lumoslab-innovation/openhunteraiLocal-first AI red team for web, API, and LLM application security. Attacker-style reasoning, evidence-backed findings, and skills for AI coding agents.
Your local AI red team.
Attacker-style reasoning for web, API, and LLM application security.
Quick start · Agent skill · Assessment model · Architecture · Docs · Star history
OpenHunterAI brings scope, scan activity, findings, and remediation into one local workspace. Start without an account, connect your model providers, and assess .
| Capability | What you get |
|---|---|
| Local workspace | No signup; projects and scan records in your local database |
| Explicit scope | Domain verification, deterministic plans, human approval gates |
| Multiple signal sources | Browser inspection, recon, ZAP, and a Nuclei adapter |
| AI-assisted investigation | OpenHack/Strix adapter boundaries; bring your own runtimes |
| Evidence & remediation | Sanitized findings, coverage gaps, fix guidance, manual retest |
| Portable workflow | A skill for Codex, Claude Code, Gemini CLI, Grok Build, and OMP |
Alpha. Integration coverage depends on configured runtimes. A healthy workspace or an empty report does not prove a target is secure.
OpenHunterAI keeps the useful core of the 48bf9036 technical requirements: assess externally observable behaviour from an attacker's perspective. Source code is not required. Every run stays constrained to a verified public target and an approved scope.
flowchart LR
S["1. Lock scope"] --> M["2. Map surface"]
M --> B["3. Establish baseline"]
B --> H["4. Test bounded hypotheses"]
H --> E["5. Gate evidence"]
E --> R["6. Report and retest"]| Stage | Output | Control |
|---|---|---|
| Scope lock | Verified host, approved paths, scan plan | Authorization before work begins |
| Surface mapping | Browser and recon signals | Public, in-scope surface only |
| Baseline | Normal responses and coverage context | Bounded workers and adapter policies |
| Hypothesis testing | Candidate security signals | No destructive actions; sensitive validation needs approval |
| Evidence gate | Sanitized, reproducible finding | Separate observed signals from analyst judgement |
| Report and retest | Fix guidance, limitations, manual confirmation | A human owns impact decisions and closure |
OpenAPI/Swagger descriptions, Postman examples, sanitized HTTP captures, and dedicated test accounts can help define the agreed test surface. Automated import or retention of raw sensitive traffic is not a promised capability.
Requires Git, Node.js 22+, and Docker with Compose v2.
git clone https://github.com/LumosLab-Innovation/OpenHunterAI.git
cd OpenHunterAI
node ops/local.mjs start
Open localhost:3001. First startup builds the images,
applies database migrations, and creates a private .env.local with generated secrets.
.env.local; run node ops/local.mjs restart.| Command | Purpose |
|---|---|
node ops/local.mjs status | Inspect services |
node ops/local.mjs logs public-api | Diagnose API errors |
node ops/local.mjs stop | Stop; keep database volumes |
Included: browser inspection, ZAP, recon, and the Nuclei adapter.
Bring separately: OpenHack and Strix runtimes.
Optional interactive target-login capture: node ops/local.mjs start --with-browser.
Before scanning, resolve the Nuclei template-policy blocker. The adapter is packaged, but a reviewed template bundle is not yet supplied.
Local means the workspace runs on your machine, not permission to scan localhost/private networks. Keep its ports on loopback. Setup, model configuration, and troubleshooting →
Run in the application repository you want your agent to assess:
npx --yes skills add LumosLab-Innovation/OpenHunterAI --skill openhunter --agent codex claude-code gemini-cli grok --yes
Reload your coding agent, then ask:
Use OpenHunter to check my workspace and prepare a scoped security assessment. Wait for my approval before starting a scan.
OMP discovers the shared .agents/skills installation through its Agents
provider. The skill includes a read-only API helper; installation does not start
a scan. Client compatibility →
flowchart LR
UI["Local workspace<br/>React + Vite"] --> API["Public API<br/>Scope + scan plan"]
API --> BUS["NATS<br/>Orchestrator + workers"]
BUS --> EVIDENCE["Internal API<br/>Findings + reporting"]
EVIDENCE --> DB[("Postgres")]
API <--> DB
API -->|"Activity + reports"| UIThe public API builds the plan; Go workers execute it through bounded adapters. Signals pass through the findings policy before entering reports. Reporting is a backend service, not a separate scan worker.
Report a bug, suggest an improvement, or help clarify the docs. Read contribution rules first; disclose vulnerabilities privately, without credentials or raw target data.
Source-available under PolyForm Noncommercial 1.0.0. Commercial licensing: LICENSING.md. Upstream tools and attribution retain their own notices.