Analysis
Multi-Agent AI Security Risks: Understanding the Challenges of Collaborative AI Systems
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Single-source analysis — one report is available.
Why it matters
Multi-agent AI systems introduce compounding attack surfaces where a single compromised agent can propagate malicious instructions across an entire workflow, so defenders need to understand these emerging risk classes.
HACKLIDO publishes an explainer on security risks in Multi-Agent AI Systems, describing how collaborative agents that exchange information and use external tools expand the attack surface. It catalogs risk classes including prompt injection, agent-to-agent trust exploitation, excessive permissions, sensitive data leakage, and tool abuse, and outlines best practices for building secure collaborative AI applications.