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SanMuzZzZz/LuaN1aoAgent
github.comrepo

SanMuzZzZz/LuaN1aoAgent

LuaN1aoAgent v2 is a TypeScript rewrite of an autonomous, authorized security-research agent built on the Pi SDK, splitting work into Planner, Executor, and Observer (Supervisor/Projector) roles that coordinate via a persisted task graph and an evidence-backed reasoning/operation graph. It runs Executors in per-task Docker sandboxes with a protocol-aware Go network Gateway that enforces IP/domain scope, supports CVE/advisory lookups via NVD and web search, browser rendering, and traffic capture/replay through an authenticated web workbench. The project targets authorized pentesting/CTF-style engagements, with explicit scope enforcement, SOCKS5 egress routing, and human-facing observability (TUI + web UI) for tracing hypotheses to confirmed vulnerabilities and exploits.

TL;DR An autonomous multi-agent (Planner/Executor/Observer) AI pentesting framework in TypeScript with sandboxed Docker execution, scope-enforced network gateway, and evidence-graph tracing of vulnerabilities to exploits.
Document

What it is

The GitHub README for LuaN1aoAgent v2, a TypeScript-on-Pi-SDK rewrite of an autonomous security-research agent. The catalog summary covers the Planner/Executor/Observer split and the evidence-backed causal graph; the page adds operational detail and two caveats that change how you should evaluate it.

How it works

Beyond the three-role framing, the page specifies that the Observer is actually two independent modes, not one component:

  • Supervisor (hot-path): inspects recent Executor actions and decides continue / checkpoint / stop / return-to-Planner.
  • Projector (asynchronous): converts normalized observations into reasoning- and operation-graph deltas without blocking the Executor loop.

Each role terminates through a schema-validated structured tool — planner_submit, task_result_submit, control_submit, graph_delta_submit — and every Supervisor/Projector invocation uses a fresh Pi session with no shared hidden model history. The Planner's language is a fixed set of graph operations (create_tasks, patch_task, replace_dependencies, set_task_status, set_node_status); new evidence patches existing tasks rather than regenerating the plan. Large tool outputs spill to content-addressed artifacts with preview + provenance instead of inflating context, and only "ready" tasks enter a deterministic admitted wave (independent tasks may run concurrently).

Preconditions / Affected

Executors run Pi coding tools (read, grep, find, ls, …) inside a configured sandbox boundary. Runs are bounded by per-task turn budgets and a global run-time budget; provider failures are classified as retryable with bounded fresh-session retries. Intended for authorized security research/pentesting only.

Caveats

Two are stated explicitly on the page and matter for anyone deciding whether to adopt or trust it:

  • v2 is not an in-place refactor of the Python v1 runtime. It is a new implementation with different configuration, persistence, Agent lifecycle, and observability contracts — migrating from v1 is not a version bump.
  • No v2 benchmark numbers exist yet. v1's reported benchmarks are explicitly not attributed to v2; v2 results will be published only after reproducible reruns on a frozen release. Treat any performance expectation carried over from v1 as unsupported.

Provenance enforcement (confirmed Vulnerability and successful Exploit nodes cannot be written without evidence references) is a design guarantee described in the README, not an independently verified property.

Technologies named here

  • LuaN1aoAgent v2
  • Pi SDK
  • LuaN1aoAgent v1
  • vulnerability_search tool
  • NVD
  • web_search tool
  • web_fetch tool
  • browser_render tool
  • Bash tool
  • read/grep/find/ls tools
  • artifact_read / artifact_write
  • route_open / route_status / route_stop / route_reconnect
  • Docker
  • macOS Seatbelt
  • Linux Bubblewrap
  • Go protocol Gateway
  • Chisel
  • SOCKS5 proxy
  • Eyadkelleh/awesome-skills-security
  • ljagiello/ctf-skills
  • npx skills installer
  • Web workbench
  • TUI
  • TypeScript
  • Node.js
  • npm
  • SSH

Techniques named here

  • Recon Task
  • Auth Task
  • Validation Task
  • Evidence-backed hypothesis-to-exploit reasoning chain
  • CVE/advisory research via vulnerability_search
  • Sandboxed autonomous exploitation validation
  • Traffic capture and replay
  • Transparent HTTP/HTTPS interception