61 matches found
aimp
AIMP β AI Mesh Protocol An experimental, serverless networking protocol for resilient state synchronization between autonomous agents in fragmented, low-bandwidth networks. Built on Merkle-CRDTs and cryptographic identity β no central authority, no global DNS, always writeable. Papers | Version|...
ClawGuard
ClawGuard π‘οΈ δΈζη Our Project:https://github.com/SafeAgent-Beihang/clawguard ClawGuard is a security toolkit designed to mitigate risks associated with autonomous agents, such as OpenClaw and other LLM-driven entities. As agents gain more autonomy to execute code, access APIs, and manage files,...
strix
Strix The open-source AI pentesting tool. Autonomous AI hackers that find and fix your appβs vulnerabilities. !TIP New! Strix integrates seamlessly with GitHub Actions and CI/CD pipelines. Automatically scan for vulnerabilit...
hexstrike-ai
HexStrike AI MCP Agents v6.0 AI-Powered MCP Cybersecurity Automation Platform Advanced AI-powered penetration testing MCP framework with 150+ security tools and 12+ autonomous AI agents π What's New β’ ποΈ Architecture β’ π Installation β’ π οΈ Features β’ π€ AI Agents β’ π‘ API Reference Follow Our Social...
acp-framework-en
ACP β 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 ...
apex v2.4.0-canary.d5c18874
Pensar Apex AI-powered penetration testing using autonomous agents β 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
β‘ 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
π§ 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...
From CRUD to Autonomous Agents: Formal Validation and Zero-Trust Security for Semantic Gateways in AI-Native Enterprise Systems
Enterprise software engineering is shifting away from deterministic CRUD/REST architectures toward AI-native systems where large language models act as cognitive orchestrators. This transition introduces a critical security tension: probabilistic LLMs weaken classical mechanisms for validation,...
Poster: ClawdGo: Endogenous Security Awareness Training for Autonomous AI Agents
Autonomous AI agents deployed on platforms such as OpenClaw face prompt injection, memory poisoning, supply-chain attacks, and social engineering, yet existing defences address only the platform perimeter, leaving the agent's own threat judgement entirely untrained. We present ClawdGo, a framewor...