AgentRiskBOM: A Risk-Scoping Security Bill of Materials for Agentic AI Systems

Agentic AI systems retrieve private context, invoke tools, write files, call external services, coordinate with other agents, and may act without human approval. Existing bill of materials artifacts improve transparency for dependencies, model metadata, and training provenance, but leave an agent...

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...

ACIArena: Toward Unified Evaluation for Agent Cascading Injection

Collaboration and information sharing empower Multi-Agent Systems MAS but also introduce a critical security risk known as Agent Cascading Injection ACI. In such attacks, a compromised agent exploits inter-agent trust to propagate malicious instructions, causing cascading failures across the...

Towards Unifying Quantitative Security Benchmarking for Multi Agent Systems

Evolving AI systems increasingly deploy multi-agent architectures where autonomous agents collaborate, share information, and delegate tasks through developing protocols. This connectivity, while powerful, introduces novel security risks. One such risk is a cascading risk: a breach in one agent c...

The Dark Side of LLMs Agent-Based Attacks for Complete Computer Takeover

The rapid adoption of Large Language Model LLM agents and multi-agent systems enables unprecedented capabilities in natural language processing and generation. However, these systems have introduced unprecedented security vulnerabilities that extend beyond traditional prompt injection attacks. Th...

A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures

In recent years, Large-Language-Model-driven AI agents have exhibited unprecedented intelligence, flexibility, and adaptability, and are rapidly changing human production and lifestyle. Nowadays, agents are undergoing a new round of evolution. They no longer act as an isolated island like LLMs...