菜单
Detect unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access.
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基于 SOC 职业分类
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| name | detecting-aws-cloudtrail-anomalies |
| description | Detect unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access. |
| domain | cybersecurity |
| subdomain | cloud-security |
| tags | ["cloud-security","aws","cloudtrail","anomaly-detection","threat-detection","boto3"] |
| version | 1.0 |
| author | mahipal |
| license | Apache-2.0 |
| nist_csf | ["PR.IR-01","ID.AM-08","GV.SC-06","DE.CM-01"] |
AWS CloudTrail records API calls across AWS services. This skill covers querying CloudTrail events with boto3's lookup_events API, building statistical baselines of normal API activity, detecting anomalies such as unusual event sources, geographic anomalies, high-frequency API calls, and first-time API usage patterns that indicate compromised credentials or insider threats.
boto3 libraryUse boto3 CloudTrail client's lookup_events to retrieve recent API activity with pagination.
Aggregate events by user, source IP, event source, and event name to establish normal behavior patterns.
Flag unusual patterns: new event sources per user, first-time API calls, geographic IP changes, high error rates, and sensitive API usage (IAM, KMS, S3 policy changes).
Produce a JSON report with anomaly scores, top suspicious users, and recommended investigation actions.
JSON report with event statistics, baseline deviations, anomalous users/IPs, sensitive API calls, and error rate analysis.