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efca3ec611
Mapped every skill to NIST CSF 2.0 subcategory IDs (GV/ID/PR/DE/RS/RC functions) based on subdomain and content analysis. Restores 11 skills corrupted during prior rebase, re-enriching with ATLAS, D3FEND, NIST AI RMF, and CSF 2.0 fields. All 754 skills now carry structured mappings for all 5 security frameworks: - MITRE ATT&CK (in tags) - MITRE ATLAS v5.5 (atlas_techniques) - MITRE D3FEND v1.3 (d3fend_techniques) - NIST AI RMF 1.0 (nist_ai_rmf) - NIST CSF 2.0 (nist_csf)
3.0 KiB
3.0 KiB
name, description, domain, subdomain, tags, version, author, license, nist_csf
| name | description | domain | subdomain | tags | version | author | license | nist_csf | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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. | cybersecurity | cloud-security |
|
1.0 | mahipal | 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
- 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]