Fully autonomous AI Agents system capable of performing complex penetration testing tasks
-
Updated
Aug 6, 2026 - Go
Fully autonomous AI Agents system capable of performing complex penetration testing tasks
HexStrike AI MCP Agents is an advanced MCP server that lets AI agents (Claude, GPT, Copilot, etc.) autonomously run 150+ cybersecurity tools for automated pentesting, vulnerability discovery, bug bounty automation, and security research. Seamlessly bridge LLMs with real-world offensive security capabilities.
The system of action for AI-native cybersecurity—where intent becomes governed execution, evidence becomes operational memory, and every operation improves the next.
safe execution paths for agents - zero trust, zero setup, zero latency.
PentestAgent is an AI agent framework for black-box security testing, supporting bug bounty, red-team, and penetration testing workflows.
Akto is the fastest growing AI Security platform for your teams to secure AI agents, MCPs, LLMs, Agent skills, Gen AI apps in your organization.
LuaN1aoAgent is a fully autonomous AI penetration testing agent driven by graph-based cognitive reasoning.
Autonomous AI pentesting engine, continuous offensive security across web, cloud, identity, CI/CD, IaC, databases, Active Directory, Kubernetes and IoT firmware. Agentic reasoning plus real exploit execution deliver proof-based vulnerabilities. Privacy gateway: the LLM never sees your real IPs, hosts or creds, nothing leaves your perimeter.
PentestCode - Multi-agent AI penetration testing system with persistent engagement state, strategic coordination, and parallel autonomous operations.
An intentionally vulnerable OWASP LLM Top 10 training platform for AI Security, Prompt Injection, RAG Security, Agent Security, and GenAI penetration testing.
AI EDR for developer workstations and autonomous agent fleets. Build Swarm Detection & Response platforms with Clawdstrike.
Static security scanner for LLM agents — prompt injection, MCP config auditing, taint analysis. 51 rules mapped to OWASP Agentic Top 10 (2026). Works with LangChain, CrewAI, AutoGen.
A comprehensive reference for securing Large Language Models (LLMs). Covers OWASP GenAI Top-10 risks, prompt injection, adversarial attacks, real-world incidents, and practical defenses. Includes catalogs of red-teaming tools, guardrails, and mitigation strategies to help developers, researchers, and security teams deploy AI responsibly.
Security scanner for Agent Skills — uncover hidden threats before deployment.
A professional AI security range for red teaming, vulnerability research, defensive validation, and hands-on AI/ML security training.
The CoSAI Risk Map is a framework for identifying, analyzing, and mitigating security risks in Artificial Intelligence systems. As traditional software security practices are not always sufficient for AI, this project provides a shared understanding and a common language for addressing the unique security challenges of the AI development lifecycle.
MCP Security Solution for Agentic AI — real-time proxying, behavior analysis, and malicious tool detection
Fast local Rust scanner for AI-agent prompt injection, credential leaks, exfiltration, and risky tool calls
Secure mcp infrastructure to audit and control every data access by AI agents with minimal efforts
Runtime security for AI agents. In-process, zero dependencies, Apache 2.0.
Add a description, image, and links to the ai-security-tool topic page so that developers can more easily learn about it.
To associate your repository with the ai-security-tool topic, visit your repo's landing page and select "manage topics."