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一分鐘完成驗證AI engineering + security team for your codebase: understands intended behavior, reviews it, tests attacks safely in sandboxes, patches verified issues, and keeps monitoring. Built for HackATL
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檢視完整 README ↗Status: implementation in progress. Runtime packages and integration tests now exist. Specifications still describe capabilities beyond the implemented scope. See Current implementation status.
An autonomous software engineering and cybersecurity platform, being built for HackATL and intended to grow into a real product.
The one-line concept: an AI engineering team that understands your software, makes sure it works correctly, challenges its security, repairs verified problems, and keeps defending it after deployment.
| Pillar | Question it answers | Spec |
|---|---|---|
| 1. Code intelligence, review & repair | Does the software actually work the way it is supposed to? | 05, 06 |
| 2. Seven-agent cybersecurity team | Even if it works, can an attacker exploit it? | 07, 08, agents/ |
| 3. Continuous monitoring & RL defense | As the software changes and runs, how do we keep it secure? | 09, 10, 17 |
The pillars are not three products in one dashboard. They share one version-aware Unified Intelligence Layer (11) and one closed loop:
UNDERSTAND → REVIEW → TEST → ATTACK SAFELY → DIAGNOSE → REPAIR → VERIFY → MONITOR → LEARN → REPEAT
| # | Agent | Team | Role |
|---|---|---|---|
| 1 | Scout | Red | Reconnaissance; produces evidence-backed vulnerability hypotheses |
| 2 | Probe | Red | Validates hypotheses with non-destructive tests in authorized sandboxes |
| 3 | Trace | Red | Attack-path and impact analysis; labels unverified steps as hypotheses |
| 4 | Diagnose | Blue | Root cause and remediation strategy, grounded in intended behavior |
| 5 | Patch | Blue | Candidate fix in an isolated worktree; never merges or deploys |
| 6 | Fortify | Blue | Hardening and prevention recommendations, regression tests |
| 7 | Verify | Independent | Re-runs the exploit and functional tests; accepts or rejects on evidence |
These are product runtime agents. They are distinct from the development coding agents (Claude Code etc.) that build this repository — see AGENTS.md and docs/prompts/.
docs/ Specifications, architecture, agent contracts, planning, research
frontend/ Next.js + TypeScript dashboard (not yet implemented)
backend/ FastAPI control-plane API (not yet implemented)
code-intelligence/ Repository indexing, symbol/call graphs, retrieval (not yet implemented)
code-review/ Functional review + candidate repair engine (not yet implemented)
security-agents/ Seven-agent runtime + orchestrator + tool registry (not yet implemented)
rl-defense/ Gymnasium env, Double DQN, baselines, evaluation (not yet implemented)
monitoring/ Event ingestion, correlation, scheduling (not yet implemented)
shared/ Cross-subsystem contracts (Pydantic → JSON Schema → TS) (not yet implemented)
tests/ Cross-subsystem integration / e2e suites (not yet implemented)
scripts/ Developer tooling (not yet implemented)
examples/ Deliberately vulnerable demo targets (not yet implemented)
Each directory's README defines its future responsibilities, interfaces, and dependencies.
Next.js · React · TypeScript · Tailwind | Python · FastAPI · Pydantic v2 |
Anthropic Claude (model id configurable, default claude-haiku-5-5) |
Tree-sitter | PostgreSQL | Docker-isolated sandboxes | PyTorch · Gymnasium · Double DQN |
Vercel (frontend) · Railway (backend) — not provisioned.
| Area | Status |
|---|---|
| Repository skeleton, docs, shared contracts (Pydantic + generated JSON Schema/TS) | ✅ |
| Backend (FastAPI + PostgreSQL), worker, monitoring ingestion, incidents API | ✅ implemented, tested locally and in CI |
| Code intelligence, functional reviewer, seven runtime security agents | ✅ implemented; live-model runs are opt-in |
| RL defense (simulation-only DDQN, evaluation bundles) | ✅ implemented; recommendations are never applied automatically |
| Frontend console (assessments, findings, approvals, scopes, expectations, monitoring, incidents, settings, Defense Lab) | ✅ implemented; browser e2e against the real local stack with scripted (non-live) model transports |
| Functional remediation pause/resume, hardened Docker sandbox proof, unified M7 demo | 🚧 in progress (see coordination/MILESTONES.md) |
| CI | ✅ GitHub Actions workflows in .github/workflows |
| Infrastructure / deployment | ❌ Not provisioned |
| License | Proprietary, all rights reserved (interim) — LICENSE, LICENSE-DECISION.md |
See CONTRIBUTING.md, docs/24_DEVELOPMENT_STANDARDS.md, and SECURITY.md. This project builds offensive-security tooling; all security testing must target only explicitly authorized, isolated environments (docs/15_SECURITY_BOUNDARIES.md).
Versioned ATT&CK/D3FEND/CWE catalogs, deterministic CVSS 4.0, persisted incident handling aligned to NIST SP 800-61r3, and OWASP LLM Top 10 2025/2026 platform self-assessments are implemented on this branch. See standards, incident handling, and OWASP coverage. Controls have explicit gaps; these are not certification or comprehensive detection claims. The frontend renders the incident lifecycle, approval gates and simulated-drill labels. No production containment is executed.