JoasASantos/NeuroSploit

Health v2 · maintenance only

Adoption not part of the score

1462 stars · 343 forks observed · 2026-10-19

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

NeuroSploit is an AI-powered penetration testing framework written in Rust that turns a URL, repository, app, or host into an autonomous security engagement. It orchestrates a pool of LLMs and 435 markdown-defined agents to recon targets, select and run relevant agents in parallel, chain findings, and validate results via cross-model voting before reporting.

Use cases

• automate penetration testing of a web application
• run black-box security assessments against a URL or IP
• orchestrate multiple LLM agents for offensive security tasks
• perform recon and vulnerability discovery on a target host
• augment red team operations with AI-driven tooling
• solve CTF challenges with automated agent pipelines
• validate security findings with cross-model voting

When to choose

• you want an autonomous, multi-model AI harness for penetration testing workflows
• you need a CLI-only tool that runs on Kali Linux or similar environments
• you want agent selection driven by discovered attack surface
• you need findings validated by cross-model voting and tool receipts

When to avoid

• you need a GUI-based vulnerability scanner
• you lack access to LLM API keys or subscription-based models
• you require guaranteed accuracy without human review of AI-generated findings
• your use case is defensive security monitoring rather than offensive testing

Facets

framework · maturity active

penetration-testing agent-framework llm-inference security cli osint security penetration-testing artificial-intelligence large-language-models cli rust red-team ethical-hacking ctf-tools kali-linux multi-agent llm-orchestration vulnerability-scanning autonomous-agents ai-agents command-line linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="JoasASantos/NeuroSploit")