What problem does it solve?
Multi-agent AI systems can leak data between agents, allow impersonation across boundaries, or let low-privilege agents reach high-privilege tools through message routing. This Skill provides a structured dialogue-based testing methodology to identify these inter-agent communication vulnerabilities before they are exploited.
Core Features & Use Cases
- Cross-Agent Data Leakage Testing: Probes whether one agent can retrieve another agent's private messages, memory, or secrets.
- Boundary and Impersonation Checks: Tests whether messages can be sent as another agent or injected into another agent's context.
- Channel Security and Privilege Escalation Probes: Verifies encryption of inter-agent transport and whether routing enables unauthorized privileged actions.
- Use Case: A security engineer auditing a multi-agent customer support platform uses this Skill to confirm that a low-privilege triage agent cannot access the admin agent's tools or read other agents' conversation history.
Quick Start
Use the inter-agent communication security detection skill to test whether this multi-agent system leaks data across agents or allows privilege escalation through message routing.