界面已本地化;技能介绍与说明文档按所选语言由 AI 自动翻译,代码、命令、路径和专业术语保留原文,以原作者文档为准。
探索技能
效率与协作 · SKILL.md

performing-cloud-forensics-with-aws-cloudtrail

performing-cloud-forensics-with-aws-cloudtrail

【效率与协作】Perform forensic investigation of AWS environments using CloudTrail logs to reconstruct attacker activity, identify compromised credentials, and analyze API call patterns.

独立 GitHub 快照 · 自动分类 · 以原作者文档为准

技能说明

GitHub

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. domain: cybersecurity subdomain: cloud-security tags: [cloud-security, aws, cloudtrail, forensics, incident-response, dfir, boto3, s3] version: "1.0" author: mahipal license: Apache-2.0

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

ConceptDescription
LookupEventsCloudTrail API to query management events (last 90 days)
Athena QueriesSQL queries against CloudTrail logs in S3 for historical analysis
User Agent AnalysisIdentify tool signatures (AWS CLI, SDK, console, custom)
AccessKeyIdTrack activity by specific IAM access key
EventNameAWS API action name (e.g., GetObject, CreateUser, AssumeRole)
sourceIPAddressOrigin IP of API call for geolocation analysis

Tools & Systems

ToolPurpose
boto3 CloudTrail clientProgrammatic CloudTrail event lookup
AWS AthenaSQL-based analysis of CloudTrail S3 logs
AWS CLICommand-line CloudTrail queries
jqJSON processing for CloudTrail event parsing
CloudTrail LakeAdvanced 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]
我的收藏