🧠 NeuroSploit v3.6.3
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 v3.6.3 — resumable interrupted runs + crash-proof browsing: If a run is interrupted (terminal closed, Ctrl-C, crash),
/continuenow relaunches it on the same target and carries the recovered findings forward — the offer appears right at launch. And opening/results,/findingor/reportwhile a run streams no longer corrupts the terminal: live output is paused for the picker (still captured in/logs) and restored on exit. (v3.6.2 added live Codex tool-by-tool streaming + the full activity feed in/logs//status; v3.6.1 added GPT-5.6 sol/terra/luna and the Codex exit-1 fix; v3.6.0 added AI-agent/LLM/MCP/Skills/n8n testing + onboarding wizard + Cloud scope.) (v3.5.4 added robust attack chaining + false-positive reduction; v3.5.3 GitHub/GitLab/Jira integrations; v3.5.2 the DEPTH doctrine + report-hygiene — 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 417 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 / AD and cloud (AWS/GCP/Azure) 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_assertgate 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. - 🔬 Deterministic HTTP probe — before the model recon, the harness runs a real request/response analysis (status/redirects, security headers, cookie flags, CORS reflection, tech fingerprint, linked JS, 404 baseline, high-signal paths) and feeds those observed facts into recon, so agent selection and exploitation decisions are grounded in evidence — not the model's guess.
- 🔗 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.
- ☁️ Cloud testing — AWS / GCP / Azure agents that drive the provider CLIs
(
aws/gcloud/az). Connect viacreds.yaml: AWS keys, a Google service-account JSON, or an Azure service principal — see Cloud credentials. - 🧰 Misconfig & CVE hunting, safely — dedicated agents for absurd
misconfigs (exposed
.git/.env, debug/actuator, default creds, dashboards, CORS), a CVE Hunter (smart, targetednuclei), a PoC Developer (writes reproducible scripts to the run'spocs/), and rate-limit testing — all under a strict data-safety/PII guardrail (no destructive or state-changing actions; PII proven with a masked sample, never dumped). - 🕵️ Burp/ZAP proxy —
/proxy <url>(or/burp) routes agent traffic through your local intercepting proxy so you can inspect & replay in Burp. - 🗺️ 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 olderv3.4.0branch.
📦 Install (one line)
Linux / macOS (x64 & arm64):
curl -fsSL https://raw.githubusercontent.com/JoasASantos/NeuroSploit/main/setup.sh | bashWindows (PowerShell, x64 & arm64):
irm https://raw.githubusercontent.com/JoasASantos/NeuroSploit/main/install.ps1 | iexSupported 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 --mcpFull step-by-step for every mode (black/white/grey/host) is in TUTORIAL.md.
No login? Use an API key instead — see Authentication.
🔌 Integrations (GitHub · GitLab · Jira)
Wire NeuroSploit into your SDLC. Toggle from the REPL (/integrations) or the CLI
(neurosploit integrations enable github|gitlab|jira). Tokens are never stored
— only the name of the env var is saved; the value is read from your environment.
export GITHUB_TOKEN=ghp_... # PAT with `repo` scope (private repos)
neurosploit integrations enable github
# Review a Pull Request's code (clones the PR head, white-box) and comment back:
neurosploit pr digininja/DVWA 42 --subscription --model anthropic:claude-opus-4-8 --comment
# Watch a branch and re-review on every new commit:
neurosploit watch myorg/private-app --branch main --subscription --model anthropic:claude-opus-4-8
# Private GitLab repo (token-injected clone) — works in whitebox/greybox:
export GITLAB_TOKEN=glpat-... ; neurosploit integrations enable gitlab
neurosploit whitebox https://gitlab.com/myorg/private-svc --subscription --model anthropic:claude-opus-4-8
# Open a Jira card per finding (any engagement):
export JIRA_EMAIL=you@org.com JIRA_API_TOKEN=... # set base/project once: /integrations setup jira
neurosploit whitebox https://github.com/myorg/app --jira --subscription --model anthropic:claude-opus-4-8| Integration | What you get | Env vars |
|---|---|---|
| GitHub | private clone · pr review + comment · watch branch | GITHUB_TOKEN |
| GitLab | private clone for whitebox/greybox | GITLAB_TOKEN |
| Jira | one card per finding (--jira) | JIRA_EMAIL, JIRA_API_TOKEN |
📖 Step-by-step setup for each tool: TUTORIAL-INTEGRATION.md.
☁️ Cloud credentials (AWS/GCP/Azure)
Add a cloud block to creds.yaml and the harness exports the right env vars so
the AWS/GCP/Azure agents can drive aws / gcloud / az. Secrets stay in your
file/secret-manager; agents do read-only enumeration first, never destructive.
# --- AWS: static keys (or a named profile) ---
aws:
access_key_id: AKIA...
secret_access_key: ...
# session_token: ... # if using temporary creds
region: us-east-1
# profile: my-sso-profile # alternative to keys
# --- GCP: service-account JSON (path recommended; inline single-line also works) ---
gcp:
service_account_json: /path/to/sa.json
project: my-project-id
# --- Azure: service principal (recommended for automation) ---
azure:
tenant_id: ...
client_id: ...
client_secret: ...
subscription_id: ...neurosploit host my-cloud-account --creds creds.yaml \
--subscription --model anthropic:claude-opus-4-8 -vAgents cover IAM privilege-escalation, storage exposure (S3/GCS/Blob), compute &
network exposure, secrets (Secrets Manager / Secret Manager / Key Vault),
service-account/SP abuse, and identity enumeration (Entra ID). Best-practice
auth: AWS access keys or profile; GCP a service-account JSON
(GOOGLE_APPLICATION_CREDENTIALS); Azure a service principal
(az login --service-principal).
👥 Multiple identities — access-control testing (IDOR / BOLA / BFLA)
Give NeuroSploit two or more named roles in creds.yaml and it authenticates
as each and tests cross-role access (a low-priv role reaching another user's
object or an admin function is a finding):
admin:
jwt: eyJ... # per role: jwt | header (raw) | cookie | apikey | login+username+password
user:
apikey: abc123 # → X-Api-Key: abc123
victim:
cookie: "session=deadbeef"neurosploit run https://app.example --creds creds.yaml \
--subscription --model anthropic:claude-opus-4-8 -vEach finding is proven with the authorized vs unauthorized request pair, under the data-safety guardrail (read-only, PII masked).
🏷️ Identification & attribution (anti-plagiarism)
Every request is tagged with an identifying User-Agent (default
NeuroSploit/<ver> …, change with /ua or NEUROSPLOIT_UA) plus an
X-NeuroSploit-Scan header, and every finding is stamped "Identified and
validated by NeuroSploit" — so provenance travels in the traffic, the finding
text, findings.json and the report footer.
Build
cd neurosploit-rs
cargo build --release # → target/release/neurosploitRequires 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/neurosploitOr 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 examplesOptions (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-proOr 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 -vHow 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 | running → complete 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.