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Mahipal
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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.
97 lines
3.3 KiB
Markdown
97 lines
3.3 KiB
Markdown
---
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name: performing-cloud-forensics-with-aws-cloudtrail
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description: Investigate AWS account compromise by querying CloudTrail with boto3's LookupEvents
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or AWS Athena SQL over S3-delivered logs, filtering on suspicious user agents, source IPs, and
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event names to reconstruct an attacker timeline. Use when tracing unauthorized API calls, S3
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data exfiltration, IAM privilege escalation, or credential exposure, and building a forensic
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report of findings and remediation steps.
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domain: cybersecurity
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subdomain: cloud-security
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tags:
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- cloud-security
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- aws
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- cloudtrail
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- forensics
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- incident-response
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- dfir
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- boto3
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- s3
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version: '1.0'
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author: mahipal
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license: Apache-2.0
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nist_csf:
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- PR.IR-01
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- ID.AM-08
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- GV.SC-06
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- DE.CM-01
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mitre_attack:
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- T1078.004
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- T1530
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- T1537
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- T1580
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- T1003
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---
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# Performing Cloud Forensics with AWS CloudTrail
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## When to Use
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- When investigating suspected AWS account compromise
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- After detecting unauthorized API calls or credential exposure
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- During incident response involving cloud infrastructure
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- When analyzing S3 data exfiltration or IAM privilege escalation
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- For post-incident forensic timeline reconstruction
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## Prerequisites
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- AWS account with CloudTrail enabled (management and data events)
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- IAM permissions for cloudtrail:LookupEvents, s3:GetObject, athena:StartQueryExecution
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- boto3 Python SDK installed
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- CloudTrail logs delivered to S3 with optional Athena table configured
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- AWS CLI configured with appropriate credentials
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## Workflow
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1. **Scope Investigation**: Identify timeframe, affected accounts, and compromised credentials.
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2. **Query CloudTrail**: Use boto3 lookup_events or Athena to retrieve relevant API events.
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3. **Filter by Indicators**: Search for suspicious user agents, source IPs, and event names.
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4. **Reconstruct Timeline**: Build chronological sequence of attacker actions from API calls.
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5. **Analyze Access Patterns**: Identify data access, IAM changes, and resource modifications.
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6. **Identify Persistence**: Check for new IAM users, access keys, roles, or Lambda functions.
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7. **Generate Report**: Produce forensic timeline with findings and remediation steps.
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## Key Concepts
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| Concept | Description |
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|---------|-------------|
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| LookupEvents | CloudTrail API to query management events (last 90 days) |
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| Athena Queries | SQL queries against CloudTrail logs in S3 for historical analysis |
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| User Agent Analysis | Identify tool signatures (AWS CLI, SDK, console, custom) |
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| AccessKeyId | Track activity by specific IAM access key |
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| EventName | AWS API action name (e.g., GetObject, CreateUser, AssumeRole) |
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| sourceIPAddress | Origin IP of API call for geolocation analysis |
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## Tools & Systems
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| Tool | Purpose |
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|------|---------|
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| boto3 CloudTrail client | Programmatic CloudTrail event lookup |
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| AWS Athena | SQL-based analysis of CloudTrail S3 logs |
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| AWS CLI | Command-line CloudTrail queries |
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| jq | JSON processing for CloudTrail event parsing |
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| CloudTrail Lake | Advanced event data store with SQL query support |
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## Output Format
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```
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Forensic Report: AWS-IR-[DATE]-[SEQ]
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Account: [AWS Account ID]
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Timeframe: [Start] to [End]
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Compromised Credentials: [Access Key IDs]
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Suspicious Events: [Count]
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Source IPs: [List of attacker IPs]
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Actions Taken: [API calls by attacker]
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Data Accessed: [S3 objects, secrets, etc.]
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Persistence Mechanisms: [New users, keys, roles]
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```
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