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new asl aws detections
This commit is contained in:
Patrick Bareiss
committed by
ljstella
ljstella
parent
22c3c2dc08
commit
ebca30164d
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name: ASL AWS Create Policy Version to allow all resources
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id: 22cc7a62-3884-48c4-82da-592b8199b72f
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version: 1
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date: '2024-12-12'
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author: Patrick Bareiss, Splunk
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status: production
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type: TTP
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description: The following analytic identifies the creation of a new AWS IAM policy version that allows access to all resources. It detects this activity by analyzing AWS CloudTrail logs for the CreatePolicyVersion event with a policy document that grants broad permissions. This behavior is significant because it violates the principle of least privilege, potentially exposing the environment to misuse or abuse. If confirmed malicious, an attacker could gain extensive access to AWS resources, leading to unauthorized actions, data exfiltration, or further compromise of the AWS environment.
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data_source: []
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search: '`amazon_security_lake` api.operation=CreatePolicy | spath input=api.request.data | spath input=policyDocument | regex Statement{}.Action="\*" | regex Statement{}.Resource="\*" | fillnull | stats count min(_time) as firstTime max(_time) as lastTime by api.operation actor.user.uid http_request.user_agent src_endpoint.ip cloud.region api.request.data | rename actor.user.uid as user, src_endpoint.ip as src_ip, cloud.region as region, http_request.user_agent as user_agent | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`asl_aws_create_policy_version_to_allow_all_resources_filter`'
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how_to_implement: The detection is based on Amazon Security Lake events from Amazon Web Services (AWS), which is a centralized data lake that provides security-related data from AWS services. To use this detection, you must ingest CloudTrail logs from Amazon Security Lake into Splunk. To run this search, ensure that you ingest events using the latest version of Splunk Add-on for Amazon Web Services (https://splunkbase.splunk.com/app/1876) or the Federated Analytics App.
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known_false_positives: While this search has no known false positives, it is possible that an AWS admin has legitimately created a policy to allow a user to access all resources. That said, AWS strongly advises against granting full control to all AWS resources and you must verify this activity.
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references:
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- https://bishopfox.com/blog/privilege-escalation-in-aws
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- https://rhinosecuritylabs.com/aws/aws-privilege-escalation-methods-mitigation-part-2/
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drilldown_searches:
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- name: View the detection results for - "$user$"
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search: '%original_detection_search% | search user = "$user$"'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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- name: View risk events for the last 7 days for - "$user$"
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search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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tags:
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analytic_story:
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- AWS IAM Privilege Escalation
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asset_type: AWS Account
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confidence: 70
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impact: 70
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message: User $user$ created a policy version that allows them to access any resource in their account.
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mitre_attack_id:
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- T1078.004
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- T1078
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observable:
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- name: user
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type: User
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role:
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- Victim
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product:
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- Splunk Enterprise
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- Splunk Enterprise Security
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- Splunk Cloud
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required_fields:
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- api.operation
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- api.request.data
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- actor.user.uid
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- http_request.user_agent
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- src_endpoint.ip
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- src_endpoint.domain
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- cloud.region
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risk_score: 49
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security_domain: network
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tests:
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- name: True Positive Test
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attack_data:
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- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1078/aws_create_policy_version/asl_ocsf_cloudtrail.json
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sourcetype: aws:cloudtrail:lake
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source: aws_asl
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name: ASL AWS CreateAccessKey
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id: d130cccd-41fe-483f-a70c-25d238bfce31
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version: 1
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date: '2024-12-12'
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author: Patrick Bareiss, Splunk
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status: production
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type: Hunting
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description: The following analytic identifies the creation of AWS IAM access keys by a user for another user, which can indicate privilege escalation. It leverages AWS CloudTrail logs to detect instances where the user creating the access key is different from the user for whom the key is created. This activity is significant because unauthorized access key creation can allow attackers to establish persistence or exfiltrate data via AWS APIs. If confirmed malicious, this could lead to unauthorized access to AWS services, data exfiltration, and long-term persistence in the environment.
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data_source: []
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search: '`amazon_security_lake` api.operation=CreateAccessKey | fillnull | stats count min(_time) as firstTime max(_time) as lastTime by api.operation actor.user.uid http_request.user_agent src_endpoint.ip cloud.region | rename actor.user.uid as user, src_endpoint.ip as src_ip, cloud.region as region, http_request.user_agent as user_agent | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` |`asl_aws_createaccesskey_filter`'
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how_to_implement: The detection is based on Amazon Security Lake events from Amazon Web Services (AWS), which is a centralized data lake that provides security-related data from AWS services. To use this detection, you must ingest CloudTrail logs from Amazon Security Lake into Splunk. To run this search, ensure that you ingest events using the latest version of Splunk Add-on for Amazon Web Services (https://splunkbase.splunk.com/app/1876) or the Federated Analytics App.
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known_false_positives: While this search has no known false positives, it is possible that an AWS admin has legitimately created keys for another user.
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references:
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- https://bishopfox.com/blog/privilege-escalation-in-aws
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- https://rhinosecuritylabs.com/aws/aws-privilege-escalation-methods-mitigation-part-2/
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tags:
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analytic_story:
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- AWS IAM Privilege Escalation
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asset_type: AWS Account
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confidence: 90
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impact: 70
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message: User $user$ is attempting to create access keys
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mitre_attack_id:
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- T1136.003
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- T1136
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observable:
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- name: src_ip
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type: IP Address
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role:
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- Attacker
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- name: user
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type: User
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role:
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- Attacker
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product:
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- Splunk Enterprise
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- Splunk Enterprise Security
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- Splunk Cloud
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required_fields:
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- api.operation
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- actor.user.uid
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- http_request.user_agent
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- src_endpoint.ip
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- src_endpoint.domain
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- cloud.region
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risk_score: 63
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security_domain: network
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tests:
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- name: True Positive Test
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attack_data:
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- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1078/asl_ocsf_cloudtrail.json
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sourcetype: aws:cloudtrail:lake
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source: aws_asl
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@@ -0,0 +1,64 @@
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name: ASL AWS Credential Access GetPasswordData
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id: a79b607a-50cc-4704-bb9d-eff280cb78c2
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version: 1
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date: '2024-12-12'
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author: Patrick Bareiss, Splunk
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status: production
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type: Anomaly
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description: The following analytic identifies more than 10 GetPasswordData API calls within a 5-minute window in your AWS account. It leverages AWS CloudTrail logs to detect this activity by counting the distinct instance IDs accessed. This behavior is significant as it may indicate an attempt to retrieve encrypted administrator passwords for running Windows instances, which is a critical security concern. If confirmed malicious, attackers could gain unauthorized access to administrative credentials, potentially leading to full control over the affected instances and further compromise of the AWS environment.
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data_source: []
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search: '`amazon_security_lake` api.operation=GetPasswordData | spath input=api.request.data | fillnull | stats count min(_time) as firstTime max(_time) as lastTime by api.operation actor.user.uid http_request.user_agent src_endpoint.ip cloud.region instanceId | rename actor.user.uid as user, src_endpoint.ip as src_ip, cloud.region as region, http_request.user_agent as user_agent | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` |`asl_aws_credential_access_getpassworddata_filter`'
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how_to_implement: The detection is based on Amazon Security Lake events from Amazon Web Services (AWS), which is a centralized data lake that provides security-related data from AWS services. To use this detection, you must ingest CloudTrail logs from Amazon Security Lake into Splunk. To run this search, ensure that you ingest events using the latest version of Splunk Add-on for Amazon Web Services (https://splunkbase.splunk.com/app/1876) or the Federated Analytics App.
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known_false_positives: Administrator tooling or automated scripts may make these calls but it is highly unlikely to make several calls in a short period of time.
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references:
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- https://attack.mitre.org/techniques/T1552/
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- https://stratus-red-team.cloud/attack-techniques/AWS/aws.credential-access.ec2-get-password-data/
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drilldown_searches:
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- name: View the detection results for - "$user_arn$"
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search: '%original_detection_search% | search user_arn = "$user_arn$"'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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- name: View risk events for the last 7 days for - "$user_arn$"
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search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user_arn$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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tags:
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analytic_story:
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- AWS Identity and Access Management Account Takeover
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asset_type: AWS Account
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confidence: 70
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impact: 70
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message: User $user$ is seen to make mulitple `GetPasswordData` API calls
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mitre_attack_id:
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- T1586
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- T1586.003
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- T1110
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- T1110.001
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observable:
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- name: src_ip
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type: IP Address
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role:
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- Attacker
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- name: user
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type: User
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role:
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- Victim
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product:
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- Splunk Enterprise
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- Splunk Enterprise Security
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- Splunk Cloud
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required_fields:
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- api.operation
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- actor.user.uid
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- http_request.user_agent
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- src_endpoint.ip
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- src_endpoint.domain
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- cloud.region
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risk_score: 49
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security_domain: threat
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tests:
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- name: True Positive Test
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attack_data:
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- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1552/aws_getpassworddata/asl_ocsf_cloudtrail.json
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sourcetype: aws:cloudtrail:lake
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source: aws_asl
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@@ -0,0 +1,63 @@
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name: ASL AWS Credential Access RDS Password reset
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id: d15e9bd9-ef64-4d84-bc04-f62955a9fee8
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version: 1
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date: '2024-12-12'
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author: Patrick Bareiss, Splunk
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status: production
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type: TTP
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description: The following analytic detects the resetting of the master user password for an Amazon RDS DB instance. It leverages AWS CloudTrail logs to identify events where the `ModifyDBInstance` API call includes a new `masterUserPassword` parameter. This activity is significant because unauthorized password resets can grant attackers access to sensitive data stored in production databases, such as credit card information, PII, and healthcare data. If confirmed malicious, this could lead to data breaches, regulatory non-compliance, and significant reputational damage. Immediate investigation is required to determine the legitimacy of the password reset.
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data_source: []
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search: '`amazon_security_lake` api.operation=ModifyDBInstance OR api.operation=ModifyDBCluster | spath input=api.request.data | search masterUserPassword=* | fillnull | stats count min(_time) as firstTime max(_time) as lastTime by api.operation actor.user.uid http_request.user_agent src_endpoint.ip cloud.region api.request.data | rename actor.user.uid as user, src_endpoint.ip as src_ip, cloud.region as region, http_request.user_agent as user_agent | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` |`asl_aws_credential_access_rds_password_reset_filter`'
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how_to_implement: You must install splunk AWS add on and Splunk App for AWS. This search works with AWS CloudTrail logs.
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known_false_positives: Users may genuinely reset the RDS password.
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references:
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- https://aws.amazon.com/premiumsupport/knowledge-center/reset-master-user-password-rds
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drilldown_searches:
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- name: View the detection results for - "$database_id$"
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search: '%original_detection_search% | search database_id = "$database_id$"'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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- name: View risk events for the last 7 days for - "$database_id$"
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search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$database_id$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
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earliest_offset: $info_min_time$
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latest_offset: $info_max_time$
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tags:
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analytic_story:
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- AWS Identity and Access Management Account Takeover
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asset_type: AWS Account
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confidence: 70
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impact: 70
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message: User $user$ is seen to reset the password for database
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mitre_attack_id:
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- T1586
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- T1586.003
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- T1110
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observable:
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- name: database_id
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type: Endpoint
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role:
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- Victim
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- name: src
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type: IP Address
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role:
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- Attacker
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product:
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- Splunk Enterprise
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- Splunk Enterprise Security
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- Splunk Cloud
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required_fields:
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- api.operation
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- api.request.data
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- actor.user.uid
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- http_request.user_agent
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- src_endpoint.ip
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- src_endpoint.domain
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- cloud.region
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risk_score: 49
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security_domain: threat
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tests:
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- name: True Positive Test
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attack_data:
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- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1110.002/aws_rds_password_reset/asl_ocsf_cloudtrail.json
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sourcetype: aws:cloudtrail:lake
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source: aws_asl
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