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Mahipal
2fb6a9faff
Each rewritten description now states both what the skill does (concrete capability, named tools/artifacts) and an explicit when-to-use trigger, improving agent discovery/activation. Grounded in each skill's own body; changes confined to the `description` field only (bodies and all other frontmatter untouched). Produced by a gated audit->rewrite->recheck loop (548 -> 0 flagged) with a sampled anti-invention check (0 ungrounded). Schema: 817/817 pass. Framework-ID gate: 0 defects.
3.3 KiB
3.3 KiB
name, description, domain, subdomain, tags, version, author, license, nist_csf, mitre_attack
| name | description | domain | subdomain | tags | version | author | license | nist_csf | mitre_attack | |||||||||||||||||
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| performing-cloud-forensics-with-aws-cloudtrail | 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. | cybersecurity | cloud-security |
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1.0 | mahipal | Apache-2.0 |
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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]