Detecting Aws Cloudtrail Anomalies

---
name: Tespit etme-aws-cloudtrail-anomalies
description: tespit etme
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.
tags:
- boto3
- anomaly-Tespit
- aws
- cloudtrail
- fetih
- cloud-security
- cybersecurity
- threat-Tespit
- siber-güvenlik
triggers:
- AWS
- Azure
- GCP
- anomalies
- api
- bulut güvenliği
- cloud
- cloud security
- cloudtrail
- Tespit etme
- incident
- threat
category: cloud-security
source_subdomain: cloud-security
nist_csf:
- PR.IR-01
- ID.AM-08
- GV.SC-06
- DE.CM-01
adapted_for: fetih
---

# Detection Aws Cloudtrail Anomalies


## Genel Bakış

AWS CloudTrail records API calls across AWS services. bu skill covers querying CloudTrail events with boto3's `lookup_events` API, building statistical baselines of normal API activity, Tespit etme 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.


## Ne Zaman Kullanılır

- investigating yaparken security incidents that require Tespit etme aws cloudtrail anomalies
- building yaparken Tespit rules or threat hunting queries for this domain
- SOC yaparken: analysts need structured procedures for this analysis type
- validating yaparken security monitoring coverage for related attack techniques

## Ön Gereksinimler

- Python 3.9+ with `boto3` library
- AWS credentials with CloudTrail read permissions (cloudtrail:LookupEvents)
- Understanding of AWS IAM and common API patterns
- CloudTrail enabled in target AWS account (management events at minimum)

## Adımlar

### Adım 1: Query CloudTrail Events
Use boto3 CloudTrail client's lookup_events to retrieve recent API activity with pagination.

### Adım 2: Build Activity Baseline
Aggregate events by user, source IP, event source, and event name to establish normal behavior patterns.

### Adım 3: tespit etme
Anomalies
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).

### Adım 4: Generate Tespit Report
Produce a JSON report with anomaly scores, top suspicious users, and recommended investigation actions.

## Expected Output

JSON report with event statistics, baseline deviations, anomalous users/IPs, sensitive API calls, and error rate analysis.

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