Identity-based security infrastructure for multi-agent AI systems
Deploy an open-source security layer around multi-agent systems so authorization decisions use each agent's cryptographic identity and the full delegation chain, rather than relying on bearer tokens or a statically defined request path.
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From IBM Technology — Kagenti’s Approach to Multi-Agent Security for AI Agents at 01:06
Problem: A confused deputy can receive a valid credential through an agent chain and use it to access data or tools it was never authorized to reach, potentially leaving only normal-looking authorized activity in the audit trail.
For: Organizations running multi-agent AI systems in production, including systems that process patient records, financial histories, internal communications, or other protected information.
Products from this video
AuthBridge Envoy Proxy Istio Keycloak MLflow OpenTelemetry Phoenix SPIFFE
Examples
- A hospital patient-billing system: Agent A orchestrates agents B, C, and D with a bearer token for patient data; Agent D receives the token while verifying insurance, and the delegation-chain policy blocks Agent D from patient records because it is not authorized for that resource.
Other takes on AI security infrastructure
- Agentic consent governance layer for autonomous AI systems
- Enterprise agentic last-mile identity and access control layer
- AI-agent security and control infrastructure for enterprises
- A guardrail tool that enforces strict test-driven development and other engineering rules for AI coding agents
- AI-powered scam-interception and threat-intelligence service
- Secure compiler for AI-agent skills
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