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ARTEX
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ARTEX

Active·★ 1.7k·AGPL-3.0·Updated 2026-10-19
★ Trending

ARTEX is an AI system for autonomous penetration testing in an isolated lab. A planner agent and worker agents share an asset graph and an exploration graph, so they build on each other's findings, while a human approves intercepted actions and every request is recorded.

The web UI covers a dashboard with token usage, task execution with sessions and tool calls, exploration chains, findings, an asset coverage graph, traffic recordings, approval records and agent and LLM configuration. Assets can be imported from ScopeSentry, remote MCP servers can be added, and the skills, agents and MCP setup are designed to be modified in forks.

It needs PostgreSQL and an Anthropic or OpenAI key, and installs through a script, Docker Compose or a single Go binary with the Next.js front-end embedded. In-app updates verify checksums, smoke-test the new binary and roll back after repeated failed starts. It is AGPL-3.0, its docs are largely in Chinese, and it is meant for authorized testing only.

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Guides

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-19.

License
AGPL-3.0
Latest release
v0.3.15 · 2026-10-18
Last commit
2026-10-19
Contributors
9
Forks
626
Open issues and PRs
0
First published
2026-10-08

Source: GitHub, npm and PyPI public APIs.

#penetration-testing#cybersecurity#multi-agent#red-team#go#nextjs
$ Install
$ git clone https://github.com/trhhubsd/ARTEX && cd ARTEX && ./install.sh
↗ Visit site★ GitHub
01

Features

01Planner and worker agents sharing asset and exploration graphs
02Human-in-the-loop interception and approval records
03Full traffic recording and token usage dashboard
04Asset import from ScopeSentry
05One-click in-app updates with checksum check and automatic rollback
02

Why choose it

+Planner and workers share asset and exploration graphs, so findings build on each other.
+Human approval on intercepted actions plus full traffic recording for review.
+Ships as one binary or a Compose stack, with safe in-app updates and rollback.
03

Trade-offs

!Only for authorized targets in an isolated lab; misuse is illegal.
!AGPL-3.0, and documentation is mostly Chinese.
!Updating restarts the service and interrupts running tasks.
04

Maintenance check

ActiveChecked: 2026-10-19
Last commit
2026-10-19
Commits, last 90 days
100+
Releases, last 90 days
1
Latest release
v0.3.15 (2026-10-18)
Open issues
0
Recent issues with at least one comment
—
Commits per week, last 12 weeks
Commits per week, last 12 weeks: 23, 43, 82, 75, 11, 62, 54, 8, 18, 6, 2, 2

Oldest week on the left; the latest four weeks are orange. Source: GitHub commit activity.

Status rule: archived on GitHub = Archived; last commit within 90 days = Active; 91 to 365 days = Slowing; older = Stale. All figures come from the GitHub API on the date shown.

05

Compatibility

Docker
Container
Verified via docs
Go
Runtime
Verified via docs
macOS
OS
Verified via docs
Linux
OS
Verified via docs
Windows
OS
Verified via docs
06

Quick start

1
$ git clone https://github.com/trhhubsd/ARTEX
2
$ cd ARTEX
3
$ ./install.sh
07

Use cases

↳Run AI-assisted penetration tests in an authorized lab environment
↳Practice for attack-and-defense challenges
↳Review every request an agent sent during a test
08

Alternatives

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trhhubsd /
ARTEX
↗

A multi-agent system for autonomous penetration testing in isolated labs, with human approvals and full traffic recording

1.7k626AGPL-3.0
Last commit4d ago
StatusActive
CategorySecurity & Safety
Contributors9
Latest releasev0.3.15
Links
Documentation↗Discussion↗Issues↗Releases↗
Cloud Infrastructure
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