- Select all / Clear all buttons in the Leads step toolbar - respects the
current search filter, so filtering to "sql" then Select all only pins
those, not all 412 leads. The per-category master switch (already
select/deselect-all for that category, indeterminate when partial) was
the only bulk control before; this adds the "everything" case.
- '+ Custom lead' now generates an ACTUAL specialist-agent markdown file
(agents_md/vulns/custom_<slug>.md, same format every other agent uses)
via the claude CLI on the operator's Anthropic subscription
(claude-opus-4-8 by default - matches the harness's own default model),
instead of folding free text into --focus. The new lead is immediately
selectable and pinnable via --only like any other agent; verified the
Rust harness's own agent loader picks it up (agent count went 435 -> 436,
neurosploit agents confirmed it).
Two things found and fixed while wiring this up:
- the skip-permissions flag gave the model file/bash tool access, which
made it try to write the file itself and narrate doing so instead of
just returning text. Dropped the flag (pure text completion needs no
tools) and told it explicitly not to use any.
- Even so, defensively strip anything before the first '# ' heading
before saving, in case a model still prepends commentary.
Falls back to the old free-text-focus behavior if generation fails
(claude not installed/logged in, malformed output, timeout) so the
operator's intent isn't lost.
- New "Custom Leads" category, shown first, so generated leads have a
visible home instead of landing in the catch-all "Other" bucket.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0129WdYHccPsH27k5GGuwijd
🧠 NeuroSploit v4.0.0
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. Version-by-version changes live in 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 435 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 |
| AI / LLM red-team | neurosploit aitest <ai-url> |
jailbreaks & prompt injection + OWASP LLM Top 10 / MCP against a live AI agent |
| AI Skills / n8n | neurosploit skills <file|folder> |
white-box audit of Skill/plugin & n8n workflow definitions |
| 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 receipt (evidence, not
paraphrase). Empirical (raw tool output) for black-box/host/AI, symbolic
(
file:lineinto the reviewed source — a code citation is the receipt) for white-box SAST & skills audits, and either for grey-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 — any primitive pivots. 13 multi-stage chain agents (SQLi→RCE→LPE, SSRF→cloud creds, upload→LFI→RCE→LPE, CVE→RCE→pivot, …) plus a chaining doctrine that turns any confirmed foothold into the next step: reduce it to a primitive (exec / read / write / request-forgery / identity / secret) and pivot — file-upload→RCE, SSRF→metadata creds, IDOR→takeover — reusing looted creds and reasoning about business logic (payment/tenancy/workflow abuse). Each stage proven; strictly non-destructive (no data loss, no DB overwrite, no DoS).
- ☁️ 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. - 🤖 LLM red-teaming — 30 AI agents that jailbreak & prompt-inject a live AI system across scenarios: AdvPrefix, PAIR, TAP, Crescendo, many-shot, persona/DAN, encoding/obfuscation, refusal-suppression; plus indirect injection (RAG/web/email/tool output), goal hijacking, tool/function-call abuse, and system-prompt exfiltration. Each runs an attacker→LLM-judge loop (baseline refusal → technique → verdict) and proves the bypass with a benign, redacted receipt. Maps to OWASP LLM Top 10 (2025), MCP threats & OWASP AI Exchange; Skill/plugin & n8n files audited white-box.
- 🧰 Misconfig & CVE hunting → exploitation, safely — a full CVE pipeline:
version fingerprint (pin exact versions) → research analyst (map to
NVD/GHSA CVEs, judge reachability) → PoC finder (locate/vet/adapt a public
PoC) → exploit scripter (write a custom exploit when none exists). Every PoC
is written to the run's
pocs/folder and referenced in the report so findings are reproducible. Plus absurd-misconfig agents (exposed.git/.env, debug/actuator, default creds, dashboards, CORS) and rate-limit testing — all under a strict data-safety/PII guardrail (no destructive/state-changing actions; PII proven with a masked sample, never dumped). - 🎯 Re-test one vulnerability —
--only <agent>(repeatable / comma-separated) runs exactly the agent(s) you name and skips recon-based selection — re-test a single finding fast. Works onrun/whitebox/greybox;neurosploit agentslists the names. - 🔬 White-box stays white-box — code agents run under a static-review
doctrine (symbolic
file:linereceipts, source-to-sink taint tracing, manifest version→CVE) that forbids hallucinated live/black-box network actions, and can emit a repro PoC topocs/. - 🗣️ Natural-language REPL — in the interactive session, just describe what you want, in any language: "testa https://loja.com com opus, foco em SQLi, fora de escopo /admin, roda". A hybrid parser sets target/models/focus/ objective/out-of-scope and toggles (Burp, browser, votes, recon depth) and can launch — zero-token deterministic parse for the common shapes, model fallback for anything ambiguous. No flags to memorize.
- 🔀 CI/CD PR gate —
neurosploit pr <repo> <n> --fail-on criticalreviews a pull request, and on a confirmed finding at/above the threshold it fails the check, sets aneurosploit/securitycommit status, and posts a REQUEST_CHANGES review — so branch protection blocks the merge. Ready-made GitHub Actions workflows included (PR gate + a@neurosploitmention bot that runs a scan when a writer comments). See Integrations. - 🎯 Engagement objective & out-of-scope — give the goal/context and hard
exclusions in words (
/objective,/scope-out, or--objective/--out-of-scope); both steer every agent prompt. - 📸 Proof screenshots in reports — agents capture visual proof per finding
(
evidence/<finding-id>-N.png), embedded beside its vulnerability in the Typst/HTML/Markdown reports. - 🖥️ Local, uncensored & CPU-only models —
ollama:andllamacpp:run the whole engagement on your box with no API key and no data leaving the host.llamacpp:speaks to allama-serverOpenAI-compatible endpoint (LLAMACPP_BASE_URL, default localhost:8080); themodelis whatever gguf you loaded. Ideal for offline/air-gapped work and unfiltered offensive prompting. - 🕵️ 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 | 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.
🖥️ Web console (NEW in v4.0.0)
A browser UI for the same harness: a categorized lead board (toggle agents by category, add
custom leads, Start Exploitation), a live structured findings view, run history, and a real
REPL — all driven by spawning the compiled CLI, never a reimplementation of it.
cd neurosploit-rs && cargo build --release # once
node web/server.js # → http://localhost:4173
Zero npm dependencies. Full API reference: web/API.md.
🔌 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
# Same, but BLOCK the merge on a confirmed critical: fails the check, sets a
# `neurosploit/security` commit status, and posts a REQUEST_CHANGES review.
neurosploit pr digininja/DVWA 42 --model anthropic:claude-opus-4-8 --comment --fail-on critical
# 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 · PR gate (--fail-on: fail check + commit status + REQUEST_CHANGES) · watch branch |
GITHUB_TOKEN |
| GitLab | private clone for whitebox/greybox | GITLAB_TOKEN |
| Jira | one card per finding (--jira) |
JIRA_EMAIL, JIRA_API_TOKEN |
Automations (GitHub Actions)
Two ready-made workflows ship in examples/github-actions/ — copy
them into your repo:
neurosploit-pr-gate.yml— reviews every PR and blocks the merge on a confirmed critical. Make it enforcing: Settings → Branches → require theneurosploit-pr-gatestatus check (and/or require review to honor the REQUEST_CHANGES). SetANTHROPIC_API_KEY(or swap the model) in Actions secrets; the built-inGITHUB_TOKENcovers statuses/reviews.neurosploit-mention.yml— comment@neurosploiton a PR or issue to trigger a scan (only repo writers can). Text after the mention is the instruction (any language):@neurosploit focus SQLi and IDOR, or@neurosploit scan https://staging.appfor a black-box run.
📖 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 -v
Agents 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 -v
Each 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/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 MOONSHOT_API_KEY=... # moonshot:* (Kimi K3/K2)
export OPENROUTER_API_KEY=... # openrouter:*
export OPENCODE_API_KEY=... # opencode:* (OpenCode Zen gateway)
export NOUS_API_KEY=... # nous:* (Nous Portal — Hermes)
# ollama / llamacpp need 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 |
moonshot: |
MOONSHOT_API_KEY |
api.moonshot.ai |
openrouter: |
OPENROUTER_API_KEY |
openrouter.ai |
opencode: |
OPENCODE_API_KEY |
opencode.ai/zen (OpenCode Zen gateway) |
nous: |
NOUS_API_KEY |
inference-api.nousresearch.com (Hermes 4) |
ollama: |
(none) | localhost:11434 |
llamacpp: |
(none) | localhost:8080 |
Run ./target/release/neurosploit models for the full provider/model list.
Local, uncensored & CPU-only —
ollama:andllamacpp:run entirely on your box with no API key and no data leaving the host.llamacpp:targets allama-serverOpenAI-compatible endpoint (override withLLAMACPP_BASE_URL); themodelis whatever gguf you loaded. Ideal for offline engagements and unfiltered offensive prompting.
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 |
opencode: |
opencode |
opencode auth login (or /connect in the TUI) — Zen/plan account |
nous: |
hermes |
hermes setup --portal — Nous Portal OAuth |
opencode: also gets the Playwright MCP (--mcp) like anthropic/openai do.
nous: relies on Hermes's own built-in toolsets (web/terminal/computer-use)
instead — it has no CLI-level MCP hook.
./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 |
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.