About

Imported from mukul975/anthropic-cybersecurity-skills (skills/performing-cloud-forensics-with-aws-cloudtrail/SKILL.md). Install upstream with npx skills add mukul975/anthropic-cybersecurity-skills --skill performing-cloud-forensics-with-aws-cloudtrail. Copyright stays with the author (Apache-2.0).

Performing Cloud Forensics with AWS CloudTrail

Name: performing-cloud-forensics-with-aws-cloudtrail
Author: mukul975

When to Use

When investigating suspected AWS account compromise
After detecting unauthorized API calls or credential exposure
During incident response involving cloud infrastructure
When analyzing S3 data exfiltration or IAM privilege escalation
For post-incident forensic timeline reconstruction

Prerequisites

AWS account with CloudTrail enabled (management and data events)
IAM permissions for cloudtrail:LookupEvents, s3:GetObject, athena:StartQueryExecution
boto3 Python SDK installed
CloudTrail logs delivered to S3 with optional Athena table configured
AWS CLI configured with appropriate credentials

Workflow

Scope Investigation: Identify timeframe, affected accounts, and compromised credentials.
Query CloudTrail: Use boto3 lookup_events or Athena to retrieve relevant API events.
Filter by Indicators: Search for suspicious user agents, source IPs, and event names.
Reconstruct Timeline: Build chronological sequence of attacker actions from API calls.
Analyze Access Patterns: Identify data access, IAM changes, and resource modifications.
Identify Persistence: Check for new IAM users, access keys, roles, or Lambda functions.
Generate Report: Produce forensic timeline with findings and remediation steps.

Key Concepts

Concept	Description
LookupEvents	CloudTrail API to query management events (last 90 days)
Athena Queries	SQL queries against CloudTrail logs in S3 for historical analysis
User Agent Analysis	Identify tool signatures (AWS CLI, SDK, console, custom)
AccessKeyId	Track activity by specific IAM access key
EventName	AWS API action name (e.g., GetObject, CreateUser, AssumeRole)
sourceIPAddress	Origin IP of API call for geolocation analysis

Tools & Systems

Tool	Purpose
boto3 CloudTrail client	Programmatic CloudTrail event lookup
AWS Athena	SQL-based analysis of CloudTrail S3 logs
AWS CLI	Command-line CloudTrail queries
jq	JSON processing for CloudTrail event parsing
CloudTrail Lake	Advanced event data store with SQL query support

Output Format

Forensic Report: AWS-IR-[DATE]-[SEQ]
Account: [AWS Account ID]
Timeframe: [Start] to [End]
Compromised Credentials: [Access Key IDs]
Suspicious Events: [Count]
Source IPs: [List of attacker IPs]
Actions Taken: [API calls by attacker]
Data Accessed: [S3 objects, secrets, etc.]
Persistence Mechanisms: [New users, keys, roles]

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml

targets:
  - https://api.opensmartroute.ai/api/v1/registry/mukul975-anthropic-cybersecurity-skills-performing-cloud-e8609c/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

mukul975-anthropic-cybersecurity-skills-performing-cloud-e8609c.ocm.jsonjson

{
  "ocm": "1",
  "id": "mukul975-anthropic-cybersecurity-skills-performing-cloud-e8609c",
  "kind": "skill",
  "name": "performing-cloud-forensics-with-aws-cloudtrail",
  "description": "Investigate AWS account compromise by querying CloudTrail with boto3's LookupEvents or AWS Athena SQL over S3-delivered logs, filtering on suspicious user agents, source IPs, and event names to reconstruct an attacker timeline. Use when tracing unauthorized API calls, S3 data exfiltration, IAM privilege escalation, or credential exposure, and building a forensic report of findings and remediation steps.",
  "publisher": "mukul975",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "coding",
      "data_analysis"
    ],
    "tags": [
      "skill-md",
      "cloud-security",
      "aws",
      "cloudtrail",
      "forensics",
      "incident-response",
      "dfir",
      "boto3",
      "s3",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Investigate AWS account compromise by querying CloudTrail with boto3's LookupEvents or AWS Athena SQL over S3-delivered logs, filtering on suspicious user agents, source IPs, and event names to reconstruct an attacker timeline. Use when tracing unauthorized API calls, S3 data exfiltration, IAM privilege escalation, or credential exposure, and building a forensic report of findings and remediation steps."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/mukul975/anthropic-cybersecurity-skills",
      "path": "skills/performing-cloud-forensics-with-aws-cloudtrail/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/mukul975/anthropic-cybersecurity-skills/blob/HEAD/skills/performing-cloud-forensics-with-aws-cloudtrail/SKILL.md",
      "key": "mukul975/anthropic-cybersecurity-skills/skills/performing-cloud-forensics-with-aws-cloudtrail/SKILL.md"
    },
    "license": "Apache-2.0"
  },
  "instructions": "# Performing Cloud Forensics with AWS CloudTrail\n\n## When to Use\n\n- When investigating suspected AWS account compromise\n- After detecting unauthorized API calls or credential exposure\n- During incident response involving cloud infrastructure\n- When analyzing S3 data exfiltration or IAM privilege escalation\n- For post-incident forensic timeline reconstruction\n\n## Prerequisites\n\n- AWS account with CloudTrail enabled (management and data events)\n- IAM permissions for cloudtrail:LookupEvents, s3:GetObject, athena:StartQueryExecution\n- boto3 Python SDK installed\n- CloudTrail logs delivered to S3 wi",
  "cost": {
    "context_tokens": 645
  }
}

Fetch it by URL: GET /api/v1/registry/mukul975-anthropic-cybersecurity-skills-performing-cloud-e8609c/manifest?version=1.0.0

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