Code Signing for AI Agents: Why We Need a Chain of Trust

Signed, Sealed, Deployed: Why Code Signing for AI Agents Is Long Overdue

In software supply chain security, code signing is table stakes. It's how we know a binary came from a trusted developer and wasn’t tampered with in transit. But in the world of AI agents—increasingly complex logic that interfaces with models and systems—we still lack a standard for signing and verifying agent packages.

That’s a problem.

Here’s the risk:

AI agents are increasingly being built by third-party developers and distributed across teams, companies, or cloud marketplaces.

Unlike static LLM prompts, agents can execute arbitrary logic, integrate APIs, and make decisions. If tampered with, they become insider threats with admin keys.

Without provenance, enterprises have no easy or continuous way of verifying:

• Who really built the agent
• What libraries, dependencies or tools it includes
• Whether the container or package has been altered post-certification

A good starting point? Digitally signed, containerized AI agents.

Using tools like Sigstore and Cosign, developers can generate verifiable signatures for their agents packaged into OCI containers. Better yet, extend this with:

• Embedded SBOMs (Software Bill of Materials)
• Runtime manifests and cryptographic "handshake verification" protocols
• Trust certificates for model orchestration logic

Enterprises can validate these packages pre-deployment, track versioning, and dynamically revoke trust when vulnerabilities or non-compliance with PBAC are discovered.

Not just DevSecOps hygiene—static security must meet dynamic trust enforcement frameworks to make AI agent deployments viable at enterprise scale.

In a truly zero-trust AI agent architecture, we can't just secure independent system components. We must create a fundamentally new layer of trust.

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