What is AI code provenance?
AI code provenance is the record of how AI-generated or AI-assisted code was produced: which model, prompt, agent, and editing session created it, who reviewed it, and how it was modified before release.
Resource
AI code provenance
AI code provenance captures the origin, review, and modification history of AI-generated code. It makes agentic application security explainable by preserving the evidence behind every AI-assisted change.
What it is
- A record of which model, prompt, and agent produced a code change.
- A trace of human or independent review applied before the change advanced.
- An evidence input that helps a security verification body evaluate whether an AI-generated change can support a release decision.
What it is not
- It is not a guarantee that AI-generated code is safe.
- It is not a replacement for testing, review, or verification.
- It is not complete without reviewer attestation and policy binding.
Provenance capture points
| Capture point | What to record | Why it matters |
|---|---|---|
| IDE / agent session | Model, prompt, agent identity | Reconstruct how the change was produced |
| MCP server call | Tool invoked, parameters, returned context | Show what the agent accessed |
| Repository commit | Diff, author, reviewer | Prove a human reviewed the change |
| CI evaluation | Tests and scanner results on the artifact | Corroborate AI claims |
| Release decision | Policy version and outcome | Preserve the basis for shipping |
Frequently asked questions
Why does AI code provenance matter?
Without provenance, reviewers cannot reconstruct how a change was produced. Provenance makes AI-generated decisions explainable, auditable, and defensible after the fact.
What should an AI code provenance record include?
At minimum: model identity and version, prompt or instruction context, agent or tool identity, editing session boundaries, diff or artifact references, reviewer attestation, and policy version under which it was reviewed.
How does GoSentrix use AI code provenance?
GoSentrix captures provenance signals as evidence inputs, qualifies them by source and corroboration, and evaluates them against customer-defined policy. Provenance alone does not authorize a release; it enables review and verification.
Related reading
What is an AI-BOM?
Structured provenance records for AI models, prompts, agents, and artifacts.
MCP governance
Govern Model Context Protocol servers and agent-tool interactions.
What is agentic application security?
Governance for AI-generated code and coding agents.
Doctrine
The public operating doctrine for release-evidence verification.
Trace every AI-assisted change.
GoSentrix captures AI code provenance and evaluates it against versioned policy for consequential release decisions.