strix

Strix The open-source AI pentesting tool. Autonomous AI hackers that find and fix your app’s vulnerabilities. !TIP New! Strix integrates seamlessly with GitHub Actions and CI/CD pipelines. Automatically scan for vulnerabilit...

caido

Website • Dashboard • Docs • Roadmap • Branding • Discord 👋 Welcome Welcome to Caido! Caido aims to help security professionals and enthusiasts audit web applications with efficiency and ease. Here you can get involved with the development of our software. You can learn about upcoming Caido...

ClawGuard

ClawGuard 🛡️ 中文版 Nuestro proyecto:https://github.com/SafeAgent-Beihang/clawguard ClawGuard es un toolkit de seguridad diseñado para mitigar los riesgos asociados con los agentes autónomos, como OpenClaw y otras entidades impulsadas por LLM. A medida que los agentes ganan más autonomía para ejecuta...

hexstrike-ai

HexStrike AI MCP Agents v6.0 Plataforma de Automatización de Ciberseguridad MCP impulsada por IA Marco MCP de pruebas de penetración avanzado impulsado por IA con más de 150 herramientas de seguridad y más de 12 agentes autónomos de IA 📋 Novedades • 🏗️ Arquitectura • 🚀 Instalación • 🛠️...

aimp

AIMP — Protocolo de Malla de IA Un protocolo de red experimental y sin servidor para la sincronización de estado resiliente entre agentes autónomos en redes fragmentadas y de bajo ancho de banda. Construido sobre Merkle-CRDTs e identidad criptográfica — sin autoridad central, sin DNS global,...

acp-framework-en

ACP — Agent Control Protocol Admission control for agent actions. Before any agent mutates system state, ACP answers four questions: Who is this agent? What are they authorized to do? Is this action policy-compliant? Can the outcome be traced to an accountable institution? Cryptographic identity ...

Dark-Moon v1.4.0

DarkMoon Open-source autonomous AI penetration testing — finds, exploits and qualifies every vulnerability on your own infrastructure ⭐ Star DarkMoon · 🚀 Quick Start · 🧩 Integrations · 📊 Benchmark · 🔒 Darkmoon Pro · ▶️ Watch the demo Pro DarkMoon is autonomous AI penetration testing for your own...

apex v2.4.0-canary.d5c18874

Pensar Apex AI-powered penetration testing using autonomous agents — directly in your terminal. Run blackbox and whitebox pentests that explore, reason, and surface real vulnerabilities. Want to run from the cloud or integrate it with your CI/CD? See Pensar Console. Use Cases Developers Run...

Vulnera

Strix The open-source AI pentesting tool. Autonomous AI h...

snyk-agentic-appsec-poc

Snyk Agentic AppSec POC Proof of concept demonstrating autono...

SeClaw: Spec-Driven Security Task Synthesis for Evaluating Autonomous Agents

Autonomous LLM agents increasingly operate in stateful environments where they access tools, files, memory, and external services. While such capabilities enable complex real-world workflows, they also introduce security risks that are difficult to capture with existing evaluations. Current agent...

The Importance of Out-Of-Band Metadata for Safe Autonomous Agents: The Redpanda Agentic Data Plane

AI agents are increasingly expected to operate as digital employees: accessing enterprise data, making decisions, and taking actions autonomously. But agents are simultaneously less predictable than humans -- prone to hallucination, misinterpretation, and adversarial manipulation -- and more...

Security of OpenClaw Agents: Fundamentals, Attacks, and Countermeasures

The rapid evolution of large language model LLM-driven autonomous agents has given rise to OpenClaw, a new class of open-source agent frameworks that operate as continuously running, skill-augmented systems with persistent memory, multi-channel interaction, and high degrees of autonomy. Such...

IronCurtain 0.11.0

IronCurtain is an early-stage research project exploring how to make AI agents safe enough to be genuinely useful. It is a runtime for autonomous AI agents, where security policy is derived from a human-readable constitution. APIs, configuration formats, and architecture may change...

shadowstrike

⚡ ShadowStrike AI-Powered Advanced Security Testing Platf...

AI Agents May Always Fall for Prompt Injections

Prompt injection is the most critical vulnerability in deployed AI agents. Despite recent progress, we show that the prevailing defense paradigm data-instruction separation both fails to detect attacks that operate through contextual manipulation and degrades contextually appropriate behavior. We...

kernel-exploit-intelligence

🐧 Kernel Exploit Intelligence KEI !KEI Logo./assets/logo...

From Specification to Deployment: Empirical Evidence from a W3C VC + DID Trust Infrastructure for Autonomous Agents

Autonomous AI agents now transact at production scale -- 69,000 bots executing 165 million transactions across 50 million USDC in cumulative volume on a single marketplace -- without any shared trust layer between participants. Regulatory frameworks Singapore IMDA, NIST CAISI, EU AI Act and major...

Autonomous LLM Agent Worms: Cross-Platform Propagation, Automated Discovery and Temporal Re-Entry Defense

Autonomous LLM agents operate as long-running processes with persistent workspaces, memory files, scheduled task state, and messaging integrations. These features create a new propagation risk: attacker-influenced content can be written into persistent agent state, re-enter the LLM decision conte...

Security Attack and Defense Strategies for Autonomous Agent Frameworks: A Layered Review with OpenClaw As a Case Study

Autonomous agent frameworks built upon large language models LLMs are evolving into complex, tool-integrated, and continuously operating systems, introducing security risks beyond traditional prompt-level vulnerabilities. As this paradigm is still at an early stage of development, a timely and...