detecting-aws-cloudtrail-anomalies

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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仓库: xalgord/xalgorix
最近来源活动: 2026年6月6日 16:41
检测到的 SKILL.md 语言: 英语
星标: 813
分支: 146

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Detecting AWS CloudTrail Anomalies

Overview

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.

When to Use

When investigating security incidents that require detecting aws cloudtrail anomalies

When building detection rules or threat hunting queries for this domain

When SOC analysts need structured procedures for this analysis type

When validating security monitoring coverage for related attack techniques

Detection Gaps & Validation

lookup_events is management-events only, last 90 days: S3/Lambda data events are not returned and read-only List/Describe/Get calls are excluded. Bulk GetObject exfil or enumeration will be invisible unless you read the trail's S3/CloudWatch Logs destination instead.

The log can be turned off or steered around: attackers run StopLogging/UpdateTrail/DeleteTrail, disable the trail's KMS key, or simply operate in a region the trail doesn't cover. Alert on those control-plane events themselves and confirm the trail is multi-region.

Identity attribution traps: assumed-role activity shows the role ARN, not the human — correlate sourceIdentity/session name; sourceIPAddress is often an AWS service hostname (*.amazonaws.com) for service-initiated calls, which naive geo/IP-anomaly logic mislabels.

Baseline & threshold evasion: "first-time API" rules misfire after legitimate new deployments; high-error-rate recon can be paced under thresholds. Tune with per-principal baselines and exclude known automation ARNs.

Validate the detection: check aws cloudtrail get-trail-status shows IsLogging: true and the trail is IsMultiRegionTrail; then perform a benign sensitive call (e.g., iam:CreateUser then delete) and confirm it surfaces in your pipeline within the expected window.

Prerequisites

Python 3.9+ with boto3 library