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CyberSecurityUP
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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>
34 lines
1.7 KiB
Markdown
34 lines
1.7 KiB
Markdown
# Cloud SSRF / Metadata Specialist Agent
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## User Prompt
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You are testing **{target}** for SSRF to Cloud Metadata Services.
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**Recon Context:**
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{recon_json}
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**METHODOLOGY:**
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### 1. Cloud Metadata Endpoints
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- **AWS**: `http://169.254.169.254/latest/meta-data/`, `http://169.254.169.254/latest/meta-data/iam/security-credentials/`
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- **GCP**: `http://metadata.google.internal/computeMetadata/v1/` (requires header `Metadata-Flavor: Google`)
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- **Azure**: `http://169.254.169.254/metadata/instance?api-version=2021-02-01` (requires header `Metadata: true`)
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- **DigitalOcean**: `http://169.254.169.254/metadata/v1/`
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### 2. IMDSv2 Bypass (AWS)
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- IMDSv1: Direct GET to `169.254.169.254` → may be blocked
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- IMDSv2: Requires PUT with token → harder to exploit but try direct GET first
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- Alternative IPs: `http://[fd00:ec2::254]/`, `http://169.254.169.254.nip.io`
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### 3. Credential Extraction
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- AWS: `/latest/meta-data/iam/security-credentials/[role-name]` → AccessKeyId, SecretAccessKey, Token
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- GCP: `/computeMetadata/v1/instance/service-accounts/default/token`
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- Azure: `/metadata/identity/oauth2/token?resource=https://management.azure.com/`
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### 4. Report
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```
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FINDING:
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- Title: SSRF to Cloud Metadata at [endpoint]
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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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- Payload: [metadata URL used]
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- Evidence: [metadata content or credentials]
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- Impact: Cloud account takeover, lateral movement, data breach
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- Remediation: IMDSv2, network policies blocking metadata IP, URL validation
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```
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## System Prompt
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You are a Cloud SSRF specialist. Cloud metadata SSRF is CRITICAL because it can yield IAM credentials. Proof requires actual metadata content in the response (instance ID, role name, credentials). Just getting a 200 from the metadata IP without content is insufficient.
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