_user_field.json index 7d06ec752f..fa333f68b5 100644 --- a/investigations/aws_user_activities_by_user_field.json +++ b/investigations/aws_user_activities_by_user_field.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-03-12", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information.", - "entities": [ + "creation_date": "2018-03-12", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information.", + "entities": [ + "user" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd76", + "investigate": { + "splunk": { + "fields_required": [ "user" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd76", - "investigate": { - "splunk": { - "fields_required": [ - "user" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "14400", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType " - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-03-12", - "name": "Investigate AWS User Activities by user field", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "14400", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType " + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-03-12", + "name": "Investigate AWS User Activities by user field", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/aws_user_activity_by_accesskeyid.json b/investigations/aws_user_activity_by_accesskeyid.json index 08359e7320..fd5a1ab6cb 100644 --- a/investigations/aws_user_activity_by_accesskeyid.json +++ b/investigations/aws_user_activity_by_accesskeyid.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-06-08", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials.", - "entities": [ + "creation_date": "2018-06-08", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials.", + "entities": [ + "accessKeyId" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "703b65a4-a0ae-4171-965d-45507506c64f", + "investigate": { + "splunk": { + "fields_required": [ "accessKeyId" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "703b65a4-a0ae-4171-965d-45507506c64f", - "investigate": { - "splunk": { - "fields_required": [ - "accessKeyId" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "0", - "latest_time": "14400" - }, - "search": "| search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-06-08", - "name": "AWS Investigate User Activities By AccessKeyId", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "0", + "latest_time": "14400" + }, + "search": "| search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-06-08", + "name": "AWS Investigate User Activities By AccessKeyId", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/aws_user_activity_by_src_user.json b/investigations/aws_user_activity_by_src_user.json index 1349c88aee..dd2b43cd17 100644 --- a/investigations/aws_user_activity_by_src_user.json +++ b/investigations/aws_user_activity_by_src_user.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-06-08", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs.", - "entities": [ + "creation_date": "2018-06-08", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs.", + "entities": [ + "src_user" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "b0d2e6a8-75fa-4b1b-9486-3d32acadf891", + "investigate": { + "splunk": { + "fields_required": [ "src_user" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "b0d2e6a8-75fa-4b1b-9486-3d32acadf891", - "investigate": { - "splunk": { - "fields_required": [ - "src_user" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "14400", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-06-08", - "name": "AWS Investigate User Activities By Source User", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "14400", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-06-08", + "name": "AWS Investigate User Activities By Source User", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/dns_hijack_enrichment.json b/investigations/dns_hijack_enrichment.json index 337a931cd9..072fb24372 100644 --- a/investigations/dns_hijack_enrichment.json +++ b/investigations/dns_hijack_enrichment.json @@ -1,50 +1,50 @@ { - "creation_date": "2017-04-10", - "data_metadata": { - "data_source": [ - "Censys", - "Passive Total", - "WHOIS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "This Playbook is part of the Splunk Analytic Story called DNS Hijacking. It is made to be run when the Detection Search within that story called \"DNS Record Changed\" is used to identify DNS record changes for cloud and corporate domains used in your environment. The detection search is dependent on a support searched called \"Discover DNS Records\" which finds the common DNS responses for the last 30 days of monitored corporate domains and cloud providers (located in lookups: cim_corporate_email_domains.csv, cim_corporate_web_domains.csv, and cloud_domains.csv from Splunk CIM App). These responses are stored under the lookup called discovered_dns_records.csv. The playbook starts with the changed DNS records and uses MaxMind, whois, Censys, Malware Domain List, and PassiveTotal to gather attributes of the DNS records for comparison against expected values. The resulting enrichment is displayed in Mission Control and posted back to the Notable Event in Splunk ES.", - "how_to_implement": "If Splunk>Phantom is also configured in your environment, a Playbook called \"DNS Hijack Enrichment\" can be configured to run when any results are found by this detection search. The playbook takes in the DNS record changed and uses Geoip, whois, Censys and PassiveTotal to detect if DNS issuers changed. To use this integration, install the Phantom App for Splunk https://splunkbase.splunk.com/app/3411/, add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active.
        (Playbook Link:https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/).

        ", - "id": "c096f721-8842-42ce-bfc7-74bd9a72c712", - "investigate": { - "phantom": { - "phantom_server": "automation (hostname)", - "playbook_name": "community/dns_hijack_enrichment", - "playbook_url": "https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/", - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "sensitivity": "green", - "severity": "medium" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } + "creation_date": "2017-04-10", + "data_metadata": { + "data_source": [ + "Censys", + "Passive Total", + "WHOIS" ], - "modification_date": "2019-02-14", - "name": "DNS Hijack Enrichment", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "phantom", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This Playbook is part of the Splunk Analytic Story called DNS Hijacking. It is made to be run when the Detection Search within that story called \"DNS Record Changed\" is used to identify DNS record changes for cloud and corporate domains used in your environment. The detection search is dependent on a support searched called \"Discover DNS Records\" which finds the common DNS responses for the last 30 days of monitored corporate domains and cloud providers (located in lookups: cim_corporate_email_domains.csv, cim_corporate_web_domains.csv, and cloud_domains.csv from Splunk CIM App). These responses are stored under the lookup called discovered_dns_records.csv. The playbook starts with the changed DNS records and uses MaxMind, whois, Censys, Malware Domain List, and PassiveTotal to gather attributes of the DNS records for comparison against expected values. The resulting enrichment is displayed in Mission Control and posted back to the Notable Event in Splunk ES.", + "how_to_implement": "If Splunk>Phantom is also configured in your environment, a Playbook called \"DNS Hijack Enrichment\" can be configured to run when any results are found by this detection search. The playbook takes in the DNS record changed and uses Geoip, whois, Censys and PassiveTotal to detect if DNS issuers changed. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \n\n(Playbook Link:`https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/`).\n\n", + "id": "c096f721-8842-42ce-bfc7-74bd9a72c712", + "investigate": { + "phantom": { + "phantom_server": "automation (hostname)", + "playbook_name": "community/dns_hijack_enrichment", + "playbook_url": "https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/", + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "sensitivity": "green", + "severity": "medium" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "modification_date": "2019-02-14", + "name": "DNS Hijack Enrichment", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "phantom", + "version": "1.0" +} diff --git a/investigations/dns_server_history.json b/investigations/dns_server_history.json index ab794049d5..331b263370 100644 --- a/investigations/dns_server_history.json +++ b/investigations/dns_server_history.json @@ -1,50 +1,50 @@ { - "creation_date": "2017-04-10", - "data_metadata": { - "data_source": [ - "DNS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours.", - "entities": [ + "creation_date": "2017-04-10", + "data_metadata": { + "data_source": [ + "DNS" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours.", + "entities": [ + "src_ip" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting your DNS traffic", + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", + "investigate": { + "splunk": { + "fields_required": [ "src_ip" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting your DNS traffic", - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd72", - "investigate": { - "splunk": { - "fields_required": [ - "src_ip" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "0", - "latest_time": "86400" - }, - "search": "| search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-11-09", - "name": "Get DNS Server History for a host", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "0", + "latest_time": "86400" + }, + "search": "| search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-11-09", + "name": "Get DNS Server History for a host", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/dns_traffic_stats.json b/investigations/dns_traffic_stats.json index bbded61821..9bedfdef42 100644 --- a/investigations/dns_traffic_stats.json +++ b/investigations/dns_traffic_stats.json @@ -1,55 +1,55 @@ { - "creation_date": "2017-04-10", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "DNS" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. ", - "entities": [ + "creation_date": "2017-04-10", + "data_metadata": { + "data_models": [ + "Network_Traffic" + ], + "data_source": [ + "DNS" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. ", + "entities": [ + "src_ip", + "dest_ip" + ], + "how_to_implement": "You must be ingesting your network traffic", + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd73", + "investigate": { + "splunk": { + "fields_required": [ "src_ip", "dest_ip" - ], - "how_to_implement": "You must be ingesting your network traffic", - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd73", - "investigate": { - "splunk": { - "fields_required": [ - "src_ip", - "dest_ip" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "0", - "latest_time": "86400" - }, - "search": "| tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as \"bytes_out\" sum(All_Traffic.bytes_in) as \"bytes_in\" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} | eval ratio = (bytes_out/bytes_in) | table ratio" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-11-09", - "name": "Get DNS traffic ratio", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "0", + "latest_time": "86400" + }, + "search": "| tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as \"bytes_out\" sum(All_Traffic.bytes_in) as \"bytes_in\" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} | eval ratio = (bytes_out/bytes_in) | table ratio" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-11-09", + "name": "Get DNS traffic ratio", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/domain_cert_investigation.json b/investigations/domain_cert_investigation.json index c7b09a792f..c7298c8813 100644 --- a/investigations/domain_cert_investigation.json +++ b/investigations/domain_cert_investigation.json @@ -1,57 +1,57 @@ { - "creation_date": "2019-04-29", - "data_metadata": { - "data_source": [ - "Censys" - ], - "providing_technologies": [ - "Censys" - ] - }, - "description": "Investigate domain names and URLs of a potentially malicious website. These domain names and URLs could come from anywhere, but this Playbook was designed to work with the Splunk Analytic Story focused on evilginx2 phishing techniques that harvest credentials from fake login sites. The full investigation is only completed if at least one of the TLS certificates of the domains matches the issuer distinguished name of Let's Encrypt, which is a free service that provides automatically issued TLS certificates. This Playbook gathers certificate information for the domains, queries whois for the domains, takes a screenshot of each of the URLs, and does a urlscan.io scan of each of the URLs. Finally, all the results are formatted together and posted to the event comments.", - "how_to_implement": "To successfully implement this phantom playbook, you must integrate Enterprise Security with Phantom. Configure this playbook in the correlation search `Detect DNS requests to Phishing Sites leveraging EvilGinx2` ,as an adaptive response action.", - "id": "c096f721-8842-42ce-2fc7-742d8272b712", - "investigate": { - "phantom": { - "phantom_server": "automation (hostname)", - "playbook_name": "community/lets_encrypt_domain_investigate", - "playbook_url": "https://my.phantom.us/4.2/playbook/lets-encrypt-domain-investigate/", - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "0", - "latest_time": "86400" - }, - "sensitivity": "green", - "severity": "medium" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "rnolen@splunk.com", - "name": "Russell Nolen " - }, - { - "company": "Splunk", - "email": "proyer@splunk.com", - "name": "Philip Royer" - } + "creation_date": "2019-04-29", + "data_metadata": { + "data_source": [ + "Censys" ], - "modification_date": "2019-04-29", - "name": "Domain Certificate Investigation", - "original_authors": [ - { - "company": "Splunk", - "email": "rnolen@splunk.com", - "name": "Russell Nolen " - }, - { - "company": "Splunk", - "email": "proyer@splunk.com", - "name": "Philip Royer" - } - ], - "spec_version": 2, - "type": "phantom", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Censys" + ] + }, + "description": "Investigate domain names and URLs of a potentially malicious website. These domain names and URLs could come from anywhere, but this Playbook was designed to work with the Splunk Analytic Story focused on evilginx2 phishing techniques that harvest credentials from fake login sites. The full investigation is only completed if at least one of the TLS certificates of the domains matches the issuer distinguished name of Let's Encrypt, which is a free service that provides automatically issued TLS certificates. This Playbook gathers certificate information for the domains, queries whois for the domains, takes a screenshot of each of the URLs, and does a urlscan.io scan of each of the URLs. Finally, all the results are formatted together and posted to the event comments.", + "how_to_implement": "To successfully implement this phantom playbook, you must integrate Enterprise Security with Phantom. Configure this playbook in the correlation search `Detect DNS requests to Phishing Sites leveraging EvilGinx2` ,as an adaptive response action.", + "id": "c096f721-8842-42ce-2fc7-742d8272b712", + "investigate": { + "phantom": { + "phantom_server": "automation (hostname)", + "playbook_name": "community/lets_encrypt_domain_investigate", + "playbook_url": "https://my.phantom.us/4.2/playbook/lets-encrypt-domain-investigate/", + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "0", + "latest_time": "86400" + }, + "sensitivity": "green", + "severity": "medium" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "rnolen@splunk.com", + "name": "Russell Nolen " + }, + { + "company": "Splunk", + "email": "proyer@splunk.com", + "name": "Philip Royer" + } + ], + "modification_date": "2019-04-29", + "name": "Domain Certificate Investigation", + "original_authors": [ + { + "company": "Splunk", + "email": "rnolen@splunk.com", + "name": "Russell Nolen " + }, + { + "company": "Splunk", + "email": "proyer@splunk.com", + "name": "Philip Royer" + } + ], + "spec_version": 2, + "type": "phantom", + "version": "1.0" +} diff --git a/investigations/email_sent_to_hidden_cobra_actors.json b/investigations/email_sent_to_hidden_cobra_actors.json index a1c0e3b2d5..b6ee40f8ae 100644 --- a/investigations/email_sent_to_hidden_cobra_actors.json +++ b/investigations/email_sent_to_hidden_cobra_actors.json @@ -1,54 +1,54 @@ { - "creation_date": "2018-06-14", - "data_metadata": { - "data_models": [ - "Email" - ], - "data_source": [ - "Email" - ], - "providing_technologies": [ - "Microsoft Exchange" - ] - }, - "description": "This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to misswang8107@gmail.com, and from redhat@gmail.com.", - "entities": [ + "creation_date": "2018-06-14", + "data_metadata": { + "data_models": [ + "Email" + ], + "data_source": [ + "Email" + ], + "providing_technologies": [ + "Microsoft Exchange" + ] + }, + "description": "This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`.", + "entities": [ + "src_user", + "recipient" + ], + "how_to_implement": "To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model.", + "id": "5df39b3f-347d-4869-b673-8r45ad4616fe", + "investigate": { + "splunk": { + "fields_required": [ "src_user", "recipient" - ], - "how_to_implement": "To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model.", - "id": "5df39b3f-347d-4869-b673-8r45ad4616fe", - "investigate": { - "splunk": { - "fields_required": [ - "src_user", - "recipient" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "86400", - "latest_time": "0" - }, - "search": "| from datamodel Email.All_Email | search recipient=misswang8107@gmail.com OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) as lastTime values(dest) values(src) by src_user recipient | `ctime(firstTime)` | `ctime(lastTime)`" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-06-14", - "name": "Get Outbound Emails to Hidden Cobra Threat Actors", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "86400", + "latest_time": "0" + }, + "search": "| from datamodel Email.All_Email | search recipient=misswang8107@gmail.com OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) as lastTime values(dest) values(src) by src_user recipient | `ctime(firstTime)` | `ctime(lastTime)`" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-06-14", + "name": "Get Outbound Emails to Hidden Cobra Threat Actors", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/excessive_account_lockouts_enrichment.json b/investigations/excessive_account_lockouts_enrichment.json index 185e3d8c29..df6fbc8369 100644 --- a/investigations/excessive_account_lockouts_enrichment.json +++ b/investigations/excessive_account_lockouts_enrichment.json @@ -1,50 +1,50 @@ { - "creation_date": "2017-08-17", - "data_metadata": { - "data_models": [ - "Change" - ], - "data_source": [ - "Windows Event Logs" - ], - "providing_technologies": [ - "Microsoft Windows" - ] - }, - "description": "This Playbook is part of the Splunk Analytic Story called Account Monitoring and Controls. It is made to be run when the Detection Search within that story called \"Detect Excessive Account Lockouts From Endpoint\" is used to identify a potential attack in which multiple Active Directory user accounts are locked out from logging in because an adversary attempted incorrect credentials repeatedly against many user accounts. This Playbook runs the Context-gathering and Investigative searches linked in the Splunk Analytic Story to enrich the event with a broad array of information about the users and computers involved. Then the Playbook uses Windows Remote Management to login to the source of the lockouts, gather more information, and allow Phantom to shutdown the server after prompting an analyst or responder.", - "how_to_implement": "Import playbook into phantom", - "id": "ab62b5c1-95d4-4e71-8fd7-53a55db33da4", - "investigate": { - "phantom": { - "phantom_server": "automation (hostname)", - "playbook_name": "community/excessive_account_lockouts_enrichment_and_response", - "playbook_url": "https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/", - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-4h@h", - "latest_time": "-5m@m" - }, - "sensitivity": "green", - "severity": "medium" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "creation_date": "2017-08-17", + "data_metadata": { + "data_models": [ + "Change" ], - "modification_date": "2019-02-14", - "name": "Excessive Account Lockouts Enrichment And Response", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_source": [ + "Windows Event Logs" ], - "spec_version": 2, - "type": "phantom", - "version": "2.0" -} \ No newline at end of file + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This Playbook is part of the Splunk Analytic Story called Account Monitoring and Controls. It is made to be run when the Detection Search within that story called \"Detect Excessive Account Lockouts From Endpoint\" is used to identify a potential attack in which multiple Active Directory user accounts are locked out from logging in because an adversary attempted incorrect credentials repeatedly against many user accounts. This Playbook runs the Context-gathering and Investigative searches linked in the Splunk Analytic Story to enrich the event with a broad array of information about the users and computers involved. Then the Playbook uses Windows Remote Management to login to the source of the lockouts, gather more information, and allow Phantom to shutdown the server after prompting an analyst or responder.", + "how_to_implement": "Import playbook into phantom", + "id": "ab62b5c1-95d4-4e71-8fd7-53a55db33da4", + "investigate": { + "phantom": { + "phantom_server": "automation (hostname)", + "playbook_name": "community/excessive_account_lockouts_enrichment_and_response", + "playbook_url": "https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/", + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-4h@h", + "latest_time": "-5m@m" + }, + "sensitivity": "green", + "severity": "medium" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2019-02-14", + "name": "Excessive Account Lockouts Enrichment And Response", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "phantom", + "version": "2.0" +} diff --git a/investigations/first_occurrence_mac_address.json b/investigations/first_occurrence_mac_address.json index b1d95211f5..5975a9853b 100644 --- a/investigations/first_occurrence_mac_address.json +++ b/investigations/first_occurrence_mac_address.json @@ -1,54 +1,54 @@ { - "creation_date": "2017-06-14", - "data_metadata": { - "data_models": [ - "Network_Sessions" - ], - "data_source": [ - "IP Address Assignment" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro", - "Microsoft Windows" - ] - }, - "description": "This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network.", - "entities": [ + "creation_date": "2017-06-14", + "data_metadata": { + "data_models": [ + "Network_Sessions" + ], + "data_source": [ + "IP Address Assignment" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro", + "Microsoft Windows" + ] + }, + "description": "This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network.", + "entities": [ + "src_mac" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting the logs from your DHCP server.", + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd33", + "investigate": { + "splunk": { + "fields_required": [ "src_mac" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting the logs from your DHCP server.", - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd33", - "investigate": { - "splunk": { - "fields_required": [ - "src_mac" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "864000", - "latest_time": "86400" - }, - "search": "| tstats allow_old_summaries=true count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= {src_mac} by All_Sessions.src_ip All_Sessions.user | `ctime(lastTime)` | `ctime(firstTime)`" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-13", - "name": "Get First Occurrence and Last Occurrence of a MAC Address", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "864000", + "latest_time": "86400" + }, + "search": "| tstats allow_old_summaries=true count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= {src_mac} by All_Sessions.src_ip All_Sessions.user | `ctime(lastTime)` | `ctime(firstTime)`" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-13", + "name": "Get First Occurrence and Last Occurrence of a MAC Address", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_acl_details.json b/investigations/get_acl_details.json index 30b94150ee..7655ba3522 100644 --- a/investigations/get_acl_details.json +++ b/investigations/get_acl_details.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-01-18", - "data_metadata": { - "data_source": [ - "AWS Description" - ], - "data_sourcetypes": [ - "aws:description" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID", - "entities": [ + "creation_date": "2018-01-18", + "data_metadata": { + "data_source": [ + "AWS Description" + ], + "data_sourcetypes": [ + "aws:description" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID", + "entities": [ + "networkAclId" + ], + "how_to_implement": "In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs.", + "id": "f3fb4d1b-5f33-4b01-b541-c7ah9534c242", + "investigate": { + "splunk": { + "fields_required": [ "networkAclId" - ], - "how_to_implement": "In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs.", - "id": "f3fb4d1b-5f33-4b01-b541-c7ah9534c242", - "investigate": { - "splunk": { - "fields_required": [ - "networkAclId" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "3600", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:description id={networkAclId} | table id account_id vpc_id network_acl_entries{}.*" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-01-22", - "name": "AWS Network ACL Details from ID", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "3600", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:description id={networkAclId} | table id account_id vpc_id network_acl_entries{}.*" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-01-22", + "name": "AWS Network ACL Details from ID", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_all_aws_activitiy_from_city.json b/investigations/get_all_aws_activitiy_from_city.json index 0f4dfde1c0..ff03995ce5 100644 --- a/investigations/get_all_aws_activitiy_from_city.json +++ b/investigations/get_all_aws_activitiy_from_city.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-03-19", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful.", - "entities": [ + "creation_date": "2018-03-19", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful.", + "entities": [ + "City" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "0abeeb40-1255-4b68-91d1-7a7eb410c4b8", + "investigate": { + "splunk": { + "fields_required": [ "City" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "0abeeb40-1255-4b68-91d1-7a7eb410c4b8", - "investigate": { - "splunk": { - "fields_required": [ - "City" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "14400", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-03-19", - "name": "Get All AWS Activity From City", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "14400", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-19", + "name": "Get All AWS Activity From City", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_all_aws_activitiy_from_country.json b/investigations/get_all_aws_activitiy_from_country.json index 96b7874904..3f8149927d 100644 --- a/investigations/get_all_aws_activitiy_from_country.json +++ b/investigations/get_all_aws_activitiy_from_country.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-03-19", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful.", - "entities": [ + "creation_date": "2018-03-19", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful.", + "entities": [ + "Country" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "e763cdb9-00da-41e0-9bda-444debc9501a", + "investigate": { + "splunk": { + "fields_required": [ "Country" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "e763cdb9-00da-41e0-9bda-444debc9501a", - "investigate": { - "splunk": { - "fields_required": [ - "Country" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "14400", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-03-19", - "name": "Get All AWS Activity From Country", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "14400", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-19", + "name": "Get All AWS Activity From Country", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_all_aws_activitiy_from_region.json b/investigations/get_all_aws_activitiy_from_region.json index 85e0ee4a95..04cc6bc93d 100644 --- a/investigations/get_all_aws_activitiy_from_region.json +++ b/investigations/get_all_aws_activitiy_from_region.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-03-19", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful.", - "entities": [ + "creation_date": "2018-03-19", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful.", + "entities": [ + "Region" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "5b794bef-1743-4f6f-804a-43915a2702ff", + "investigate": { + "splunk": { + "fields_required": [ "Region" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "5b794bef-1743-4f6f-804a-43915a2702ff", - "investigate": { - "splunk": { - "fields_required": [ - "Region" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "14400", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-03-19", - "name": "Get All AWS Activity From Region", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "14400", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-19", + "name": "Get All AWS Activity From Region", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_all_aws_activitiy_from_src_ip.json b/investigations/get_all_aws_activitiy_from_src_ip.json index ae304c30c0..e2305313ac 100644 --- a/investigations/get_all_aws_activitiy_from_src_ip.json +++ b/investigations/get_all_aws_activitiy_from_src_ip.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-03-19", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful.", - "entities": [ + "creation_date": "2018-03-19", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful.", + "entities": [ + "src_ip" + ], + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "446ec87a-85c6-40d4-b060-bea4498281d6", + "investigate": { + "splunk": { + "fields_required": [ "src_ip" - ], - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "446ec87a-85c6-40d4-b060-bea4498281d6", - "investigate": { - "splunk": { - "fields_required": [ - "src_ip" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "14400", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-03-19", - "name": "Get All AWS Activity From IP Address", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "14400", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-19", + "name": "Get All AWS Activity From IP Address", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_all_backup_data_for_host.json b/investigations/get_all_backup_data_for_host.json index 5e03a6bc5b..0a5fd853e7 100644 --- a/investigations/get_all_backup_data_for_host.json +++ b/investigations/get_all_backup_data_for_host.json @@ -1,52 +1,52 @@ { - "creation_date": "2017-06-19", - "data_metadata": { - "data_source": [ - "Backup Systems" - ], - "data_sourcetypes": [ - "netbackup_logs" - ], - "providing_technologies": [ - "Netbackup" - ] - }, - "description": "Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully.", - "entities": [ + "creation_date": "2017-06-19", + "data_metadata": { + "data_source": [ + "Backup Systems" + ], + "data_sourcetypes": [ + "netbackup_logs" + ], + "providing_technologies": [ + "Netbackup" + ] + }, + "description": "Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully.", + "entities": [ + "dest" + ], + "how_to_implement": "The successfully implement this search you must first send your backup logs to Splunk.", + "id": "bc91a8cf-aaaa-4bb2-8140-e756cc06fd72", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "The successfully implement this search you must first send your backup logs to Splunk.", - "id": "bc91a8cf-aaaa-4bb2-8140-e756cc06fd72", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "1209600", - "latest_time": "0" - }, - "search": "| search sourcetype=\"netbackup_logs\" dest={dest}" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2017-09-12", - "name": "All backup logs for host", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "1209600", + "latest_time": "0" + }, + "search": "| search sourcetype=\"netbackup_logs\" dest={dest}" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2017-09-12", + "name": "All backup logs for host", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_authentication_logs_for_endpoint.json b/investigations/get_authentication_logs_for_endpoint.json index 840a669f00..e947d04eed 100644 --- a/investigations/get_authentication_logs_for_endpoint.json +++ b/investigations/get_authentication_logs_for_endpoint.json @@ -1,54 +1,54 @@ { - "creation_date": "2017-04-10", - "data_metadata": { - "data_models": [ - "Authentication" - ], - "data_source": [ - "Authentication" - ], - "providing_technologies": [ - "Microsoft Windows", - "Linux", - "macOS" - ] - }, - "description": "This search returns all users that have attempted to access a particular endpoint.", - "entities": [ + "creation_date": "2017-04-10", + "data_metadata": { + "data_models": [ + "Authentication" + ], + "data_source": [ + "Authentication" + ], + "providing_technologies": [ + "Microsoft Windows", + "Linux", + "macOS" + ] + }, + "description": "This search returns all users that have attempted to access a particular endpoint.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model.", + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model.", - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd76", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "43200", - "latest_time": "1" - }, - "search": "| tstats count from datamodel=Authentication where Authentication.dest={dest} by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name(\"Authentication\")`" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-11-01", - "name": "Get Authentication Logs For Endpoint", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "43200", + "latest_time": "1" + }, + "search": "| tstats count from datamodel=Authentication where Authentication.dest={dest} by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name(\"Authentication\")`" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-11-01", + "name": "Get Authentication Logs For Endpoint", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_backup_logs_for_endpoint.json b/investigations/get_backup_logs_for_endpoint.json index 2d6080afd5..7747f878e4 100644 --- a/investigations/get_backup_logs_for_endpoint.json +++ b/investigations/get_backup_logs_for_endpoint.json @@ -1,52 +1,52 @@ { - "creation_date": "2017-08-24", - "data_metadata": { - "data_source": [ - "Backup Systems" - ], - "data_sourcetypes": [ - "netbackup_logs" - ], - "providing_technologies": [ - "Netbackup" - ] - }, - "description": "This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week.", - "entities": [ + "creation_date": "2017-08-24", + "data_metadata": { + "data_source": [ + "Backup Systems" + ], + "data_sourcetypes": [ + "netbackup_logs" + ], + "providing_technologies": [ + "Netbackup" + ] + }, + "description": "This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting your backup logs.", + "id": "fdcfb369-1725-4c24-824a-22972d7f0d44", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "You must be ingesting your backup logs.", - "id": "fdcfb369-1725-4c24-824a-22972d7f0d44", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "604800", - "latest_time": "0" - }, - "search": "| search sourcetype=\"netbackup_logs\" COMPUTERNAME={dest} | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-09-14", - "name": "Get Backup Logs For Endpoint", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "604800", + "latest_time": "0" + }, + "search": "| search sourcetype=\"netbackup_logs\" COMPUTERNAME={dest} | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-14", + "name": "Get Backup Logs For Endpoint", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_certificate_for_domain.json b/investigations/get_certificate_for_domain.json index 993ea93fc3..d8c99dc48f 100644 --- a/investigations/get_certificate_for_domain.json +++ b/investigations/get_certificate_for_domain.json @@ -1,51 +1,51 @@ { - "channel": "ESCU", - "creation_date": "2019-04-29", - "data_metadata": { - "data_models": [ - "Certificates" - ], - "data_source": [ - "Certificate Logs" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro" - ] - }, - "description": "This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by \"Let's Encrypt\" are widely used by attackers.", - "how_to_implement": "You must be ingesting your certificates or SSL logs from your network traffic into your Certificates datamodel. Please note the wildcard(*) before domain in the search syntax, we use to match for all domain and subdomain combinations", - "id": "bc91a8cf-35e7-4bb2-2240-e756cc06fd73", - "investigate": { - "splunk": { - "fields_required": [ - "domain" - ], - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*{domain} by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `ctime(firstTime)` | `ctime(lastTime)`" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "channel": "ESCU", + "creation_date": "2019-04-29", + "data_metadata": { + "data_models": [ + "Certificates" ], - "modification_date": "2019-04-29", - "name": "Get Certificate logs for a domain", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_source": [ + "Certificate Logs" ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Splunk Stream", + "Bro" + ] + }, + "description": "This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by \"Let's Encrypt\" are widely used by attackers.", + "how_to_implement": "You must be ingesting your certificates or SSL logs from your network traffic into your Certificates datamodel. Please note the wildcard(*) before domain in the search syntax, we use to match for all domain and subdomain combinations", + "id": "bc91a8cf-35e7-4bb2-2240-e756cc06fd73", + "investigate": { + "splunk": { + "fields_required": [ + "domain" + ], + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*{domain} by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `ctime(firstTime)` | `ctime(lastTime)`" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2019-04-29", + "name": "Get Certificate logs for a domain", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_ec2_details_by_instance_id.json b/investigations/get_ec2_details_by_instance_id.json index 1bf2d0781f..3c66ed03d6 100644 --- a/investigations/get_ec2_details_by_instance_id.json +++ b/investigations/get_ec2_details_by_instance_id.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-02-12", - "data_metadata": { - "data_source": [ - "AWS Description" - ], - "data_sourcetypes": [ - "aws:description" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search queries AWS description logs and returns all the information about a specific instance via the instanceId field", - "entities": [ + "creation_date": "2018-02-12", + "data_metadata": { + "data_source": [ + "AWS Description" + ], + "data_sourcetypes": [ + "aws:description" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search queries AWS description logs and returns all the information about a specific instance via the instanceId field", + "entities": [ + "instanceId" + ], + "how_to_implement": "In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs.", + "id": "f3db4d1b-5f33-4b01-c541-c7ah9514c242", + "investigate": { + "splunk": { + "fields_required": [ "instanceId" - ], - "how_to_implement": "In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs.", - "id": "f3db4d1b-5f33-4b01-c541-c7ah9514c242", - "investigate": { - "splunk": { - "fields_required": [ - "instanceId" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "86400", - "latest_time": "0" - }, - "search": "| search sourcetype=\"aws:description\" source=\"*:ec2_instances\"| dedup id sortby -_time | search id={instanceId} | spath output=tags path=tags | eval tags=mvzip(key,value,\" = \"), ip_address=if((ip_address == \"null\"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as \"Account ID\", id as ID, instance_type as Type, ip_address as \"IP Address\", key_name as \"Key Pair\", launch_time as \"Launch Time\", placement as \"Availability Zone\", state as State, subnet_id as Subnet, \"tags.Name\" as Name, vpc_id as VPC" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-02-12", - "name": "Get EC2 Instance Details by instanceId", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "86400", + "latest_time": "0" + }, + "search": "| search sourcetype=\"aws:description\" source=\"*:ec2_instances\"| dedup id sortby -_time | search id={instanceId} | spath output=tags path=tags | eval tags=mvzip(key,value,\" = \"), ip_address=if((ip_address == \"null\"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as \"Account ID\", id as ID, instance_type as Type, ip_address as \"IP Address\", key_name as \"Key Pair\", launch_time as \"Launch Time\", placement as \"Availability Zone\", state as State, subnet_id as Subnet, \"tags.Name\" as Name, vpc_id as VPC" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-02-12", + "name": "Get EC2 Instance Details by instanceId", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_ec2_launch_details.json b/investigations/get_ec2_launch_details.json index f2d220fc05..b7c4898fcc 100644 --- a/investigations/get_ec2_launch_details.json +++ b/investigations/get_ec2_launch_details.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-03-12", - "data_metadata": { - "data_source": [ - "AWS CloudTrail Logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search returns some of the launch details for a EC2 instance.", - "entities": [ + "creation_date": "2018-03-12", + "data_metadata": { + "data_source": [ + "AWS CloudTrail Logs" + ], + "data_sourcetypes": [ + "aws:cloudtrail" + ], + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search returns some of the launch details for a EC2 instance.", + "entities": [ + "dest" + ], + "how_to_implement": "In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs.", + "id": "0e40fe83-3edb-4d86-8206-8fed36529ca6", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs.", - "id": "0e40fe83-3edb-4d86-8206-8fed36529ca6", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "7200", - "latest_time": "0" - }, - "search": "| search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-03-12", - "name": "Get EC2 Launch Details", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "7200", + "latest_time": "0" + }, + "search": "| search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-03-12", + "name": "Get EC2 Launch Details", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_email_info.json b/investigations/get_email_info.json index e707660300..620230261b 100644 --- a/investigations/get_email_info.json +++ b/investigations/get_email_info.json @@ -1,52 +1,52 @@ { - "creation_date": "2017-04-21", - "data_metadata": { - "data_models": [ - "Email" - ], - "data_source": [ - "Email" - ], - "providing_technologies": [ - "Microsoft Exchange" - ] - }, - "description": "This search returns all the information Splunk might have collected a specific email message over the last 2 hours.", - "entities": [ + "creation_date": "2017-04-21", + "data_metadata": { + "data_models": [ + "Email" + ], + "data_source": [ + "Email" + ], + "providing_technologies": [ + "Microsoft Exchange" + ] + }, + "description": "This search returns all the information Splunk might have collected a specific email message over the last 2 hours.", + "entities": [ + "message_id" + ], + "how_to_implement": "To successfully implement this search you must be ingesting your email logs or capturing unencrypted network traffic which contains email communications.", + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd75", + "investigate": { + "splunk": { + "fields_required": [ "message_id" - ], - "how_to_implement": "To successfully implement this search you must be ingesting your email logs or capturing unencrypted network traffic which contains email communications.", - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd75", - "investigate": { - "splunk": { - "fields_required": [ - "message_id" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "0", - "latest_time": "7200" - }, - "search": "| from datamodel Email.All_Email | search message_id={message_id}" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-11-09", - "name": "Get Email Info", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "0", + "latest_time": "7200" + }, + "search": "| from datamodel Email.All_Email | search message_id={message_id}" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-11-09", + "name": "Get Email Info", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_emails_from_sender.json b/investigations/get_emails_from_sender.json index 9c6a097c0d..bcf134e827 100644 --- a/investigations/get_emails_from_sender.json +++ b/investigations/get_emails_from_sender.json @@ -1,52 +1,52 @@ { - "creation_date": "2017-04-21", - "data_metadata": { - "data_models": [ - "Email" - ], - "data_source": [ - "Email" - ], - "providing_technologies": [ - "Microsoft Exchange" - ] - }, - "description": "This search returns all the emails from a specific sender over the last 24 and next hours.", - "entities": [ + "creation_date": "2017-04-21", + "data_metadata": { + "data_models": [ + "Email" + ], + "data_source": [ + "Email" + ], + "providing_technologies": [ + "Microsoft Exchange" + ] + }, + "description": "This search returns all the emails from a specific sender over the last 24 and next hours.", + "entities": [ + "src_user" + ], + "how_to_implement": "To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model.", + "id": "5df39b3f-447d-4869-b673-8f45ad4616fe", + "investigate": { + "splunk": { + "fields_required": [ "src_user" - ], - "how_to_implement": "To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model.", - "id": "5df39b3f-447d-4869-b673-8f45ad4616fe", - "investigate": { - "splunk": { - "fields_required": [ - "src_user" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "86400", - "latest_time": "86400" - }, - "search": "| from datamodel Email.All_Email | search src_user={src_user}" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-11-09", - "name": "Get Emails From Specific Sender", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "86400", + "latest_time": "86400" + }, + "search": "| from datamodel Email.All_Email | search src_user={src_user}" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-11-09", + "name": "Get Emails From Specific Sender", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_emails_from_source.json b/investigations/get_emails_from_source.json index fbb1a12aa1..fde3cd21ae 100644 --- a/investigations/get_emails_from_source.json +++ b/investigations/get_emails_from_source.json @@ -1,52 +1,52 @@ { - "creation_date": "2019-02-21", - "data_metadata": { - "data_models": [ - "Email" - ], - "data_source": [ - "Email" - ], - "providing_technologies": [ - "Microsoft Exchange" - ] - }, - "description": "This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source.", - "entities": [ + "creation_date": "2019-02-21", + "data_metadata": { + "data_models": [ + "Email" + ], + "data_source": [ + "Email" + ], + "providing_technologies": [ + "Microsoft Exchange" + ] + }, + "description": "This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source.", + "entities": [ + "src" + ], + "how_to_implement": "To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model.", + "id": "ddc7af28-c34d-4392-af93-7f29a4e8806c", + "investigate": { + "splunk": { + "fields_required": [ "src" - ], - "how_to_implement": "To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model.", - "id": "ddc7af28-c34d-4392-af93-7f29a4e8806c", - "investigate": { - "splunk": { - "fields_required": [ - "src" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "172800", - "latest_time": "86400" - }, - "search": "|tstats `summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email by All_Email.src |`drop_dm_object_name(All_Email)` | `ctime(firstTime)` | `ctime(lastTime)`" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2019-02-21", - "name": "Get History Of Email Sources", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "172800", + "latest_time": "86400" + }, + "search": "|tstats `summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email by All_Email.src |`drop_dm_object_name(All_Email)` | `ctime(firstTime)` | `ctime(lastTime)`" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2019-02-21", + "name": "Get History Of Email Sources", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_logon_rights_modifications_for_endpoint.json b/investigations/get_logon_rights_modifications_for_endpoint.json index 5dd1e27256..89fe197674 100644 --- a/investigations/get_logon_rights_modifications_for_endpoint.json +++ b/investigations/get_logon_rights_modifications_for_endpoint.json @@ -1,52 +1,52 @@ { - "creation_date": "2017-08-16", - "data_metadata": { - "data_eventtypes": [ - "wineventlog_security" - ], - "data_source": [ - "Windows Event Logs" - ], - "providing_technologies": [ - "Microsoft Windows" - ] - }, - "description": "This search allows you to retrieve any modifications to logon rights associated with a specific host.", - "entities": [ + "creation_date": "2017-08-16", + "data_metadata": { + "data_eventtypes": [ + "wineventlog_security" + ], + "data_source": [ + "Windows Event Logs" + ], + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search allows you to retrieve any modifications to logon rights associated with a specific host.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search you must be ingesting your Windows event logs", + "id": "03bffe94-ec7a-4cbe-b677-6af40d1c4505", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "To successfully implement this search you must be ingesting your Windows event logs", - "id": "03bffe94-ec7a-4cbe-b677-6af40d1c4505", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "86400", - "latest_time": "86400" - }, - "search": "| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest={dest} | rename user as \"Account Modified\" | table _time, dest, \"Account Modified\", Access_Right, signature" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-09-12", - "name": "Get Logon Rights Modifications For Endpoint", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "86400", + "latest_time": "86400" + }, + "search": "| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest={dest} | rename user as \"Account Modified\" | table _time, dest, \"Account Modified\", Access_Right, signature" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-12", + "name": "Get Logon Rights Modifications For Endpoint", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/investigations/get_logon_rights_modifications_for_user.json b/investigations/get_logon_rights_modifications_for_user.json index 49d0cf833d..18033e06eb 100644 --- a/investigations/get_logon_rights_modifications_for_user.json +++ b/investigations/get_logon_rights_modifications_for_user.json @@ -1,52 +1,52 @@ { - "creation_date": "2017-08-16", - "data_metadata": { - "data_eventtypes": [ - "wineventlog_security" - ], - "data_source": [ - "Windows Event Logs" - ], - "providing_technologies": [ - "Microsoft Windows" - ] - }, - "description": "This search allows you to retrieve any modifications to logon rights for a specific user account.", - "entities": [ + "creation_date": "2017-08-16", + "data_metadata": { + "data_eventtypes": [ + "wineventlog_security" + ], + "data_source": [ + "Windows Event Logs" + ], + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search allows you to retrieve any modifications to logon rights for a specific user account.", + "entities": [ + "user" + ], + "how_to_implement": "To successfully implement this search you must be ingesting your Windows event logs", + "id": "552bc86c-f72c-4d44-b3f2-06ede13af7bb", + "investigate": { + "splunk": { + "fields_required": [ "user" - ], - "how_to_implement": "To successfully implement this search you must be ingesting your Windows event logs", - "id": "552bc86c-f72c-4d44-b3f2-06ede13af7bb", - "investigate": { - "splunk": { - "fields_required": [ - "user" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "86400", - "latest_time": "86400" - }, - "search": "| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user={user} | rename user as \"Account Modified\" | table _time, dest, \"Account Modified\", Access_Right, signature" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2019-02-27", - "name": "Get Logon Rights Modifications For User", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "86400", + "latest_time": "86400" + }, + "search": "| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user={user} | rename user as \"Account Modified\" | table _time, dest, \"Account Modified\", Access_Right, signature" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2019-02-27", + "name": "Get Logon Rights Modifications For User", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/investigations/get_network_traffic_from_src_ip.json b/investigations/get_network_traffic_from_src_ip.json index 7eade03e42..248e8419d1 100644 --- a/investigations/get_network_traffic_from_src_ip.json +++ b/investigations/get_network_traffic_from_src_ip.json @@ -1,54 +1,54 @@ { - "creation_date": "2018-06-15", - "data_metadata": { - "data_models": [ - "Network_Traffic" - ], - "data_source": [ - "Network Communications" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro", - "Palo Alto Firewall" - ] - }, - "description": "This search allows you to find all the network traffic from a specific IP address.", - "entities": [ + "creation_date": "2018-06-15", + "data_metadata": { + "data_models": [ + "Network_Traffic" + ], + "data_source": [ + "Network Communications" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro", + "Palo Alto Firewall" + ] + }, + "description": "This search allows you to find all the network traffic from a specific IP address.", + "entities": [ + "src_ip" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model.", + "id": "9df9ca9c-a02b-4f48-9eba-0bac55179050", + "investigate": { + "splunk": { + "fields_required": [ "src_ip" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model.", - "id": "9df9ca9c-a02b-4f48-9eba-0bac55179050", - "investigate": { - "splunk": { - "fields_required": [ - "src_ip" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "3600", - "latest_time": "3600" - }, - "search": "| from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip}" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-06-15", - "name": "Investigate Network Traffic From src_ip", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "3600", + "latest_time": "3600" + }, + "search": "| from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip}" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-06-15", + "name": "Investigate Network Traffic From src_ip", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_notable_history_for_endpoint.json b/investigations/get_notable_history_for_endpoint.json index b70e5db9b8..af10d43721 100644 --- a/investigations/get_notable_history_for_endpoint.json +++ b/investigations/get_notable_history_for_endpoint.json @@ -1,49 +1,49 @@ { - "creation_date": "2017-03-15", - "data_metadata": { - "data_source": [ - "Notable Events" - ], - "providing_technologies": [ - "Splunk Enterprise Security" - ] - }, - "description": "This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation.", - "entities": [ + "creation_date": "2017-03-15", + "data_metadata": { + "data_source": [ + "Notable Events" + ], + "providing_technologies": [ + "Splunk Enterprise Security" + ] + }, + "description": "This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation.", + "entities": [ + "dest" + ], + "how_to_implement": "If you are using Enterprise Security you are likely already creating notable events with your correlation rules. No additional configuration is necessary.", + "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "If you are using Enterprise Security you are likely already creating notable events with your correlation rules. No additional configuration is necessary.", - "id": "3d6c3213-5fff-4a1e-b57d-b24c262171e7", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "864000", - "latest_time": "86400" - }, - "search": "| search `notable` | search dest={dest} | table _time, rule_name, owner, priority, severity, status_description" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-20", - "name": "Get Notable History", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "864000", + "latest_time": "86400" + }, + "search": "| search `notable` | search dest={dest} | table _time, rule_name, owner, priority, severity, status_description" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-20", + "name": "Get Notable History", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/investigations/get_notable_info.json b/investigations/get_notable_info.json index 9eadd0ebb4..37e95962d1 100644 --- a/investigations/get_notable_info.json +++ b/investigations/get_notable_info.json @@ -1,49 +1,49 @@ { - "creation_date": "2017-03-15", - "data_metadata": { - "data_source": [ - "Notable Events" - ], - "providing_technologies": [ - "Splunk Enterprise Security" - ] - }, - "description": "This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation.", - "entities": [ + "creation_date": "2017-03-15", + "data_metadata": { + "data_source": [ + "Notable Events" + ], + "providing_technologies": [ + "Splunk Enterprise Security" + ] + }, + "description": "This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation.", + "entities": [ + "event_id" + ], + "how_to_implement": "If you are using Enterprise Security you are likely already creating notable events with your correlation rules. No additional configuration is necessary.", + "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", + "investigate": { + "splunk": { + "fields_required": [ "event_id" - ], - "how_to_implement": "If you are using Enterprise Security you are likely already creating notable events with your correlation rules. No additional configuration is necessary.", - "id": "f3fb4d1b-5f33-4b01-b541-c7af9534c242", - "investigate": { - "splunk": { - "fields_required": [ - "event_id" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "3600", - "latest_time": "3600" - }, - "search": "| search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-20", - "name": "Get Notable Info", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "3600", + "latest_time": "3600" + }, + "search": "| search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-20", + "name": "Get Notable Info", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_parent_process_info.json b/investigations/get_parent_process_info.json index cf1f353a87..cf027bead6 100644 --- a/investigations/get_parent_process_info.json +++ b/investigations/get_parent_process_info.json @@ -1,58 +1,58 @@ { - "creation_date": "2017-08-22", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] - }, - "description": "This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest", - "entities": [ + "creation_date": "2017-08-22", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest", + "entities": [ + "process_name", + "dest" + ], + "how_to_implement": "You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", + "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", + "investigate": { + "splunk": { + "fields_required": [ "process_name", "dest" - ], - "how_to_implement": "You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the \"process\" field in the Endpoint data model.", - "id": "fecf2918-670d-4f1c-872b-3d7317a41bf9", - "investigate": { - "splunk": { - "fields_required": [ - "process_name", - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "0", - "latest_time": "86400" - }, - "search": "| tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = {process_name} Processes.dest = {dest} by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`| `ctime(lastTime)`" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2019-02-28", - "name": "Get Parent Process Info", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "0", + "latest_time": "86400" + }, + "search": "| tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = {process_name} Processes.dest = {dest} by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name(\"Processes\")` | `ctime(firstTime)`| `ctime(lastTime)`" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2019-02-28", + "name": "Get Parent Process Info", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/investigations/get_process_creating_dns_traffic.json b/investigations/get_process_creating_dns_traffic.json index c92587d3cb..8a09023714 100644 --- a/investigations/get_process_creating_dns_traffic.json +++ b/investigations/get_process_creating_dns_traffic.json @@ -1,56 +1,56 @@ { - "creation_date": "2017-04-10", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] - }, - "description": "While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic.", - "entities": [ + "creation_date": "2017-04-10", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic.", + "entities": [ + "dest" + ], + "how_to_implement": "You must be ingesting endpoint data that associates processes with network events into the Endpoint datamodel. This can come from endpoint protection products such as carbon black, or endpoint data sources such as Sysmon.", + "id": "910e6512-edc9-4f93-ba24-5b786f47a672", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "You must be ingesting endpoint data that associates processes with network events into the Endpoint datamodel. This can come from endpoint protection products such as carbon black, or endpoint data sources such as Sysmon.", - "id": "910e6512-edc9-4f93-ba24-5b786f47a672", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "3600", - "latest_time": "86400" - }, - "search": "| tstats `summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `ctime(firstTime)`|`ctime(lastTime)` | search [| tstats `summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest]" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2019-04-01", - "name": "Get Process Responsible For The DNS Traffic", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "3600", + "latest_time": "86400" + }, + "search": "| tstats `summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `ctime(firstTime)`|`ctime(lastTime)` | search [| tstats `summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest]" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2019-04-01", + "name": "Get Process Responsible For The DNS Traffic", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/investigations/get_process_info.json b/investigations/get_process_info.json index 3faa9c3bf0..a9454cb2b2 100644 --- a/investigations/get_process_info.json +++ b/investigations/get_process_info.json @@ -1,58 +1,58 @@ { - "creation_date": "2017-03-15", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] - }, - "description": "This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address.", - "entities": [ + "creation_date": "2017-03-15", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address.", + "entities": [ + "process_name", + "dest" + ], + "how_to_implement": "To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model.", + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", + "investigate": { + "splunk": { + "fields_required": [ "process_name", "dest" - ], - "how_to_implement": "To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model.", - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd71", - "investigate": { - "splunk": { - "fields_required": [ - "process_name", - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "7200", - "latest_time": "7200" - }, - "search": "| tstats `summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`|`ctime(lastTime)` " - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2019-04-01", - "name": "Get Process Info", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "7200", + "latest_time": "7200" + }, + "search": "| tstats `summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `ctime(firstTime)`|`ctime(lastTime)` " + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2019-04-01", + "name": "Get Process Info", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/investigations/get_process_info_for_port.json b/investigations/get_process_info_for_port.json index 20c98a559b..841aaaed8a 100644 --- a/investigations/get_process_info_for_port.json +++ b/investigations/get_process_info_for_port.json @@ -1,57 +1,57 @@ { - "creation_date": "2017-06-25", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint Intel" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro", - "Bluecoat", - "Palo Alto Firewall" - ] - }, - "description": "This search will return information about the process associated with observed network traffic to a specific destination port from a specific host.", - "entities": [ + "creation_date": "2017-06-25", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint Intel" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro", + "Bluecoat", + "Palo Alto Firewall" + ] + }, + "description": "This search will return information about the process associated with observed network traffic to a specific destination port from a specific host.", + "entities": [ + "dest_port", + "dest" + ], + "how_to_implement": "To successfully implement this search you must be ingesting endpoint data that associates processes with network events and populate the Endpoint Datamodel", + "id": "9925d08f-561e-4faa-8912-e3888a842341", + "investigate": { + "splunk": { + "fields_required": [ "dest_port", "dest" - ], - "how_to_implement": "To successfully implement this search you must be ingesting endpoint data that associates processes with network events and populate the Endpoint Datamodel", - "id": "9925d08f-561e-4faa-8912-e3888a842341", - "investigate": { - "splunk": { - "fields_required": [ - "dest_port", - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "7200", - "latest_time": "7200" - }, - "search": "| tstats `summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `ctime(firstTime)`|`ctime(lastTime)` | search [| tstats `summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port={dest_port} by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest]" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2019-04-01", - "name": "Get Process Information For Port Activity", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "7200", + "latest_time": "7200" + }, + "search": "| tstats `summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `ctime(firstTime)`|`ctime(lastTime)` | search [| tstats `summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port={dest_port} by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest]" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2019-04-01", + "name": "Get Process Information For Port Activity", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/investigations/get_rdp_authentications.json b/investigations/get_rdp_authentications.json index dbaea6019f..664e0e84aa 100644 --- a/investigations/get_rdp_authentications.json +++ b/investigations/get_rdp_authentications.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-12-14", - "data_metadata": { - "data_models": [ - "Authentication" - ], - "data_source": [ - "Authentication" - ], - "providing_technologies": [ - "Microsoft Windows" - ] - }, - "description": "This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. ", - "entities": [ + "creation_date": "2018-12-14", + "data_metadata": { + "data_models": [ + "Authentication" + ], + "data_source": [ + "Authentication" + ], + "providing_technologies": [ + "Microsoft Windows" + ] + }, + "description": "This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. ", + "entities": [ + "dest" + ], + "how_to_implement": "You must be populating the Authentication data model with security events from your Windows event logs.", + "id": "b6618e8e-be04-40a0-a0b9-f0bd4b6c81bc", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "You must be populating the Authentication data model with security events from your Windows event logs.", - "id": "b6618e8e-be04-40a0-a0b9-f0bd4b6c81bc", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "86400", - "latest_time": "0" - }, - "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Authentication where Authentication.signature_id=4624 Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app Authentication.user Authentication.signature Authentication.src_nt_domain | `ctime(lastTime)` | `ctime(firstTime)` | `drop_dm_object_name(\"Authentication\")`| table firstTime lastTime src src_nt_domain dest user app count | sort count" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } - ], - "modification_date": "2018-12-14", - "name": "Investigate Successful Remote Desktop Authentications", - "original_authors": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "86400", + "latest_time": "0" + }, + "search": "| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Authentication where Authentication.signature_id=4624 Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app Authentication.user Authentication.signature Authentication.src_nt_domain | `ctime(lastTime)` | `ctime(firstTime)` | `drop_dm_object_name(\"Authentication\")`| table firstTime lastTime src src_nt_domain dest user app count | sort count" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "modification_date": "2018-12-14", + "name": "Investigate Successful Remote Desktop Authentications", + "original_authors": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_registry_activities.json b/investigations/get_registry_activities.json index 3277be5f8e..ef1d276836 100644 --- a/investigations/get_registry_activities.json +++ b/investigations/get_registry_activities.json @@ -1,56 +1,56 @@ { - "creation_date": "2018-08-07", - "data_metadata": { - "data_models": [ - "Endpoint" - ], - "data_source": [ - "Endpoint" - ], - "providing_technologies": [ - "Carbon Black Response", - "CrowdStrike Falcon", - "Sysmon", - "Tanium", - "Ziften" - ] - }, - "description": "This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer.", - "entities": [ + "creation_date": "2018-08-07", + "data_metadata": { + "data_models": [ + "Endpoint" + ], + "data_source": [ + "Endpoint" + ], + "providing_technologies": [ + "Carbon Black Response", + "CrowdStrike Falcon", + "Sysmon", + "Tanium", + "Ziften" + ] + }, + "description": "This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes.", + "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes.", - "id": "fecf2918-670d-4f1c-872b-3d7317a41xf9", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "0", - "latest_time": "86400" - }, - "search": "| tstats `summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = \"{dest}\" by Registry.process_id Registry.dest | `drop_dm_object_name(\"Registry\")` | join [| tstats `summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name(\"Processes\")`]" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2019-03-01", - "name": "Get Registry Activities", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "0", + "latest_time": "86400" + }, + "search": "| tstats `summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = \"{dest}\" by Registry.process_id Registry.dest | `drop_dm_object_name(\"Registry\")` | join [| tstats `summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name(\"Processes\")`]" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2019-03-01", + "name": "Get Registry Activities", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/investigations/get_risk_for_endpoint.json b/investigations/get_risk_for_endpoint.json index 195a7eaaf4..379391ee8b 100644 --- a/investigations/get_risk_for_endpoint.json +++ b/investigations/get_risk_for_endpoint.json @@ -1,52 +1,52 @@ { - "creation_date": "2017-10-14", - "data_metadata": { - "data_models": [ - "Risk" - ], - "data_source": [ - "Risk Scores" - ], - "providing_technologies": [ - "Splunk Enterprise Security" - ] - }, - "description": "For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\\_name) ", - "entities": [ + "creation_date": "2017-10-14", + "data_metadata": { + "data_models": [ + "Risk" + ], + "data_source": [ + "Risk Scores" + ], + "providing_technologies": [ + "Splunk Enterprise Security" + ] + }, + "description": "For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\\_name) ", + "entities": [ + "dest" + ], + "how_to_implement": "Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework", + "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework", - "id": "fdcfb369-1725-4c24-824a-22972d7f0d65", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "604800", - "latest_time": "0" - }, - "search": "| from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `ctime(firstTime)` | `ctime(lastTime)`" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-10-19", - "name": "Get Risk Modifiers For Endpoint", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "604800", + "latest_time": "0" + }, + "search": "| from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `ctime(firstTime)` | `ctime(lastTime)`" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-10-19", + "name": "Get Risk Modifiers For Endpoint", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_risk_for_user.json b/investigations/get_risk_for_user.json index 33a0b68595..0387cb6dd9 100644 --- a/investigations/get_risk_for_user.json +++ b/investigations/get_risk_for_user.json @@ -1,52 +1,52 @@ { - "creation_date": "2017-10-14", - "data_metadata": { - "data_models": [ - "Risk" - ], - "data_source": [ - "Risk Scores" - ], - "providing_technologies": [ - "Splunk Enterprise Security" - ] - }, - "description": "For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user ", - "entities": [ + "creation_date": "2017-10-14", + "data_metadata": { + "data_models": [ + "Risk" + ], + "data_source": [ + "Risk Scores" + ], + "providing_technologies": [ + "Splunk Enterprise Security" + ] + }, + "description": "For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user ", + "entities": [ + "user" + ], + "how_to_implement": "Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework", + "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", + "investigate": { + "splunk": { + "fields_required": [ "user" - ], - "how_to_implement": "Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework", - "id": "fdcfb369-1725-4c24-824a-22972d7f0d55", - "investigate": { - "splunk": { - "fields_required": [ - "user" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "604800", - "latest_time": "0" - }, - "search": "| from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`ctime(firstTime)` |`ctime(lastTime)` " - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-10-19", - "name": "Get Risk Modifiers For User", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "604800", + "latest_time": "0" + }, + "search": "| from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`ctime(firstTime)` |`ctime(lastTime)` " + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-10-19", + "name": "Get Risk Modifiers For User", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_update_logs_for_endpoint.json b/investigations/get_update_logs_for_endpoint.json index 37362deca5..9272488e4f 100644 --- a/investigations/get_update_logs_for_endpoint.json +++ b/investigations/get_update_logs_for_endpoint.json @@ -1,54 +1,54 @@ { - "creation_date": "2017-08-24", - "data_metadata": { - "data_models": [ - "Updates" - ], - "data_source": [ - "Update Logs" - ], - "providing_technologies": [ - "Microsoft Windows", - "Linux", - "macOS" - ] - }, - "description": "This search will tell you give you the update logs for a specific endpoint for the last week.", - "entities": [ + "creation_date": "2017-08-24", + "data_metadata": { + "data_models": [ + "Updates" + ], + "data_source": [ + "Update Logs" + ], + "providing_technologies": [ + "Microsoft Windows", + "Linux", + "macOS" + ] + }, + "description": "This search will tell you give you the update logs for a specific endpoint for the last week.", + "entities": [ + "dest" + ], + "how_to_implement": "You need to be ingesting the update logs from your various systems.", + "id": "d98675ed-da43-4a7e-96a7-eeca3232ba8e", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "You need to be ingesting the update logs from your various systems.", - "id": "d98675ed-da43-4a7e-96a7-eeca3232ba8e", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "604800", - "latest_time": "0" - }, - "search": "| from datamodel Updates.Updates | search (vendor_product=\"Microsoft Windows\" OR vendor_product=\"OSX:Update\" OR vendor_product=\"Linux:Update\") dest={dest}" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-08-24", - "name": "Get Update Logs For Endpoint", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "604800", + "latest_time": "0" + }, + "search": "| from datamodel Updates.Updates | search (vendor_product=\"Microsoft Windows\" OR vendor_product=\"OSX:Update\" OR vendor_product=\"Linux:Update\") dest={dest}" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-08-24", + "name": "Get Update Logs For Endpoint", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_user_info_from_identity_table.json b/investigations/get_user_info_from_identity_table.json index f614f02d4c..66e8e7efbd 100644 --- a/investigations/get_user_info_from_identity_table.json +++ b/investigations/get_user_info_from_identity_table.json @@ -1,49 +1,49 @@ { - "creation_date": "2017-04-10", - "data_metadata": { - "data_source": [ - "Identity Table" - ], - "providing_technologies": [ - "Splunk Enterprise Security" - ] - }, - "description": "Gather more information about the user identified in the Notable Event.", - "entities": [ + "creation_date": "2017-04-10", + "data_metadata": { + "data_source": [ + "Identity Table" + ], + "providing_technologies": [ + "Splunk Enterprise Security" + ] + }, + "description": "Gather more information about the user identified in the Notable Event.", + "entities": [ + "user" + ], + "how_to_implement": "To successfully implement this search you must have populated the identity table with information about your users.", + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", + "investigate": { + "splunk": { + "fields_required": [ "user" - ], - "how_to_implement": "To successfully implement this search you must have populated the identity table with information about your users.", - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd74", - "investigate": { - "splunk": { - "fields_required": [ - "user" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "864000", - "latest_time": "86400" - }, - "search": "| `identities` | search identity={user} | table _time, identity, first, last, email, category, watchlist" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-20", - "name": "Get User Information from Identity Table", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "864000", + "latest_time": "86400" + }, + "search": "| `identities` | search identity={user} | table _time, identity, first, last, email, category, watchlist" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-20", + "name": "Get User Information from Identity Table", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_vulnerability_logs_for_endpoint.json b/investigations/get_vulnerability_logs_for_endpoint.json index 655c42d16d..d2c1bbe19b 100644 --- a/investigations/get_vulnerability_logs_for_endpoint.json +++ b/investigations/get_vulnerability_logs_for_endpoint.json @@ -1,52 +1,52 @@ { - "creation_date": "2017-08-24", - "data_metadata": { - "data_models": [ - "Vulnerabilities" - ], - "data_source": [ - "Vulnerability Scanner" - ], - "providing_technologies": [ - "Nessus" - ] - }, - "description": "This search will show you any vulnerabilities noted for a specific endpoint for the last week.", - "entities": [ + "creation_date": "2017-08-24", + "data_metadata": { + "data_models": [ + "Vulnerabilities" + ], + "data_source": [ + "Vulnerability Scanner" + ], + "providing_technologies": [ + "Nessus" + ] + }, + "description": "This search will show you any vulnerabilities noted for a specific endpoint for the last week.", + "entities": [ + "dest" + ], + "how_to_implement": "You need to be ingesting the logs from your vulnerability scanner.", + "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "You need to be ingesting the logs from your vulnerability scanner.", - "id": "df7a7f50-30f2-4cde-8448-69d2d5f9b3c5", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "604800", - "latest_time": "0" - }, - "search": "| from datamodel Vulnerabilities.Vulnerabilities | search dest={dest}" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-09-10", - "name": "Get Vulnerability Logs For Endpoint", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "604800", + "latest_time": "0" + }, + "search": "| from datamodel Vulnerabilities.Vulnerabilities | search dest={dest}" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-10", + "name": "Get Vulnerability Logs For Endpoint", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_web_activity.json b/investigations/get_web_activity.json index 6b58df52b8..c3fcded957 100644 --- a/investigations/get_web_activity.json +++ b/investigations/get_web_activity.json @@ -1,55 +1,55 @@ { - "creation_date": "2017-04-21", - "data_metadata": { - "data_models": [ - "Web" - ], - "data_source": [ - "Web" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro", - "Bluecoat", - "Palo Alto Firewall" - ] - }, - "description": "This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity.", - "entities": [ + "creation_date": "2017-04-21", + "data_metadata": { + "data_models": [ + "Web" + ], + "data_source": [ + "Web" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro", + "Bluecoat", + "Palo Alto Firewall" + ] + }, + "description": "This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity.", + "entities": [ + "dest" + ], + "how_to_implement": "To successfully implement this search you must be ingesting your web traffic and populating the Web data model.", + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", + "investigate": { + "splunk": { + "fields_required": [ "dest" - ], - "how_to_implement": "To successfully implement this search you must be ingesting your web traffic and populating the Web data model.", - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd22", - "investigate": { - "splunk": { - "fields_required": [ - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "3600", - "latest_time": "3600" - }, - "search": "| from datamodel Web.Web | search src={dest}" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-11-09", - "name": "Investigate Web Activity From Host", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "3600", + "latest_time": "3600" + }, + "search": "| from datamodel Web.Web | search src={dest}" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-11-09", + "name": "Investigate Web Activity From Host", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_web_activity_by_src_ip.json b/investigations/get_web_activity_by_src_ip.json index 8d9f7cfc3a..5765e68d3a 100644 --- a/investigations/get_web_activity_by_src_ip.json +++ b/investigations/get_web_activity_by_src_ip.json @@ -1,55 +1,55 @@ { - "creation_date": "2018-06-15", - "data_metadata": { - "data_models": [ - "Web" - ], - "data_source": [ - "Web" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro", - "Bluecoat", - "Palo Alto Firewall" - ] - }, - "description": "This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity.", - "entities": [ + "creation_date": "2018-06-15", + "data_metadata": { + "data_models": [ + "Web" + ], + "data_source": [ + "Web" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro", + "Bluecoat", + "Palo Alto Firewall" + ] + }, + "description": "This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity.", + "entities": [ + "src_ip" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting your web traffic and populating the web data model.", + "id": "2f5b960b-71df-49c0-affc-74992ce60e45", + "investigate": { + "splunk": { + "fields_required": [ "src_ip" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting your web traffic and populating the web data model.", - "id": "2f5b960b-71df-49c0-affc-74992ce60e45", - "investigate": { - "splunk": { - "fields_required": [ - "src_ip" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "3600", - "latest_time": "3600" - }, - "search": "| from datamodel Web.Web | search src={src_ip}" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-06-15", - "name": "Investigate Web Activity From src_ip", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "3600", + "latest_time": "3600" + }, + "search": "| from datamodel Web.Web | search src={src_ip}" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-06-15", + "name": "Investigate Web Activity From src_ip", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_web_posts_by_src.json b/investigations/get_web_posts_by_src.json index c31b64f4fc..42e88158e9 100644 --- a/investigations/get_web_posts_by_src.json +++ b/investigations/get_web_posts_by_src.json @@ -1,55 +1,55 @@ { - "creation_date": "2018-12-06", - "data_metadata": { - "data_models": [ - "Web" - ], - "data_source": [ - "Web" - ], - "providing_technologies": [ - "Splunk Stream", - "Bro", - "Bluecoat", - "Palo Alto Firewall" - ] - }, - "description": "This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. ", - "entities": [ + "creation_date": "2018-12-06", + "data_metadata": { + "data_models": [ + "Web" + ], + "data_source": [ + "Web" + ], + "providing_technologies": [ + "Splunk Stream", + "Bro", + "Bluecoat", + "Palo Alto Firewall" + ] + }, + "description": "This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. ", + "entities": [ + "src" + ], + "how_to_implement": "To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model.", + "id": "f5c39fac-205c-4e07-9004-8fd61ea3431a", + "investigate": { + "splunk": { + "fields_required": [ "src" - ], - "how_to_implement": "To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model.", - "id": "f5c39fac-205c-4e07-9004-8fd61ea3431a", - "investigate": { - "splunk": { - "fields_required": [ - "src" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "3600", - "latest_time": "3600" - }, - "search": "| tstats `summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name(\"Web\")`| where like(src, \"{src}\") and like(http_method, \"POST\")" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } - ], - "modification_date": "2018-12-06", - "name": "Investigate Web POSTs From src", - "original_authors": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "3600", + "latest_time": "3600" + }, + "search": "| tstats `summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name(\"Web\")`| where like(src, \"{src}\") and like(http_method, \"POST\")" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "modification_date": "2018-12-06", + "name": "Investigate Web POSTs From src", + "original_authors": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_web_session_info.json b/investigations/get_web_session_info.json index 6cb6b9dcc6..78a8aeef8b 100644 --- a/investigations/get_web_session_info.json +++ b/investigations/get_web_session_info.json @@ -1,52 +1,52 @@ { - "creation_date": "2018-10-08", - "data_metadata": { - "data_source": [ - "Network Communications" - ], - "data_sourcetypes": [ - "stream:http" - ], - "providing_technologies": [ - "Splunk Stream" - ] - }, - "description": "This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code.", - "entities": [ + "creation_date": "2018-10-08", + "data_metadata": { + "data_source": [ + "Network Communications" + ], + "data_sourcetypes": [ + "stream:http" + ], + "providing_technologies": [ + "Splunk Stream" + ] + }, + "description": "This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code.", + "entities": [ + "session_id" + ], + "how_to_implement": "This search leverages data extracted from Stream:HTTP. You must configure the HTTP stream using the Splunk Stream App on your Splunk Stream deployment server.", + "id": "bc91a8cf-35e7-4bb2-1120-e756cc06fd89", + "investigate": { + "splunk": { + "fields_required": [ "session_id" - ], - "how_to_implement": "This search leverages data extracted from Stream:HTTP. You must configure the HTTP stream using the Splunk Stream App on your Splunk Stream deployment server.", - "id": "bc91a8cf-35e7-4bb2-1120-e756cc06fd89", - "investigate": { - "splunk": { - "fields_required": [ - "session_id" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "3600", - "latest_time": "3600" - }, - "search": "| search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) by src_ip status" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-10-08", - "name": "Get Web Session Information via session_id", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "3600", + "latest_time": "3600" + }, + "search": "| search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) by src_ip status" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-10-08", + "name": "Get Web Session Information via session_id", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/get_wmi_sysmon_events.json b/investigations/get_wmi_sysmon_events.json index ba634a1ece..b08a92f975 100644 --- a/investigations/get_wmi_sysmon_events.json +++ b/investigations/get_wmi_sysmon_events.json @@ -1,54 +1,54 @@ { - "creation_date": "2018-10-23", - "data_metadata": { - "data_source": [ - "Endpoint Intel" - ], - "data_sourcetypes": [ - "XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" - ], - "providing_technologies": [ - "Sysmon" - ] - }, - "description": "This search queries Sysmon WMI events for the host of interest.", - "entities": [ + "creation_date": "2018-10-23", + "data_metadata": { + "data_source": [ + "Endpoint Intel" + ], + "data_sourcetypes": [ + "XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" + ], + "providing_technologies": [ + "Sysmon" + ] + }, + "description": "This search queries Sysmon WMI events for the host of interest.", + "entities": [ + "process", + "dest" + ], + "how_to_implement": "To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate events for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields.", + "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", + "investigate": { + "splunk": { + "fields_required": [ "process", "dest" - ], - "how_to_implement": "To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate events for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields.", - "id": "155e0571-7db6-42f2-aa62-9a3a4cf35c94", - "investigate": { - "splunk": { - "fields_required": [ - "process", - "dest" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "7200", - "latest_time": "7200" - }, - "search": "sourcetype=\"XmlWinEventLog:Microsoft-Windows-Sysmon/Operational\" EventCode>18 EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-10-23", - "name": "Get Sysmon WMI Activity for Host", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "7200", + "latest_time": "7200" + }, + "search": "sourcetype=\"XmlWinEventLog:Microsoft-Windows-Sysmon/Operational\" EventCode>18 EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-10-23", + "name": "Get Sysmon WMI Activity for Host", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/suspicious_email_attachment_investigate_and_delete.json b/investigations/suspicious_email_attachment_investigate_and_delete.json index 997d10bf37..8f5d618347 100644 --- a/investigations/suspicious_email_attachment_investigate_and_delete.json +++ b/investigations/suspicious_email_attachment_investigate_and_delete.json @@ -1,57 +1,57 @@ { - "creation_date": "2019-06-03", - "data_metadata": { - "data_source": [ - "Microsoft Exchange", - "SMTP", - "Cuckoo", - "Splunk Enterprise Security", - "VirusTotal", - "DeepSight" - ], - "providing_technologies": [ - "Microsoft Exchange", - "SMTP", - "Cuckoo", - "Splunk Enterprise Security", - "VirusTotal", - "DeepSight" - ] - }, - "description": "Investigate an email with a suspicious file attachment detected by Splunk Enterprise Security. Detonate the file attachment in a sandbox, gather network behavior from the sandbox results, and pivot on those network indicators with both external reputation queries and internal Splunk Common Information Model searches. After confirming the results with an analyst prompt, delete the email from the user's inbox, hopefully before they have opened it.", - "how_to_implement": "Synchronize the community playbook repository in Phantom, then open the playbook and follow the deployment notes to configure it for your environment.", - "id": "3096f721-8842-42ce-2fc7-742d8372b712", - "investigate": { - "phantom": { - "phantom_server": "automation (hostname)", - "playbook_name": "community/suspicious_email_attachment_investigate_and_delete", - "playbook_url": "https://my.phantom.us/4.2/playbook/suspicious-email-attachment-investigate-and-delete/", - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "0", - "latest_time": "86400" - }, - "sensitivity": "green", - "severity": "medium" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "proyer@splunk.com", - "name": "Philip Royer" - } + "creation_date": "2019-06-03", + "data_metadata": { + "data_source": [ + "Microsoft Exchange", + "SMTP", + "Cuckoo", + "Splunk Enterprise Security", + "VirusTotal", + "DeepSight" ], - "modification_date": "2019-06-03", - "name": "Suspicious Email Attachment Investigate and Delete", - "original_authors": [ - { - "company": "Splunk", - "email": "proyer@splunk.com", - "name": "Philip Royer" - } - ], - "spec_version": 2, - "type": "phantom", - "version": "1.0" -} \ No newline at end of file + "providing_technologies": [ + "Microsoft Exchange", + "SMTP", + "Cuckoo", + "Splunk Enterprise Security", + "VirusTotal", + "DeepSight" + ] + }, + "description": "Investigate an email with a suspicious file attachment detected by Splunk Enterprise Security. Detonate the file attachment in a sandbox, gather network behavior from the sandbox results, and pivot on those network indicators with both external reputation queries and internal Splunk Common Information Model searches. After confirming the results with an analyst prompt, delete the email from the user's inbox, hopefully before they have opened it.", + "how_to_implement": "Synchronize the community playbook repository in Phantom, then open the playbook and follow the deployment notes to configure it for your environment.", + "id": "3096f721-8842-42ce-2fc7-742d8372b712", + "investigate": { + "phantom": { + "phantom_server": "automation (hostname)", + "playbook_name": "community/suspicious_email_attachment_investigate_and_delete", + "playbook_url": "https://my.phantom.us/4.2/playbook/suspicious-email-attachment-investigate-and-delete/", + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "0", + "latest_time": "86400" + }, + "sensitivity": "green", + "severity": "medium" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "proyer@splunk.com", + "name": "Philip Royer" + } + ], + "modification_date": "2019-06-03", + "name": "Suspicious Email Attachment Investigate and Delete", + "original_authors": [ + { + "company": "Splunk", + "email": "proyer@splunk.com", + "name": "Philip Royer" + } + ], + "spec_version": 2, + "type": "phantom", + "version": "1.0" +} diff --git a/investigations/suspicious_strings_in_HTTP_header.json b/investigations/suspicious_strings_in_HTTP_header.json index b52fe2a7d3..f7764add50 100644 --- a/investigations/suspicious_strings_in_HTTP_header.json +++ b/investigations/suspicious_strings_in_HTTP_header.json @@ -1,54 +1,54 @@ { - "creation_date": "2017-06-26", - "data_metadata": { - "data_source": [ - "Network Communications" - ], - "data_sourcetypes": [ - "stream:http" - ], - "providing_technologies": [ - "Splunk Stream" - ] - }, - "description": "This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the \"payload\" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest.", - "entities": [ + "creation_date": "2017-06-26", + "data_metadata": { + "data_source": [ + "Network Communications" + ], + "data_sourcetypes": [ + "stream:http" + ], + "providing_technologies": [ + "Splunk Stream" + ] + }, + "description": "This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the \"payload\" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest.", + "entities": [ + "src_ip", + "dest_ip" + ], + "how_to_implement": "This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field.", + "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd89", + "investigate": { + "splunk": { + "fields_required": [ "src_ip", "dest_ip" - ], - "how_to_implement": "This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field.", - "id": "bc91a8cf-35e7-4bb2-8140-e756cc06fd89", - "investigate": { - "splunk": { - "fields_required": [ - "src_ip", - "dest_ip" - ], - "schedule": { - "cron_schedule": "", - "earliest_time": "3600", - "latest_time": "3600" - }, - "search": "| search sourcetype=stream:http src_ip=\"{src_ip}\" dest_ip=\"{dest_ip}\" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field=\"cs_content_type\" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, \"application\"), \"True\", \"False\") | rename suspicious_strings_found AS \"Suspicious Content-Type Found\" | fields \"Suspicious Content-Type Found\", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-10-20", - "name": "Investigate Suspicious Strings in HTTP Header", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "spec_version": 2, - "type": "splunk", - "version": "1.0" -} \ No newline at end of file + ], + "schedule": { + "cron_schedule": "", + "earliest_time": "3600", + "latest_time": "3600" + }, + "search": "| search sourcetype=stream:http src_ip=\"{src_ip}\" dest_ip=\"{dest_ip}\" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field=\"cs_content_type\" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, \"application\"), \"True\", \"False\") | rename suspicious_strings_found AS \"Suspicious Content-Type Found\" | fields \"Suspicious Content-Type Found\", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-10-20", + "name": "Investigate Suspicious Strings in HTTP Header", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "1.0" +} diff --git a/investigations/user_activity_via_cloudtrail.json b/investigations/user_activity_via_cloudtrail.json index bda5509c5f..da345eadb9 100644 --- a/investigations/user_activity_via_cloudtrail.json +++ b/investigations/user_activity_via_cloudtrail.json @@ -1,54 +1,54 @@ { - "creation_date": "2018-01-22", - "data_metadata": { - "data_source": [ - "AWS CloudTrail logs" - ], - "data_sourcetypes": [ - "aws:cloudtrail" - ], - "providing_technologies": [ - "AWS" - ] - }, - "description": "This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information.", - "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", - "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", - "investigate": { - "splunk": { - "fields_required": [ - "user" - ], - "schedule": { - "cron_schedule": "0 * * * *", - "earliest_time": "-70m@m", - "latest_time": "-10m@m" - }, - "search": "| search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType" - } - }, - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - }, - { - "company": "Splunk", - "email": "jbrewer@splunk.com", - "name": "Jason Brewer" - } + "creation_date": "2018-01-22", + "data_metadata": { + "data_source": [ + "AWS CloudTrail logs" ], - "modification_date": "2019-04-30", - "name": "AWS Investigate User Activities By ARN", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } + "data_sourcetypes": [ + "aws:cloudtrail" ], - "spec_version": 2, - "type": "splunk", - "version": "2.0" -} \ No newline at end of file + "providing_technologies": [ + "AWS" + ] + }, + "description": "This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information.", + "how_to_implement": "You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.", + "id": "bc91a8cd-35e7-4bb2-6140-e756cc46fd71", + "investigate": { + "splunk": { + "fields_required": [ + "user" + ], + "schedule": { + "cron_schedule": "0 * * * *", + "earliest_time": "-70m@m", + "latest_time": "-10m@m" + }, + "search": "| search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType" + } + }, + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + }, + { + "company": "Splunk", + "email": "jbrewer@splunk.com", + "name": "Jason Brewer" + } + ], + "modification_date": "2019-04-30", + "name": "AWS Investigate User Activities By ARN", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "spec_version": 2, + "type": "splunk", + "version": "2.0" +} diff --git a/stories/account_monitoring.json b/stories/account_monitoring.json index c5a65c1f70..3a91ff4068 100644 --- a/stories/account_monitoring.json +++ b/stories/account_monitoring.json @@ -1,64 +1,64 @@ { - "category": [ - "Best Practices" - ], - "channel": "ESCU", - "creation_date": "2017-08-05", - "description": "A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts.", - "detections": [ - { - "detection_id": "475b9e27-17e4-46e2-b7e2-648221be3b89", - "name": "Identify New User Accounts", - "type": "splunk" - }, - { - "detection_id": "b25f6f62-0782-43c1-b403-083231ffd97d", - "name": "Short Lived Windows Accounts", - "type": "splunk" - }, - { - "detection_id": "c026e3dd-7e18-4abb-8f41-929e836efe74", - "name": "Detect Excessive Account Lockouts From Endpoint", - "type": "splunk" - }, - { - "detection_id": "95a7f9a5-6096-437e-a19e-86f42ac609bd", - "name": "Detect Excessive User Account Lockouts", - "type": "splunk" - } - ], - "id": "8892a655-6205-55f7-abba-06460e38c8ae", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - }, - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-09-06", - "name": "Account Monitoring and Controls", - "narrative": "Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - }, - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Best Practices" + ], + "channel": "ESCU", + "creation_date": "2017-08-05", + "description": "A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts.", + "detections": [ + { + "detection_id": "475b9e27-17e4-46e2-b7e2-648221be3b89", + "name": "Identify New User Accounts", + "type": "splunk" + }, + { + "detection_id": "b25f6f62-0782-43c1-b403-083231ffd97d", + "name": "Short Lived Windows Accounts", + "type": "splunk" + }, + { + "detection_id": "c026e3dd-7e18-4abb-8f41-929e836efe74", + "name": "Detect Excessive Account Lockouts From Endpoint", + "type": "splunk" + }, + { + "detection_id": "95a7f9a5-6096-437e-a19e-86f42ac609bd", + "name": "Detect Excessive User Account Lockouts", + "type": "splunk" + } + ], + "id": "8892a655-6205-55f7-abba-06460e38c8ae", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + }, + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-06", + "name": "Account Monitoring and Controls", + "narrative": "Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + }, + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/apache_struts.json b/stories/apache_struts.json index 5aa950f769..f1affe56b2 100644 --- a/stories/apache_struts.json +++ b/stories/apache_struts.json @@ -1,50 +1,50 @@ { - "category": [ - "Vulnerability" - ], - "channel": "ESCU", - "creation_date": "2017-03-14", - "description": "Detect and investigate activities--such as unusually long Content-Type length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities.", - "detections": [ - { - "detection_id": "57a0a2bf-353f-40c1-84dc-29293f3c35b7", - "name": "Unusually Long Content-Type Length", - "type": "splunk" - }, - { - "detection_id": "ec3b7601-689a-4463-94e0-c9f45638efb9", - "name": "Web Servers Executing Suspicious Processes", - "type": "splunk" - }, - { - "detection_id": "if1fea6da-3c86-4c1d-b255-fc3b2781a491", - "name": "Suspicious Java Classes", - "type": "splunk" - } - ], - "id": "2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e", - "maintainers": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } - ], - "modification_date": "2018-12-06", - "name": "Apache Struts Vulnerability", - "narrative": "In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack.

        The exploit involved manipulating the Content-Type HTTP header to execute commands embedded in the header.

        This Analytic Story contains two different searches that help to identify activity that may be related to this issue. The first search looks for characteristics of the Content-Type header consistent with attempts to exploit the vulnerability. This should be a relatively pertinent indicator, as the Content-Type header is generally consistent and does not have a large degree of variation.

        The second search looks for the execution of various commands typically entered on the command shell when an attacker first lands on a system. These commands are not generally executed on web servers during the course of day-to-day operation, but they may be used when the system is undergoing maintenance or troubleshooting.

        First, it is helpful is to understand how often the notable event is generated, as well as the commonalities in some of these events. This may help determine whether this is a common occurrence that is of a lesser concern or a rare event that may require more extensive investigation. It can also help to understand whether the issue is restricted to a single user or system or is broader in scope.

        When looking at the target of the behavior illustrated by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to see what other events involving the target have occurred in the recent past. This can help tie different events together and give further situational awareness regarding the target.

        Various types of information for external systems should be reviewed and (potentially) collected if the incident is, indeed, judged to be malicious. Information like this can be useful in generating your own threat intelligence to create alerts in the future.

        Looking at the country, responsible party, and fully qualified domain names associated with the external IP address--as well as the registration information associated with those domain names, if they are frequently visited by others--can help you answer the question of \"who,\" in regard to the external system. Answering that can help qualify the event and may serve useful for tracking. In addition, there are various sources that can provide some reputation information on the IP address or domain name, which can assist in determining if the event is malicious in nature. Finally, determining whether or not there are other events associated with the IP address may help connect some dots or show other events that should be brought into scope.

        Gathering various data elements on the system of interest can sometimes help quickly determine that something suspicious may be happening. Some of these items include determining who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.

        When a specific service or application is targeted, it is often helpful to know the associated version to help determine whether or not it is vulnerable to a specific exploit.

        When it is suspected there is an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.

        In the event that a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that have the file open, what processes created and/or modified the file, and the number of systems that may have this file can help to determine if the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes quickly help determine whether it is malicious in nature.

        Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if svchost.exe is found running from a location other than C:\\Windows\\System32, it is likely something malicious designed to hide in plain sight when simply reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, there may be activity initiated via a compromised website the user visited.

        It can also be very helpful to examine various behaviors of the process of interest or the parent of the process that is of interest. For example, if it turns out that the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might also be worth further scrutiny. If a process is suspect, reviewing the network connections made around the time of the event and/or if the process spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "http://blog.talosintelligence.com/2017/03/apache-0-day-exploited.html", - "https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Vulnerability" + ], + "channel": "ESCU", + "creation_date": "2017-03-14", + "description": "Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities.", + "detections": [ + { + "detection_id": "57a0a2bf-353f-40c1-84dc-29293f3c35b7", + "name": "Unusually Long Content-Type Length", + "type": "splunk" + }, + { + "detection_id": "ec3b7601-689a-4463-94e0-c9f45638efb9", + "name": "Web Servers Executing Suspicious Processes", + "type": "splunk" + }, + { + "detection_id": "if1fea6da-3c86-4c1d-b255-fc3b2781a491", + "name": "Suspicious Java Classes", + "type": "splunk" + } + ], + "id": "2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e", + "maintainers": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "modification_date": "2018-12-06", + "name": "Apache Struts Vulnerability", + "narrative": "In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \n\nThe exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\n\nThis Analytic Story contains two different searches that help to identify activity that may be related to this issue. The first search looks for characteristics of the `Content-Type` header consistent with attempts to exploit the vulnerability. This should be a relatively pertinent indicator, as the `Content-Type` header is generally consistent and does not have a large degree of variation.\n\nThe second search looks for the execution of various commands typically entered on the command shell when an attacker first lands on a system. These commands are not generally executed on web servers during the course of day-to-day operation, but they may be used when the system is undergoing maintenance or troubleshooting.\n\nFirst, it is helpful is to understand how often the notable event is generated, as well as the commonalities in some of these events. This may help determine whether this is a common occurrence that is of a lesser concern or a rare event that may require more extensive investigation. It can also help to understand whether the issue is restricted to a single user or system or is broader in scope.\n\nWhen looking at the target of the behavior illustrated by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to see what other events involving the target have occurred in the recent past. This can help tie different events together and give further situational awareness regarding the target.\n\nVarious types of information for external systems should be reviewed and (potentially) collected if the incident is, indeed, judged to be malicious. Information like this can be useful in generating your own threat intelligence to create alerts in the future.\n\nLooking at the country, responsible party, and fully qualified domain names associated with the external IP address--as well as the registration information associated with those domain names, if they are frequently visited by others--can help you answer the question of \"who,\" in regard to the external system. Answering that can help qualify the event and may serve useful for tracking. In addition, there are various sources that can provide some reputation information on the IP address or domain name, which can assist in determining if the event is malicious in nature. Finally, determining whether or not there are other events associated with the IP address may help connect some dots or show other events that should be brought into scope.\n\nGathering various data elements on the system of interest can sometimes help quickly determine that something suspicious may be happening. Some of these items include determining who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\n\nWhen a specific service or application is targeted, it is often helpful to know the associated version to help determine whether or not it is vulnerable to a specific exploit.\n\nWhen it is suspected there is an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\n\nIn the event that a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that have the file open, what processes created and/or modified the file, and the number of systems that may have this file can help to determine if the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes quickly help determine whether it is malicious in nature.\n\nOften, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if `svchost.exe` is found running from a location other than `C:\\Windows\\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, there may be activity initiated via a compromised website the user visited.\n\nIt can also be very helpful to examine various behaviors of the process of interest or the parent of the process that is of interest. For example, if it turns out that the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might also be worth further scrutiny. If a process is suspect, reviewing the network connections made around the time of the event and/or if the process spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "http://blog.talosintelligence.com/2017/03/apache-0-day-exploited.html", + "https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/asset_tracking.json b/stories/asset_tracking.json index 959a210d1f..076f5b5fd5 100644 --- a/stories/asset_tracking.json +++ b/stories/asset_tracking.json @@ -1,39 +1,39 @@ { - "category": [ - "Best Practices" - ], - "channel": "ESCU", - "creation_date": "2017-06-01", - "description": "Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further.", - "detections": [ - { - "detection_id": "dcfd6b40-42f9-469d-a433-2e53f7489ff4", - "name": "Detect Unauthorized Assets by MAC address", - "type": "splunk" - } - ], - "id": "91c676cf-0b23-438d-abee-f6335e1fce77", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-13", - "name": "Asset Tracking", - "narrative": "This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Best Practices" + ], + "channel": "ESCU", + "creation_date": "2017-06-01", + "description": "Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further.", + "detections": [ + { + "detection_id": "dcfd6b40-42f9-469d-a433-2e53f7489ff4", + "name": "Detect Unauthorized Assets by MAC address", + "type": "splunk" + } + ], + "id": "91c676cf-0b23-438d-abee-f6335e1fce77", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-13", + "name": "Asset Tracking", + "narrative": "This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/aws_cross_account_activity.json b/stories/aws_cross_account_activity.json index efe0de5fad..94625c66eb 100644 --- a/stories/aws_cross_account_activity.json +++ b/stories/aws_cross_account_activity.json @@ -1,39 +1,39 @@ { - "category": [ - "Cloud Security" - ], - "channel": "ESCU", - "creation_date": "2018-06-04", - "description": "Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity.", - "detections": [ - { - "detection_id": "64fbbddf-fabf-4edf-80b3-0cc36ef37727", - "name": "AWS Cross Account Activity From Previously Unseen Account", - "type": "splunk" - } - ], - "id": "2f2f610a-d64d-48c2-b57c-967a2b49ab5a", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-06-04", - "name": "AWS Cross Account Activity", - "narrative": "Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.

        Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.

        This Analytic Story includes searches that will help you monitor your AWS CloudTrail logs for evidence of suspicious cross-account activity. For example, while accessing multiple AWS accounts and roles may be perfectly valid behavior, it may be suspicious when an account requests privileges of an account it has not accessed in the past. After identifying suspicious activities, you can use the provided investigative searches to help you probe more deeply.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Cloud Security" + ], + "channel": "ESCU", + "creation_date": "2018-06-04", + "description": "Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity.", + "detections": [ + { + "detection_id": "64fbbddf-fabf-4edf-80b3-0cc36ef37727", + "name": "AWS Cross Account Activity From Previously Unseen Account", + "type": "splunk" + } + ], + "id": "2f2f610a-d64d-48c2-b57c-967a2b49ab5a", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-06-04", + "name": "AWS Cross Account Activity", + "narrative": "Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\n\nHerein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\n\nThis Analytic Story includes searches that will help you monitor your AWS CloudTrail logs for evidence of suspicious cross-account activity. For example, while accessing multiple AWS accounts and roles may be perfectly valid behavior, it may be suspicious when an account requests privileges of an account it has not accessed in the past. After identifying suspicious activities, you can use the provided investigative searches to help you probe more deeply.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/aws_cryptomining.json b/stories/aws_cryptomining.json index 663ffde0a8..18f787a106 100644 --- a/stories/aws_cryptomining.json +++ b/stories/aws_cryptomining.json @@ -1,59 +1,59 @@ { - "category": [ - "Cloud Security" - ], - "channel": "ESCU", - "creation_date": "2018-03-08", - "description": "Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior.", - "detections": [ - { - "detection_id": "ada0f478-84a8-4641-a3f3-d82362d6fd75", - "name": "EC2 Instance Started In Previously Unseen Region", - "type": "splunk" - }, - { - "detection_id": "2a9b80d3-6340-4345-b5ad-290bf5d0dac4", - "name": "Abnormally High AWS Instances Launched by User", - "type": "splunk" - }, - { - "detection_id": "65541c80-03c7-4e05-83c8-1dcd57a2e1ad", - "name": "EC2 Instance Started With Previously Unseen Instance Type", - "type": "splunk" - }, - { - "detection_id": "347ec301-601b-48b9-81aa-9ddf9c829dd3", - "name": "EC2 Instance Started With Previously Unseen AMI", - "type": "splunk" - }, - { - "detection_id": "22773e84-bac0-4595-b086-20d3f735b4f1", - "name": "EC2 Instance Started With Previously Unseen User", - "type": "splunk" - } - ], - "id": "ced74200-8465-4bc3-bd2c-9a782eec6750", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-03-08", - "name": "AWS Cryptomining", - "narrative": "Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority.

        Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN.

        When malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So, it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated.

        This Analytic Story is focused on detecting suspicious new instances in your EC2 environment to help prevent such a disaster. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Cloud Security" + ], + "channel": "ESCU", + "creation_date": "2018-03-08", + "description": "Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior.", + "detections": [ + { + "detection_id": "ada0f478-84a8-4641-a3f3-d82362d6fd75", + "name": "EC2 Instance Started In Previously Unseen Region", + "type": "splunk" + }, + { + "detection_id": "2a9b80d3-6340-4345-b5ad-290bf5d0dac4", + "name": "Abnormally High AWS Instances Launched by User", + "type": "splunk" + }, + { + "detection_id": "65541c80-03c7-4e05-83c8-1dcd57a2e1ad", + "name": "EC2 Instance Started With Previously Unseen Instance Type", + "type": "splunk" + }, + { + "detection_id": "347ec301-601b-48b9-81aa-9ddf9c829dd3", + "name": "EC2 Instance Started With Previously Unseen AMI", + "type": "splunk" + }, + { + "detection_id": "22773e84-bac0-4595-b086-20d3f735b4f1", + "name": "EC2 Instance Started With Previously Unseen User", + "type": "splunk" + } + ], + "id": "ced74200-8465-4bc3-bd2c-9a782eec6750", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-08", + "name": "AWS Cryptomining", + "narrative": "Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \n\nCryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \n\nWhen malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So, it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \n\nThis Analytic Story is focused on detecting suspicious new instances in your EC2 environment to help prevent such a disaster. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/aws_ec2.json b/stories/aws_ec2.json index 6aadbcd2a0..5b1d9145d3 100644 --- a/stories/aws_ec2.json +++ b/stories/aws_ec2.json @@ -1,54 +1,54 @@ { - "category": [ - "Cloud Security" - ], - "channel": "ESCU", - "creation_date": "2018-02-09", - "description": "Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it.", - "detections": [ - { - "detection_id": "ada0f478-84a8-4641-a3f3-d82362d6fd75", - "name": "EC2 Instance Started In Previously Unseen Region", - "type": "splunk" - }, - { - "detection_id": "ada0f478-84a8-4641-s3f3-d82362dffd75", - "name": "Abnormally High AWS Instances Terminated by User", - "type": "splunk" - }, - { - "detection_id": "2a9b80d3-6340-4345-b5ad-290bf5d0dac4", - "name": "Abnormally High AWS Instances Launched by User", - "type": "splunk" - }, - { - "detection_id": "22773e84-bac0-4595-b086-20d3f735b4f1", - "name": "EC2 Instance Started With Previously Unseen User", - "type": "splunk" - } - ], - "id": "2e8948a5-5239-406b-b56b-6c50f1268af3", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-02-09", - "name": "Suspicious AWS EC2 Activities", - "narrative": "AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Cloud Security" + ], + "channel": "ESCU", + "creation_date": "2018-02-09", + "description": "Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it.", + "detections": [ + { + "detection_id": "ada0f478-84a8-4641-a3f3-d82362d6fd75", + "name": "EC2 Instance Started In Previously Unseen Region", + "type": "splunk" + }, + { + "detection_id": "ada0f478-84a8-4641-s3f3-d82362dffd75", + "name": "Abnormally High AWS Instances Terminated by User", + "type": "splunk" + }, + { + "detection_id": "2a9b80d3-6340-4345-b5ad-290bf5d0dac4", + "name": "Abnormally High AWS Instances Launched by User", + "type": "splunk" + }, + { + "detection_id": "22773e84-bac0-4595-b086-20d3f735b4f1", + "name": "EC2 Instance Started With Previously Unseen User", + "type": "splunk" + } + ], + "id": "2e8948a5-5239-406b-b56b-6c50f1268af3", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-02-09", + "name": "Suspicious AWS EC2 Activities", + "narrative": "AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/aws_ec2_modifications.json b/stories/aws_ec2_modifications.json index eb5c79a2dc..d2916d3431 100644 --- a/stories/aws_ec2_modifications.json +++ b/stories/aws_ec2_modifications.json @@ -1,39 +1,39 @@ { - "category": [ - "Cloud Security" - ], - "channel": "ESCU", - "creation_date": "2018-04-09", - "description": "Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation.", - "detections": [ - { - "detection_id": "56f91724-cf3f-4666-84e1-e3712fb41e76", - "name": "EC2 Instance Modified With Previously Unseen User", - "type": "splunk" - } - ], - "id": "73de57ef-0dfc-411f-b1e7-fa24428aeae0", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-04-09", - "name": "Unusual AWS EC2 Modifications", - "narrative": "A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised.

        Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Cloud Security" + ], + "channel": "ESCU", + "creation_date": "2018-04-09", + "description": "Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation.", + "detections": [ + { + "detection_id": "56f91724-cf3f-4666-84e1-e3712fb41e76", + "name": "EC2 Instance Modified With Previously Unseen User", + "type": "splunk" + } + ], + "id": "73de57ef-0dfc-411f-b1e7-fa24428aeae0", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-04-09", + "name": "Unusual AWS EC2 Modifications", + "narrative": "A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \n\n Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/aws_network_acl.json b/stories/aws_network_acl.json index 55b8610709..909664d29d 100644 --- a/stories/aws_network_acl.json +++ b/stories/aws_network_acl.json @@ -1,55 +1,55 @@ { - "category": [ - "Cloud Security" - ], - "channel": "ESCU", - "creation_date": "2018-01-10", - "description": "Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it.", - "detections": [ - { - "detection_id": "ada0f478-84a8-4641-a3f1-d82362d6bd75", - "name": "AWS Network Access Control List Created with All Open Ports", - "type": "splunk" - }, - { - "detection_id": "ada0f478-84a8-4641-a3f1-d82362d6fd75", - "name": "AWS Network Access Control List Deleted", - "type": "splunk" - }, - { - "detection_id": "ada0f278-84a8-46w1-a3f1-w32372d4bd53", - "name": "Detect Spike in blocked Outbound Traffic from your AWS", - "type": "splunk" - }, - { - "detection_id": "ada0f478-84a8-4641-a1f1-e32372d4bd53", - "name": "Detect Spike in Network ACL Activity", - "type": "splunk" - } - ], - "id": "2e8948a5-5239-406b-b56b-6c50ff268af4", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-05-21", - "name": "AWS Network ACL Activity", - "narrative": "AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", - "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Cloud Security" + ], + "channel": "ESCU", + "creation_date": "2018-01-10", + "description": "Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it.", + "detections": [ + { + "detection_id": "ada0f478-84a8-4641-a3f1-d82362d6bd75", + "name": "AWS Network Access Control List Created with All Open Ports", + "type": "splunk" + }, + { + "detection_id": "ada0f478-84a8-4641-a3f1-d82362d6fd75", + "name": "AWS Network Access Control List Deleted", + "type": "splunk" + }, + { + "detection_id": "ada0f278-84a8-46w1-a3f1-w32372d4bd53", + "name": "Detect Spike in blocked Outbound Traffic from your AWS", + "type": "splunk" + }, + { + "detection_id": "ada0f478-84a8-4641-a1f1-e32372d4bd53", + "name": "Detect Spike in Network ACL Activity", + "type": "splunk" + } + ], + "id": "2e8948a5-5239-406b-b56b-6c50ff268af4", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-05-21", + "name": "AWS Network ACL Activity", + "narrative": "AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", + "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "2.0" +} diff --git a/stories/aws_provisioning.json b/stories/aws_provisioning.json index 5578051b88..9d58cf26e2 100644 --- a/stories/aws_provisioning.json +++ b/stories/aws_provisioning.json @@ -1,54 +1,54 @@ { - "category": [ - "Cloud Security" - ], - "channel": "ESCU", - "creation_date": "2018-03-16", - "description": "Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network.", - "detections": [ - { - "detection_id": "ceb8d3d8-06cb-49eb-beaf-829526e33ff0", - "name": "AWS Cloud Provisioning From Previously Unseen Country", - "type": "splunk" - }, - { - "detection_id": "7971d3df-da82-4648-a6e5-b5637bea5253", - "name": "AWS Cloud Provisioning From Previously Unseen Region", - "type": "splunk" - }, - { - "detection_id": "344a1778-0b25-490c-adb1-de8beddf59cd", - "name": "AWS Cloud Provisioning From Previously Unseen City", - "type": "splunk" - }, - { - "detection_id": "42e15012-ac14-4801-94f4-f1acbe64880b", - "name": "AWS Cloud Provisioning From Previously Unseen IP Address", - "type": "splunk" - } - ], - "id": "3338b567-3804-4261-9889-cf0ca4753c7f", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-03-16", - "name": "AWS Suspicious Provisioning Activities", - "narrative": "Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).
        This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Cloud Security" + ], + "channel": "ESCU", + "creation_date": "2018-03-16", + "description": "Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network.", + "detections": [ + { + "detection_id": "ceb8d3d8-06cb-49eb-beaf-829526e33ff0", + "name": "AWS Cloud Provisioning From Previously Unseen Country", + "type": "splunk" + }, + { + "detection_id": "7971d3df-da82-4648-a6e5-b5637bea5253", + "name": "AWS Cloud Provisioning From Previously Unseen Region", + "type": "splunk" + }, + { + "detection_id": "344a1778-0b25-490c-adb1-de8beddf59cd", + "name": "AWS Cloud Provisioning From Previously Unseen City", + "type": "splunk" + }, + { + "detection_id": "42e15012-ac14-4801-94f4-f1acbe64880b", + "name": "AWS Cloud Provisioning From Previously Unseen IP Address", + "type": "splunk" + } + ], + "id": "3338b567-3804-4261-9889-cf0ca4753c7f", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-03-16", + "name": "AWS Suspicious Provisioning Activities", + "narrative": "Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\nThis Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/aws_s3.json b/stories/aws_s3.json index e60e937c1c..34f327b436 100644 --- a/stories/aws_s3.json +++ b/stories/aws_s3.json @@ -1,50 +1,50 @@ { - "category": [ - "Cloud Security" - ], - "channel": "ESCU", - "creation_date": "2018-06-25", - "description": "Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required.", - "detections": [ - { - "detection_id": "2a9b80d3-6340-4345-b5ad-290bf3d0dac4", - "name": "Detect New Open S3 buckets", - "type": "splunk" - }, - { - "detection_id": "2a9b80d3-6340-4345-b5ad-291bq3d0daq4", - "name": "Detect S3 access from a new IP", - "type": "splunk" - }, - { - "detection_id": "ad12w478-84a8-4641-a3w1-e32372q4bd53", - "name": "Detect Spike in S3 Bucket deletion", - "type": "splunk" - } - ], - "id": "2e8948a5-5239-406b-b56b-6c50w3168af3", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-07-24", - "name": "Suspicious AWS S3 Activities", - "narrative": "As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.

        Amazon's \"shared responsibility\" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.

        Among things to look out for are S3 access from unfamiliar locations and by unfamiliar users. Some of the searches in this Analytic Story help you detect suspicious behavior and others help you investigate more deeply, when the situation warrants. ", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", - "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Cloud Security" + ], + "channel": "ESCU", + "creation_date": "2018-06-25", + "description": "Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required.", + "detections": [ + { + "detection_id": "2a9b80d3-6340-4345-b5ad-290bf3d0dac4", + "name": "Detect New Open S3 buckets", + "type": "splunk" + }, + { + "detection_id": "2a9b80d3-6340-4345-b5ad-291bq3d0daq4", + "name": "Detect S3 access from a new IP", + "type": "splunk" + }, + { + "detection_id": "ad12w478-84a8-4641-a3w1-e32372q4bd53", + "name": "Detect Spike in S3 Bucket deletion", + "type": "splunk" + } + ], + "id": "2e8948a5-5239-406b-b56b-6c50w3168af3", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-07-24", + "name": "Suspicious AWS S3 Activities", + "narrative": "As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\n\nAmazon's \"shared responsibility\" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\n\nAmong things to look out for are S3 access from unfamiliar locations and by unfamiliar users. Some of the searches in this Analytic Story help you detect suspicious behavior and others help you investigate more deeply, when the situation warrants. ", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", + "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "2.0" +} diff --git a/stories/aws_suspcious_traffic.json b/stories/aws_suspcious_traffic.json index efaf82c5ac..a59cc5f920 100644 --- a/stories/aws_suspcious_traffic.json +++ b/stories/aws_suspcious_traffic.json @@ -1,39 +1,39 @@ { - "category": [ - "Cloud Security" - ], - "channel": "ESCU", - "creation_date": "2018-05-07", - "description": "Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC).", - "detections": [ - { - "detection_id": "ada0f278-84a8-46w1-a3f1-w32372d4bd53", - "name": "Detect Spike in blocked Outbound Traffic from your AWS", - "type": "splunk" - } - ], - "id": "2e8948a5-5239-406b-b56b-6c50f2168af3", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-05-07", - "name": "Suspicious AWS Traffic", - "narrative": "A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network.

        Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.

        Attackers may abuse the AWS infrastructure with insecure VPCs so they can co-opt AWS resources for command-and-control nodes, data exfiltration, and more. Once an EC2 instance is compromised, an attacker may initiate outbound network connections for malicious reasons. Monitoring these network traffic behaviors is crucial for understanding the type of traffic flowing in and out of your network and to alert you to suspicious activities.

        The searches in this Analytic Story will monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Cloud Security" + ], + "channel": "ESCU", + "creation_date": "2018-05-07", + "description": "Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC).", + "detections": [ + { + "detection_id": "ada0f278-84a8-46w1-a3f1-w32372d4bd53", + "name": "Detect Spike in blocked Outbound Traffic from your AWS", + "type": "splunk" + } + ], + "id": "2e8948a5-5239-406b-b56b-6c50f2168af3", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-05-07", + "name": "Suspicious AWS Traffic", + "narrative": "A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \n\nAmazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\n\n Attackers may abuse the AWS infrastructure with insecure VPCs so they can co-opt AWS resources for command-and-control nodes, data exfiltration, and more. Once an EC2 instance is compromised, an attacker may initiate outbound network connections for malicious reasons. Monitoring these network traffic behaviors is crucial for understanding the type of traffic flowing in and out of your network and to alert you to suspicious activities.\n\nThe searches in this Analytic Story will monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/aws_user_monitoring.json b/stories/aws_user_monitoring.json index 2c16622365..405d6639b2 100644 --- a/stories/aws_user_monitoring.json +++ b/stories/aws_user_monitoring.json @@ -1,60 +1,60 @@ { - "category": [ - "Cloud Security" - ], - "channel": "ESCU", - "creation_date": "2018-03-12", - "description": "Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment.", - "detections": [ - { - "detection_id": "ada0f478-84a8-4641-a3f1-d82362d4bd55", - "name": "Detect AWS API Activities From Unapproved Accounts", - "type": "splunk" - }, - { - "detection_id": "ada0f478-84a8-4641-a3f1-d32362d4bd55", - "name": "Detect Spike in AWS API Activity", - "type": "splunk" - }, - { - "detection_id": "22773e84-bac0-4595-b086-20d3f335b4f1", - "name": "Detect new API calls from user roles", - "type": "splunk" - }, - { - "detection_id": "ada0f478-84a8-4641-a3f1-e32372d4bd53", - "name": "Detect Spike in Security Group Activity", - "type": "splunk" - }, - { - "detection_id": "2a9b80d3-6340-4345-w5ad-212bf5d1dac4", - "name": "Detect API activity from users without MFA", - "type": "splunk" - } - ], - "id": "2e8948a5-5239-406b-b56b-6c50f1269af3", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-03-12", - "name": "AWS User Monitoring", - "narrative": "It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.

        In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage.

        Fortunately, you can leverage Amazon Web Services (AWS) CloudTrail--a tool that helps you enable governance, compliance, and risk auditing of your AWS account--to give you increased visibility into your user and resource activity by recording AWS Management Console actions and API calls. You can identify which users and accounts called AWS, the source IP address from which the calls were made, and when the calls occurred.

        The detection searches in this Analytic Story are designed to help you uncover AWS API activities from users not listed in the identity table, as well as similar activities from disabled accounts.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", - "https://blog.redlock.io/cryptojacking-tesla" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Cloud Security" + ], + "channel": "ESCU", + "creation_date": "2018-03-12", + "description": "Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment.", + "detections": [ + { + "detection_id": "ada0f478-84a8-4641-a3f1-d82362d4bd55", + "name": "Detect AWS API Activities From Unapproved Accounts", + "type": "splunk" + }, + { + "detection_id": "ada0f478-84a8-4641-a3f1-d32362d4bd55", + "name": "Detect Spike in AWS API Activity", + "type": "splunk" + }, + { + "detection_id": "22773e84-bac0-4595-b086-20d3f335b4f1", + "name": "Detect new API calls from user roles", + "type": "splunk" + }, + { + "detection_id": "ada0f478-84a8-4641-a3f1-e32372d4bd53", + "name": "Detect Spike in Security Group Activity", + "type": "splunk" + }, + { + "detection_id": "2a9b80d3-6340-4345-w5ad-212bf5d1dac4", + "name": "Detect API activity from users without MFA", + "type": "splunk" + } + ], + "id": "2e8948a5-5239-406b-b56b-6c50f1269af3", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-03-12", + "name": "AWS User Monitoring", + "narrative": "It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\n\nIn addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \n\nFortunately, you can leverage Amazon Web Services (AWS) CloudTrail--a tool that helps you enable governance, compliance, and risk auditing of your AWS account--to give you increased visibility into your user and resource activity by recording AWS Management Console actions and API calls. You can identify which users and accounts called AWS, the source IP address from which the calls were made, and when the calls occurred.\n\nThe detection searches in this Analytic Story are designed to help you uncover AWS API activities from users not listed in the identity table, as well as similar activities from disabled accounts.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", + "https://blog.redlock.io/cryptojacking-tesla" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/brand_monitoring.json b/stories/brand_monitoring.json index a76a7ca7ab..3e4337f219 100644 --- a/stories/brand_monitoring.json +++ b/stories/brand_monitoring.json @@ -1,51 +1,51 @@ { - "category": [ - "Abuse" - ], - "channel": "ESCU", - "creation_date": "2017-06-01", - "description": "Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name.", - "detections": [ - { - "detection_id": "24dd17b1-e2fb-4c31-878c-d4f746595bfa", - "name": "Monitor DNS For Brand Abuse", - "type": "splunk" - }, - { - "detection_id": "b2ea1f38-3a3e-4b8a-9cf1-82760d86a6b8", - "name": "Monitor Email For Brand Abuse", - "type": "splunk" - }, - { - "detection_id": "134da869-e264-4a8f-8d7e-fcd0ec88f301", - "name": "Monitor Web Traffic For Brand Abuse", - "type": "splunk" - } - ], - "id": "91c676cf-0b23-438d-abee-f6335e1fce78", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-12-19", - "name": "Brand Monitoring", - "narrative": "While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.
        You can use our adaptation of DNSTwist, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.
        Notable events will include IP addresses, URLs, and user data. Drilling down can provide you with even more actionable intelligence, including likely geographic information, contextual searches to help you scope the problem, and investigative searches.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://blog.domaintools.com/tag/brand-monitor/", - "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", - "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Abuse" + ], + "channel": "ESCU", + "creation_date": "2017-06-01", + "description": "Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name.", + "detections": [ + { + "detection_id": "24dd17b1-e2fb-4c31-878c-d4f746595bfa", + "name": "Monitor DNS For Brand Abuse", + "type": "splunk" + }, + { + "detection_id": "b2ea1f38-3a3e-4b8a-9cf1-82760d86a6b8", + "name": "Monitor Email For Brand Abuse", + "type": "splunk" + }, + { + "detection_id": "134da869-e264-4a8f-8d7e-fcd0ec88f301", + "name": "Monitor Web Traffic For Brand Abuse", + "type": "splunk" + } + ], + "id": "91c676cf-0b23-438d-abee-f6335e1fce78", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-12-19", + "name": "Brand Monitoring", + "narrative": "While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\nYou can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\nNotable events will include IP addresses, URLs, and user data. Drilling down can provide you with even more actionable intelligence, including likely geographic information, contextual searches to help you scope the problem, and investigative searches.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://blog.domaintools.com/tag/brand-monitor/", + "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", + "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/coldroot.json b/stories/coldroot.json index 05136674b0..b4e573f973 100644 --- a/stories/coldroot.json +++ b/stories/coldroot.json @@ -1,46 +1,46 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2019-01-29", - "description": "Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more.", - "detections": [ - { - "detection_id": "2a371608-331d-4034-ae2c-21dda8f1d0ec", - "name": "Processes Tapping Keyboard Events", - "type": "splunk" - }, - { - "detection_id": "a6fffe5e-05c3-4c04-badc-887607fbb8dc", - "name": "Osquery pack - ColdRoot detection", - "type": "splunk" - } - ], - "id": "bd91a2bc-d20b-4f44-a982-1bea98e86390", - "maintainers": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } - ], - "modification_date": "2019-01-09", - "name": "ColdRoot MacOS RAT", - "narrative": "Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.

        This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.

        Searches in this Analytic Story leverage the capabilities of OSquery to address ColdRoot detection from several different angles, such as looking for the existence of associated files and processes, and monitoring for signs of an installed keylogger.", - "original_authors": [ - { - "company": "Splunk", - "email": "jhernandez@splunk.com", - "name": "Jose Hernandez" - } - ], - "references": [ - "https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", - "https://objective-see.com/blog/blog_0x2A.html", - "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2019-01-29", + "description": "Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more.", + "detections": [ + { + "detection_id": "2a371608-331d-4034-ae2c-21dda8f1d0ec", + "name": "Processes Tapping Keyboard Events", + "type": "splunk" + }, + { + "detection_id": "a6fffe5e-05c3-4c04-badc-887607fbb8dc", + "name": "Osquery pack - ColdRoot detection", + "type": "splunk" + } + ], + "id": "bd91a2bc-d20b-4f44-a982-1bea98e86390", + "maintainers": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "modification_date": "2019-01-09", + "name": "ColdRoot MacOS RAT", + "narrative": "Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\n\nThis Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\n\nSearches in this Analytic Story leverage the capabilities of OSquery to address ColdRoot detection from several different angles, such as looking for the existence of associated files and processes, and monitoring for signs of an installed keylogger.", + "original_authors": [ + { + "company": "Splunk", + "email": "jhernandez@splunk.com", + "name": "Jose Hernandez" + } + ], + "references": [ + "https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", + "https://objective-see.com/blog/blog_0x2A.html", + "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/collection_and_staging.json b/stories/collection_and_staging.json index e5236a5bb8..093d184cdc 100644 --- a/stories/collection_and_staging.json +++ b/stories/collection_and_staging.json @@ -1,60 +1,60 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2018-01-08", - "description": "Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. ", - "detections": [ - { - "detection_id": "b5541828-8ffd-4070-9d95-b3da4de924cb", - "name": "Suspicious writes to windows Recycle Bin", - "type": "splunk" - }, - { - "detection_id": "cd6297cd-2bdd-4aa1-84aa-5d2f84228fac", - "name": "Suspicious writes to System Volume Information", - "type": "splunk" - }, - { - "detection_id": "ee18ed37-0802-4268-9435-b3b91aaa18xx", - "name": "Email files written outside of the Outlook directory", - "type": "splunk" - }, - { - "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b556368", - "name": "Hosts receiving high volume of network traffic from email server", - "type": "splunk" - }, - { - "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b556378", - "name": "Email servers sending high volume traffic to hosts", - "type": "splunk" - } - ], - "id": "8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-01-08", - "name": "Collection and Staging", - "narrative": "A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.

        Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence.

        Use the searches to detect and monitor suspicious behavior related to these activities.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://attack.mitre.org/wiki/Collection", - "https://attack.mitre.org/wiki/Technique/T1074" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2018-01-08", + "description": "Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. ", + "detections": [ + { + "detection_id": "b5541828-8ffd-4070-9d95-b3da4de924cb", + "name": "Suspicious writes to windows Recycle Bin", + "type": "splunk" + }, + { + "detection_id": "cd6297cd-2bdd-4aa1-84aa-5d2f84228fac", + "name": "Suspicious writes to System Volume Information", + "type": "splunk" + }, + { + "detection_id": "ee18ed37-0802-4268-9435-b3b91aaa18xx", + "name": "Email files written outside of the Outlook directory", + "type": "splunk" + }, + { + "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b556368", + "name": "Hosts receiving high volume of network traffic from email server", + "type": "splunk" + }, + { + "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b556378", + "name": "Email servers sending high volume traffic to hosts", + "type": "splunk" + } + ], + "id": "8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-01-08", + "name": "Collection and Staging", + "narrative": "A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\n\n Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \n\nUse the searches to detect and monitor suspicious behavior related to these activities.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://attack.mitre.org/wiki/Collection", + "https://attack.mitre.org/wiki/Technique/T1074" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/command_and_control.json b/stories/command_and_control.json index b90ef5035e..6fd0da3968 100644 --- a/stories/command_and_control.json +++ b/stories/command_and_control.json @@ -1,100 +1,100 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2018-06-01", - "description": "Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators.", - "detections": [ - { - "detection_id": "e9c102de-4d43-42a7-b1c8-8062ea297419", - "name": "Detect Large Outbound ICMP Packets", - "type": "splunk" - }, - { - "detection_id": "54dc1265-2f74-4b6d-b30d-49eb506a31b3", - "name": "Protocol or Port Mismatch", - "type": "splunk" - }, - { - "detection_id": "104658f4-afdc-499f-9719-17a43f9826f4", - "name": "Detection of DNS Tunnels", - "type": "splunk" - }, - { - "detection_id": "ea688274-9c06-4473-b951-e4cb7a5d7a45", - "name": "TOR Traffic", - "type": "splunk" - }, - { - "detection_id": "ce5a0962-849f-4720-a678-753fe6674479", - "name": "Prohibited Network Traffic Allowed", - "type": "splunk" - }, - { - "detection_id": "74ec6f18-604b-4202-a567-86b2066be3ce", - "name": "Clients Connecting to Multiple DNS Servers", - "type": "splunk" - }, - { - "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f5", - "name": "DNS Query Length With High Standard Deviation", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", - "name": "Detect hosts connecting to dynamic domain providers", - "type": "splunk" - }, - { - "detection_id": "104658f4-afdc-499e-9719-17243f9826f1", - "name": "Excessive DNS Failures", - "type": "splunk" - }, - { - "detection_id": "05437c07-62f5-452e-afdc-04dd44815bb9", - "name": "Detect Long DNS TXT Record Response", - "type": "splunk" - }, - { - "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", - "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", - "type": "splunk" - }, - { - "detection_id": "ada0f278-84a8-46w1-a3f1-w32372d4bd53", - "name": "Detect Spike in blocked Outbound Traffic from your AWS", - "type": "splunk" - }, - { - "detection_id": "85fbcfe8-9718-4911-adf6-7000d077a3a9", - "name": "DNS Query Length Outliers - MLTK", - "type": "splunk" - } - ], - "id": "943773c6-c4de-4f38-89a8-0b92f98804d8", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-06-01", - "name": "Command and Control", - "narrative": "Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.

        Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://attack.mitre.org/wiki/Command_and_Control", - "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2018-06-01", + "description": "Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators.", + "detections": [ + { + "detection_id": "e9c102de-4d43-42a7-b1c8-8062ea297419", + "name": "Detect Large Outbound ICMP Packets", + "type": "splunk" + }, + { + "detection_id": "54dc1265-2f74-4b6d-b30d-49eb506a31b3", + "name": "Protocol or Port Mismatch", + "type": "splunk" + }, + { + "detection_id": "104658f4-afdc-499f-9719-17a43f9826f4", + "name": "Detection of DNS Tunnels", + "type": "splunk" + }, + { + "detection_id": "ea688274-9c06-4473-b951-e4cb7a5d7a45", + "name": "TOR Traffic", + "type": "splunk" + }, + { + "detection_id": "ce5a0962-849f-4720-a678-753fe6674479", + "name": "Prohibited Network Traffic Allowed", + "type": "splunk" + }, + { + "detection_id": "74ec6f18-604b-4202-a567-86b2066be3ce", + "name": "Clients Connecting to Multiple DNS Servers", + "type": "splunk" + }, + { + "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f5", + "name": "DNS Query Length With High Standard Deviation", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", + "name": "Detect hosts connecting to dynamic domain providers", + "type": "splunk" + }, + { + "detection_id": "104658f4-afdc-499e-9719-17243f9826f1", + "name": "Excessive DNS Failures", + "type": "splunk" + }, + { + "detection_id": "05437c07-62f5-452e-afdc-04dd44815bb9", + "name": "Detect Long DNS TXT Record Response", + "type": "splunk" + }, + { + "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", + "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", + "type": "splunk" + }, + { + "detection_id": "ada0f278-84a8-46w1-a3f1-w32372d4bd53", + "name": "Detect Spike in blocked Outbound Traffic from your AWS", + "type": "splunk" + }, + { + "detection_id": "85fbcfe8-9718-4911-adf6-7000d077a3a9", + "name": "DNS Query Length Outliers - MLTK", + "type": "splunk" + } + ], + "id": "943773c6-c4de-4f38-89a8-0b92f98804d8", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-06-01", + "name": "Command and Control", + "narrative": "Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\n\nBecause this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://attack.mitre.org/wiki/Command_and_Control", + "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/common_phishing_frameworks.json b/stories/common_phishing_frameworks.json index 2db15b40fd..299f8c0b76 100644 --- a/stories/common_phishing_frameworks.json +++ b/stories/common_phishing_frameworks.json @@ -1,41 +1,41 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2019-04-29", - "description": "Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. ", - "detections": [ - { - "detection_id": "24dd17b1-e2fb-4c31-878c-d4f226595bfa", - "name": "Detect DNS requests to Phishing Sites leveraging EvilGinx2", - "type": "splunk" - } - ], - "id": "9a64ab44-9214-4639-8163-7eaa2621bd61", - "maintainers": [ - { - "company": "Splunk", - "email": "research@splunk.com", - "name": "Splunk Research Team" - } - ], - "modification_date": "2019-04-29", - "name": "Common Phishing Frameworks", - "narrative": "As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.

        This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2.", - "original_authors": [ - { - "company": "Splunk", - "email": "research@splunk.com", - "name": "Splunk Research Team" - } - ], - "references": [ - "https://github.com/kgretzky/evilginx2", - "https://attack.mitre.org/techniques/T1192/", - "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2019-04-29", + "description": "Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. ", + "detections": [ + { + "detection_id": "24dd17b1-e2fb-4c31-878c-d4f226595bfa", + "name": "Detect DNS requests to Phishing Sites leveraging EvilGinx2", + "type": "splunk" + } + ], + "id": "9a64ab44-9214-4639-8163-7eaa2621bd61", + "maintainers": [ + { + "company": "Splunk", + "email": "research@splunk.com", + "name": "Splunk Research Team" + } + ], + "modification_date": "2019-04-29", + "name": "Common Phishing Frameworks", + "narrative": "As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\n\nThis Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2.", + "original_authors": [ + { + "company": "Splunk", + "email": "research@splunk.com", + "name": "Splunk Research Team" + } + ], + "references": [ + "https://github.com/kgretzky/evilginx2", + "https://attack.mitre.org/techniques/T1192/", + "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" } diff --git a/stories/credential_dumping.json b/stories/credential_dumping.json index 5520663440..4fc14cd739 100644 --- a/stories/credential_dumping.json +++ b/stories/credential_dumping.json @@ -1,56 +1,56 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2018-08-08", - "description": "Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attmpts to dump credentials.", - "detections": [ - { - "detection_id": "c2590137-0b08-4985-9ec5-6ae23d92f63d", - "name": "Attempt To Set Default PowerShell Execution Policy To Unrestricted", - "type": "splunk" - }, - { - "detection_id": "14038953-e5f2-4daf-acff-5452062baf03", - "name": "Attempted Credential Dump From Registry Via Reg.exe", - "type": "splunk" - }, - { - "detection_id": "98917be2-bfc8-475a-8618-a9bb06575188", - "name": "Detect Mimikatz Via PowerShell And EventCode 4703", - "type": "splunk" - }, - { - "detection_id": "2c365e57-4414-4540-8dc0-73ab10729996", - "name": "Detect Mimikatz Via PowerShell And EventCode 4663", - "type": "splunk" - } - ], - "id": "854d78bf-d0e2-4f4e-b05c-640905f86d7a", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-08-08", - "name": "Credential Dumping", - "narrative": "Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.

        Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.

        The detection searches in this Analytic Story monitor for the process reg.exe with the \"save\" parameter, as well as for a target registry path that specifies a binary export of credentials from the registry. In addition, the analytics flag Windows events and activities associated with the use of Mimikatz functionality in Powershell Empire.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://attack.mitre.org/wiki/Technique/T1003", - "https://www.powershellempire.com/?page_id=112", - "https://4iq.com/4iq-discovers-1-4-billion-clear-text-credentials-single-database/" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2018-08-08", + "description": "Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attmpts to dump credentials.", + "detections": [ + { + "detection_id": "c2590137-0b08-4985-9ec5-6ae23d92f63d", + "name": "Attempt To Set Default PowerShell Execution Policy To Unrestricted", + "type": "splunk" + }, + { + "detection_id": "14038953-e5f2-4daf-acff-5452062baf03", + "name": "Attempted Credential Dump From Registry Via Reg.exe", + "type": "splunk" + }, + { + "detection_id": "98917be2-bfc8-475a-8618-a9bb06575188", + "name": "Detect Mimikatz Via PowerShell And EventCode 4703", + "type": "splunk" + }, + { + "detection_id": "2c365e57-4414-4540-8dc0-73ab10729996", + "name": "Detect Mimikatz Via PowerShell And EventCode 4663", + "type": "splunk" + } + ], + "id": "854d78bf-d0e2-4f4e-b05c-640905f86d7a", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-08-08", + "name": "Credential Dumping", + "narrative": "Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\n\nOnce attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\n\nThe detection searches in this Analytic Story monitor for the process **reg.exe** with the \"save\" parameter, as well as for a target registry path that specifies a binary export of credentials from the registry. In addition, the analytics flag Windows events and activities associated with the use of Mimikatz functionality in Powershell Empire.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://attack.mitre.org/wiki/Technique/T1003", + "https://www.powershellempire.com/?page_id=112", + "https://4iq.com/4iq-discovers-1-4-billion-clear-text-credentials-single-database/" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/data_protection.json b/stories/data_protection.json index bd3803197a..20dc216ae1 100644 --- a/stories/data_protection.json +++ b/stories/data_protection.json @@ -1,51 +1,51 @@ { - "category": [ - "Abuse" - ], - "channel": "ESCU", - "creation_date": "2017-06-01", - "description": "Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration.", - "detections": [ - { - "detection_id": "104658f4-afdc-499f-9719-17a43f9826f4", - "name": "Detection of DNS Tunnels", - "type": "splunk" - }, - { - "detection_id": "104658f4-afdc-499f-9719-17a43f9826f5", - "name": "Detect USB device insertion", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", - "name": "Detect hosts connecting to dynamic domain providers", - "type": "splunk" - } - ], - "id": "91c676cf-0b23-438d-abee-f6335e1fce33", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-14", - "name": "Data Protection", - "narrative": "Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.cisecurity.org/controls/data-protection/", - "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", - "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Abuse" + ], + "channel": "ESCU", + "creation_date": "2017-06-01", + "description": "Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration.", + "detections": [ + { + "detection_id": "104658f4-afdc-499f-9719-17a43f9826f4", + "name": "Detection of DNS Tunnels", + "type": "splunk" + }, + { + "detection_id": "104658f4-afdc-499f-9719-17a43f9826f5", + "name": "Detect USB device insertion", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", + "name": "Detect hosts connecting to dynamic domain providers", + "type": "splunk" + } + ], + "id": "91c676cf-0b23-438d-abee-f6335e1fce33", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-14", + "name": "Data Protection", + "narrative": "Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.cisecurity.org/controls/data-protection/", + "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", + "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/defense_evasion.json b/stories/defense_evasion.json index 1fd2adb761..88275812d5 100644 --- a/stories/defense_evasion.json +++ b/stories/defense_evasion.json @@ -1,59 +1,59 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2017-10-11", - "description": "Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious reg.exe processes, files hidden with attrib.exe and disabling user-account control, among many others ", - "detections": [ - { - "detection_id": "a6b3ab4e-dd77-4213-95fa-fc94701995e0", - "name": "Suspicious Reg.exe Process", - "type": "splunk" - }, - { - "detection_id": "bbc644bc-37df-4e1a-9c88-ec9a53e2038c", - "name": "Disabling Remote User Account Control", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264g9f", - "name": "Hiding Files And Directories With Attrib.exe", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264x9f", - "name": "Reg.exe used to hide files/directories via registry keys", - "type": "splunk" - }, - { - "detection_id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", - "name": "Remote Registry Key modifications", - "type": "splunk" - } - ], - "id": "56e24a28-5003-4047-b2db-e8f3c4618064", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-05-31", - "name": "Windows Defense Evasion Tactics", - "narrative": "Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://attack.mitre.org/wiki/Defense_Evasion" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2017-10-11", + "description": "Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others ", + "detections": [ + { + "detection_id": "a6b3ab4e-dd77-4213-95fa-fc94701995e0", + "name": "Suspicious Reg.exe Process", + "type": "splunk" + }, + { + "detection_id": "bbc644bc-37df-4e1a-9c88-ec9a53e2038c", + "name": "Disabling Remote User Account Control", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264g9f", + "name": "Hiding Files And Directories With Attrib.exe", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264x9f", + "name": "Reg.exe used to hide files/directories via registry keys", + "type": "splunk" + }, + { + "detection_id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", + "name": "Remote Registry Key modifications", + "type": "splunk" + } + ], + "id": "56e24a28-5003-4047-b2db-e8f3c4618064", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-05-31", + "name": "Windows Defense Evasion Tactics", + "narrative": "Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://attack.mitre.org/wiki/Defense_Evasion" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/detect_unauthorized_processes.json b/stories/detect_unauthorized_processes.json index 1a36ff8105..08d18bf09e 100644 --- a/stories/detect_unauthorized_processes.json +++ b/stories/detect_unauthorized_processes.json @@ -1,39 +1,39 @@ { - "category": [ - "Best Practices" - ], - "channel": "ESCU", - "creation_date": "2017-06-26", - "description": "Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. ", - "detections": [ - { - "detection_id": "a51bfe1a-94f0-48cc-b4e4-b6ae50145893", - "name": "Prohibited Software On Endpoint", - "type": "splunk" - } - ], - "id": "8892a655-6205-43f7-abba-06460e38c8ae", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-09-15", - "name": "Monitor for Unauthorized Software", - "narrative": "It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.

        It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. ", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/" - ], - "spec_version": 2, - "usecase": "Compliance", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Best Practices" + ], + "channel": "ESCU", + "creation_date": "2017-06-26", + "description": "Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. ", + "detections": [ + { + "detection_id": "a51bfe1a-94f0-48cc-b4e4-b6ae50145893", + "name": "Prohibited Software On Endpoint", + "type": "splunk" + } + ], + "id": "8892a655-6205-43f7-abba-06460e38c8ae", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-15", + "name": "Monitor for Unauthorized Software", + "narrative": "It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\n\nIt is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. ", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/" + ], + "spec_version": 2, + "usecase": "Compliance", + "version": "1.0" +} diff --git a/stories/dhs_report_TA18-074A.json b/stories/dhs_report_TA18-074A.json index 7be7c52275..e705bae9d1 100644 --- a/stories/dhs_report_TA18-074A.json +++ b/stories/dhs_report_TA18-074A.json @@ -1,104 +1,104 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2018-03-19", - "description": "Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more.", - "detections": [ - { - "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b936378", - "name": "SMB Traffic Spike", - "type": "splunk" - }, - { - "detection_id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", - "name": "SMB Traffic Spike - MLTK", - "type": "splunk" - }, - { - "detection_id": "b89919ed-fe5f-492c-b139-95dbb162040e", - "name": "Processes launching netsh", - "type": "splunk" - }, - { - "detection_id": "a6b3ab4e-dd77-4213-95fa-fc94701995e0", - "name": "Suspicious Reg.exe Process", - "type": "splunk" - }, - { - "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", - "name": "Sc.exe Manipulating Windows Services", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", - "name": "Registry Keys Used For Persistence", - "type": "splunk" - }, - { - "detection_id": "b89919ed-fe5f-492c-b139-151bb162040e", - "name": "Create local admin accounts using net.exe", - "type": "splunk" - }, - { - "detection_id": "a4214f0b-e01c-41bc-8cc4-d2b71e3056b4", - "name": "Single Letter Process On Endpoint", - "type": "splunk" - }, - { - "detection_id": "d5af132c-7c17-439c-9d31-13d55340f36c", - "name": "Scheduled Task Name Used by Dragonfly Threat Actors", - "type": "splunk" - }, - { - "detection_id": "9be56c82-b1cc-4318-87eb-d138afaaca39", - "name": "Malicious PowerShell Process - Execution Policy Bypass", - "type": "splunk" - }, - { - "detection_id": "7f5fb3e1-4209-414-90db-0ec21b936378", - "name": "Detect Outbound SMB Traffic", - "type": "splunk" - }, - { - "detection_id": "b25f6f62-0712-43c1-b203-083231ffd97d", - "name": "Detect New Local Admin account", - "type": "splunk" - }, - { - "detection_id": "b89919ed-fe5f-492c-b139-151xb162040e", - "name": "Detect PsExec With accepteula Flag", - "type": "splunk" - }, - { - "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", - "name": "First time seen command line argument", - "type": "splunk" - } - ], - "id": "0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-03-19", - "name": "DHS Report TA18-074A", - "narrative": "The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity.

        There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure.

        One joint Technical Alert (TA) issued by the Department of Homeland and the FBI in mid-March of 2018 attributed some cyber activity targeting utility infrastructure to operatives sponsored by the Russian government. The hackers executed spearfishing attacks, installed malware, employed watering-hole domains, and more. While they caused no physical damage, the attacks provoked fears that a nation-state could turn off water, redirect power, or compromise a nuclear power plant.

        Suspicious activities--spikes in SMB traffic, processes that launch netsh (to modify the network configuration), suspicious registry modifications, and many more--may all be events you may wish to investigate further. While the use of these technique may be an indication that a nation-state actor is attempting to compromise your environment, it is important to note that these techniques are often employed by other groups, as well.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://www.us-cert.gov/ncas/alerts/TA18-074A" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2018-03-19", + "description": "Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more.", + "detections": [ + { + "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b936378", + "name": "SMB Traffic Spike", + "type": "splunk" + }, + { + "detection_id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", + "name": "SMB Traffic Spike - MLTK", + "type": "splunk" + }, + { + "detection_id": "b89919ed-fe5f-492c-b139-95dbb162040e", + "name": "Processes launching netsh", + "type": "splunk" + }, + { + "detection_id": "a6b3ab4e-dd77-4213-95fa-fc94701995e0", + "name": "Suspicious Reg.exe Process", + "type": "splunk" + }, + { + "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", + "name": "Sc.exe Manipulating Windows Services", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", + "name": "Registry Keys Used For Persistence", + "type": "splunk" + }, + { + "detection_id": "b89919ed-fe5f-492c-b139-151bb162040e", + "name": "Create local admin accounts using net.exe", + "type": "splunk" + }, + { + "detection_id": "a4214f0b-e01c-41bc-8cc4-d2b71e3056b4", + "name": "Single Letter Process On Endpoint", + "type": "splunk" + }, + { + "detection_id": "d5af132c-7c17-439c-9d31-13d55340f36c", + "name": "Scheduled Task Name Used by Dragonfly Threat Actors", + "type": "splunk" + }, + { + "detection_id": "9be56c82-b1cc-4318-87eb-d138afaaca39", + "name": "Malicious PowerShell Process - Execution Policy Bypass", + "type": "splunk" + }, + { + "detection_id": "7f5fb3e1-4209-414-90db-0ec21b936378", + "name": "Detect Outbound SMB Traffic", + "type": "splunk" + }, + { + "detection_id": "b25f6f62-0712-43c1-b203-083231ffd97d", + "name": "Detect New Local Admin account", + "type": "splunk" + }, + { + "detection_id": "b89919ed-fe5f-492c-b139-151xb162040e", + "name": "Detect PsExec With accepteula Flag", + "type": "splunk" + }, + { + "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", + "name": "First time seen command line argument", + "type": "splunk" + } + ], + "id": "0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-03-19", + "name": "DHS Report TA18-074A", + "narrative": "The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \n\nThere is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \n\nOne joint Technical Alert (TA) issued by the Department of Homeland and the FBI in mid-March of 2018 attributed some cyber activity targeting utility infrastructure to operatives sponsored by the Russian government. The hackers executed spearfishing attacks, installed malware, employed watering-hole domains, and more. While they caused no physical damage, the attacks provoked fears that a nation-state could turn off water, redirect power, or compromise a nuclear power plant.\n\nSuspicious activities--spikes in SMB traffic, processes that launch netsh (to modify the network configuration), suspicious registry modifications, and many more--may all be events you may wish to investigate further. While the use of these technique may be an indication that a nation-state actor is attempting to compromise your environment, it is important to note that these techniques are often employed by other groups, as well.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://www.us-cert.gov/ncas/alerts/TA18-074A" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "2.0" +} diff --git a/stories/disable_security_tools.json b/stories/disable_security_tools.json index b9a2fd9961..804b9b77c1 100644 --- a/stories/disable_security_tools.json +++ b/stories/disable_security_tools.json @@ -1,61 +1,61 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2018-04-09", - "description": "Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious reg.exe processes, processes launching netsh, and many others.", - "detections": [ - { - "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", - "name": "Sc.exe Manipulating Windows Services", - "type": "splunk" - }, - { - "detection_id": "a6b3ab4e-dd77-4213-95fa-fc94701995e0", - "name": "Suspicious Reg.exe Process", - "type": "splunk" - }, - { - "detection_id": "b89919ed-fe5f-492c-b139-95dbb162040e", - "name": "Processes launching netsh", - "type": "splunk" - }, - { - "detection_id": "c8e349c6-b97c-486e-8949-bd7bcd1f3910", - "name": "Attempt To Stop Security Service", - "type": "splunk" - }, - { - "detection_id": "6bc5243e-ef36-45dc-9b12-f4a6be131159", - "name": "Attempt To Add Certificate To Untrusted Store", - "type": "splunk" - } - ], - "id": "fcc27099-46a0-46b0-a271-5c7dab56b6f1", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-04-09", - "name": "Disabling Security Tools", - "narrative": "Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running).", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://attack.mitre.org/wiki/Technique/T1089", - "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", - "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2018-04-09", + "description": "Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others.", + "detections": [ + { + "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", + "name": "Sc.exe Manipulating Windows Services", + "type": "splunk" + }, + { + "detection_id": "a6b3ab4e-dd77-4213-95fa-fc94701995e0", + "name": "Suspicious Reg.exe Process", + "type": "splunk" + }, + { + "detection_id": "b89919ed-fe5f-492c-b139-95dbb162040e", + "name": "Processes launching netsh", + "type": "splunk" + }, + { + "detection_id": "c8e349c6-b97c-486e-8949-bd7bcd1f3910", + "name": "Attempt To Stop Security Service", + "type": "splunk" + }, + { + "detection_id": "6bc5243e-ef36-45dc-9b12-f4a6be131159", + "name": "Attempt To Add Certificate To Untrusted Store", + "type": "splunk" + } + ], + "id": "fcc27099-46a0-46b0-a271-5c7dab56b6f1", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-04-09", + "name": "Disabling Security Tools", + "narrative": "Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running).", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://attack.mitre.org/wiki/Technique/T1089", + "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", + "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/dns_amplification_attacks.json b/stories/dns_amplification_attacks.json index 9e4eb40f06..505aa01880 100644 --- a/stories/dns_amplification_attacks.json +++ b/stories/dns_amplification_attacks.json @@ -1,40 +1,40 @@ { - "category": [ - "Abuse" - ], - "channel": "ESCU", - "creation_date": "2016-08-24", - "description": "DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to ANY queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims.", - "detections": [ - { - "detection_id": "8fa891f7-a533-4b3c-af85-5aa2e7c1f1eb", - "name": "Large Volume of DNS ANY Queries", - "type": "splunk" - } - ], - "id": "e8afd39e-3294-11e6-b39d-a45e60c6700", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2016-09-13", - "name": "DNS Amplification Attacks", - "narrative": "The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to ANY queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The ANY requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.

        The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.us-cert.gov/ncas/alerts/TA13-088A", - "https://deepthought.isc.org/article/AA-00897/0/What-is-a-DNS-Amplification-Attack.html" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Abuse" + ], + "channel": "ESCU", + "creation_date": "2016-08-24", + "description": "DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims.", + "detections": [ + { + "detection_id": "8fa891f7-a533-4b3c-af85-5aa2e7c1f1eb", + "name": "Large Volume of DNS ANY Queries", + "type": "splunk" + } + ], + "id": "e8afd39e-3294-11e6-b39d-a45e60c6700", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2016-09-13", + "name": "DNS Amplification Attacks", + "narrative": "The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\n\nThe search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.us-cert.gov/ncas/alerts/TA13-088A", + "https://deepthought.isc.org/article/AA-00897/0/What-is-a-DNS-Amplification-Attack.html" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/dns_hijacking.json b/stories/dns_hijacking.json index 1d9e4eee80..830f00f5ae 100644 --- a/stories/dns_hijacking.json +++ b/stories/dns_hijacking.json @@ -1,57 +1,57 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2017-11-21", - "description": "Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records.", - "detections": [ - { - "detection_id": "44d3a43e-dcd5-49f7-8356-5209bb369065", - "name": "DNS record changed", - "type": "splunk" - }, - { - "detection_id": "74ec6f18-604b-4202-a567-86b2066be3ce", - "name": "Clients Connecting to Multiple DNS Servers", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", - "name": "Detect hosts connecting to dynamic domain providers", - "type": "splunk" - }, - { - "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", - "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", - "type": "splunk" - } - ], - "id": "8169f17b-ef68-4b59-aa28-586907301221", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-09-06", - "name": "DNS Hijacking", - "narrative": "Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.

        The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well.

        On January 22, 2019, the US Department of Homeland Security 2019's Cybersecurity and Infrastructure Security Agency (CISA) raised awareness of some high-profile DNS hijacking attacks against infrastructure, both in the United States and abroad. It issued Emergency Directive 19-01 (see https://cyber.dhs.gov/ed/19-01/), which summarized the activity and required government agencies to take the following four actions, all within 10 days:
        1. For all .gov or other agency-managed domains, audit public DNS records on all authoritative and secondary DNS servers, verify that they resolve to the intended location or report them to CISA.
        2. Update the passwords for all accounts on systems that can make changes to each agency 2019's DNS records.
        3. Implement multi-factor authentication (MFA) for all accounts on systems that can make changes to each agency's 2019 DNS records or, if impossible, provide CISA with the names of systems, the reasons why MFA cannot be enabled within the required timeline, and an ETA for when it can be enabled.
        4. CISA will begin regular delivery of newly added certificates to Certificate Transparency (CT) logs for agency domains via the Cyber Hygiene service. Upon receipt, agencies must immediately begin monitoring CT log data for certificates issued that they did not request. If an agency confirms that a certificate was unauthorized, it must report the certificate to the issuing certificate authority and to CISA.
        Of course, it makes sense to put equivalent actions in place within your environment, as well.

        In DNS hijacking, the attacker assumes control over an account or makes use of a DNS service exploit to make changes to DNS records. Once they gain access, attackers can substitute their own MX records, name-server records, and addresses, redirecting emails and traffic through their infrastructure, where they can read, copy, or modify information seen. They can also generate valid encryption certificates to help them avoid browser-certificate checks. In one notable attack on the Internet service provider, GoDaddy, the hackers altered Sender Policy Framework (SPF) records a relatively minor change that did not inflict excessive damage but allowed for more effective spam campaigns.

        The searches in this Analytic Story help you detect and investigate activities that may indicate that DNS hijacking has taken place within your environment.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", - "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", - "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", - "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2017-11-21", + "description": "Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records.", + "detections": [ + { + "detection_id": "44d3a43e-dcd5-49f7-8356-5209bb369065", + "name": "DNS record changed", + "type": "splunk" + }, + { + "detection_id": "74ec6f18-604b-4202-a567-86b2066be3ce", + "name": "Clients Connecting to Multiple DNS Servers", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", + "name": "Detect hosts connecting to dynamic domain providers", + "type": "splunk" + }, + { + "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", + "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", + "type": "splunk" + } + ], + "id": "8169f17b-ef68-4b59-aa28-586907301221", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-09-06", + "name": "DNS Hijacking", + "narrative": "Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\n\nThe gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \n\nOn January 22, 2019, the US Department of Homeland Security 2019's Cybersecurity and Infrastructure Security Agency (CISA) raised awareness of some high-profile DNS hijacking attacks against infrastructure, both in the United States and abroad. It issued Emergency Directive 19-01 (see https://cyber.dhs.gov/ed/19-01/), which summarized the activity and required government agencies to take the following four actions, all within 10 days:
        1. For all .gov or other agency-managed domains, audit public DNS records on all authoritative and secondary DNS servers, verify that they resolve to the intended location or report them to CISA.
        2. Update the passwords for all accounts on systems that can make changes to each agency 2019's DNS records.
        3. Implement multi-factor authentication (MFA) for all accounts on systems that can make changes to each agency's 2019 DNS records or, if impossible, provide CISA with the names of systems, the reasons why MFA cannot be enabled within the required timeline, and an ETA for when it can be enabled.
        4. CISA will begin regular delivery of newly added certificates to Certificate Transparency (CT) logs for agency domains via the Cyber Hygiene service. Upon receipt, agencies must immediately begin monitoring CT log data for certificates issued that they did not request. If an agency confirms that a certificate was unauthorized, it must report the certificate to the issuing certificate authority and to CISA.
        Of course, it makes sense to put equivalent actions in place within your environment, as well. \n\nIn DNS hijacking, the attacker assumes control over an account or makes use of a DNS service exploit to make changes to DNS records. Once they gain access, attackers can substitute their own MX records, name-server records, and addresses, redirecting emails and traffic through their infrastructure, where they can read, copy, or modify information seen. They can also generate valid encryption certificates to help them avoid browser-certificate checks. In one notable attack on the Internet service provider, GoDaddy, the hackers altered Sender Policy Framework (SPF) records a relatively minor change that did not inflict excessive damage but allowed for more effective spam campaigns.\n\nThe searches in this Analytic Story help you detect and investigate activities that may indicate that DNS hijacking has taken place within your environment.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", + "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", + "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", + "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" } diff --git a/stories/dynamic_dns.json b/stories/dynamic_dns.json index 9a8631a4d2..f7095657c2 100644 --- a/stories/dynamic_dns.json +++ b/stories/dynamic_dns.json @@ -1,47 +1,47 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2017-11-21", - "description": "Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists.", - "detections": [ - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", - "name": "Detect hosts connecting to dynamic domain providers", - "type": "splunk" - }, - { - "detection_id": "134da869-e264-4a8f-8d7e-fcd01c18f301", - "name": "Detect web traffic to dynamic domain providers", - "type": "splunk" - } - ], - "id": "8169f17b-ef68-4b59-aae8-586907301221", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-09-06", - "name": "Dynamic DNS", - "narrative": "Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", - "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", - "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", - "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2017-11-21", + "description": "Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists.", + "detections": [ + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", + "name": "Detect hosts connecting to dynamic domain providers", + "type": "splunk" + }, + { + "detection_id": "134da869-e264-4a8f-8d7e-fcd01c18f301", + "name": "Detect web traffic to dynamic domain providers", + "type": "splunk" + } + ], + "id": "8169f17b-ef68-4b59-aae8-586907301221", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-09-06", + "name": "Dynamic DNS", + "narrative": "Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", + "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", + "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", + "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "2.0" +} diff --git a/stories/emotet.json b/stories/emotet.json index 11371d7023..9933be645a 100644 --- a/stories/emotet.json +++ b/stories/emotet.json @@ -1,81 +1,81 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2018-09-11", - "description": "Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment.", - "detections": [ - { - "detection_id": "44fddcb2-8d3b-454c-874e-7c6de5a4f7ac", - "name": "Detect Rare Executables", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", - "name": "Registry Keys Used For Persistence", - "type": "splunk" - }, - { - "detection_id": "b89919ed-fe5f-492c-b139-95dbb162039e", - "name": "Detect Use of cmd.exe to Launch Script Interpreters", - "type": "splunk" - }, - { - "detection_id": "a51bfe1a-94f0-48cc-b4e4-b6ae50145893", - "name": "Prohibited Software On Endpoint", - "type": "splunk" - }, - { - "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b936378", - "name": "SMB Traffic Spike", - "type": "splunk" - }, - { - "detection_id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", - "name": "SMB Traffic Spike - MLTK", - "type": "splunk" - }, - { - "detection_id": "473bd65f-06ca-4dfe-a2b8-ba04ab4a0084", - "name": "Suspicious Email Attachment Extensions", - "type": "splunk" - }, - { - "detection_id": "56e877a6-1455-4479-ada6-0550dc1e22f8", - "name": "Email Attachments With Lots Of Spaces", - "type": "splunk" - }, - { - "detection_id": "1297fb80-f42a-4q4a-9c8b-78c061417cf6", - "name": "Detection of tools built by NirSoft", - "type": "splunk" - } - ], - "id": "bb9f5ed2-916e-4364-bb6d-91c310efcf52", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-09-11", - "name": "Emotet Malware (DHS Report TA18-201A)", - "narrative": "The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants.

        According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.

        The searches in this Analytic Story will help you find executables that are rarely used in your environment, specific registry paths that malware often uses to ensure survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that Emotet or other malware has compromised your environment. ", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.us-cert.gov/ncas/alerts/TA18-201A", - "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", - "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2018-09-11", + "description": "Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment.", + "detections": [ + { + "detection_id": "44fddcb2-8d3b-454c-874e-7c6de5a4f7ac", + "name": "Detect Rare Executables", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", + "name": "Registry Keys Used For Persistence", + "type": "splunk" + }, + { + "detection_id": "b89919ed-fe5f-492c-b139-95dbb162039e", + "name": "Detect Use of cmd.exe to Launch Script Interpreters", + "type": "splunk" + }, + { + "detection_id": "a51bfe1a-94f0-48cc-b4e4-b6ae50145893", + "name": "Prohibited Software On Endpoint", + "type": "splunk" + }, + { + "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b936378", + "name": "SMB Traffic Spike", + "type": "splunk" + }, + { + "detection_id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", + "name": "SMB Traffic Spike - MLTK", + "type": "splunk" + }, + { + "detection_id": "473bd65f-06ca-4dfe-a2b8-ba04ab4a0084", + "name": "Suspicious Email Attachment Extensions", + "type": "splunk" + }, + { + "detection_id": "56e877a6-1455-4479-ada6-0550dc1e22f8", + "name": "Email Attachments With Lots Of Spaces", + "type": "splunk" + }, + { + "detection_id": "1297fb80-f42a-4q4a-9c8b-78c061417cf6", + "name": "Detection of tools built by NirSoft", + "type": "splunk" + } + ], + "id": "bb9f5ed2-916e-4364-bb6d-91c310efcf52", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-09-11", + "name": "Emotet Malware (DHS Report TA18-201A)", + "narrative": "The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \n\nAccording to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\n\nThe searches in this Analytic Story will help you find executables that are rarely used in your environment, specific registry paths that malware often uses to ensure survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that Emotet or other malware has compromised your environment. ", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.us-cert.gov/ncas/alerts/TA18-201A", + "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", + "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/file_extension_abuse.json b/stories/file_extension_abuse.json index 9bef3c576f..110a5f8cd4 100644 --- a/stories/file_extension_abuse.json +++ b/stories/file_extension_abuse.json @@ -1,50 +1,50 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2018-01-26", - "description": "Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques.", - "detections": [ - { - "detection_id": "b06a555e-dce0-417d-a2eb-28a5d8d66ef7", - "name": "Execution of File with Multiple Extensions", - "type": "splunk" - }, - { - "detection_id": "ab0353e6-a956-420b-b724-a8b4846d5d5a", - "name": "Execution of File With Spaces Before Extension", - "type": "splunk" - }, - { - "detection_id": "1b989a0e-0129-4446-a695-f193a5b746fc", - "name": "Suspicious Changes to File Associations", - "type": "splunk" - } - ], - "id": "30552a76-ac78-48e4-b3c0-de4e34e9563d", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-01-26", - "name": "Windows File Extension and Association Abuse", - "narrative": "Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications.

        Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in .doc or .docx, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using winword.exe. The user will typically also presume that the .docx file is safe.

        Attackers take advantage of this expectation by obfuscating the true file extension. They can accomplish this in a couple of ways. One technique involves inserting multiple spaces in the file name before the extension to hide the extension from the GUI, obscuring the true nature of the file. Another approach involves prepending the real extension with a different one. This is especially effective when Windows is configured to \"hide extensions for known file types.\" In this case, the real extension is not displayed, but the prepended one is, leading end users to believe the file is a different type than it actually is.

        Changing the association between a file extension and an application can allow an attacker to execute arbitrary code. The technique typically involves changing the association for an often-launched file type to associate instead with a malicious program the attacker has dropped on the endpoint. When the end user launches a file that has been manipulated in this way, it will execute the attacker's malware. It will also execute the application the end user expected to run, cleverly obscuring the fact that something suspicious has occurred.

        Run the searches in this story to detect and investigate suspicious behavior that may indicate abuse or manipulation of Windows file extensions and/or associations.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", - "https://attack.mitre.org/wiki/Technique/T1042" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2018-01-26", + "description": "Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques.", + "detections": [ + { + "detection_id": "b06a555e-dce0-417d-a2eb-28a5d8d66ef7", + "name": "Execution of File with Multiple Extensions", + "type": "splunk" + }, + { + "detection_id": "ab0353e6-a956-420b-b724-a8b4846d5d5a", + "name": "Execution of File With Spaces Before Extension", + "type": "splunk" + }, + { + "detection_id": "1b989a0e-0129-4446-a695-f193a5b746fc", + "name": "Suspicious Changes to File Associations", + "type": "splunk" + } + ], + "id": "30552a76-ac78-48e4-b3c0-de4e34e9563d", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-01-26", + "name": "Windows File Extension and Association Abuse", + "narrative": "Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \n\n Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \n\n Attackers take advantage of this expectation by obfuscating the true file extension. They can accomplish this in a couple of ways. One technique involves inserting multiple spaces in the file name before the extension to hide the extension from the GUI, obscuring the true nature of the file. Another approach involves prepending the real extension with a different one. This is especially effective when Windows is configured to \"hide extensions for known file types.\" In this case, the real extension is not displayed, but the prepended one is, leading end users to believe the file is a different type than it actually is.\n\nChanging the association between a file extension and an application can allow an attacker to execute arbitrary code. The technique typically involves changing the association for an often-launched file type to associate instead with a malicious program the attacker has dropped on the endpoint. When the end user launches a file that has been manipulated in this way, it will execute the attacker's malware. It will also execute the application the end user expected to run, cleverly obscuring the fact that something suspicious has occurred.\n\nRun the searches in this story to detect and investigate suspicious behavior that may indicate abuse or manipulation of Windows file extensions and/or associations.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", + "https://attack.mitre.org/wiki/Technique/T1042" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/hidden_cobra_malware.json b/stories/hidden_cobra_malware.json index 45eab14274..d96ddf0a2f 100644 --- a/stories/hidden_cobra_malware.json +++ b/stories/hidden_cobra_malware.json @@ -1,85 +1,85 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2018-06-14", - "description": "Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A.", - "detections": [ - { - "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b936378", - "name": "SMB Traffic Spike", - "type": "splunk" - }, - { - "detection_id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", - "name": "SMB Traffic Spike - MLTK", - "type": "splunk" - }, - { - "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", - "name": "First time seen command line argument", - "type": "splunk" - }, - { - "detection_id": "7f5fb3e1-4209-414-90db-0ec21b936378", - "name": "Detect Outbound SMB Traffic", - "type": "splunk" - }, - { - "detection_id": "272b8407-842d-4b3d-bead-a704584003d3", - "name": "Remote Desktop Network Traffic", - "type": "splunk" - }, - { - "detection_id": "f5939373-8054-40ad-8c64-cec478a22a4a", - "name": "Remote Desktop Process Running On System", - "type": "splunk" - }, - { - "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f5", - "name": "DNS Query Length With High Standard Deviation", - "type": "splunk" - }, - { - "detection_id": "qw9919ed-fe5f-492c-b139-151bb162140e", - "name": "Create or delete hidden shares using net.exe", - "type": "splunk" - }, - { - "detection_id": "57f76b8a-32f0-42ed-b358-d9fa3ca7bac8", - "name": "Suspicious File Write", - "type": "splunk" - }, - { - "detection_id": "85fbcfe8-9718-4911-adf6-7000d077a3a9", - "name": "DNS Query Length Outliers - MLTK", - "type": "splunk" - } - ], - "id": "baf7580b-d4b4-4774-8173-7d198e9da335", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-06-14", - "name": "Hidden Cobra Malware", - "narrative": "North Korea's government-sponsored \"cyber army\" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as \"Hidden Cobra,\" has surreptitiously crept onto the collective radar as a preeminent global threat.

        These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie \"The Interview\" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.

        In June of 2018, The Department of Homeland Security, together with the FBI and other U.S. government partners, issued Technical Alert (TA-18-149A) to advise the public about two variants of North Korean malware. One variant, dubbed \"Joanap,\" is a multi-stage peer-to-peer botnet that allows North Korean state actors to exfiltrate data, download and execute secondary payloads, and initialize proxy communications. The other variant, \"Brambul,\" is a Windows32 SMB worm that is dropped into a victim network. When executed, the malware attempts to spread laterally within a victim's local subnet, connecting via the SMB protocol and initiating brute-force password attacks. It reports details to the Hidden Cobra actors via email, so they can use the information for secondary remote operations.

        Among other searches in this Analytic Story is a detection search that looks for the creation or deletion of hidden shares, such as, \"adnim$,\" which the Hidden Cobra malware creates on the target system. Another looks for the creation of three malicious files associated with the malware. You can also use a search in this story to investigate activity that indicates that malware is sending email back to the attackers.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", - "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2018-06-14", + "description": "Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A.", + "detections": [ + { + "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b936378", + "name": "SMB Traffic Spike", + "type": "splunk" + }, + { + "detection_id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", + "name": "SMB Traffic Spike - MLTK", + "type": "splunk" + }, + { + "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", + "name": "First time seen command line argument", + "type": "splunk" + }, + { + "detection_id": "7f5fb3e1-4209-414-90db-0ec21b936378", + "name": "Detect Outbound SMB Traffic", + "type": "splunk" + }, + { + "detection_id": "272b8407-842d-4b3d-bead-a704584003d3", + "name": "Remote Desktop Network Traffic", + "type": "splunk" + }, + { + "detection_id": "f5939373-8054-40ad-8c64-cec478a22a4a", + "name": "Remote Desktop Process Running On System", + "type": "splunk" + }, + { + "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f5", + "name": "DNS Query Length With High Standard Deviation", + "type": "splunk" + }, + { + "detection_id": "qw9919ed-fe5f-492c-b139-151bb162140e", + "name": "Create or delete hidden shares using net.exe", + "type": "splunk" + }, + { + "detection_id": "57f76b8a-32f0-42ed-b358-d9fa3ca7bac8", + "name": "Suspicious File Write", + "type": "splunk" + }, + { + "detection_id": "85fbcfe8-9718-4911-adf6-7000d077a3a9", + "name": "DNS Query Length Outliers - MLTK", + "type": "splunk" + } + ], + "id": "baf7580b-d4b4-4774-8173-7d198e9da335", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-06-14", + "name": "Hidden Cobra Malware", + "narrative": "North Korea's government-sponsored \"cyber army\" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as \"Hidden Cobra,\" has surreptitiously crept onto the collective radar as a preeminent global threat.\n\nThese state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie \"The Interview\" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\n\nIn June of 2018, The Department of Homeland Security, together with the FBI and other U.S. government partners, issued Technical Alert (TA-18-149A) to advise the public about two variants of North Korean malware. One variant, dubbed \"Joanap,\" is a multi-stage peer-to-peer botnet that allows North Korean state actors to exfiltrate data, download and execute secondary payloads, and initialize proxy communications. The other variant, \"Brambul,\" is a Windows32 SMB worm that is dropped into a victim network. When executed, the malware attempts to spread laterally within a victim's local subnet, connecting via the SMB protocol and initiating brute-force password attacks. It reports details to the Hidden Cobra actors via email, so they can use the information for secondary remote operations.\n\nAmong other searches in this Analytic Story is a detection search that looks for the creation or deletion of hidden shares, such as, \"adnim$,\" which the Hidden Cobra malware creates on the target system. Another looks for the creation of three malicious files associated with the malware. You can also use a search in this story to investigate activity that indicates that malware is sending email back to the attackers.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", + "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "2.0" +} diff --git a/stories/host_redirection.json b/stories/host_redirection.json index c160b07189..0fe7df4662 100644 --- a/stories/host_redirection.json +++ b/stories/host_redirection.json @@ -1,49 +1,49 @@ { - "category": [ - "Abuse" - ], - "channel": "ESCU", - "creation_date": "2017-06-18", - "description": "Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website.", - "detections": [ - { - "detection_id": "74ec6f18-604b-4202-a567-86b2066be3ce", - "name": "Clients Connecting to Multiple DNS Servers", - "type": "splunk" - }, - { - "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", - "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", - "type": "splunk" - }, - { - "detection_id": "06a6fc63-a72d-41dc-8736-7e3dd9612116", - "name": "Windows hosts file modification", - "type": "splunk" - } - ], - "id": "2e8948a5-5239-406b-b56b-6c50fe268af4", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2017-09-14", - "name": "Host Redirection", - "narrative": "Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Abuse" + ], + "channel": "ESCU", + "creation_date": "2017-06-18", + "description": "Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website.", + "detections": [ + { + "detection_id": "74ec6f18-604b-4202-a567-86b2066be3ce", + "name": "Clients Connecting to Multiple DNS Servers", + "type": "splunk" + }, + { + "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", + "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", + "type": "splunk" + }, + { + "detection_id": "06a6fc63-a72d-41dc-8736-7e3dd9612116", + "name": "Windows hosts file modification", + "type": "splunk" + } + ], + "id": "2e8948a5-5239-406b-b56b-6c50fe268af4", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2017-09-14", + "name": "Host Redirection", + "narrative": "Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/jboss_vulnerabilities.json b/stories/jboss_vulnerabilities.json index d3b7db5501..481ec47c78 100644 --- a/stories/jboss_vulnerabilities.json +++ b/stories/jboss_vulnerabilities.json @@ -1,44 +1,44 @@ { - "category": [ - "Vulnerability" - ], - "channel": "ESCU", - "creation_date": "2016-10-04", - "description": "In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others.", - "detections": [ - { - "detection_id": "c8bff7a4-11ea-4416-a27d-c5bca472913d", - "name": "Detect malicious requests to exploit JBoss servers", - "type": "splunk" - }, - { - "detection_id": "104658f4-afdc-499e-9719-17243f982681", - "name": "Detect attackers scanning for vulnerable JBoss servers", - "type": "splunk" - } - ], - "id": "1f5294cb-b85f-4c2d-9c58-ffcf248f52bd", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-14", - "name": "JBoss Vulnerability", - "narrative": "This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.

        It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.

        When looking at the target of the behavior uncovered by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to identify other recent events involving the target. This can help tie different events together and give further situational awareness regarding the target host.

        Various types of information for external systems should be reviewed and, potentially, collected if the incident is, indeed, judged to be malicious. This data may be useful for generating your own threat intelligence, so you can create future alerts.

        The following factors may assist you in determining whether the event is malicious:
        • Country of origin
        • Responsible party
        • Fully qualified domain names associated with the external IP address
        • Registration of fully qualified domain names associated with external IP address
        Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you qualify and understand the event and possible motivation for the attack. In addition, there are various sources that may provide reputation information on the IP address or domain name, which can assist you in determining whether the event is malicious in nature. Finally, determining whether there are other events associated with the IP address may help connect data points or expose other historic events that might be brought back into scope.

        Gathering various data on the system of interest can sometimes help quickly determine whether something suspicious is happening. Some of these items include determining who else may have logged into the system recently, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and/or whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.

        When a specific service or application is targeted, it is often helpful to know the associated version, to help determine whether it is vulnerable to a specific exploit.

        If you suspect an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.

        If a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that opened the file, the processes that may have created and/or modified the file, and how many other systems potentially have this file can you determine whether the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes help you quickly determine if it is malicious in nature.

        Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if svchost.exe is found running from a location other than C:\\Windows\\System32, it is likely something malicious designed to hide in plain sight when simply reviewing process names.

        It can also be helpful to examine various behaviors of and the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see whether the parent process spawned other processes that might also warrant further scrutiny. If a process is suspect, a review of the network connections made around the time of the event and noting whether the process has spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Vulnerability" + ], + "channel": "ESCU", + "creation_date": "2016-10-04", + "description": "In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others.", + "detections": [ + { + "detection_id": "c8bff7a4-11ea-4416-a27d-c5bca472913d", + "name": "Detect malicious requests to exploit JBoss servers", + "type": "splunk" + }, + { + "detection_id": "104658f4-afdc-499e-9719-17243f982681", + "name": "Detect attackers scanning for vulnerable JBoss servers", + "type": "splunk" + } + ], + "id": "1f5294cb-b85f-4c2d-9c58-ffcf248f52bd", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-14", + "name": "JBoss Vulnerability", + "narrative": "This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\n\nIt is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\n\nWhen looking at the target of the behavior uncovered by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to identify other recent events involving the target. This can help tie different events together and give further situational awareness regarding the target host.\n\nVarious types of information for external systems should be reviewed and, potentially, collected if the incident is, indeed, judged to be malicious. This data may be useful for generating your own threat intelligence, so you can create future alerts.\n\nThe following factors may assist you in determining whether the event is malicious:
        • Country of origin
        • Responsible party
        • Fully qualified domain names associated with the external IP address
        • Registration of fully qualified domain names associated with external IP address
        Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you qualify and understand the event and possible motivation for the attack. In addition, there are various sources that may provide reputation information on the IP address or domain name, which can assist you in determining whether the event is malicious in nature. Finally, determining whether there are other events associated with the IP address may help connect data points or expose other historic events that might be brought back into scope.\n\nGathering various data on the system of interest can sometimes help quickly determine whether something suspicious is happening. Some of these items include determining who else may have logged into the system recently, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and/or whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\n\nWhen a specific service or application is targeted, it is often helpful to know the associated version, to help determine whether it is vulnerable to a specific exploit.\n\nIf you suspect an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\n\nIf a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that opened the file, the processes that may have created and/or modified the file, and how many other systems potentially have this file can you determine whether the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes help you quickly determine if it is malicious in nature.\n\nOften, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if svchost.exe is found running from a location other than `C:\\Windows\\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. \n\nIt can also be helpful to examine various behaviors of and the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see whether the parent process spawned other processes that might also warrant further scrutiny. If a process is suspect, a review of the network connections made around the time of the event and noting whether the process has spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/lateral_movement.json b/stories/lateral_movement.json index 34fc59fddb..5c5e735fe4 100644 --- a/stories/lateral_movement.json +++ b/stories/lateral_movement.json @@ -1,60 +1,60 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2016-09-13", - "description": "Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts.", - "detections": [ - { - "detection_id": "1297fb80-f42a-4b4a-9c8a-88c066237cf6", - "name": "Schtasks scheduling job on remote system", - "type": "splunk" - }, - { - "detection_id": "f5939373-8054-40ad-8c64-cec478a22a4a", - "name": "Remote Desktop Process Running On System", - "type": "splunk" - }, - { - "detection_id": "272b8407-842d-4b3d-bead-a704584003d3", - "name": "Remote Desktop Network Traffic", - "type": "splunk" - }, - { - "detection_id": "f5939373-8054-40ad-8c64-cec478a22a4b", - "name": "Detect Activity Related to Pass the Hash Attacks", - "type": "splunk" - }, - { - "detection_id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", - "name": "Remote Registry Key modifications", - "type": "splunk" - } - ], - "id": "399d65dc-1f08-499b-a259-aad9051f38ad", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-05-31", - "name": "Lateral Movement", - "narrative": "Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.

        Indications of lateral movement can include the abuse of system utilities (such as psexec.exe), unauthorized use of remote desktop services, file/admin$ shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or \"crown jewels\" to a persistent threat actor.

        An adversary can use lateral movement for multiple purposes, including remote execution of tools, pivoting to additional systems, obtaining access to specific information or files, access to additional credentials, exfiltrating data, or delivering a secondary effect. Adversaries may use legitimate credentials alongside inherent network and operating-system functionality to remotely connect to other systems and remain under the radar of network defenders.

        If there is evidence of lateral movement, it is imperative for analysts to collect evidence of the associated offending hosts. For example, an attacker might leverage host A to gain access to host B. From there, the attacker may try to move laterally to host C. In this example, the analyst should gather as much information as possible from all three hosts.

        It is also important to collect authentication logs for each host, to ensure that the offending accounts are well-documented. Analysts should account for all processes to ensure that the attackers did not install unauthorized software.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://www.binarydefense.com/bds/reliably-detecting-pass-the-hash-through-event-log-analysis/", - "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2016-09-13", + "description": "Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts.", + "detections": [ + { + "detection_id": "1297fb80-f42a-4b4a-9c8a-88c066237cf6", + "name": "Schtasks scheduling job on remote system", + "type": "splunk" + }, + { + "detection_id": "f5939373-8054-40ad-8c64-cec478a22a4a", + "name": "Remote Desktop Process Running On System", + "type": "splunk" + }, + { + "detection_id": "272b8407-842d-4b3d-bead-a704584003d3", + "name": "Remote Desktop Network Traffic", + "type": "splunk" + }, + { + "detection_id": "f5939373-8054-40ad-8c64-cec478a22a4b", + "name": "Detect Activity Related to Pass the Hash Attacks", + "type": "splunk" + }, + { + "detection_id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", + "name": "Remote Registry Key modifications", + "type": "splunk" + } + ], + "id": "399d65dc-1f08-499b-a259-aad9051f38ad", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-05-31", + "name": "Lateral Movement", + "narrative": "Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\n\nIndications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or \"crown jewels\" to a persistent threat actor.\n\nAn adversary can use lateral movement for multiple purposes, including remote execution of tools, pivoting to additional systems, obtaining access to specific information or files, access to additional credentials, exfiltrating data, or delivering a secondary effect. Adversaries may use legitimate credentials alongside inherent network and operating-system functionality to remotely connect to other systems and remain under the radar of network defenders.\n\nIf there is evidence of lateral movement, it is imperative for analysts to collect evidence of the associated offending hosts. For example, an attacker might leverage host A to gain access to host B. From there, the attacker may try to move laterally to host C. In this example, the analyst should gather as much information as possible from all three hosts. \n\n It is also important to collect authentication logs for each host, to ensure that the offending accounts are well-documented. Analysts should account for all processes to ensure that the attackers did not install unauthorized software.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://www.binarydefense.com/bds/reliably-detecting-pass-the-hash-through-event-log-analysis/", + "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/malicious_powershell.json b/stories/malicious_powershell.json index e06b69dddb..c2ef152530 100644 --- a/stories/malicious_powershell.json +++ b/stories/malicious_powershell.json @@ -1,60 +1,60 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2016-09-18", - "description": "Attackers are finding stealthy ways \"live off the land,\" leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent.", - "detections": [ - { - "detection_id": "ee18ed37-0802-4268-9435-b3b91aaa18db", - "name": "Malicious PowerShell Process - Connect To Internet With Hidden Window", - "type": "splunk" - }, - { - "detection_id": "c4db14d9-7909-48b4-a054-aa14d89dbb19", - "name": "Malicious PowerShell Process - Encoded Command", - "type": "splunk" - }, - { - "detection_id": "2cdb91d2-542c-497f-b252-be495e71f38c", - "name": "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", - "type": "splunk" - }, - { - "detection_id": "cde75cf6-3c7a-4dd6-af01-27cdb4511fd4", - "name": "Malicious PowerShell Process With Obfuscation Techniques", - "type": "splunk" - }, - { - "detection_id": "c2590137-0b08-4985-9ec5-6ae23d92f63d", - "name": "Attempt To Set Default PowerShell Execution Policy To Unrestricted", - "type": "splunk" - } - ], - "id": "2c8ff66e-0b57-42af-8ad7-912438a403fc", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-08-23", - "name": "Malicious PowerShell", - "narrative": "The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.

        The following factors may assist you in determining whether the event is malicious:
        • Country of origin
        • Responsible party
        • Fully qualified domain names associated with the external IP address
        • Registration of fully qualified domain names associated with external IP address
        Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you answer some questions surrounding the attacker and details related to the external system. In addition, there are various sources--such as VirusTotal— that can provide some reputation information on the IP address or domain name, which can assist in determining whether the event is malicious. Finally, determining whether there are other events associated with the IP address may help connect data points or show other events that should be brought into scope.

        Gathering data on the system of interest can sometimes help you quickly determine whether something suspicious is happening. Some of these items include finding out who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.

        Often, a simple inspection of the process name and path can tell you if the system has been compromised. For example, if svchost.exe is found running from a location other than C:\\Windows\\System32, it is likely something malicious designed to hide in plain sight when cursorily reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, that could be indicative of activity initiated via a compromised website a user visited.

        It can also be very helpful to examine various behaviors of the process of interest or the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might be worth further scrutiny. If a process is suspect, a review of the network connections made in and around the time of the event and/or whether the process spawned any child processes could be helpful, as well.

        In the event a system is suspected of having been compromised via a malicious website, we suggest reviewing the browsing activity from that system around the time of the event. If categories are given for the URLs visited, that can help you zero in on possible malicious sites.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", - "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "4.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2016-09-18", + "description": "Attackers are finding stealthy ways \"live off the land,\" leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent.", + "detections": [ + { + "detection_id": "ee18ed37-0802-4268-9435-b3b91aaa18db", + "name": "Malicious PowerShell Process - Connect To Internet With Hidden Window", + "type": "splunk" + }, + { + "detection_id": "c4db14d9-7909-48b4-a054-aa14d89dbb19", + "name": "Malicious PowerShell Process - Encoded Command", + "type": "splunk" + }, + { + "detection_id": "2cdb91d2-542c-497f-b252-be495e71f38c", + "name": "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", + "type": "splunk" + }, + { + "detection_id": "cde75cf6-3c7a-4dd6-af01-27cdb4511fd4", + "name": "Malicious PowerShell Process With Obfuscation Techniques", + "type": "splunk" + }, + { + "detection_id": "c2590137-0b08-4985-9ec5-6ae23d92f63d", + "name": "Attempt To Set Default PowerShell Execution Policy To Unrestricted", + "type": "splunk" + } + ], + "id": "2c8ff66e-0b57-42af-8ad7-912438a403fc", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-08-23", + "name": "Malicious PowerShell", + "narrative": "The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\nThe following factors may assist you in determining whether the event is malicious:
        • Country of origin
        • Responsible party
        • Fully qualified domain names associated with the external IP address
        • Registration of fully qualified domain names associated with external IP address
        Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you answer some questions surrounding the attacker and details related to the external system. In addition, there are various sources--such as VirusTotal— that can provide some reputation information on the IP address or domain name, which can assist in determining whether the event is malicious. Finally, determining whether there are other events associated with the IP address may help connect data points or show other events that should be brought into scope.\nGathering data on the system of interest can sometimes help you quickly determine whether something suspicious is happening. Some of these items include finding out who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\nOften, a simple inspection of the process name and path can tell you if the system has been compromised. For example, if `svchost.exe` is found running from a location other than `C:\\Windows\\System32`, it is likely something malicious designed to hide in plain sight when cursorily reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, that could be indicative of activity initiated via a compromised website a user visited.\nIt can also be very helpful to examine various behaviors of the process of interest or the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might be worth further scrutiny. If a process is suspect, a review of the network connections made in and around the time of the event and/or whether the process spawned any child processes could be helpful, as well.\nIn the event a system is suspected of having been compromised via a malicious website, we suggest reviewing the browsing activity from that system around the time of the event. If categories are given for the URLs visited, that can help you zero in on possible malicious sites.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", + "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "4.0" +} diff --git a/stories/monitor_backups.json b/stories/monitor_backups.json index 7347e70aa5..f76bef7558 100644 --- a/stories/monitor_backups.json +++ b/stories/monitor_backups.json @@ -1,44 +1,44 @@ { - "category": [ - "Best Practices" - ], - "channel": "ESCU", - "creation_date": "2017-06-15", - "description": "Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints.", - "detections": [ - { - "detection_id": "a34aae96-ccf8-4aaa-952c-3ea21444444f", - "name": "Unsuccessful Netbackup backups", - "type": "splunk" - }, - { - "detection_id": "a34aae96-ccf8-4aef-952c-3ea214444440", - "name": "Extended Period Without Successful Netbackup Backups", - "type": "splunk" - } - ], - "id": "abe807c7-1eb6-4304-ac32-6e7aacdb891d", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-09-12", - "name": "Monitor Backup Solution", - "narrative": "Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/" - ], - "spec_version": 2, - "usecase": "Compliance", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Best Practices" + ], + "channel": "ESCU", + "creation_date": "2017-06-15", + "description": "Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints.", + "detections": [ + { + "detection_id": "a34aae96-ccf8-4aaa-952c-3ea21444444f", + "name": "Unsuccessful Netbackup backups", + "type": "splunk" + }, + { + "detection_id": "a34aae96-ccf8-4aef-952c-3ea214444440", + "name": "Extended Period Without Successful Netbackup Backups", + "type": "splunk" + } + ], + "id": "abe807c7-1eb6-4304-ac32-6e7aacdb891d", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-12", + "name": "Monitor Backup Solution", + "narrative": "Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/" + ], + "spec_version": 2, + "usecase": "Compliance", + "version": "1.0" +} diff --git a/stories/monitor_for_updates.json b/stories/monitor_for_updates.json index 8b5da564fe..31f094574a 100644 --- a/stories/monitor_for_updates.json +++ b/stories/monitor_for_updates.json @@ -1,39 +1,39 @@ { - "category": [ - "Best Practices" - ], - "channel": "ESCU", - "creation_date": "2017-08-15", - "description": "Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches.", - "detections": [ - { - "detection_id": "1a77c08c-2f56-409c-a2d3-7d64617edd4f", - "name": "No Windows Updates in a time frame", - "type": "splunk" - } - ], - "id": "9ef8d677-7b52-4213-a038-99cfc7acc2d8", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2017-09-15", - "name": "Monitor for Updates", - "narrative": "It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.

        Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.

        Microsoft releases updates for Windows systems on a monthly cadence. They should be installed as soon as possible after following internal testing and validation procedures. Patches and updates for other systems or applications are typically released as needed.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://learn.cisecurity.org/20-controls-download" - ], - "spec_version": 2, - "usecase": "Compliance", - "version": "1.0" + "category": [ + "Best Practices" + ], + "channel": "ESCU", + "creation_date": "2017-08-15", + "description": "Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches.", + "detections": [ + { + "detection_id": "1a77c08c-2f56-409c-a2d3-7d64617edd4f", + "name": "No Windows Updates in a time frame", + "type": "splunk" + } + ], + "id": "9ef8d677-7b52-4213-a038-99cfc7acc2d8", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2017-09-15", + "name": "Monitor for Updates", + "narrative": "It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\n\nSearches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\n\nMicrosoft releases updates for Windows systems on a monthly cadence. They should be installed as soon as possible after following internal testing and validation procedures. Patches and updates for other systems or applications are typically released as needed.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://learn.cisecurity.org/20-controls-download" + ], + "spec_version": 2, + "usecase": "Compliance", + "version": "1.0" } diff --git a/stories/mudcarp.json b/stories/mudcarp.json index 0259eb3d9d..42fd8a57ea 100644 --- a/stories/mudcarp.json +++ b/stories/mudcarp.json @@ -1,61 +1,61 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU channel", - "creation_date": "2018-07-24", - "description": "Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group.", - "detections": [ - { - "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", - "name": "First time seen command line argument", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", - "name": "Registry Keys Used For Persistence", - "type": "splunk" - }, - { - "detection_id": "ee18ed37-0802-4268-9435-b3b91aaa18db", - "name": "Malicious PowerShell Process - Connect To Internet With Hidden Window", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6a4264e7f", - "name": "Unusually Long Command Line", - "type": "splunk" - }, - { - "detection_id": "57edaefa-a73b-45e5-bbae-f39c1473f941", - "name": "Unusually Long Command Line - MLTK", - "type": "splunk" - } - ], - "id": "988C59C5-0A1C-45B6-A555-0C62276E327E", - "maintainers": [ - { - "company": "iDefense", - "email": "iDefense.IntelOps@accenture.com", - "name": "iDefense Cyber Espionage Team" - } - ], - "modification_date": "2018-07-24", - "name": "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", - "narrative": "This story was created as a joint effort between iDefense and Splunk.

        iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, \"Orz,\" which is associated with the threat actors known as MUDCARP (as well as \"temp.Periscope\" and \"Leviathan\"). The file is executed using Wscript.

        The MUDCARP techniques include the use of the compressed-folders module from Microsoft, zipfldr.dll, with RouteTheCall export to run the malicious process or command. After a successful reboot, the malware is made persistent by a manipulating [HKEY_CURRENT_USER\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Run]'help'='c:\\\\windows\\\\system32\\\\rundll32.exe c:\\\\windows\\\\system32\\\\zipfldr.dll,RouteTheCall c:\\\\programdata\\\\winapp.exe'. Though this technique is not exclusive to MUDCARP, it has been spotted in the group's arsenal of advanced techniques seen in the wild.

        This Analytic Story searches for evidence of tactics, techniques, and procedures (TTPs) that allow for the use of a endpoint detection-and-response (EDR) bypass technique to mask the true parent of a malicious process. It can also be set as a registry key for further sandbox evasion and to allow the malware to launch only after reboot.

        If behavioral searches included in this story yield positive hits, iDefense recommends conducting IOC searches for the following:

        • www.chemscalere[.]com
        • chemscalere[.]com
        • about.chemscalere[.]com
        • autoconfig.chemscalere[.]com
        • autodiscover.chemscalere[.]com
        • catalog.chemscalere[.]com
        • cpanel.chemscalere[.]com
        • db.chemscalere[.]com
        • ftp.chemscalere[.]com
        • mail.chemscalere[.]com
        • news.chemscalere[.]com
        • update.chemscalere[.]com
        • webmail.chemscalere[.]com
        • www.candlelightparty[.]org
        • candlelightparty[.]org
        • newapp.freshasianews[.]com
        In addition, iDefense also recommends that organizations review their environments for activity related to the following hashes:

        • cd195ee448a3657b5c2c2d13e9c7a2e2
        • b43ad826fe6928245d3c02b648296b43
        • 889a9b52566448231f112a5ce9b5dfaf
        • b8ec65dab97cdef3cd256cc4753f0c54
        • 04d83cd3813698de28cfbba326d7647c
        ", - "original_authors": [ - { - "company": "iDefense", - "email": "iDefense.IntelOps@accenture.com", - "name": "iDefense Cyber Espionage Team" - } - ], - "references": [ - "https://intelgraph.idefense.com/#/node/threat_group/view/29fbec10-8cc8-4662-8362-2c24c1eeb74c", - "https://intelgraph.idefense.com/#/node/intelligence_alert/view/62bb3669-9386-4264-b51a-59876cf50ffe", - "http://blog.amossys.fr/badflick-is-not-so-bad.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU channel", + "creation_date": "2018-07-24", + "description": "Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group.", + "detections": [ + { + "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", + "name": "First time seen command line argument", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", + "name": "Registry Keys Used For Persistence", + "type": "splunk" + }, + { + "detection_id": "ee18ed37-0802-4268-9435-b3b91aaa18db", + "name": "Malicious PowerShell Process - Connect To Internet With Hidden Window", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6a4264e7f", + "name": "Unusually Long Command Line", + "type": "splunk" + }, + { + "detection_id": "57edaefa-a73b-45e5-bbae-f39c1473f941", + "name": "Unusually Long Command Line - MLTK", + "type": "splunk" + } + ], + "id": "988C59C5-0A1C-45B6-A555-0C62276E327E", + "maintainers": [ + { + "company": "iDefense", + "email": "iDefense.IntelOps@accenture.com", + "name": "iDefense Cyber Espionage Team" + } + ], + "modification_date": "2018-07-24", + "name": "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", + "narrative": "This story was created as a joint effort between iDefense and Splunk.\n\niDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, \"Orz,\" which is associated with the threat actors known as MUDCARP (as well as \"temp.Periscope\" and \"Leviathan\"). The file is executed using Wscript.\n\nThe MUDCARP techniques include the use of the compressed-folders module from Microsoft, zipfldr.dll, with RouteTheCall export to run the malicious process or command. After a successful reboot, the malware is made persistent by a manipulating `[HKEY_CURRENT_USER\\SOFTWARE\\Microsoft\\Windows\\CurrentVersion\\Run]'help'='c:\\\\windows\\\\system32\\\\rundll32.exe c:\\\\windows\\\\system32\\\\zipfldr.dll,RouteTheCall c:\\\\programdata\\\\winapp.exe'`. Though this technique is not exclusive to MUDCARP, it has been spotted in the group's arsenal of advanced techniques seen in the wild.\n\nThis Analytic Story searches for evidence of tactics, techniques, and procedures (TTPs) that allow for the use of a endpoint detection-and-response (EDR) bypass technique to mask the true parent of a malicious process. It can also be set as a registry key for further sandbox evasion and to allow the malware to launch only after reboot.\n\nIf behavioral searches included in this story yield positive hits, iDefense recommends conducting IOC searches for the following:\n\n
        • www.chemscalere[.]com
        • chemscalere[.]com
        • about.chemscalere[.]com
        • autoconfig.chemscalere[.]com
        • autodiscover.chemscalere[.]com
        • catalog.chemscalere[.]com
        • cpanel.chemscalere[.]com
        • db.chemscalere[.]com
        • ftp.chemscalere[.]com
        • mail.chemscalere[.]com
        • news.chemscalere[.]com
        • update.chemscalere[.]com
        • webmail.chemscalere[.]com
        • www.candlelightparty[.]org
        • candlelightparty[.]org
        • newapp.freshasianews[.]com
        In addition, iDefense also recommends that organizations review their environments for activity related to the following hashes:\n\n
        • cd195ee448a3657b5c2c2d13e9c7a2e2
        • b43ad826fe6928245d3c02b648296b43
        • 889a9b52566448231f112a5ce9b5dfaf
        • b8ec65dab97cdef3cd256cc4753f0c54
        • 04d83cd3813698de28cfbba326d7647c
        ", + "original_authors": [ + { + "company": "iDefense", + "email": "iDefense.IntelOps@accenture.com", + "name": "iDefense Cyber Espionage Team" + } + ], + "references": [ + "https://intelgraph.idefense.com/#/node/threat_group/view/29fbec10-8cc8-4662-8362-2c24c1eeb74c", + "https://intelgraph.idefense.com/#/node/intelligence_alert/view/62bb3669-9386-4264-b51a-59876cf50ffe", + "http://blog.amossys.fr/badflick-is-not-so-bad.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/netsh_abuse.json b/stories/netsh_abuse.json index cdf920a523..3565d7c929 100644 --- a/stories/netsh_abuse.json +++ b/stories/netsh_abuse.json @@ -1,46 +1,46 @@ { - "category": [ - "Abuse" - ], - "channel": "ESCU", - "creation_date": "2017-01-04", - "description": "Detect activities and various techniques associated with the abuse of netsh.exe, which can disable local firewall settings or set up a remote connection to a host from an infected system.", - "detections": [ - { - "detection_id": "b89919ed-fe5f-492c-b139-95dbb162041e", - "name": "Processes created by netsh", - "type": "splunk" - }, - { - "detection_id": "b89919ed-fe5f-492c-b139-95dbb162040e", - "name": "Processes launching netsh", - "type": "splunk" - } - ], - "id": "2b1800dd-92f9-47ec-a981-fdf1351e5f65", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-01-05", - "name": "Netsh Abuse", - "narrative": "It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is netsh.exe,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. Netsh.exe can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.

        To get started, run the detection search to identify parent processes of netsh.exe.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://technet.microsoft.com/library/bb490939.aspx", - "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", - "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Abuse" + ], + "channel": "ESCU", + "creation_date": "2017-01-04", + "description": "Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system.", + "detections": [ + { + "detection_id": "b89919ed-fe5f-492c-b139-95dbb162041e", + "name": "Processes created by netsh", + "type": "splunk" + }, + { + "detection_id": "b89919ed-fe5f-492c-b139-95dbb162040e", + "name": "Processes launching netsh", + "type": "splunk" + } + ], + "id": "2b1800dd-92f9-47ec-a981-fdf1351e5f65", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-01-05", + "name": "Netsh Abuse", + "narrative": "It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\n\nTo get started, run the detection search to identify parent processes of `netsh.exe`.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://technet.microsoft.com/library/bb490939.aspx", + "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", + "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/non-secure_communications.json b/stories/non-secure_communications.json index fee4e354cc..63e59d5848 100644 --- a/stories/non-secure_communications.json +++ b/stories/non-secure_communications.json @@ -1,39 +1,39 @@ { - "category": [ - "Best Practices" - ], - "channel": "ESCU", - "creation_date": "2016-09-13", - "description": "Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted.", - "detections": [ - { - "detection_id": "6923cd64-17a0-453c-b945-81ac2d8c6db9", - "name": "Protocols passing authentication in cleartext", - "type": "splunk" - } - ], - "id": "826e6431-aeef-41b4-9fc0-6d0985d65a21", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-15", - "name": "Use of Cleartext Protocols", - "narrative": "Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.monkey.org/~dugsong/dsniff/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Best Practices" + ], + "channel": "ESCU", + "creation_date": "2016-09-13", + "description": "Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted.", + "detections": [ + { + "detection_id": "6923cd64-17a0-453c-b945-81ac2d8c6db9", + "name": "Protocols passing authentication in cleartext", + "type": "splunk" + } + ], + "id": "826e6431-aeef-41b4-9fc0-6d0985d65a21", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-15", + "name": "Use of Cleartext Protocols", + "narrative": "Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.monkey.org/~dugsong/dsniff/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/orangeworm.json b/stories/orangeworm.json index 1ee2eca54f..39a1f8415b 100644 --- a/stories/orangeworm.json +++ b/stories/orangeworm.json @@ -1,50 +1,50 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2018-06-14", - "description": "Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry.", - "detections": [ - { - "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", - "name": "First time seen command line argument", - "type": "splunk" - }, - { - "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", - "name": "Sc.exe Manipulating Windows Services", - "type": "splunk" - }, - { - "detection_id": "823136f2-d755-4b6d-ae04-372b486a5808", - "name": "First Time Seen Running Windows Service", - "type": "splunk" - } - ], - "id": "bb9f5ed2-916e-4364-bb6d-97c370efcf52", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-06-18", - "name": "Orangeworm Attack Group", - "narrative": "In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.

        Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.

        Although the group's motivation is unknown, its goal may be stealing patient information to sell on the black market. Another possible explanation is corporate espionage.

        Healthcare may be a promising target, because it is notoriously behind in technology, often using older operating systems and neglecting to patch computers. Even so, the group was able to evade detection for a full three years. Sources say that the malware spread quickly within the target networks, infecting computers used to control medical devices, such as MRI and X-ray machines.

        This Analytic Story is designed to help you detect and investigate suspicious activities that may be indicative of an Orangeworm attack. One detection search looks for command-line arguments. Another monitors for uses of sc.exe, a non-essential Windows file that can manipulate Windows services. One of the investigative searches helps you get more information on web hosts that you suspect have been compromised.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", - "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2018-06-14", + "description": "Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry.", + "detections": [ + { + "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", + "name": "First time seen command line argument", + "type": "splunk" + }, + { + "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", + "name": "Sc.exe Manipulating Windows Services", + "type": "splunk" + }, + { + "detection_id": "823136f2-d755-4b6d-ae04-372b486a5808", + "name": "First Time Seen Running Windows Service", + "type": "splunk" + } + ], + "id": "bb9f5ed2-916e-4364-bb6d-97c370efcf52", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-06-18", + "name": "Orangeworm Attack Group", + "narrative": "In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\n\nAwareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\n\nAlthough the group's motivation is unknown, its goal may be stealing patient information to sell on the black market. Another possible explanation is corporate espionage. \n\nHealthcare may be a promising target, because it is notoriously behind in technology, often using older operating systems and neglecting to patch computers. Even so, the group was able to evade detection for a full three years. Sources say that the malware spread quickly within the target networks, infecting computers used to control medical devices, such as MRI and X-ray machines.\n\nThis Analytic Story is designed to help you detect and investigate suspicious activities that may be indicative of an Orangeworm attack. One detection search looks for command-line arguments. Another monitors for uses of sc.exe, a non-essential Windows file that can manipulate Windows services. One of the investigative searches helps you get more information on web hosts that you suspect have been compromised.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", + "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "2.0" +} diff --git a/stories/phishing_payloads.json b/stories/phishing_payloads.json index 21d7d0dfbb..f567d0074f 100644 --- a/stories/phishing_payloads.json +++ b/stories/phishing_payloads.json @@ -1,44 +1,44 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2019-04-29", - "description": "Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack.", - "detections": [ - { - "detection_id": "a51bfe1a-94f0-4822-b1e4-16ae10145893", - "name": "Detect Oulook.exe writing a .zip file", - "type": "splunk" - }, - { - "detection_id": "5d814af1-1041-47b5-a9ac-d754e82e9a26", - "name": "Suspicious LNK file launching a process", - "type": "splunk" - } - ], - "id": "57226b40-94f3-4ce5-b101-a75f67759c27", - "maintainers": [ - { - "company": "Splunk", - "email": "research@splunk.com", - "name": "Splunk Research Team" - } - ], - "modification_date": "2019-04-29", - "name": "Phishing Payloads", - "narrative": "Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email.

        As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely \"automate\" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack.

        While any kind of file may contain a malicious payload, some are more likely to be perceived as benign (and thus more often escape notice) by the average victim—especially when the attacker sends an email that seems to be from one of their contacts. An example is Microsoft Office files. Most corporate users are familiar with documents with the following suffixes: .doc/.docx (MS Word), .xls/.xlsx (MS Excel), and .ppt/.pptx (MS PowerPoint), so they may click without a second thought, slashing a hole in their organizations' security.

        Following is a typical series of events, according to an [article by Trend Micro](https://blog.trendmicro.com/trendlabs-security-intelligence/rising-trend-attackers-using-lnk-files-download-malware/):
        1. Attacker sends a phishing email. Recipient downloads the attached file, which is typically a .docx or .zip file with an embedded .lnk file
        2. The .lnk file executes a PowerShell script
        3. Powershell executes a reverse shell, rendering the exploit successful
        As a side note, adversaries are likely to use a tool like Empire to craft and obfuscate payloads and their post-injection activities, such as [exfiltration, lateral movement, and persistence](https://github.com/EmpireProject/Empire).

        This Analytic Story focuses on detecting signs that a malicious payload has been injected into your environment. For example, one search detects outlook.exe writing a .zip file. Another looks for suspicious .lnk files launching processes.", - "original_authors": [ - { - "company": "Splunk", - "email": "research@splunk.com", - "name": "Splunk Research Team" - } - ], - "references": [ - "https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2019-04-29", + "description": "Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack.", + "detections": [ + { + "detection_id": "a51bfe1a-94f0-4822-b1e4-16ae10145893", + "name": "Detect Oulook.exe writing a .zip file", + "type": "splunk" + }, + { + "detection_id": "5d814af1-1041-47b5-a9ac-d754e82e9a26", + "name": "Suspicious LNK file launching a process", + "type": "splunk" + } + ], + "id": "57226b40-94f3-4ce5-b101-a75f67759c27", + "maintainers": [ + { + "company": "Splunk", + "email": "research@splunk.com", + "name": "Splunk Research Team" + } + ], + "modification_date": "2019-04-29", + "name": "Phishing Payloads", + "narrative": "Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \n\nAs most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely \"automate\" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \n\nWhile any kind of file may contain a malicious payload, some are more likely to be perceived as benign (and thus more often escape notice) by the average victim—especially when the attacker sends an email that seems to be from one of their contacts. An example is Microsoft Office files. Most corporate users are familiar with documents with the following suffixes: .doc/.docx (MS Word), .xls/.xlsx (MS Excel), and .ppt/.pptx (MS PowerPoint), so they may click without a second thought, slashing a hole in their organizations' security. \n\nFollowing is a typical series of events, according to an [article by Trend Micro](https://blog.trendmicro.com/trendlabs-security-intelligence/rising-trend-attackers-using-lnk-files-download-malware/):
        1. Attacker sends a phishing email. Recipient downloads the attached file, which is typically a .docx or .zip file with an embedded .lnk file
        2. The .lnk file executes a PowerShell script
        3. Powershell executes a reverse shell, rendering the exploit successful
        As a side note, adversaries are likely to use a tool like Empire to craft and obfuscate payloads and their post-injection activities, such as [exfiltration, lateral movement, and persistence](https://github.com/EmpireProject/Empire).\n\nThis Analytic Story focuses on detecting signs that a malicious payload has been injected into your environment. For example, one search detects outlook.exe writing a .zip file. Another looks for suspicious .lnk files launching processes.", + "original_authors": [ + { + "company": "Splunk", + "email": "research@splunk.com", + "name": "Splunk Research Team" + } + ], + "references": [ + "https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" } diff --git a/stories/prohibited_traffic_and_protocol_mismatch.json b/stories/prohibited_traffic_and_protocol_mismatch.json index 5b6a40c98b..07b3af2faa 100644 --- a/stories/prohibited_traffic_and_protocol_mismatch.json +++ b/stories/prohibited_traffic_and_protocol_mismatch.json @@ -1,54 +1,54 @@ { - "category": [ - "Best Practices" - ], - "channel": "ESCU", - "creation_date": "2017-04-18", - "description": "Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers.", - "detections": [ - { - "detection_id": "ea688274-9c06-4473-b951-e4cb7a5d7a45", - "name": "TOR Traffic", - "type": "splunk" - }, - { - "detection_id": "ce5a0962-849f-4720-a678-753fe6674479", - "name": "Prohibited Network Traffic Allowed", - "type": "splunk" - }, - { - "detection_id": "54dc1265-2f74-4b6d-b30d-49eb506a31b3", - "name": "Protocol or Port Mismatch", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", - "name": "Detect hosts connecting to dynamic domain providers", - "type": "splunk" - } - ], - "id": "6d13121c-90f3-446d-8ac3-27efbbc65218", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2017-09-11", - "name": "Prohibited Traffic Allowed or Protocol Mismatch", - "narrative": "A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Best Practices" + ], + "channel": "ESCU", + "creation_date": "2017-04-18", + "description": "Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers.", + "detections": [ + { + "detection_id": "ea688274-9c06-4473-b951-e4cb7a5d7a45", + "name": "TOR Traffic", + "type": "splunk" + }, + { + "detection_id": "ce5a0962-849f-4720-a678-753fe6674479", + "name": "Prohibited Network Traffic Allowed", + "type": "splunk" + }, + { + "detection_id": "54dc1265-2f74-4b6d-b30d-49eb506a31b3", + "name": "Protocol or Port Mismatch", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", + "name": "Detect hosts connecting to dynamic domain providers", + "type": "splunk" + } + ], + "id": "6d13121c-90f3-446d-8ac3-27efbbc65218", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2017-09-11", + "name": "Prohibited Traffic Allowed or Protocol Mismatch", + "narrative": "A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/ransomware.json b/stories/ransomware.json index 92c9e00216..0836778930 100644 --- a/stories/ransomware.json +++ b/stories/ransomware.json @@ -1,126 +1,126 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2017-07-24", - "description": "Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others.", - "detections": [ - { - "detection_id": "ad517544-aff9-4c96-bd99-d6eb43bfbb6a", - "name": "Windows Event Log Cleared", - "type": "splunk" - }, - { - "detection_id": "2827c0fd-e1be-4868-ae25-59d28e0f9d4f", - "name": "Suspicious wevtutil Usage", - "type": "splunk" - }, - { - "detection_id": "b6e0ff70-b122-4227-9368-4cf322ab43c3", - "name": "USN Journal Deletion", - "type": "splunk" - }, - { - "detection_id": "b89919ed-ee5f-492c-b139-95dbb162039e", - "name": "Deleting Shadow Copies", - "type": "splunk" - }, - { - "detection_id": "fdb0f805-74e4-4539-8c00-618927333aae", - "name": "Spike in File Writes", - "type": "splunk" - }, - { - "detection_id": "ce5a0962-849f-4720-a678-753fe6674479", - "name": "Prohibited Network Traffic Allowed", - "type": "splunk" - }, - { - "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b936378", - "name": "SMB Traffic Spike", - "type": "splunk" - }, - { - "detection_id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", - "name": "SMB Traffic Spike - MLTK", - "type": "splunk" - }, - { - "detection_id": "a9e5c5db-db11-43ca-86a8-c852d1b2c0ec", - "name": "Common Ransomware Extensions", - "type": "splunk" - }, - { - "detection_id": "ada0f478-84a8-4641-a3f1-d82362d6bd71", - "name": "Common Ransomware Notes", - "type": "splunk" - }, - { - "detection_id": "a34aae96-ccf8-4aef-952c-3ea21444444d", - "name": "System Processes Run From Unexpected Locations", - "type": "splunk" - }, - { - "detection_id": "d25d2c3d-d9d8-40ec-8fdf-e86fe155a3da", - "name": "Remote Process Instantiation via WMI", - "type": "splunk" - }, - { - "detection_id": "ea688274-9c06-4473-b951-e4cb7a5d7a45", - "name": "TOR Traffic", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", - "name": "Registry Keys Used For Persistence", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6a4264e7f", - "name": "Unusually Long Command Line", - "type": "splunk" - }, - { - "detection_id": "57edaefa-a73b-45e5-bbae-f39c1473f941", - "name": "Unusually Long Command Line - MLTK", - "type": "splunk" - }, - { - "detection_id": "1297fb80-f42a-4b4a-9c8b-78c066437cf6", - "name": "Scheduled tasks used in BadRabbit ransomware", - "type": "splunk" - }, - { - "detection_id": "1297fb80-f42a-4b4a-9c8a-88c066437cf6", - "name": "Schtasks used for forcing a reboot", - "type": "splunk" - } - ], - "id": "cf309d0d-d4aa-4fbb-963d-1e79febd3756", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-09-10", - "name": "Ransomware", - "narrative": "Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://www.symantec.com/connect/blogs/what-you-need-know-about-wannacry-ransomware", - "https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", - "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2017-07-24", + "description": "Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others.", + "detections": [ + { + "detection_id": "ad517544-aff9-4c96-bd99-d6eb43bfbb6a", + "name": "Windows Event Log Cleared", + "type": "splunk" + }, + { + "detection_id": "2827c0fd-e1be-4868-ae25-59d28e0f9d4f", + "name": "Suspicious wevtutil Usage", + "type": "splunk" + }, + { + "detection_id": "b6e0ff70-b122-4227-9368-4cf322ab43c3", + "name": "USN Journal Deletion", + "type": "splunk" + }, + { + "detection_id": "b89919ed-ee5f-492c-b139-95dbb162039e", + "name": "Deleting Shadow Copies", + "type": "splunk" + }, + { + "detection_id": "fdb0f805-74e4-4539-8c00-618927333aae", + "name": "Spike in File Writes", + "type": "splunk" + }, + { + "detection_id": "ce5a0962-849f-4720-a678-753fe6674479", + "name": "Prohibited Network Traffic Allowed", + "type": "splunk" + }, + { + "detection_id": "7f5fb3e1-4209-4914-90db-0ec21b936378", + "name": "SMB Traffic Spike", + "type": "splunk" + }, + { + "detection_id": "d25773ba-9ad8-48d1-858e-07ad0bbeb828", + "name": "SMB Traffic Spike - MLTK", + "type": "splunk" + }, + { + "detection_id": "a9e5c5db-db11-43ca-86a8-c852d1b2c0ec", + "name": "Common Ransomware Extensions", + "type": "splunk" + }, + { + "detection_id": "ada0f478-84a8-4641-a3f1-d82362d6bd71", + "name": "Common Ransomware Notes", + "type": "splunk" + }, + { + "detection_id": "a34aae96-ccf8-4aef-952c-3ea21444444d", + "name": "System Processes Run From Unexpected Locations", + "type": "splunk" + }, + { + "detection_id": "d25d2c3d-d9d8-40ec-8fdf-e86fe155a3da", + "name": "Remote Process Instantiation via WMI", + "type": "splunk" + }, + { + "detection_id": "ea688274-9c06-4473-b951-e4cb7a5d7a45", + "name": "TOR Traffic", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", + "name": "Registry Keys Used For Persistence", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6a4264e7f", + "name": "Unusually Long Command Line", + "type": "splunk" + }, + { + "detection_id": "57edaefa-a73b-45e5-bbae-f39c1473f941", + "name": "Unusually Long Command Line - MLTK", + "type": "splunk" + }, + { + "detection_id": "1297fb80-f42a-4b4a-9c8b-78c066437cf6", + "name": "Scheduled tasks used in BadRabbit ransomware", + "type": "splunk" + }, + { + "detection_id": "1297fb80-f42a-4b4a-9c8a-88c066437cf6", + "name": "Schtasks used for forcing a reboot", + "type": "splunk" + } + ], + "id": "cf309d0d-d4aa-4fbb-963d-1e79febd3756", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-09-10", + "name": "Ransomware", + "narrative": "Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://www.symantec.com/connect/blogs/what-you-need-know-about-wannacry-ransomware", + "https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", + "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/routers_and_infrastructure.json b/stories/routers_and_infrastructure.json index 5539e68ff8..ebc6cc2aa4 100644 --- a/stories/routers_and_infrastructure.json +++ b/stories/routers_and_infrastructure.json @@ -1,40 +1,40 @@ { - "category": [ - "Best Practices" - ], - "channel": "ESCU", - "creation_date": "2017-06-01", - "description": "Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers.", - "detections": [ - { - "detection_id": "104658f4-afdc-499e-9719-17243rr826f1", - "name": "Detect New Login Attempts to Routers", - "type": "splunk" - } - ], - "id": "91c676cf-0b23-438d-abee-f6335e177e77", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-12", - "name": "Router & Infrastructure Security", - "narrative": "Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.

        This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", - "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Best Practices" + ], + "channel": "ESCU", + "creation_date": "2017-06-01", + "description": "Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers.", + "detections": [ + { + "detection_id": "104658f4-afdc-499e-9719-17243rr826f1", + "name": "Detect New Login Attempts to Routers", + "type": "splunk" + } + ], + "id": "91c676cf-0b23-438d-abee-f6335e177e77", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-12", + "name": "Router & Infrastructure Security", + "narrative": "Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\n\nThis Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", + "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/samsam.json b/stories/samsam.json index ea755ab61a..55aa4e049c 100644 --- a/stories/samsam.json +++ b/stories/samsam.json @@ -1,101 +1,101 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2018-12-13", - "description": "Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more.", - "detections": [ - { - "detection_id": "b89919ed-ee5f-492c-b139-95dbb162039e", - "name": "Deleting Shadow Copies", - "type": "splunk" - }, - { - "detection_id": "fdb0f805-74e4-4539-8c00-618927333aae", - "name": "Spike in File Writes", - "type": "splunk" - }, - { - "detection_id": "a9e5c5db-db11-43ca-86a8-c852d1b2c0ec", - "name": "Common Ransomware Extensions", - "type": "splunk" - }, - { - "detection_id": "ada0f478-84a8-4641-a3f1-d82362d6bd71", - "name": "Common Ransomware Notes", - "type": "splunk" - }, - { - "detection_id": "a51bfe1a-94f0-48cc-b4e4-b6ae50145893", - "name": "Prohibited Software On Endpoint", - "type": "splunk" - }, - { - "detection_id": "b89919ed-fe5f-492c-b139-151xb162040e", - "name": "Detect PsExec With accepteula Flag", - "type": "splunk" - }, - { - "detection_id": "272b8407-842d-4b3d-bead-a704584003d3", - "name": "Remote Desktop Network Traffic", - "type": "splunk" - }, - { - "detection_id": "104658f4-afdc-499e-9719-17243f982681", - "name": "Detect attackers scanning for vulnerable JBoss servers", - "type": "splunk" - }, - { - "detection_id": "c8bff7a4-11ea-4416-a27d-c5bca472913d", - "name": "Detect malicious requests to exploit JBoss servers", - "type": "splunk" - }, - { - "detection_id": "a98727cc-286b-4ff2-b898-41df64695923", - "name": "Remote Desktop Network Bruteforce", - "type": "splunk" - }, - { - "detection_id": "02c6cfc2-ae66-4735-bfc7-6291da834cbf", - "name": "File with Samsam Extension", - "type": "splunk" - }, - { - "detection_id": "69c12d59-d951-431e-ab77-ec426b8d65e6", - "name": "Samsam Test File Write", - "type": "splunk" - }, - { - "detection_id": "503d17cb-9eab-4cf8-a20e-01d5c6987ae3", - "name": "Batch File Write to System32", - "type": "splunk" - } - ], - "id": "c4b89506-fbcf-4cb7-bfd6-527e54789604", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-12-13", - "name": "SamSam Ransomware", - "narrative": "The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.

        Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a \"spray-and-pray\" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.

        SamSam attacks are different beasts. They have become progressively more targeted and skillful than typical ransomware attacks. First, malicious actors break into a victim's network, surveil it, then run the malware manually. The attacks are tailored to cause maximum damage and the threat actors usually demand amounts in the tens of thousands of dollars.

        In a typical attack on one large healthcare organization in 2018, the company ended up paying a ransom of four Bitcoins, then worth $56,707. Reports showed that access to the company's files was restored within two hours of paying the sum.

        According to Sophos, SamSam previously leveraged RDP to gain access to targeted networks via brute force. SamSam is not spread automatically, like other malware. It requires skill because it forces the attacker to adapt their tactics to the individual environment. Next, the actors escalate their privileges to admin level. They scan the networks for worthy targets, using conventional tools, such as PsExec or PaExec, to deploy/execute, quickly encrypting files.

        This Analytic Story includes searches designed to help detect and investigate signs of the SamSam ransomware, such as the creation of fileswrites to system32, writes with tell-tale extensions, batch files written to system32, and evidence of brute-force attacks via RDP.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", - "https://www.sophos.com/en-us/medialibrary/PDFs/technical-papers/SamSam-ransomware-chooses-Its-targets-carefully-wpna.pdf", - "https://www.sophos.com/en-us/medialibrary/PDFs/technical-papers/SamSam-The-Almost-Six-Million-Dollar-Ransomware.pdf?cmp=26061" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2018-12-13", + "description": "Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more.", + "detections": [ + { + "detection_id": "b89919ed-ee5f-492c-b139-95dbb162039e", + "name": "Deleting Shadow Copies", + "type": "splunk" + }, + { + "detection_id": "fdb0f805-74e4-4539-8c00-618927333aae", + "name": "Spike in File Writes", + "type": "splunk" + }, + { + "detection_id": "a9e5c5db-db11-43ca-86a8-c852d1b2c0ec", + "name": "Common Ransomware Extensions", + "type": "splunk" + }, + { + "detection_id": "ada0f478-84a8-4641-a3f1-d82362d6bd71", + "name": "Common Ransomware Notes", + "type": "splunk" + }, + { + "detection_id": "a51bfe1a-94f0-48cc-b4e4-b6ae50145893", + "name": "Prohibited Software On Endpoint", + "type": "splunk" + }, + { + "detection_id": "b89919ed-fe5f-492c-b139-151xb162040e", + "name": "Detect PsExec With accepteula Flag", + "type": "splunk" + }, + { + "detection_id": "272b8407-842d-4b3d-bead-a704584003d3", + "name": "Remote Desktop Network Traffic", + "type": "splunk" + }, + { + "detection_id": "104658f4-afdc-499e-9719-17243f982681", + "name": "Detect attackers scanning for vulnerable JBoss servers", + "type": "splunk" + }, + { + "detection_id": "c8bff7a4-11ea-4416-a27d-c5bca472913d", + "name": "Detect malicious requests to exploit JBoss servers", + "type": "splunk" + }, + { + "detection_id": "a98727cc-286b-4ff2-b898-41df64695923", + "name": "Remote Desktop Network Bruteforce", + "type": "splunk" + }, + { + "detection_id": "02c6cfc2-ae66-4735-bfc7-6291da834cbf", + "name": "File with Samsam Extension", + "type": "splunk" + }, + { + "detection_id": "69c12d59-d951-431e-ab77-ec426b8d65e6", + "name": "Samsam Test File Write", + "type": "splunk" + }, + { + "detection_id": "503d17cb-9eab-4cf8-a20e-01d5c6987ae3", + "name": "Batch File Write to System32", + "type": "splunk" + } + ], + "id": "c4b89506-fbcf-4cb7-bfd6-527e54789604", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-12-13", + "name": "SamSam Ransomware", + "narrative": "The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\n\nAlthough categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a \"spray-and-pray\" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\n\nSamSam attacks are different beasts. They have become progressively more targeted and skillful than typical ransomware attacks. First, malicious actors break into a victim's network, surveil it, then run the malware manually. The attacks are tailored to cause maximum damage and the threat actors usually demand amounts in the tens of thousands of dollars.\n\nIn a typical attack on one large healthcare organization in 2018, the company ended up paying a ransom of four Bitcoins, then worth $56,707. Reports showed that access to the company's files was restored within two hours of paying the sum.\n\nAccording to Sophos, SamSam previously leveraged RDP to gain access to targeted networks via brute force. SamSam is not spread automatically, like other malware. It requires skill because it forces the attacker to adapt their tactics to the individual environment. Next, the actors escalate their privileges to admin level. They scan the networks for worthy targets, using conventional tools, such as PsExec or PaExec, to deploy/execute, quickly encrypting files.\n\nThis Analytic Story includes searches designed to help detect and investigate signs of the SamSam ransomware, such as the creation of fileswrites to system32, writes with tell-tale extensions, batch files written to system32, and evidence of brute-force attacks via RDP.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", + "https://www.sophos.com/en-us/medialibrary/PDFs/technical-papers/SamSam-ransomware-chooses-Its-targets-carefully-wpna.pdf", + "https://www.sophos.com/en-us/medialibrary/PDFs/technical-papers/SamSam-The-Almost-Six-Million-Dollar-Ransomware.pdf?cmp=26061" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/service_abuse.json b/stories/service_abuse.json index d28e8554f6..e3a862a720 100644 --- a/stories/service_abuse.json +++ b/stories/service_abuse.json @@ -1,50 +1,50 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2017-11-02", - "description": "Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner.", - "detections": [ - { - "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", - "name": "Sc.exe Manipulating Windows Services", - "type": "splunk" - }, - { - "detection_id": "8470d755-0c13-45b3-bd63-387a373c10cf", - "name": "Reg.exe Manipulating Windows Services Registry Keys", - "type": "splunk" - }, - { - "detection_id": "823136f2-d755-4b6d-ae04-372b486a5808", - "name": "First Time Seen Running Windows Service", - "type": "splunk" - } - ], - "id": "6dbd810e-f66d-414b-8dfc-e46de55cbfe2", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2017-11-02", - "name": "Windows Service Abuse", - "narrative": "The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://attack.mitre.org/wiki/Technique/T1050", - "https://attack.mitre.org/wiki/Technique/T1031" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "3.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2017-11-02", + "description": "Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner.", + "detections": [ + { + "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", + "name": "Sc.exe Manipulating Windows Services", + "type": "splunk" + }, + { + "detection_id": "8470d755-0c13-45b3-bd63-387a373c10cf", + "name": "Reg.exe Manipulating Windows Services Registry Keys", + "type": "splunk" + }, + { + "detection_id": "823136f2-d755-4b6d-ae04-372b486a5808", + "name": "First Time Seen Running Windows Service", + "type": "splunk" + } + ], + "id": "6dbd810e-f66d-414b-8dfc-e46de55cbfe2", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2017-11-02", + "name": "Windows Service Abuse", + "narrative": "The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://attack.mitre.org/wiki/Technique/T1050", + "https://attack.mitre.org/wiki/Technique/T1031" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "3.0" +} diff --git a/stories/spectre_meltdown.json b/stories/spectre_meltdown.json index 315f52fb11..6360626eb2 100644 --- a/stories/spectre_meltdown.json +++ b/stories/spectre_meltdown.json @@ -1,39 +1,39 @@ { - "category": [ - "Vulnerability" - ], - "channel": "ESCU", - "creation_date": "2018-01-08", - "description": "Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story.", - "detections": [ - { - "detection_id": "354be8e0-32cd-4da0-8c47-796de13b60ea", - "name": "Spectre and Meltdown Vulnerable Systems", - "type": "splunk" - } - ], - "id": "6d3306f6-bb2b-4219-8609-8efad64032f2", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-01-08", - "name": "Spectre And Meltdown Vulnerabilities", - "narrative": "Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://meltdownattack.com/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Vulnerability" + ], + "channel": "ESCU", + "creation_date": "2018-01-08", + "description": "Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story.", + "detections": [ + { + "detection_id": "354be8e0-32cd-4da0-8c47-796de13b60ea", + "name": "Spectre and Meltdown Vulnerable Systems", + "type": "splunk" + } + ], + "id": "6d3306f6-bb2b-4219-8609-8efad64032f2", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-01-08", + "name": "Spectre And Meltdown Vulnerabilities", + "narrative": "Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://meltdownattack.com/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/splunk_information_disclosure.json b/stories/splunk_information_disclosure.json index 12a61e53d1..cfff8792f5 100644 --- a/stories/splunk_information_disclosure.json +++ b/stories/splunk_information_disclosure.json @@ -1,41 +1,41 @@ { - "category": [ - "Vulnerability" - ], - "channel": "ESCU", - "creation_date": "2018-06-14", - "description": "Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users.", - "detections": [ - { - "detection_id": "f6a26b7b-7e80-4963-a9a8-d836e7534ebd", - "name": "Splunk Enterprise Information Disclosure", - "type": "splunk" - } - ], - "id": "1fc34cbc-34e9-43ba-87ab-6811c9e95400", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2018-06-14", - "name": "Splunk Enterprise Vulnerability CVE-2018-11409", - "narrative": "Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.

        Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.

        Read more in Splunk's official response: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings.

        A detection search within this Analytic Story looks for vulnerabilities described in CVE-2018-11409: Information Exposure (https://nvd.nist.gov/vuln/detail/CVE-2018-11409). If it turns up activities that may be specific, you can use the included investigative searches to return information regarding web activity and network traffic by src_ip.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://nvd.nist.gov/vuln/detail/CVE-2018-11409", - "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", - "https://www.exploit-db.com/exploits/44865/" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Vulnerability" + ], + "channel": "ESCU", + "creation_date": "2018-06-14", + "description": "Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users.", + "detections": [ + { + "detection_id": "f6a26b7b-7e80-4963-a9a8-d836e7534ebd", + "name": "Splunk Enterprise Information Disclosure", + "type": "splunk" + } + ], + "id": "1fc34cbc-34e9-43ba-87ab-6811c9e95400", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2018-06-14", + "name": "Splunk Enterprise Vulnerability CVE-2018-11409", + "narrative": "Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\n\nSplunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\n\nRead more in Splunk's official response: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings.\n\nA detection search within this Analytic Story looks for vulnerabilities described in CVE-2018-11409: Information Exposure (https://nvd.nist.gov/vuln/detail/CVE-2018-11409). If it turns up activities that may be specific, you can use the included investigative searches to return information regarding web activity and network traffic by src_ip.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://nvd.nist.gov/vuln/detail/CVE-2018-11409", + "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", + "https://www.exploit-db.com/exploits/44865/" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/splunk_vulnerabilities.json b/stories/splunk_vulnerabilities.json index 47799f8516..b23431114d 100644 --- a/stories/splunk_vulnerabilities.json +++ b/stories/splunk_vulnerabilities.json @@ -1,40 +1,40 @@ { - "category": [ - "Vulnerability" - ], - "channel": "ESCU", - "creation_date": "2016-09-13", - "description": "Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains.", - "detections": [ - { - "detection_id": "d199fb99-2312-451a-9daa-e5efa6ed76a7", - "name": "Open Redirect in Splunk Web", - "type": "splunk" - } - ], - "id": "4e692b96-de2d-4bd1-9105-37e2368a8db1", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-19", - "name": "Splunk Enterprise Vulnerability", - "narrative": "This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:

        • Splunk Enterprise 6.4.x, prior to 6.4.3
        • Splunk Enterprise 6.3.x, prior to 6.3.6
        • Splunk Enterprise 6.2.x, prior to 6.2.10
        • Splunk Enterprise 6.1.x, prior to 6.1.11
        • Splunk Enterprise 6.0.x, prior to 6.0.12
        • Splunk Enterprise 5.0.x, prior to 5.0.16
        • Splunk Light, prior to 6.4.3
        CVE-2016-4859 allows attackers to redirect users to arbitrary web sites and conduct phishing attacks via unspecified vectors. (Credit: Noriaki Iwasaki, Cyber Defense Institute, Inc.).

        It is important to ensure that your Splunk deployment is being kept up to date and is properly configured. This detection search allows analysts to monitor internal logs to ensure users are properly authenticated and cannot be redirected to any malicious third-party websites.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "http://www.splunk.com/view/SP-CAAAPQ6#announce", - "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Vulnerability" + ], + "channel": "ESCU", + "creation_date": "2016-09-13", + "description": "Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains.", + "detections": [ + { + "detection_id": "d199fb99-2312-451a-9daa-e5efa6ed76a7", + "name": "Open Redirect in Splunk Web", + "type": "splunk" + } + ], + "id": "4e692b96-de2d-4bd1-9105-37e2368a8db1", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-19", + "name": "Splunk Enterprise Vulnerability", + "narrative": "This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\n\n
        • Splunk Enterprise 6.4.x, prior to 6.4.3
        • Splunk Enterprise 6.3.x, prior to 6.3.6
        • Splunk Enterprise 6.2.x, prior to 6.2.10
        • Splunk Enterprise 6.1.x, prior to 6.1.11
        • Splunk Enterprise 6.0.x, prior to 6.0.12
        • Splunk Enterprise 5.0.x, prior to 5.0.16
        • Splunk Light, prior to 6.4.3
        CVE-2016-4859 allows attackers to redirect users to arbitrary web sites and conduct phishing attacks via unspecified vectors. (Credit: Noriaki Iwasaki, Cyber Defense Institute, Inc.).\n\nIt is important to ensure that your Splunk deployment is being kept up to date and is properly configured. This detection search allows analysts to monitor internal logs to ensure users are properly authenticated and cannot be redirected to any malicious third-party websites.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "http://www.splunk.com/view/SP-CAAAPQ6#announce", + "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "1.0" +} diff --git a/stories/sql_injection.json b/stories/sql_injection.json index 3145079c7d..fe8dbb6a70 100644 --- a/stories/sql_injection.json +++ b/stories/sql_injection.json @@ -1,41 +1,41 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2016-09-13", - "description": "Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters.", - "detections": [ - { - "detection_id": "e0aad4cf-0790-423b-8328-7564d0d938f9", - "name": "SQL Injection with Long URLs", - "type": "splunk" - } - ], - "id": "4f6632f5-449c-4686-80df-57625f59bab3", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-09-19", - "name": "SQL Injection", - "narrative": "It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.

        This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.owasp.org/index.php/SQL_Injection", - "https://www.owasp.org/index.php/Blind_SQL_Injection", - "https://www.incapsula.com/web-application-security/sql-injection.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2016-09-13", + "description": "Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters.", + "detections": [ + { + "detection_id": "e0aad4cf-0790-423b-8328-7564d0d938f9", + "name": "SQL Injection with Long URLs", + "type": "splunk" + } + ], + "id": "4f6632f5-449c-4686-80df-57625f59bab3", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-09-19", + "name": "SQL Injection", + "narrative": "It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\n\nThis Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.owasp.org/index.php/SQL_Injection", + "https://www.owasp.org/index.php/Blind_SQL_Injection", + "https://www.incapsula.com/web-application-security/sql-injection.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/suspicious_cmd_line_executions.json b/stories/suspicious_cmd_line_executions.json index 1cb91b59e5..4c97a3cb68 100644 --- a/stories/suspicious_cmd_line_executions.json +++ b/stories/suspicious_cmd_line_executions.json @@ -1,66 +1,66 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2017-10-09", - "description": "Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems.", - "detections": [ - { - "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", - "name": "First time seen command line argument", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6a4264e7f", - "name": "Unusually Long Command Line", - "type": "splunk" - }, - { - "detection_id": "57edaefa-a73b-45e5-bbae-f39c1473f941", - "name": "Unusually Long Command Line - MLTK", - "type": "splunk" - }, - { - "detection_id": "dcfd6b40-42f9-469d-a433-2e53f7486664", - "name": "Detect Prohibited Applications Spawning cmd.exe", - "type": "splunk" - }, - { - "detection_id": "b89919ed-fe5f-492c-b139-95dbb162039e", - "name": "Detect Use of cmd.exe to Launch Script Interpreters", - "type": "splunk" - }, - { - "detection_id": "a34aae96-ccf8-4aef-952c-3ea21444444d", - "name": "System Processes Run From Unexpected Locations", - "type": "splunk" - } - ], - "id": "f4368ddf-d59f-4192-84f6-778ac5a3ffc7", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2017-10-23", - "name": "Suspicious Command-Line Executions", - "narrative": "The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://attack.mitre.org/wiki/Technique/T1059", - "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", - "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2017-10-09", + "description": "Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems.", + "detections": [ + { + "detection_id": "9be56c82-b1cc-4318-87eb-q138afaaqa39", + "name": "First time seen command line argument", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6a4264e7f", + "name": "Unusually Long Command Line", + "type": "splunk" + }, + { + "detection_id": "57edaefa-a73b-45e5-bbae-f39c1473f941", + "name": "Unusually Long Command Line - MLTK", + "type": "splunk" + }, + { + "detection_id": "dcfd6b40-42f9-469d-a433-2e53f7486664", + "name": "Detect Prohibited Applications Spawning cmd.exe", + "type": "splunk" + }, + { + "detection_id": "b89919ed-fe5f-492c-b139-95dbb162039e", + "name": "Detect Use of cmd.exe to Launch Script Interpreters", + "type": "splunk" + }, + { + "detection_id": "a34aae96-ccf8-4aef-952c-3ea21444444d", + "name": "System Processes Run From Unexpected Locations", + "type": "splunk" + } + ], + "id": "f4368ddf-d59f-4192-84f6-778ac5a3ffc7", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2017-10-23", + "name": "Suspicious Command-Line Executions", + "narrative": "The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://attack.mitre.org/wiki/Technique/T1059", + "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", + "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "2.0" +} diff --git a/stories/suspicious_dns_traffic.json b/stories/suspicious_dns_traffic.json index 7f4f3b471f..657b44e66d 100644 --- a/stories/suspicious_dns_traffic.json +++ b/stories/suspicious_dns_traffic.json @@ -1,76 +1,76 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2016-09-13", - "description": "Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses.", - "detections": [ - { - "detection_id": "104658f4-afdc-499e-9719-17243f9826f1", - "name": "Excessive DNS Failures", - "type": "splunk" - }, - { - "detection_id": "74ec6f18-604b-4202-a567-86b2066be3ce", - "name": "Clients Connecting to Multiple DNS Servers", - "type": "splunk" - }, - { - "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f5", - "name": "DNS Query Length With High Standard Deviation", - "type": "splunk" - }, - { - "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", - "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", - "type": "splunk" - }, - { - "detection_id": "05437c07-62f5-452e-afdc-04dd44815bb9", - "name": "Detect Long DNS TXT Record Response", - "type": "splunk" - }, - { - "detection_id": "104658f4-afdc-499f-9719-17a43f9826f4", - "name": "Detection of DNS Tunnels", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", - "name": "Detect hosts connecting to dynamic domain providers", - "type": "splunk" - }, - { - "detection_id": "85fbcfe8-9718-4911-adf6-7000d077a3a9", - "name": "DNS Query Length Outliers - MLTK", - "type": "splunk" - } - ], - "id": "3c3835c0-255d-4f9e-ab84-e29ec9ec9b56", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2017-09-18", - "name": "Suspicious DNS Traffic", - "narrative": "Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", - "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", - "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2016-09-13", + "description": "Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses.", + "detections": [ + { + "detection_id": "104658f4-afdc-499e-9719-17243f9826f1", + "name": "Excessive DNS Failures", + "type": "splunk" + }, + { + "detection_id": "74ec6f18-604b-4202-a567-86b2066be3ce", + "name": "Clients Connecting to Multiple DNS Servers", + "type": "splunk" + }, + { + "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f5", + "name": "DNS Query Length With High Standard Deviation", + "type": "splunk" + }, + { + "detection_id": "1a67f15a-f4ff-4170-84e9-08cf6f75d6f6", + "name": "DNS Query Requests Resolved by Unauthorized DNS Servers", + "type": "splunk" + }, + { + "detection_id": "05437c07-62f5-452e-afdc-04dd44815bb9", + "name": "Detect Long DNS TXT Record Response", + "type": "splunk" + }, + { + "detection_id": "104658f4-afdc-499f-9719-17a43f9826f4", + "name": "Detection of DNS Tunnels", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5464g9f", + "name": "Detect hosts connecting to dynamic domain providers", + "type": "splunk" + }, + { + "detection_id": "85fbcfe8-9718-4911-adf6-7000d077a3a9", + "name": "DNS Query Length Outliers - MLTK", + "type": "splunk" + } + ], + "id": "3c3835c0-255d-4f9e-ab84-e29ec9ec9b56", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2017-09-18", + "name": "Suspicious DNS Traffic", + "narrative": "Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", + "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", + "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/suspicious_emails.json b/stories/suspicious_emails.json index a7e6bbf6ee..78894521ff 100644 --- a/stories/suspicious_emails.json +++ b/stories/suspicious_emails.json @@ -32,7 +32,7 @@ ], "modification_date": "2017-09-19", "name": "Suspicious Emails", - "narrative": "It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.

        Once a phishing message has been detected, the next steps are to answer the following questions:
        • Which users have received this or a similar message in the past?
        • When did the targeted campaign begin?
        • Have any users interacted with the content of the messages (by downloading an attachment or clicking on a malicious URL)?
        This Analytic Story provides detection searches to identify suspicious emails, as well as contextual and investigative searches to help answer some of these questions.", + "narrative": "It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\n\nOnce a phishing message has been detected, the next steps are to answer the following questions:
        • Which users have received this or a similar message in the past?
        • When did the targeted campaign begin?
        • Have any users interacted with the content of the messages (by downloading an attachment or clicking on a malicious URL)?
        This Analytic Story provides detection searches to identify suspicious emails, as well as contextual and investigative searches to help answer some of these questions.", "original_authors": [ { "company": "Splunk", diff --git a/stories/suspicious_event_log_activity.json b/stories/suspicious_event_log_activity.json index 073201439f..60bfe08ba8 100644 --- a/stories/suspicious_event_log_activity.json +++ b/stories/suspicious_event_log_activity.json @@ -1,56 +1,56 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2017-02-17", - "description": "Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense.", - "detections": [ - { - "detection_id": "b89919ed-ee5f-492c-b139-95dbb162039e", - "name": "Deleting Shadow Copies", - "type": "splunk" - }, - { - "detection_id": "ad517544-aff9-4c96-bd99-d6eb43bfbb6a", - "name": "Windows Event Log Cleared", - "type": "splunk" - }, - { - "detection_id": "2827c0fd-e1be-4868-ae25-59d28e0f9d4f", - "name": "Suspicious wevtutil Usage", - "type": "splunk" - }, - { - "detection_id": "b6e0ff70-b122-4227-9368-4cf322ab43c3", - "name": "USN Journal Deletion", - "type": "splunk" - } - ], - "id": "b6db2c60-a281-48b4-95f1-2cd99ed56835", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2017-09-12", - "name": "Windows Log Manipulation", - "narrative": "Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.

        The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified).", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", - "https://zeltser.com/security-incident-log-review-checklist/", - "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html" - ], - "spec_version": 2, - "usecase": "Security Monitoring", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2017-02-17", + "description": "Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense.", + "detections": [ + { + "detection_id": "b89919ed-ee5f-492c-b139-95dbb162039e", + "name": "Deleting Shadow Copies", + "type": "splunk" + }, + { + "detection_id": "ad517544-aff9-4c96-bd99-d6eb43bfbb6a", + "name": "Windows Event Log Cleared", + "type": "splunk" + }, + { + "detection_id": "2827c0fd-e1be-4868-ae25-59d28e0f9d4f", + "name": "Suspicious wevtutil Usage", + "type": "splunk" + }, + { + "detection_id": "b6e0ff70-b122-4227-9368-4cf322ab43c3", + "name": "USN Journal Deletion", + "type": "splunk" + } + ], + "id": "b6db2c60-a281-48b4-95f1-2cd99ed56835", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2017-09-12", + "name": "Windows Log Manipulation", + "narrative": "Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\n\nThe Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified).", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", + "https://zeltser.com/security-incident-log-review-checklist/", + "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html" + ], + "spec_version": 2, + "usecase": "Security Monitoring", + "version": "2.0" +} diff --git a/stories/suspicious_mshta_activities.json b/stories/suspicious_mshta_activities.json index 09f94d043b..7e7a9c46bd 100644 --- a/stories/suspicious_mshta_activities.json +++ b/stories/suspicious_mshta_activities.json @@ -1,51 +1,51 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2018-08-07", - "description": "Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code.", - "detections": [ - { - "detection_id": "b89919ed-fe5f-492c-b139-95dqb161039e", - "name": "Detect mshta.exe running scripts in command-line arguments", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", - "name": "Registry Keys Used For Persistence", - "type": "splunk" - }, - { - "detection_id": "dcfd6b40-42f9-469d-a433-2e53f7486664", - "name": "Detect Prohibited Applications Spawning cmd.exe", - "type": "splunk" - } - ], - "id": "2b1800dd-92f9-47dd-a981-fdf13w1q5d55", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-08-07", - "name": "Suspicious MSHTA Activity", - "narrative": "One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.

        One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).

        The searches in this story help you detect and investigate suspicious activity that may indicate that an attacker is leveraging mshta.exe to execute malicious code.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://redcanary.com/blog/windows-registry-attacks-threat-detection/", - "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", - "https://attack.mitre.org/wiki/Technique/T1170" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2018-08-07", + "description": "Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code.", + "detections": [ + { + "detection_id": "b89919ed-fe5f-492c-b139-95dqb161039e", + "name": "Detect mshta.exe running scripts in command-line arguments", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", + "name": "Registry Keys Used For Persistence", + "type": "splunk" + }, + { + "detection_id": "dcfd6b40-42f9-469d-a433-2e53f7486664", + "name": "Detect Prohibited Applications Spawning cmd.exe", + "type": "splunk" + } + ], + "id": "2b1800dd-92f9-47dd-a981-fdf13w1q5d55", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-08-07", + "name": "Suspicious MSHTA Activity", + "narrative": "One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\n\nOne example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\n\nThe searches in this story help you detect and investigate suspicious activity that may indicate that an attacker is leveraging mshta.exe to execute malicious code.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://redcanary.com/blog/windows-registry-attacks-threat-detection/", + "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", + "https://attack.mitre.org/wiki/Technique/T1170" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/suspicious_windows_registry_activities.json b/stories/suspicious_windows_registry_activities.json index 215a83ca1f..f3b0e11b62 100644 --- a/stories/suspicious_windows_registry_activities.json +++ b/stories/suspicious_windows_registry_activities.json @@ -1,75 +1,75 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2018-05-31", - "description": "Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system.", - "detections": [ - { - "detection_id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", - "name": "Remote Registry Key modifications", - "type": "splunk" - }, - { - "detection_id": "1b989a0e-0129-4446-a695-f193a5b746fc", - "name": "Suspicious Changes to File Associations", - "type": "splunk" - }, - { - "detection_id": "bbc644bc-37df-4e1a-9c88-ec9a53e2038c", - "name": "Disabling Remote User Account Control", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01bbb", - "name": "Registry Keys for Creating SHIM Databases", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7ba7-4295-bfe9-07de87c01bbc", - "name": "Monitor Registry Keys for Print Monitors", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264x9f", - "name": "Reg.exe used to hide files/directories via registry keys", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", - "name": "Registry Keys Used For Persistence", - "type": "splunk" - }, - { - "detection_id": "c9f4b923-f8af-4155-b697-1354f5bcbc5e", - "name": "Registry Keys Used For Privilege Escalation", - "type": "splunk" - } - ], - "id": "2b1800dd-92f9-47dd-a981-fdf1351e5d55", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-05-31", - "name": "Suspicious Windows Registry Activities", - "narrative": "Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.

        The registry is a key component of the Windows operating system. It has a hierarchical database called \"registry\" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.

        The searches in this story are designed to help you detect behaviors associated with manipulation of the Windows registry.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://redcanary.com/blog/windows-registry-attacks-threat-detection/", - "https://attack.mitre.org/wiki/Technique/T1112" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2018-05-31", + "description": "Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system.", + "detections": [ + { + "detection_id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", + "name": "Remote Registry Key modifications", + "type": "splunk" + }, + { + "detection_id": "1b989a0e-0129-4446-a695-f193a5b746fc", + "name": "Suspicious Changes to File Associations", + "type": "splunk" + }, + { + "detection_id": "bbc644bc-37df-4e1a-9c88-ec9a53e2038c", + "name": "Disabling Remote User Account Control", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01bbb", + "name": "Registry Keys for Creating SHIM Databases", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7ba7-4295-bfe9-07de87c01bbc", + "name": "Monitor Registry Keys for Print Monitors", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264x9f", + "name": "Reg.exe used to hide files/directories via registry keys", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", + "name": "Registry Keys Used For Persistence", + "type": "splunk" + }, + { + "detection_id": "c9f4b923-f8af-4155-b697-1354f5bcbc5e", + "name": "Registry Keys Used For Privilege Escalation", + "type": "splunk" + } + ], + "id": "2b1800dd-92f9-47dd-a981-fdf1351e5d55", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-05-31", + "name": "Suspicious Windows Registry Activities", + "narrative": "Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\n\n The registry is a key component of the Windows operating system. It has a hierarchical database called \"registry\" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\n\n The searches in this story are designed to help you detect behaviors associated with manipulation of the Windows registry.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://redcanary.com/blog/windows-registry-attacks-threat-detection/", + "https://attack.mitre.org/wiki/Technique/T1112" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "1.0" +} diff --git a/stories/suspicious_wmi.json b/stories/suspicious_wmi.json index 192b9a89a6..318e74a81a 100644 --- a/stories/suspicious_wmi.json +++ b/stories/suspicious_wmi.json @@ -1,70 +1,70 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2017-01-13", - "description": "Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred.", - "detections": [ - { - "detection_id": "272df6de-61f1-4784-877c-1fbc3e2d0838", - "name": "Remote WMI Command Attempt", - "type": "splunk" - }, - { - "detection_id": "d25d2c3d-d9d8-40ec-8fdf-e86fe155a3da", - "name": "Remote Process Instantiation via WMI", - "type": "splunk" - }, - { - "detection_id": "71bfdb13-f200-4c6c-b2c9-a2e07adf437d", - "name": "WMI Permanent Event Subscription", - "type": "splunk" - }, - { - "detection_id": "ad05aae6-3b2a-4f73-af97-57bd26cee3b9", - "name": "WMI Permanent Event Subscription - Sysmon", - "type": "splunk" - }, - { - "detection_id": "38cbd42c-1098-41bb-99cf-9d6d2b296d83", - "name": "WMI Temporary Event Subscription", - "type": "splunk" - }, - { - "detection_id": "24869767-8579-485d-9a4f-d9ddfd8f0cac", - "name": "Process Execution via WMI", - "type": "splunk" - }, - { - "detection_id": "aa73f80d-d728-4077-b226-81ea0c8be589", - "name": "Script Execution via WMI", - "type": "splunk" - } - ], - "id": "c8ddc5be-69bc-4202-b3ab-4010b27d7ad5", - "maintainers": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "modification_date": "2018-10-23", - "name": "Suspicious WMI Use", - "narrative": "WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration.

        The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.

        In the event that unauthorized WMI execution occurs, it will be important for analysts and investigators to determine the context of the event. These details may provide insights related to how WMI was used and to what end.", - "original_authors": [ - { - "company": "Splunk", - "email": "rvaldez@splunk.com", - "name": "Rico Valdez" - } - ], - "references": [ - "https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", - "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2017-01-13", + "description": "Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred.", + "detections": [ + { + "detection_id": "272df6de-61f1-4784-877c-1fbc3e2d0838", + "name": "Remote WMI Command Attempt", + "type": "splunk" + }, + { + "detection_id": "d25d2c3d-d9d8-40ec-8fdf-e86fe155a3da", + "name": "Remote Process Instantiation via WMI", + "type": "splunk" + }, + { + "detection_id": "71bfdb13-f200-4c6c-b2c9-a2e07adf437d", + "name": "WMI Permanent Event Subscription", + "type": "splunk" + }, + { + "detection_id": "ad05aae6-3b2a-4f73-af97-57bd26cee3b9", + "name": "WMI Permanent Event Subscription - Sysmon", + "type": "splunk" + }, + { + "detection_id": "38cbd42c-1098-41bb-99cf-9d6d2b296d83", + "name": "WMI Temporary Event Subscription", + "type": "splunk" + }, + { + "detection_id": "24869767-8579-485d-9a4f-d9ddfd8f0cac", + "name": "Process Execution via WMI", + "type": "splunk" + }, + { + "detection_id": "aa73f80d-d728-4077-b226-81ea0c8be589", + "name": "Script Execution via WMI", + "type": "splunk" + } + ], + "id": "c8ddc5be-69bc-4202-b3ab-4010b27d7ad5", + "maintainers": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "modification_date": "2018-10-23", + "name": "Suspicious WMI Use", + "narrative": "WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \n\nThe detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\n\nIn the event that unauthorized WMI execution occurs, it will be important for analysts and investigators to determine the context of the event. These details may provide insights related to how WMI was used and to what end.", + "original_authors": [ + { + "company": "Splunk", + "email": "rvaldez@splunk.com", + "name": "Rico Valdez" + } + ], + "references": [ + "https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", + "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "2.0" +} diff --git a/stories/unusual_processes.json b/stories/unusual_processes.json index be5381d491..65513f91e1 100644 --- a/stories/unusual_processes.json +++ b/stories/unusual_processes.json @@ -1,71 +1,71 @@ { - "category": [ - "Malware" - ], - "channel": "ESCU", - "creation_date": "2016-08-09", - "description": "Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation.", - "detections": [ - { - "detection_id": "29ccce64-a10c-4389-a45f-337cb29ba1f7", - "name": "Uncommon Processes On Endpoint", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6a4264e7f", - "name": "Unusually Long Command Line", - "type": "splunk" - }, - { - "detection_id": "57edaefa-a73b-45e5-bbae-f39c1473f941", - "name": "Unusually Long Command Line - MLTK", - "type": "splunk" - }, - { - "detection_id": "44fddcb2-8d3b-454c-874e-7c6de5a4f7ac", - "name": "Detect Rare Executables", - "type": "splunk" - }, - { - "detection_id": "a34aae96-ccf8-4aef-952c-3ea21444444d", - "name": "System Processes Run From Unexpected Locations", - "type": "splunk" - }, - { - "detection_id": "6c135f8d-5e60-454e-80b7-c56eed739833", - "name": "RunDLL Loading DLL By Ordinal", - "type": "splunk" - }, - { - "detection_id": "a51bfe1a-94f0-48cc-b1e4-16ae10145893", - "name": "Detect processes used for System Network Configuration Discovery", - "type": "splunk" - } - ], - "id": "f4368e3f-d59f-4192-84f6-748ac5a3ddb6", - "maintainers": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-11-20", - "name": "Unusual Processes", - "narrative": "Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.

        This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.

        In the event an unusual process is identified, it is imperative to better understand how that process was able to execute on the host, when it first executed, and whether other hosts are affected. This extra information may provide clues that can help the analyst further investigate any suspicious activity.", - "original_authors": [ - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", - "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", - "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Malware" + ], + "channel": "ESCU", + "creation_date": "2016-08-09", + "description": "Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation.", + "detections": [ + { + "detection_id": "29ccce64-a10c-4389-a45f-337cb29ba1f7", + "name": "Uncommon Processes On Endpoint", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6a4264e7f", + "name": "Unusually Long Command Line", + "type": "splunk" + }, + { + "detection_id": "57edaefa-a73b-45e5-bbae-f39c1473f941", + "name": "Unusually Long Command Line - MLTK", + "type": "splunk" + }, + { + "detection_id": "44fddcb2-8d3b-454c-874e-7c6de5a4f7ac", + "name": "Detect Rare Executables", + "type": "splunk" + }, + { + "detection_id": "a34aae96-ccf8-4aef-952c-3ea21444444d", + "name": "System Processes Run From Unexpected Locations", + "type": "splunk" + }, + { + "detection_id": "6c135f8d-5e60-454e-80b7-c56eed739833", + "name": "RunDLL Loading DLL By Ordinal", + "type": "splunk" + }, + { + "detection_id": "a51bfe1a-94f0-48cc-b1e4-16ae10145893", + "name": "Detect processes used for System Network Configuration Discovery", + "type": "splunk" + } + ], + "id": "f4368e3f-d59f-4192-84f6-748ac5a3ddb6", + "maintainers": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-11-20", + "name": "Unusual Processes", + "narrative": "Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\n\nThis Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\n\nIn the event an unusual process is identified, it is imperative to better understand how that process was able to execute on the host, when it first executed, and whether other hosts are affected. This extra information may provide clues that can help the analyst further investigate any suspicious activity.", + "original_authors": [ + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", + "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", + "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "2.0" +} diff --git a/stories/web_fraud.json b/stories/web_fraud.json index 6b3861caa1..5673b9acdd 100644 --- a/stories/web_fraud.json +++ b/stories/web_fraud.json @@ -1,51 +1,51 @@ { - "category": [ - "Abuse" - ], - "channel": "ESCU", - "creation_date": "2018-07-12", - "description": "Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets.", - "detections": [ - { - "detection_id": "31337aaa-941d-4ada-81ac-q2a17be5bf0d", - "name": "Web Fraud - Account Harvesting", - "type": "splunk" - }, - { - "detection_id": "31337bbb-bc22-4752-b599-ef192df2dc7a", - "name": "Web Fraud - Anomalous User Clickspeed", - "type": "splunk" - }, - { - "detection_id": "31337a1a-53b9-4e05-96e9-55c934cb71d3", - "name": "Web Fraud - Password Sharing Across Accounts", - "type": "splunk" - } - ], - "id": "31337aaa-bc22-4752-b599-ef112dq1dq7a", - "maintainers": [ - { - "company": "Splunk", - "email": "Mayhem@splunk.com", - "name": "Jim Apger" - } - ], - "modification_date": "2018-10-08", - "name": "Web Fraud Detection", - "narrative": "The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.

        These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.

        When developing a strategy for preventing fraud in your environment, its important to look across all of your web services for evidence that attackers are abusing enterprise resources to enumerate systems, harvest data for secondary fraudulent activity, or abuse terms of service.This Analytic Story looks for evidence of common Internet attack techniques that could be indicative of web fraud in your environmentincluding account harvesting, anomalous user clickspeed, and password sharing across accounts, to name just a few.

        The account-harvesting search focuses on web pages used for user-account registration. It detects the creation of a large number of user accounts using the same email domain name, a type of activity frequently seen in advance of a fraud campaign.

        The anomalous clickspeed search looks for users who are moving through your website at a faster-than-normal speed or with a perfect click cadence (high periodicity or low standard deviation), which could indicate that the user is a script, not an actual human.

        Another search detects incidents wherein a single password is used across multiple accounts, which may indicate that a fraudster has infiltrated your environment and embedded a common password within a script.", - "original_authors": [ - { - "company": "Splunk", - "email": "Mayhem@splunk.com", - "name": "Jim Apger" - } - ], - "references": [ - "https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", - "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718", - "https://www.otalliance.org/news-events/press-releases/online-trust-alliance-reports-doubling-cyber-incidents-2017-0" - ], - "spec_version": 2, - "usecase": "Fraud Detection", - "version": "1.0" -} \ No newline at end of file + "category": [ + "Abuse" + ], + "channel": "ESCU", + "creation_date": "2018-07-12", + "description": "Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets.", + "detections": [ + { + "detection_id": "31337aaa-941d-4ada-81ac-q2a17be5bf0d", + "name": "Web Fraud - Account Harvesting", + "type": "splunk" + }, + { + "detection_id": "31337bbb-bc22-4752-b599-ef192df2dc7a", + "name": "Web Fraud - Anomalous User Clickspeed", + "type": "splunk" + }, + { + "detection_id": "31337a1a-53b9-4e05-96e9-55c934cb71d3", + "name": "Web Fraud - Password Sharing Across Accounts", + "type": "splunk" + } + ], + "id": "31337aaa-bc22-4752-b599-ef112dq1dq7a", + "maintainers": [ + { + "company": "Splunk", + "email": "Mayhem@splunk.com", + "name": "Jim Apger" + } + ], + "modification_date": "2018-10-08", + "name": "Web Fraud Detection", + "narrative": "The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\n\nThese crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\n\nWhen developing a strategy for preventing fraud in your environment, its important to look across all of your web services for evidence that attackers are abusing enterprise resources to enumerate systems, harvest data for secondary fraudulent activity, or abuse terms of service.This Analytic Story looks for evidence of common Internet attack techniques that could be indicative of web fraud in your environmentincluding account harvesting, anomalous user clickspeed, and password sharing across accounts, to name just a few.\n\nThe account-harvesting search focuses on web pages used for user-account registration. It detects the creation of a large number of user accounts using the same email domain name, a type of activity frequently seen in advance of a fraud campaign.\n\nThe anomalous clickspeed search looks for users who are moving through your website at a faster-than-normal speed or with a perfect click cadence (high periodicity or low standard deviation), which could indicate that the user is a script, not an actual human.\n\nAnother search detects incidents wherein a single password is used across multiple accounts, which may indicate that a fraudster has infiltrated your environment and embedded a common password within a script.", + "original_authors": [ + { + "company": "Splunk", + "email": "Mayhem@splunk.com", + "name": "Jim Apger" + } + ], + "references": [ + "https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", + "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718", + "https://www.otalliance.org/news-events/press-releases/online-trust-alliance-reports-doubling-cyber-incidents-2017-0" + ], + "spec_version": 2, + "usecase": "Fraud Detection", + "version": "1.0" +} diff --git a/stories/windows_persistence.json b/stories/windows_persistence.json index 96c2823f1d..7ecfacc4aa 100644 --- a/stories/windows_persistence.json +++ b/stories/windows_persistence.json @@ -1,108 +1,108 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2017-04-19", - "description": "Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment.", - "detections": [ - { - "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01bbb", - "name": "Registry Keys for Creating SHIM Databases", - "type": "splunk" - }, - { - "detection_id": "404620de-46d8-48b6-90cc-8a8d7b0876a3", - "name": "Shim Database Installation With Suspicious Parameters", - "type": "splunk" - }, - { - "detection_id": "6e4c4588-ba2f-42fa-97e6-9f6f548eaa33", - "name": "Shim Database File Creation", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", - "name": "Registry Keys Used For Persistence", - "type": "splunk" - }, - { - "detection_id": "1297fb80-f42a-4b4a-9c8a-88c066437cf6", - "name": "Schtasks used for forcing a reboot", - "type": "splunk" - }, - { - "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", - "name": "Sc.exe Manipulating Windows Services", - "type": "splunk" - }, - { - "detection_id": "8470d755-0c13-45b3-bd63-387a373c10cf", - "name": "Reg.exe Manipulating Windows Services Registry Keys", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264g9f", - "name": "Hiding Files And Directories With Attrib.exe", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264x9f", - "name": "Reg.exe used to hide files/directories via registry keys", - "type": "splunk" - }, - { - "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5264g9f", - "name": "Detect Path Interception By Creation Of program.exe", - "type": "splunk" - }, - { - "detection_id": "f5f6af30-7ba7-4295-bfe9-07de87c01bbc", - "name": "Monitor Registry Keys for Print Monitors", - "type": "splunk" - }, - { - "detection_id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", - "name": "Remote Registry Key modifications", - "type": "splunk" - } - ], - "id": "30874d4f-20a1-488f-85ec-5d52ef74e3f9", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - }, - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "modification_date": "2018-05-31", - "name": "Windows Persistence Techniques", - "narrative": "Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - }, - { - "company": "Splunk", - "email": "bpatel@splunk.com", - "name": "Bhavin Patel" - } - ], - "references": [ - "http://www.fuzzysecurity.com/tutorials/19.html", - "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", - "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", - "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", - "https://www.defcon.org/images/defcon-22/dc-22-presentations/Bloxham/DEFCON-22-Brady-Bloxham-Windows-API-Abuse-UPDATED.pdf" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2017-04-19", + "description": "Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment.", + "detections": [ + { + "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01bbb", + "name": "Registry Keys for Creating SHIM Databases", + "type": "splunk" + }, + { + "detection_id": "404620de-46d8-48b6-90cc-8a8d7b0876a3", + "name": "Shim Database Installation With Suspicious Parameters", + "type": "splunk" + }, + { + "detection_id": "6e4c4588-ba2f-42fa-97e6-9f6f548eaa33", + "name": "Shim Database File Creation", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7aa7-4295-bfe9-07fe87c01a4b", + "name": "Registry Keys Used For Persistence", + "type": "splunk" + }, + { + "detection_id": "1297fb80-f42a-4b4a-9c8a-88c066437cf6", + "name": "Schtasks used for forcing a reboot", + "type": "splunk" + }, + { + "detection_id": "f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d", + "name": "Sc.exe Manipulating Windows Services", + "type": "splunk" + }, + { + "detection_id": "8470d755-0c13-45b3-bd63-387a373c10cf", + "name": "Reg.exe Manipulating Windows Services Registry Keys", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264g9f", + "name": "Hiding Files And Directories With Attrib.exe", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6b5264x9f", + "name": "Reg.exe used to hide files/directories via registry keys", + "type": "splunk" + }, + { + "detection_id": "c77162d3-f93c-45cc-80c8-22f6v5264g9f", + "name": "Detect Path Interception By Creation Of program.exe", + "type": "splunk" + }, + { + "detection_id": "f5f6af30-7ba7-4295-bfe9-07de87c01bbc", + "name": "Monitor Registry Keys for Print Monitors", + "type": "splunk" + }, + { + "detection_id": "c9f4b923-f8af-4155-b697-1354f5dcbc5e", + "name": "Remote Registry Key modifications", + "type": "splunk" + } + ], + "id": "30874d4f-20a1-488f-85ec-5d52ef74e3f9", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + }, + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "modification_date": "2018-05-31", + "name": "Windows Persistence Techniques", + "narrative": "Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + }, + { + "company": "Splunk", + "email": "bpatel@splunk.com", + "name": "Bhavin Patel" + } + ], + "references": [ + "http://www.fuzzysecurity.com/tutorials/19.html", + "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", + "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", + "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", + "https://www.defcon.org/images/defcon-22/dc-22-presentations/Bloxham/DEFCON-22-Brady-Bloxham-Windows-API-Abuse-UPDATED.pdf" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "2.0" +} diff --git a/stories/windows_privilege_escalation.json b/stories/windows_privilege_escalation.json index 0a7f3d1704..2b040970eb 100644 --- a/stories/windows_privilege_escalation.json +++ b/stories/windows_privilege_escalation.json @@ -1,54 +1,54 @@ { - "category": [ - "Adversary Tactics" - ], - "channel": "ESCU", - "creation_date": "2017-12-07", - "description": "Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more.", - "detections": [ - { - "detection_id": "13c2f6c3-10c5-4deb-9ba1-7c4460ebe4ae", - "name": "Overwriting Accessibility Binaries", - "type": "splunk" - }, - { - "detection_id": "c9f4b923-f8af-4155-b697-1354f5bcbc5e", - "name": "Registry Keys Used For Privilege Escalation", - "type": "splunk" - }, - { - "detection_id": "29ccce64-a10c-4389-a45f-337cb29ba1f7", - "name": "Uncommon Processes On Endpoint", - "type": "splunk" - }, - { - "detection_id": "aa0c4aeb-5b18-41c4-8c07-f1442d7599df", - "name": "Child Processes of Spoolsv.exe", - "type": "splunk" - } - ], - "id": "644e22d3-598a-429c-a007-16fdb802cae5", - "maintainers": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "modification_date": "2017-12-07", - "name": "Windows Privilege Escalation", - "narrative": "Privilege escalation is a \"land-and-expand\" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment.", - "original_authors": [ - { - "company": "Splunk", - "email": "davidd@splunk.com", - "name": "David Dorsey" - } - ], - "references": [ - "https://attack.mitre.org/wiki/Privilege_Escalation" - ], - "spec_version": 2, - "usecase": "Advanced Threat Detection", - "version": "2.0" -} \ No newline at end of file + "category": [ + "Adversary Tactics" + ], + "channel": "ESCU", + "creation_date": "2017-12-07", + "description": "Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more.", + "detections": [ + { + "detection_id": "13c2f6c3-10c5-4deb-9ba1-7c4460ebe4ae", + "name": "Overwriting Accessibility Binaries", + "type": "splunk" + }, + { + "detection_id": "c9f4b923-f8af-4155-b697-1354f5bcbc5e", + "name": "Registry Keys Used For Privilege Escalation", + "type": "splunk" + }, + { + "detection_id": "29ccce64-a10c-4389-a45f-337cb29ba1f7", + "name": "Uncommon Processes On Endpoint", + "type": "splunk" + }, + { + "detection_id": "aa0c4aeb-5b18-41c4-8c07-f1442d7599df", + "name": "Child Processes of Spoolsv.exe", + "type": "splunk" + } + ], + "id": "644e22d3-598a-429c-a007-16fdb802cae5", + "maintainers": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "modification_date": "2017-12-07", + "name": "Windows Privilege Escalation", + "narrative": "Privilege escalation is a \"land-and-expand\" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment.", + "original_authors": [ + { + "company": "Splunk", + "email": "davidd@splunk.com", + "name": "David Dorsey" + } + ], + "references": [ + "https://attack.mitre.org/wiki/Privilege_Escalation" + ], + "spec_version": 2, + "usecase": "Advanced Threat Detection", + "version": "2.0" +}