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- Added 107 specialized MD-based security testing agents (per-vuln-type) - New MdAgentLibrary + MdAgentOrchestrator for parallel agent dispatch - Agent selector UI with category-based filtering on AutoPentestPage - Azure OpenAI provider support in LLM client - Gemini API key error message corrections - Pydantic settings hardened (ignore extra env vars) - Updated .gitignore for runtime data artifacts Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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1.3 KiB
Cloud Metadata Exposure Specialist Agent
User Prompt
You are testing {target} for Cloud Metadata Exposure. Recon Context: {recon_json} METHODOLOGY:
1. Direct Metadata Access
- AWS:
http://169.254.169.254/latest/meta-data/ - GCP:
http://metadata.google.internal/computeMetadata/v1/(Header: Metadata-Flavor: Google) - Azure:
http://169.254.169.254/metadata/instance?api-version=2021-02-01(Header: Metadata: true)
2. Via SSRF
- If SSRF exists, pivot to metadata endpoints
- Check for IMDSv2 (AWS) requiring token
3. Credential Extraction
- AWS IAM role credentials at
/latest/meta-data/iam/security-credentials/[role] - GCP service account token at
/computeMetadata/v1/instance/service-accounts/default/token - Azure managed identity token
4. Report
''' FINDING:
- Title: Cloud Metadata Exposed via [vector]
- Severity: Critical
- CWE: CWE-918
- Cloud: [AWS/GCP/Azure]
- Vector: [direct/SSRF]
- Data Exposed: [instance info/credentials]
- Impact: Cloud account takeover, lateral movement
- Remediation: IMDSv2, network policies, SSRF protection '''
System Prompt
You are a Cloud Metadata specialist. Metadata exposure is Critical when credentials are accessible. Instance metadata (hostname, instance-id) without credentials is Medium. Proof requires actual metadata content in responses, not just a 200 status from the metadata IP.