LuaN1aoAgent
LuaN1aoAgent is a cognition-driven autonomous penetration testing agent utilizing dual-graph reasoning technology.
- Region
- Domestic
- Pricing
- Free
- Open source
- Yes
- GitHub Stars
- ★ 1.0k
- Source
- GitHub
- Added
- 2026-06-14
- Last verified
- 2026-06-14
Overview
LuaN1aoAgent is a next-generation autonomous penetration testing agent powered by large language models (LLM). By innovatively integrating the P-E-R (Planner-Executor-Reflector) agent collaboration framework and causal graph reasoning technology, it overcomes the limitations of traditional automated scanning tools. LuaN1ao simulates the thought process of human security experts, transforming penetration testing into an 'autonomous agent' that spans from information gathering to vulnerability exploitation. It dynamically plans attack paths, constructs rigorous evidence-hypothesis-verification logic chains, and learns from failures to automatically adjust strategies.
Key features
- ▪Dynamic attack path planning
- ▪Evidence-driven decision making
- ▪Learning from failure
- ▪Complete cognitive loop
Use cases
Pros
- +High success rate
- +Low cost
- +Adaptive strategy
- +Avoids hallucinated attacks
Limitations / notes
- -Requires internet connection
- -Higher learning curve
Who it's for
This overview was compiled by AI from public sources and may contain inaccuracies — please refer to the official site.
FAQ
Is it free?
Yes, LuaN1aoAgent is an open-source project and available for free use.
Does it support Chinese?
Yes, the project provides documentation in Chinese.
Do I need to use scientific internet access?
Not required, but access to certain external resources may be needed.
Can it be used commercially?
Yes, it can be used commercially under the Apache-2.0 license.
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