What problem does it solve?
Autonomous AI agents operate across trust boundaries and can inadvertently escalate privileges, replay messages, or execute untrusted code. This Skill defines a cryptographic, capability-based security architecture that prevents ambient authority, enforces least privilege, and provides tamper-evident audit trails for inter-agent communication and delegation.
Core Features & Use Cases
- Mutual TLS & Identity: Strong agent identities with certificate verification and automated rotation to prevent impersonation.
- Signed Message Envelopes: JWS/JWE message signing and encryption with jti replay protection and short TTLs for ephemeral capabilities.
- Capability-Based Security (ocap): Attenuation-first tokens that enforce child ⊆ parent privileges and delegation depth limits.
- WASM Sandboxing & Resource Limits: Enforce CPU, memory, execution-time, and syscall restrictions to prevent sandbox escape.
- Merkle Audit Trails: Append-only audit logs with published Merkle roots for provable custody and tamper-evidence.
- Use Case: Securely pass results between a research agent, a codegen agent, and a reviewer while ensuring each step is signed, authorized, and auditable.
Quick Start
Enable zero-trust security across your agents by enforcing mTLS, signing and verifying messages with JWS/JWE, and issuing attenuated capability tokens for delegation.