Files
CyberSecurityUP e4efa9bbb0 v3.5.2 — Exploitation Depth & Report Hygiene
Distilled from reviewing real AI-pentest output that kept stopping at "exposed"
instead of "exploited". Pure-additive, back-compatible.

Behavior (injected into black/grey/chain exploit prompts via DEPTH_DOCTRINE):
- Exposed → exploited: any info-disclosure / exposed service/WSDL / leaked
  credential|token / reachable dev host MUST be used before it's a finding;
  otherwise it's a lead, not a confirmed High/Critical.
- Chain across modules: reuse obtained session/JWT/cookie/credential and pivot
  to IDOR/privesc/exfil; report the chain, not isolated parts.
- Decode & fingerprint → CVE; audit tokens (alg-confusion/none/kid/JWKS, weak
  HS256 secret cracking, lifecycle).

Deterministic post-pass (new crates/harness/src/hygiene.rs, wired into finish()):
- calibrate severity to PROVEN impact — unproven High/Critical (hedged, no
  payload, thin evidence) capped to Medium and re-titled "(potential)";
- depth_audit — flag exposures on a host with no real exploit;
- hygiene_summary — advise consolidating hygiene classes repeated across assets.
Unit tests cover calibration + depth audit.

5 new doctrine meta-agents (scripts/build_methodology_v352.py → agents_md/meta/):
exploit_depth_doctrine, finding_chainer, artifact_decoder, token_auditor,
report_calibrator (meta 17→22, total 343→348).

Version bumped 3.5.1 → 3.5.2 across crates/app/installers/docs; RELEASE/README
updated.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-26 11:31:11 -03:00

14 KiB
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🧠 NeuroSploit v3.5.2

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Autonomous, multi-model penetration-testing harness — Rust, CLI-only.
by Joas A Santos & Red Team Leaders

If this is useful, star the repo — it helps a lot.

📖 New here? Read the full Tutorial & User Guide → — every mode, flag, config and example explained.

🆕 New in v3.5.2 — Exploitation Depth & Report Hygiene: a DEPTH doctrine makes the engine use what it finds (exposed → exploited), chain findings across modules, decode/fingerprint artifacts → CVEs, and audit tokens (JWT alg-confusion / weak HS256 secrets). A deterministic post-pass calibrates severity to proven impact and consolidates duplicated hygiene findings. See RELEASE.md.


NeuroSploit turns a URL, a source repository, a running app, or a host/IP into an autonomous security engagement. A Rust harness (tokio) drives a pool of LLMs — via API key or local subscription (Claude Code / Codex / Gemini / Grok) — recons the target, intelligently selects only the agents that match the discovered surface, runs them in parallel, chains findings into deeper impact, and validates every claim by cross-model voting + tool-receipt grounding before reporting. It ships 329 markdown agents and a Mission Control TUI.

Engagement modes

Mode Command What it does
Black-box neurosploit run <url> recon → select → exploit → vote → report
White-box neurosploit whitebox <repo> source/SAST review (file:line evidence)
Grey-box neurosploit greybox <repo> --url <app> code review + live exploitation together
Host/Infra neurosploit host <ip> --creds creds.yaml Linux / Windows / Active Directory testing
Mission Control neurosploit tui <url> live TUI panels + composer during the run
Interactive neurosploit persistent REPL session (resumes per project)

Highlights

  • 🧠 POMDP belief + value-of-information — the target is partially observable, so findings aren't booleans: a property-graph belief carries probabilities, and "scan more vs exploit now" falls out of belief entropy. The may_assert gate is a mathematical anti-hallucination rule (don't claim exploitability while the belief is diffuse).
  • 🧾 Grounding — hard rule: no claim without a tool receipt (raw tool output, not paraphrase). Empirical for black-box, symbolic (file:line) for white-box; ungrounded claims are demoted.
  • 🔗 Attack chaining — 12 multi-stage chain agents (SQLi→RCE→LPE, SSRF→AWS creds, upload→LFI→RCE→LPE, default-creds→domain, …); each stage proven before advancing.
  • 🗺️ Attack graph & kill chain — findings mapped to OWASP / CWE / MITRE ATT&CK / stage; rendered as a Mermaid graph in the report.
  • Cross-model validation — a different model adjudicates each finding; RL-weighted, recon-aware agent selection.
  • 🛰️ Mission Control TUI — live header/feed/findings/targets panels + a composer you can type in while the run streams (summary, pause, …).
  • 💾 Per-project memory<cwd>/.neurosploit/ keeps session, run history and command history; the REPL resumes on reopen. No database required.
  • 🪙 Token/cost telemetry, per-agent attribution, graceful Ctrl-C → report or discard, Typst/HTML/JSON/MD reports.

This is the slim, Rust-only distribution (neurosploit-rs/ + agents_md/). The earlier Python engine and web GUIs live on the older v3.4.0 branch.


📦 Install (one line)

Linux / macOS (x64 & arm64):

curl -fsSL https://raw.githubusercontent.com/JoasASantos/NeuroSploit/main/setup.sh | bash

Windows (PowerShell, x64 & arm64):

irm https://raw.githubusercontent.com/JoasASantos/NeuroSploit/main/install.ps1 | iex

Supported platforms

OS x64 arm64
Linux (Kali recommended)
macOS (Apple Silicon)
Windows

Pure Rust + stdlib, so it builds natively everywhere a stable Rust toolchain runs. The installer auto-detects OS/arch and installs Rust if missing. On native Windows use install.ps1; under WSL2 / Git Bash the setup.sh one-liner also works.

The installer auto-installs Rust if needed, clones the repo to ~/.neurosploit, builds the release binary, and links neurosploit into ~/.local/bin. Re-run it any time to update. Tweak with env vars: NEUROSPLOIT_REF (branch/tag), NEUROSPLOIT_DIR, PREFIX.

Prefer to build by hand?

git clone https://github.com/JoasASantos/NeuroSploit && cd NeuroSploit/neurosploit-rs
cargo build --release      # → target/release/neurosploit

Quick start (60 seconds)

# easiest path — just run it; the interactive session asks everything:
neurosploit

# or one-liner (subscription login, no API key needed):
neurosploit run http://testphp.vulnweb.com/ --subscription --model anthropic:claude-opus-4-8 -v

# white-box — review a source repository (SAST agents, file:line evidence):
git clone https://github.com/digininja/DVWA /tmp/DVWA
neurosploit whitebox /tmp/DVWA --subscription --model anthropic:claude-opus-4-8 -v

# grey-box — review the code AND exploit the running app together:
neurosploit greybox /tmp/DVWA --url http://localhost:8080/ --creds creds.yaml \
  --subscription --model anthropic:claude-opus-4-8 --mcp -v

# host / infra — Linux / Windows / Active Directory (SSH/Win creds in creds.yaml):
neurosploit host 10.0.0.10 --creds creds.yaml --subscription --model anthropic:claude-opus-4-8 -v

# 🛰  Mission Control TUI — live panels (header/feed/findings/targets) + a composer
#    you can type in WHILE the run streams (summary · pause · errors · notes):
neurosploit tui http://testphp.vulnweb.com/ --subscription --model anthropic:claude-opus-4-8 --mcp

Full step-by-step for every mode (black/white/grey/host) is in TUTORIAL.md.

No login? Use an API key instead — see Authentication.


Build

cd neurosploit-rs
cargo build --release        # → target/release/neurosploit

Requires a Rust toolchain (rustup). Recommended: run on Kali Linux (or the Kali Docker image) so the offensive tools the agents use are already present:

docker run -it --rm kalilinux/kali-rolling
apt update && apt install -y curl nmap ffuf nodejs npm
# rustscan (faster port scan): cargo install rustscan   (or grab a release from GitHub)

The agents degrade gracefully: if rustscan isn't installed they use nmap; if neither, they probe with curl. If a Playwright MCP browser is available they use it for JS-heavy pages, otherwise they fall back to curl.


Usage

Run with no arguments for an interactive wizard:

./target/release/neurosploit

Or drive it directly:

# Black-box — subscription (no API key), Opus, browser via Playwright if present, verbose
./target/release/neurosploit run http://testphp.vulnweb.com/ \
    --subscription --model anthropic:claude-opus-4-8 --mcp -v

# Black-box — API keys, multi-model voting panel (1st finds, others adjudicate)
./target/release/neurosploit run http://testphp.vulnweb.com/ \
    --model anthropic:claude-opus-4-8 --model openai:gpt-5.1 --vote-n 3

# White-box — clone a vulnerable app and review its source
git clone https://github.com/digininja/DVWA /tmp/DVWA
./target/release/neurosploit whitebox /tmp/DVWA \
    --subscription --model anthropic:claude-opus-4-8 -v

# Offline pipeline self-test (no keys/login needed)
./target/release/neurosploit run http://testphp.vulnweb.com/ --offline

# Utilities
./target/release/neurosploit agents     # library counts
./target/release/neurosploit models      # providers & models
./target/release/neurosploit --help        # full help with examples

Options (run / whitebox)

Flag Meaning
--model provider:model Repeatable. First = primary; the rest fail over and form the voting jury.
--subscription Use the local CLI login (Claude/Codex/Gemini/Grok) instead of an API key.
--mcp Enable Playwright MCP (auto-provisioned via npx; backends without MCP use built-in tools).
--vote-n N How many models must agree a finding is real (default 3 / 2 for whitebox).
--max-agents N Cap agents run (0 = all matching the recon).
--offline Exercise the full pipeline without calling any model.
-v, --verbose Log each agent as it launches, recon, and votes.

Authentication — run via API key or subscription

You can run NeuroSploit two ways. They're independent: pick per run.

1) Via API (provider API key)

Export the key(s) for the providers in your model panel, then run without --subscription. Any OpenAI-compatible provider works.

# pick one or more, depending on the models you select
export ANTHROPIC_API_KEY=sk-ant-...        # anthropic:claude-*
export OPENAI_API_KEY=sk-...               # openai:gpt-*
export GEMINI_API_KEY=AIza...              # gemini:gemini-*
export XAI_API_KEY=xai-...                 # xai:grok-*
export NVIDIA_NIM_API_KEY=nvapi-...        # nvidia_nim:*
export DEEPSEEK_API_KEY=...                # deepseek:*
export MISTRAL_API_KEY=...                 # mistral:*
export DASHSCOPE_API_KEY=...               # qwen:*  (Alibaba DashScope)
export GROQ_API_KEY=...                    # groq:*
export TOGETHER_API_KEY=...                # together:*
export OPENROUTER_API_KEY=...              # openrouter:*
# ollama needs no key (local)

# then run via API (note: NO --subscription)
./target/release/neurosploit run http://testphp.vulnweb.com/ \
    --model anthropic:claude-opus-4-8 --vote-n 3 -v

# multi-provider voting panel via API (1st finds, the others adjudicate)
./target/release/neurosploit run http://testphp.vulnweb.com/ \
    --model anthropic:claude-opus-4-8 --model openai:gpt-5.1 --model gemini:gemini-2.5-pro

Or put the keys in a .env and source it (cp .env.example .env; edit; set -a; . ./.env; set +a).

Provider → env var → endpoint (all OpenAI-compatible):

--model prefix Env var Base URL
anthropic: ANTHROPIC_API_KEY api.anthropic.com
openai: OPENAI_API_KEY api.openai.com
gemini: GEMINI_API_KEY generativelanguage.googleapis.com
xai: XAI_API_KEY api.x.ai
nvidia_nim: NVIDIA_NIM_API_KEY integrate.api.nvidia.com
deepseek: DEEPSEEK_API_KEY api.deepseek.com
mistral: MISTRAL_API_KEY api.mistral.ai
qwen: DASHSCOPE_API_KEY dashscope-intl.aliyuncs.com
groq: GROQ_API_KEY api.groq.com
together: TOGETHER_API_KEY api.together.xyz
openrouter: OPENROUTER_API_KEY openrouter.ai
ollama: (none) localhost:11434

Run ./target/release/neurosploit models for the full provider/model list.

2) Via subscription (no API key)

--subscription drives your local agentic-CLI login instead of an API key — install and log into one of the CLIs first:

--model prefix CLI used Login
anthropic: claude (Claude Code) claude then /login
openai: codex codex login
gemini: gemini gemini login
xai: grok grok login
./target/release/neurosploit run http://testphp.vulnweb.com/ \
    --subscription --model anthropic:claude-opus-4-8 --mcp -v

How it works

target ─▶ recon (curl/nmap/…) ─▶ INTELLIGENT agent selection (recon-aware)
       ─▶ parallel exploitation ─▶ cross-model validation vote
       ─▶ severity/score ─▶ report (HTML + Typst PDF) ─▶ RL reward update

Every run writes a self-contained folder runs/ns-<ts>-<target>/:

File Contents
status.json runningcomplete with a summary
recon.json / recon.md mapped attack surface
exploitation.md raw per-agent transcript
findings.json / findings.md validated findings (reuse by other tools/AIs)
report.html, report.typ, report.pdf final report (PDF via the Typst engine)

A reinforcement-learning reward store (data/rl_state_rs.json) biases agent selection on future runs.

Agent library — agents_md/ (303)

Category Count Purpose
vulns/ 196 Exploit a specific vulnerability class
recon/ 12 Information gathering / attack surface
code/ 78 White-box source-code (SAST) review
meta/ 17 Orchestrator, validator, scorers, reporter, RL

Each agent is a self-contained markdown playbook (## User Prompt methodology + ## System Prompt strict anti-false-positive rules). Drop a new .md into the matching folder and the harness picks it up.


Safety

For authorized testing only. Agents are instructed to stay in scope, never run destructive/DoS actions, and require proof-of-exploitation. You are responsible for having permission for any target.

Credits

Joas A Santos & Red Team Leaders.

License

MIT.