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Re-model the pentest agent into an autonomous, markdown-driven engine that turns a URL into a full engagement and delegates execution to a locally installed agentic CLI backend. Engine (neurosploit_agent/ + ./neurosploit launcher): - orchestrator composes ONE master prompt from the agent library + RL weights - backends: auto-detect & drive Claude Code / Codex / Grok CLI (+ Claude subscription); headless, autonomous, isolated workdir - mcp: Playwright MCP (.mcp.json) for browser-based proof-of-execution - rl: bounded per-agent reinforcement-learning weights w/ per-tech affinity, persisted to data/rl_state.json - models: latest registry incl. NVIDIA NIM provider (PR #28) - cli: interactive URL prompt + one-shot `run`, `backends`, `agents`, --dry-run Agent library (agents_md/, 213 total): - 196 vuln specialists incl. modern LLM/AI, cloud/K8s, API/auth, advanced injection, protocol smuggling, logic/crypto/supply-chain classes - 17 meta-agents: orchestrator, recon, exploit_validator, false_positive_filter, severity_assessor, impact_evaluator, reporter, rl_feedback + migrated expert roles - scripts/build_agents.py data-driven builder; REGISTRY.md index Docs: rewritten README.md, v3.3.0 RELEASE.md, .env.example (NVIDIA NIM, xAI, engine vars). Retire legacy Python orchestration (neurosploit.py + agent classes) to legacy/. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
32 lines
1.3 KiB
Markdown
32 lines
1.3 KiB
Markdown
# Cloud Metadata Exposure Specialist Agent
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## User Prompt
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You are testing **{target}** for Cloud Metadata Exposure.
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**Recon Context:**
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{recon_json}
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**METHODOLOGY:**
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### 1. Direct Metadata Access
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- AWS: `http://169.254.169.254/latest/meta-data/`
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- GCP: `http://metadata.google.internal/computeMetadata/v1/` (Header: Metadata-Flavor: Google)
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- Azure: `http://169.254.169.254/metadata/instance?api-version=2021-02-01` (Header: Metadata: true)
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### 2. Via SSRF
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- If SSRF exists, pivot to metadata endpoints
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- Check for IMDSv2 (AWS) requiring token
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### 3. Credential Extraction
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- AWS IAM role credentials at `/latest/meta-data/iam/security-credentials/[role]`
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- GCP service account token at `/computeMetadata/v1/instance/service-accounts/default/token`
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- Azure managed identity token
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### 4. Report
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'''
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FINDING:
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- Title: Cloud Metadata Exposed via [vector]
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- Severity: Critical
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- CWE: CWE-918
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- Cloud: [AWS/GCP/Azure]
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- Vector: [direct/SSRF]
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- Data Exposed: [instance info/credentials]
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- Impact: Cloud account takeover, lateral movement
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- Remediation: IMDSv2, network policies, SSRF protection
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'''
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## System Prompt
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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.
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