* [New] AWS Credentials Used from GitHub Actions and Non-CI/CD Infrastructure
Detects AWS access keys that are used from both GitHub Actions CI/CD infrastructure and non-CI/CD infrastructure. This pattern indicates potential credential theft where an attacker who has stolen AWS credentials configured as GitHub Actions secrets and is using them from their own infrastructure.
* Update initial_access_github_actions_oidc_credentials_used_from_suspicious_network.toml
* ++
* Update initial_access_github_actions_oidc_credentials_used_from_suspicious_network.toml
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Co-authored-by: shashank-elastic <91139415+shashank-elastic@users.noreply.github.com>
(cherry picked from commit 496d2e206a)
* [New] AWS Rare Source AS Organization Activity
Surfaces an AWS identity whose successful API traffic is dominated by a small set of large cloud-provider source AS organization labels, yet also shows a very small share of traffic from other AS organization names—including at least one sensitive control-plane, credential, storage, or model-invocation action on that uncommon network path with recent
activity from the uncommon path. The intent is to highlight disproportionate “baseline” cloud egress versus sparse use from rarer networks on the same principal, a shape that can appear when automation or CI credentials are reused or pivoted outside their usual hosted-cloud footprint.
* Apply suggestion from @eric-forte-elastic
Co-authored-by: Eric Forte <119343520+eric-forte-elastic@users.noreply.github.com>
* Update initial_access_aws_api_unusual_asn.toml
* Update initial_access_aws_api_unusual_asn.toml
* Update initial_access_aws_api_unusual_asn.toml
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Co-authored-by: Eric Forte <119343520+eric-forte-elastic@users.noreply.github.com>
Co-authored-by: Mika Ayenson, PhD <Mikaayenson@users.noreply.github.com>
Co-authored-by: shashank-elastic <91139415+shashank-elastic@users.noreply.github.com>
(cherry picked from commit 2177135f86)
* [New Rules] AWS Long-Term Creds Abuse Coverage
This adds a two-layer approach to long-term IAM access key (AKIA*) abuse, aligned with reporting on stolen or leaked keys often abused as seen in Kudelski Security — Trivy supply-chain report.
### Layer 1 — AWS Long-Term Access Key First Seen from Source IP (9f8e3c5e-f72e-4e91-93f6-e98a4fae3e4f)
New Terms on CloudTrail when a given AKIA succeeds from a new `source.ip` in the history window.
Goal: catch novel use of a durable key (travel, new egress, or attacker infrastructure).
### Layer 2 — AWS Long-Term Access Key Correlated with Elevated Detection Alerts
Higher-order rule on open alerts that requires both the Layer 1 rule and at least one other open alert on the same `source.ip` at medium+ severity (or equivalent risk score).
Goal: raise priority when “new IP for this key” happens together with stronger, post-compromise-style signals.
The higher-order rule correlates on `source.ip` in .alerts-security.* index. In testing, I chose to tie the same sessions together using `source.ip` vs `access_key.id` because the alerts index did not expose this field for queries.
Screenshots below show testing that verified the approach. The same operator/session across Layer 1 rule, the sibling alert, and the Layer 2 correlation rule for two separate lab scenarios (e.g. a high-severity sibling rule and a medium-severity sibling rule).
* adding IAM to rule names
* removing unnecessary ref
* Fixed Mitre tactics and tags
* [New Rules] AWS IAM Long-Term Creds Abuse Coverage
Adding min_stack to rule using the field user.entity.id, we determined AWS version 4.7.0 is compatible with Kibana versions '^8.19.4 || ^9.1.4'. We reverted the initial PR and this one adds the min_stack_version.
Original PR: - https://github.com/elastic/detection-rules/pull/5918
Revert PR: - https://github.com/elastic/detection-rules/pull/5923
(cherry picked from commit c99dc2f4cc)
* [New Rules] AWS Long-Term Creds Abuse Coverage
This adds a two-layer approach to long-term IAM access key (AKIA*) abuse, aligned with reporting on stolen or leaked keys often abused as seen in Kudelski Security — Trivy supply-chain report.
### Layer 1 — AWS Long-Term Access Key First Seen from Source IP (9f8e3c5e-f72e-4e91-93f6-e98a4fae3e4f)
New Terms on CloudTrail when a given AKIA succeeds from a new `source.ip` in the history window.
Goal: catch novel use of a durable key (travel, new egress, or attacker infrastructure).
### Layer 2 — AWS Long-Term Access Key Correlated with Elevated Detection Alerts
Higher-order rule on open alerts that requires both the Layer 1 rule and at least one other open alert on the same `source.ip` at medium+ severity (or equivalent risk score).
Goal: raise priority when “new IP for this key” happens together with stronger, post-compromise-style signals.
The higher-order rule correlates on `source.ip` in .alerts-security.* index. In testing, I chose to tie the same sessions together using `source.ip` vs `access_key.id` because the alerts index did not expose this field for queries.
Screenshots below show testing that verified the approach. The same operator/session across Layer 1 rule, the sibling alert, and the Layer 2 correlation rule for two separate lab scenarios (e.g. a high-severity sibling rule and a medium-severity sibling rule).
* adding IAM to rule names
* removing unnecessary ref
* Fixed Mitre tactics and tags
---------
Co-authored-by: Terrance DeJesus <99630311+terrancedejesus@users.noreply.github.com>
(cherry picked from commit a6d31d7dfd)
* [New Rule] AWS S3 Rapid Bucket Posture API Calls from a Single Principal
Detects the same principal (`aws.cloudtrail.user_identity.arn`) from the same `source.ip` successfully calling a tight set of read-only S3 management APIs: ``` GetBucketAcl, GetBucketPublicAccessBlock, GetBucketPolicy, GetBucketPolicyStatus, GetBucketVersioning ``` against more than 15 distinct buckets (`aws.cloudtrail.resources.arn`) within a 10-second window.
The idea is grounded in cloud reconnaissance and scanner-style behavior discussed in Kudelski Security’s analysis of the Trivy supply chain story and related cloud activity. It explicitly called out automated assessment tooling and posture-oriented API use across ~24 buckets in a short time. It also highlighted the user's blind spot in telemetry with no Data events captured for S3 buckets. So would need to rely on management APIs for detection.
All our existing detections related to S3 rely on Data events and we have no explicit detections for scanner style recon sweeps as described in this threat report.
### Rule Design
- ES|QL with date_trunc(10 seconds, …) and count_distinct(aws.cloudtrail.resources.arn) grouped by time bucket, identity ARN, and source.ip.
- Management level API calls that are commonly used to identify bucket posture including public accessibility status and whether or not versioning is enabled (necessary info for ransomeware objectives)
- Excludes AWSService, requires source.ip, non-null aws.cloudtrail.resources.arn and user_identity.arn, and session_credential_from_console IS NULL to capture programmatic sessions over console behavior.
- Threshold 15 after evaluating rule in production environment to reduce noise from benign scanners and automation.
- low severity as this rule is FP prone until users add exclusions for known scanner behaviors specific to their environment
* correcting highlighted fields
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Co-authored-by: Terrance DeJesus <99630311+terrancedejesus@users.noreply.github.com>
(cherry picked from commit ca821414a4)
* [New Rule][Rule Tuning] AWS Organizations/Account Discovery Coverage
In response to the supply chain attack highlighted in (Kudelski’s Trivy / TeamPCP analysis)[https://kudelskisecurity.com/research/investigating-two-variants-of-the-trivy-supply-chain-compromise], I've added coverage for AWS Organization and Account reconnaissance which was called out in the research.
### AWS Discovery API Calls via CLI from a Single Resource
- Expanded our existing Multi-service discovery rule to include `event.provider: oraganizations.amazonaws.com`
- added the new `aws.cloudtrail.session_credential_from_console` field to exclude console behavior from this rule, and added appropriate `min_stack` to account for introduction of the field.
GAP: This rule detects aws-cli usage only. In the mentioned reference, attackers used Botocore and Boto3 tooling for this recon activity.
SOLUTION:
### AWS Account Discovery By Rare User
- Created a new Discovery rule focused solely on Organization/Account reconnaissance.
- Made it a new terms rule to reduce false positive noise from common behavior that might be seen using Boto3 or Botocore tooling.
- excluded console session behavior and service account behavior
Testing:
- Ran PACU's organization__enum module
- created a script that can be run to validate the query
- plenty of test data in our stack to run the query against
* Update rules/integrations/aws/discovery_organization_discovery_by_rare_user.toml
Co-authored-by: Terrance DeJesus <99630311+terrancedejesus@users.noreply.github.com>
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Co-authored-by: Terrance DeJesus <99630311+terrancedejesus@users.noreply.github.com>
(cherry picked from commit c0b852a23d)
* Expand AWS CloudTrail user-agent rule for TruffleHog and Kali
- Rename rule file to initial_access_suspicious_user_agent_detected_in_cloudtrail.toml
- Rule name: AWS Suspicious User Agent Fingerprint
- Match TruffleHog in user_agent.original (successful API calls)
- Retain Kali Linux distrib#kali fingerprint for aws-cli/Boto3
- Refresh narrative and references (incl. Kudelski Trivy supply-chain analysis)
Same rule_id f80ea920-f6f5-4c8a-9761-84ac97ec0cb2.
Made-with: Cursor
* Apply suggestion from @terrancedejesus
(cherry picked from commit ae5ecd5346)
* [New Rule] AWS API Activity from S3 Browser Client
Detects AWS API activity originating from the S3 Browser application based on the user agent string. S3 Browser is a Windows-based graphical client for managing S3 buckets that is rarely used in enterprise environments but has been observed in use by threat actors for data exfiltration due to its ease of use and bulk download capabilities. This rule was inspired by the Permiso LUCR-3 research which documented Scattered Spider using S3 Browser (v10.9.9) for data theft operations. No usage captured in alert telemetry and only one user utilized this browser in prod data.
Existing Related Coverage: We have several S3-related exfiltration rules covering bucket replication, policy modifications, and ransomware indicators. This new rule closes a gap by detecting a specific attacker tooling fingerprint rather than relying solely on behavioral patterns.
* Update rules/integrations/aws/exfiltration_s3_browser_user_agent.toml
Co-authored-by: Ruben Groenewoud <78494512+Aegrah@users.noreply.github.com>
* [New Rule] AWS API Activity from Uncommon S3 Client by Rare User
This rule detects AWS API activity from S3 Browser and Cyberduck desktop clients based on user agent strings. Both are graphical S3 management tools that provide bulk upload/download capabilities and have been observed in use by threat actors for data exfiltration. S3 Browser usage is specifically documented in the Permiso blog on LUCR-3 (Scattered Spider), while Cyberduck is referenced in the MITRE ATT&CK Threat Emulation of Scattered Spider. The rule uses a New Terms approach on cloud.account.id and user.name to alert only on the first occurrence per user/account, reducing noise from repeated GetObject or PutObject operations while still capturing new suspicious tool usage.
No existing rules currently detect activity based on these specific S3 client user agents. This fills a gap in detecting exfiltration tooling commonly used in post-compromise data theft operations.
* adding space to S3 Browser
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Co-authored-by: Ruben Groenewoud <78494512+Aegrah@users.noreply.github.com>
Co-authored-by: Eric Forte <119343520+eric-forte-elastic@users.noreply.github.com>
(cherry picked from commit e49a3f0310)
## Summary
This PR adds a new detection rule for AWS CloudShell environment creation, based on the **T1059.009 - Command and Scripting Interpreter: Cloud API** technique as documented in the [AWS Threat Technique Catalog](https://aws-samples.github.io/threat-technique-catalog-for-aws/Techniques/T1059.009.html).
AWS CloudShell is a browser-based shell that provides command-line access to AWS resources directly from the AWS Management Console. While convenient for administrators, CloudShell can be abused by adversaries who gain access to compromised console sessions to execute commands, install tools, or interact with AWS services without needing local CLI credentials.
This rule detects the `CreateEnvironment` API call, which occurs when:
- A user launches CloudShell for the **first time**
- A user accesses CloudShell in a **new AWS region** (each region maintains a separate environment)
### Why `CreateEnvironment` instead of `CreateSession`?
`
While both `CreateEnviroment` and `CreateSession` are noted in the catalog for this technique, during testing I observed that:
- **`CreateEnvironment`** is called when a new CloudShell environment is created (first-time user OR new region)
- **`CreateSession`** is called when reconnecting to an existing CloudShell environment that was previously created
By focusing on `CreateEnvironment`, we capture the meaningful signal (new environment creation) while avoiding noise from users simply reconnecting to existing sessions.
(cherry picked from commit 3b59030211)
* [Rule Tuning] Entra ID OAuth Device Code Grant by Unusual User
Fixes#5790
* updated description and investigation guide
(cherry picked from commit 1d3dad243c)
* [Rule Tuning] AWS Access Token Used from Multiple Addresses
Summary
Tuning changes to reduce noise and improve fidelity for the AWS Access Token Used from Multiple Addresses rule. After several tuning this rule is still producing ~2000 alerts/day
- Added aws.cloudtrail.session_credential_from_console exclusion to filter out legitimate console login sessions
- Added Esql.event_provider_count_distinct > 1 condition requiring activity across multiple AWS services to reduce single-service noise
- Changed interval from 5m to 30m to reduce alert frequency
- Updated query time window from 30 minutes to 32 minutes to align with the from setting
- Added min_stack_version = "9.2.0" for the new console credential field (AWS integration 4.6.0+)
Rational
- Console login sessions generate temporary credentials that can appear from multiple IPs during VPN/network transitions
- Requiring activity across multiple AWS service providers increases confidence that the token is being used for broader reconnaissance rather than normal single-service operations
- Longer interval reduces duplicate alerting per access token while still catching the behavior within the 32-minute aggregation window
* Apply suggestions from code review
* Update rules/integrations/aws/initial_access_iam_session_token_used_from_multiple_addresses.toml
* Update initial_access_iam_session_token_used_from_multiple_addresses.toml
(cherry picked from commit 926befff83)
* [Rule Tuning] AWS STS Role Assumption by User
Removed AssumedRole from the `aws.cloudtrail.user_identity.type` filter to eliminate redundancy with the AWS STS Role Chaining rule. The AWS STS Role Chaining rule already covers AssumedRole identity types assuming other roles. This change ensures each rule has distinct coverage without overlapping alerts.
- Changed query filter from `aws.cloudtrail.user_identity.type: ("AssumedRole" or "IAMUser")` to `aws.cloudtrail.user_identity.type: "IAMUser"`
- Updated description to clarify the rule focuses on user-initiated role assumptions
- Minor formatting fixes to investigation guide headings
* reducing new_terms fields
reducing new_terms fields to only use "aws.cloudtrail.user_identity.arn" since we do not have to account for roles, this field is unique for IAMUsers
(cherry picked from commit 1e777d9be7)
* [Rule Tuningw] Add Console Session Filtering to AWS Temporary Credential Detection Rules
Added `aws.cloudtrail.session_credential_from_console` field filtering to 2 rules to reduce false positives from legitimate console login sessions. Console logins automatically issue temporary "ASIA" credentials, which previously triggered alerts for rules monitoring session token abuse.
- Updated false positives sections to reflect automatic console session filtering
- Updated investigation guides to note that alerts indicate non-console temporary credential usage
- min_stack_version = "9.2.0" because this field was introduced in AWS Integration version 4.6.0. 9.2.0 is the earliest major stack version supported.
Impact
- Significantly reduces false positives from legitimate AWS Management Console usage
- Improves rule fidelity by focusing detection on programmatic abuse of temporary credentials (CLI, SDK, stolen credentials)
* update boolean field value for aws.cloudtrail.session_credential_from_console
update boolean field value for aws.cloudtrail.session_credential_from_console
* removing filebeat compatibility
removing filebeat compatibility
(cherry picked from commit c5dbd90662)
* [New Rule] Okta User Authentication via Proxy Followed by Security Alert
Fixes#5751
* adjusted to EQL
* fixed syntax
* Update rules/integrations/okta/initial_access_first_occurrence_user_session_started_via_proxy.toml
Co-authored-by: Isai <59296946+imays11@users.noreply.github.com>
* removed defense evasion; adjusted maxspan to 30m
* removed Okta tag
* adding Okta back as integration tag
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Co-authored-by: Isai <59296946+imays11@users.noreply.github.com>
(cherry picked from commit 8593116f58)
Tuning based on telemetry from recent rule version 9. There are many false positives for what look like typical S3 storage object names like `BillingInformation`, `InstanceInformation` created by AWS Service accounts. I'm excluding AWS service account types from the rule for now which eliminated ~97% of the false positives over last 30 days. leaving only 66 which is acceptable for this rule and should be addressed via local exclusions.
Co-authored-by: Colson Wilhoit <48036388+DefSecSentinel@users.noreply.github.com>
(cherry picked from commit 62aa4dcedc)
Terrance DeJesus