How to secure interacting AI agents online?
Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents
May 6, 2025
https://arxiv.org/pdf/2505.02077This paper introduces "multi-agent security," a new field focused on the unique security challenges arising from interconnected AI agents. It argues that traditional cybersecurity and AI safety methods are insufficient for multi-agent systems because novel threats emerge from the interactions of these agents, not just their individual vulnerabilities.
Key points for LLM-based multi-agent systems:
- LLMs are vulnerable to novel attacks: These include secret collusion through steganography (hiding messages in plain sight within text), adversarial stealth attacks, swarm attacks, manipulation of shared environments, and cascading failures.
- Current security measures are inadequate: Standard approaches like access controls and monitoring fail because they focus on single agents, not interactions and emergent behavior.
- New security paradigms needed: The paper advocates for developing specialized security protocols, environments, and governance frameworks for multi-agent systems, leveraging ideas from cryptography, game theory, and complex systems research.
- Environment engineering crucial: Carefully shaping how agents interact and what information they have access to can be a powerful tool to mitigate threats.
- Monitoring and threat detection is a challenge: New methods are required to detect subtle, coordinated attacks and attribute malicious actions within complex multi-agent networks.
- Tool use presents security risks: While agents using tools could enhance security, it also creates new attack surfaces related to tool integrity, privilege escalation, and audit trails.
- Multi-agent adversarial testing is lacking: Current model evaluations focus on individual systems. Robust multi-agent security testing is crucial to discover and defend against novel threats.
- Societal-level threats must be considered: LLM-powered agents create a larger attack surface for social engineering and disinformation campaigns that can have broad societal impacts. Education and stronger AI governance are vital.