Eval directory
Evals for Chainguard
6 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Chainguard AI products.
About Chainguard
Chainguard is a software supply chain security company that provides hardened, minimal container images with verifiable provenance. Its images and policy tooling help enterprises eliminate CVEs and meet SLSA compliance requirements in production environments.
How complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
6/6 packs
Scoring metrics
0/6 packs
Judge rubrics
6/6 packs
Use-case maps
0/6 packs
Pack context
6/6 packs
Available eval packs for Chainguard
6 packs ready to run.
Advisory Image Operations
Evaluates Chainguard's Advisory & Image Operations across 7 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Security infrastructure eval coverage.
Custom Assembly Builds
Evaluates Chainguard's Custom Assembly & Builds across 6 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Security infrastructure eval coverage.
Policy Gates Image Lifecycle
Evaluates Chainguard's Policy Gates & Image Lifecycle across 15 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Security infrastructure eval coverage.
Registry Auth Pull Identity
Evaluates Chainguard's Registry Auth & Pull Identity across 15 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Security infrastructure eval coverage.
Sbom Provenance Artifacts
Evaluates Chainguard's SBOM & Provenance Artifacts across 14 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Security infrastructure eval coverage.
Signature Attestation Verification
Evaluates Chainguard's Signature & Attestation Verification across 16 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Security infrastructure eval coverage.
Why eval Chainguard AI
Chainguard's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for Chainguard measures four dimensions teams care about most when deploying security operations agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against Chainguard's public product surface and runnable in Corsac with your own data.