Agent-Skills.md

Agent Skills: Performing Cloud Forensics with AWS CloudTrail

Perform forensic investigation of AWS environments using CloudTrail logs to reconstruct attacker activity, identify compromised credentials, and analyze API call patterns.

UncategorizedID: plurigrid/asi/performing-cloud-forensics-with-aws-cloudtrail

Repository

plurigrid/asi
plurigridLicense: MIT
165

Install this agent skill to your local

pnpm dlx add-skill https://github.com/plurigrid/asi/tree/HEAD/plugins/asi/skills/performing-cloud-forensics-with-aws-cloudtrail

Skill Files

Browse the full folder contents for performing-cloud-forensics-with-aws-cloudtrail.

Download Skill

Loading file tree…

plugins/asi/skills/performing-cloud-forensics-with-aws-cloudtrail/SKILL.md

Skill Metadata

Name
performing-cloud-forensics-with-aws-cloudtrail
Description
Perform forensic investigation of AWS environments using CloudTrail logs to reconstruct attacker activity, identify compromised credentials, and analyze API call patterns.

Performing Cloud Forensics with AWS CloudTrail

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

  1. Scope Investigation: Identify timeframe, affected accounts, and compromised credentials.
  2. Query CloudTrail: Use boto3 lookup_events or Athena to retrieve relevant API events.
  3. Filter by Indicators: Search for suspicious user agents, source IPs, and event names.
  4. Reconstruct Timeline: Build chronological sequence of attacker actions from API calls.
  5. Analyze Access Patterns: Identify data access, IAM changes, and resource modifications.
  6. Identify Persistence: Check for new IAM users, access keys, roles, or Lambda functions.
  7. 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]