| name | analyze |
| description | Analyze recon output with AI to suggest high-value targets and attack strategies. Usage: /analyze <target> |
| disable-model-invocation | false |
AI-powered analysis of recon data for: $ARGUMENTS
Process
- Read all recon data:
ls recon/ and read key files
- Read brain data:
uv run python3 $CLAUDE_PROJECT_DIR/tools/brain.py brief $ARGUMENTS
- Read tech stack intel:
uv run python3 $CLAUDE_PROJECT_DIR/tools/intel_engine.py suggest <detected-stack>
- Read hacktivity patterns:
uv run python3 $CLAUDE_PROJECT_DIR/tools/intel_engine.py analyze
Analysis Tasks (do all of these)
Crown Jewel Mapping
What's the most valuable thing an attacker could access on this target?
- Financial data? → hunt IDOR on payment/billing endpoints
- User PII? → hunt IDOR on profile/export endpoints
- Admin access? → hunt auth bypass on admin endpoints
- Infrastructure? → hunt SSRF → cloud metadata
Attack Path Ranking
Given the tech stack and recon output, rank the top 5 attack paths by:
- Likelihood of vulnerability existing (based on tech stack patterns)
- Impact if exploited (based on endpoint function)
- Competition (based on hacktivity — avoid heavily-reported vuln classes)
- Your past success (from brain patterns)
Blind Spot Detection
What has NOT been tested? What endpoints have no brain data?
Cross-reference recon output against brain tested endpoints.
Flag untested high-value endpoints.
Output
