# JoasASantos/NeuroSploit

NeuroSploit is an advanced, AI-powered penetration testing framework designed to automate and augment various aspects of offensive security operations.

Repository: https://github.com/JoasASantos/NeuroSploit
Canonical: https://ross.abutalabs.com/products/neurosploit
Language: Rust
License: MIT
License Family: permissive
Topics: ai-agents, cybersecurity, framework, hacking, llm, pentesting, ai-penetration-testing, ai-security, ctf-tools, ethical-hacking, ethical-hacking-tools, kali-linux, kali-linux-hacking, kali-linux-tools, kali-tools, penetration-testing, penetration-testing-framework, penetration-testing-tools, redteam-tools, redteaming
Last push: 2026-08-23T19:07:24+00:00

## Health v2 (maintenance only)
Score: 85/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 99, longevity 27
- inputs: {"age_days": 381, "days_push": 10, "days_rel": 10, "gap_med": 3.0, "n_releases_24m": 23}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1347, forks 326 (observed 2026-08-28T04:04:27.494711+00:00)

## What it is
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
- artifact type: framework
- maturity: active
- function: penetration-testing, agent-framework, llm-inference, security, cli, osint
- domain: security, penetration-testing, artificial-intelligence, large-language-models
- platform: cli, rust
- tags: red-team, ethical-hacking, ctf-tools, kali-linux, multi-agent, llm-orchestration, vulnerability-scanning, autonomous-agents, ai-agents, command-line, linux

## Member repositories
- JoasASantos/NeuroSploit (main) score 85

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:27.494711+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:42:35.822330+00:00, confidence not recorded.
  - readme: https://github.com/JoasASantos/NeuroSploit (fetched 2026-08-28T04:04:27.494711+00:00, sha 1da62b593707)
- Data as of 2026-08-30T08:39:29.467469+00:00.