What it does. Detect unusual API call patterns in AWS CloudTrail logs using boto3, Part of mukul975/Anthropic-Cybersecurity-Skills (817 security skills) (mukul975/Anthropic-Cybersecurity-Skills).

Install

• npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-aws-cloudtrail-anomalies, or copy the skill folder into ~/.claude/skills/detecting-aws-cloudtrail-anomalies/.
• Raw file: curl -sL https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/HEAD/skills/detecting-aws-cloudtrail-anomalies/SKILL.md

SKILL.md (verbatim)

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
mitre_attack:
- T1078.004
- T1580
- T1538
- T1098.001
- T1526
mitre_f3:
  version: '1.1'
  tactics:
  - initial-access
  - positioning
  - defense-impairment
  techniques:
  - id: F1006.001
    name: 'Account Takeover: Exposed API Key'
    tactic: initial-access
    source: f3
  - id: T1586.003
    name: 'Compromise Accounts: Cloud Accounts'
    tactic: resource-development
    source: attack
  - id: F1005
    name: Account Manipulation
    tactic: positioning
    source: f3
  - id: F1005.002
    name: 'Account Manipulation: Add Authorized User'
    tactic: positioning
    source: f3
  - id: F1005.001
    name: 'Account Manipulation: Account Linking'
    tactic: defense-impairment
    source: f3

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

Prerequisites

• 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)

Steps

Step 1: Query CloudTrail Events

Use boto3 CloudTrail client's lookup_events to retrieve recent API activity with pagination.

Step 2: Build Activity Baseline

Aggregate events by user, source IP, event source, and event name to establish normal behavior patterns.

Step 3: Detect 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).

Step 4: Generate Detection 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.

Other files in this skill

• LICENSE
• references/api-reference.md
• scripts/agent.py

references/api-reference.md (verbatim)

API Reference: Detecting AWS CloudTrail Anomalies

boto3 CloudTrail API

import boto3

client = boto3.client("cloudtrail", region_name="us-east-1")

# Paginated event lookup
paginator = client.get_paginator("lookup_events")
pages = paginator.paginate(
    StartTime=datetime(2025, 1, 1),
    EndTime=datetime.utcnow(),
    LookupAttributes=[{"AttributeKey": "EventName", "AttributeValue": "ConsoleLogin"}],
    PaginationConfig={"MaxItems": 500, "PageSize": 50},
)
for page in pages:
    for event in page["Events"]:
        ct = json.loads(event["CloudTrailEvent"])
        print(ct["sourceIPAddress"], event["EventName"])

CloudTrail Event Fields

Sensitive API Calls to Monitor

Rate Limits

• lookup_events: 2 requests/second per account per region
• Maximum lookback: 90 days
• Max results per page: 50 events

References

• boto3 CloudTrail: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/cloudtrail.html
• CloudTrail Insights: https://docs.aws.amazon.com/awscloudtrail/latest/userguide/logging-insights-events-with-cloudtrail.html
• LookupEvents API: https://docs.aws.amazon.com/awscloudtrail/latest/APIReference/API_LookupEvents.html

Back to mukul975/Anthropic-Cybersecurity-Skills (817 security skills) or Agent skills.