Vibe Coding Security Checklist: Production Gate

A vibe coding security checklist is the gate between an AI-built prototype and software real users can trust. The risk is not that every generated line is bad. The risk is that fast code arrives with unclear ownership, unreviewed dependencies, leaked secrets, weak tests and build changes nobody meant to approve. NIST's SSDF profile says practices do not distinguish between human-written and AI-generated source code because all source code should be evaluated for vulnerabilities. Source

This checklist is for founders and small teams moving an AI-assisted app toward launch. It is our production gate, grounded in NIST and OWASP guidance. It is not a claim that Codesprint has audited a specific client app.

1. Name a human owner for every generated change

AI-generated code must have a human owner. OWASP's Secure Coding with AI Cheat Sheet says every AI-assisted change should be reviewed, approved and attributable to a developer responsible for its security and maintainability. "The AI wrote it" is not an ownership model. OWASP Secure Coding with AI

Our launch rule is one accountable reviewer per pull request, not a quick approval on the AI summary. The reviewer must understand what changed, why it changed and how to roll it back. For a solo founder, that can mean pausing the launch until a trusted engineer reviews the risky parts.

Require explicit approval for generated code that touches authentication, authorization, payments, data deletion, encryption, infrastructure or deployment. AI review comments can assist, but they do not replace a human approval.

2. Review the full diff, not the requested change

AI coding agents often edit files outside the requested scope. OWASP calls out lockfiles, CI configuration, unrelated tests, formatting changes and dependency updates as changes reviewers can miss when they focus only on the prompt. OWASP Secure Coding with AI

Our checklist requires a full diff review before merge. Flag every unexpected file, especially lockfiles, test files, Dockerfiles, deployment scripts, package scripts, workflow files and AI rule files. A routine-looking lockfile change can be a supply-chain change.

Add CODEOWNERS or equivalent review rules for sensitive paths. If the agent changed CI, infrastructure, secrets handling or security tests, require a second look from whoever owns that area.

3. Stop secret and context leakage

AI coding tools may send open files, project structure and terminal output to a model provider. OWASP warns that this context can include credentials, personal data, proprietary logic and internal architecture. It also warns that .gitignore does not stop an AI tool from reading a file on disk. OWASP Secure Coding with AI

Our gate starts with a secret scan of the repository, git history, environment files, logs and terminal output. Move secrets into a vault or environment manager. Exclude .env, private keys, service-account files and customer data from AI tool context using the tool's ignore rules.

Then check provider settings. Record what the coding tool sends, whether prompts or code are retained, and which provider account is approved for this project. OWASP SAMM says AI policy should cover which data and source code may be shared with which providers. OWASP SAMM AI-assisted development

4. Verify every AI-suggested dependency

OWASP says AI coding assistants can suggest packages that do not exist, and attackers can register those hallucinated names. Models can also suggest dependency versions with known vulnerabilities because their package knowledge is stale. OWASP Secure Coding with AI

Before installing, verify the package page, maintainer history, creation date, download pattern and repository link. Run npm audit, pip audit, govulncheck, cargo audit or the equivalent for your stack. Cross-check against OSV, GitHub Advisories or the NVD where relevant.

Pin versions and update through a normal dependency process. Do not let the coding agent bump packages as a side effect of an unrelated feature request. For launch, keep a software bill of materials or at least a reviewed lockfile and a list of direct dependencies.

5. Treat repository content as untrusted input

Agentic coding tools read issues, pull requests, comments, README files, changelogs, error traces and web pages. OWASP says those sources can carry indirect prompt injection that changes agent behavior. OWASP Secure Coding with AI

Our rule is to give the agent only the files and context needed for the task. Do not ask it to process untrusted issue bodies, external PRs or arbitrary URLs and then auto-apply the result. Review the actions after it reads outside content.

This matters for open-source templates too. A starter repo can contain prompt-injection text, malicious package scripts or unsafe defaults. Treat the template as third-party code, not as a neutral base.

6. Restrict coding agents and MCP tools

An agent with full developer permissions can install packages, run commands, edit files and push branches. OWASP recommends sandboxed environments, tool allowlists, egress controls, ephemeral credentials and resource limits. It also warns that a compromised agent context can have the same blast radius as a compromised developer workstation. OWASP Secure Coding with AI

Our production gate blocks production credentials, deployment keys, SSH keys and broad cloud tokens from the coding environment. Use a dev container, restricted shell, VM or ephemeral cloud workspace. Turn off auto-accept for unfamiliar repos and risky tasks.

If the setup uses MCP servers, keep an approved server list, pin tool definitions, review tool descriptions and apply least privilege. A coding agent does not need email, payment or admin tools unless the task truly requires them.

7. Protect the build and deployment path

AI agents can change files that execute automatically during install, build, test or deploy. OWASP lists package scripts, GitHub Actions, GitLab CI, Dockerfiles, Makefiles, setup files and generated build directives as files needing heightened scrutiny. It also recommends pinning third-party GitHub Actions to a commit SHA rather than a mutable tag. OWASP Secure Coding with AI

Our launch review diffs every build and deployment file. Look for new network calls, downloaded scripts, curl-to-shell patterns, changed permissions, new secrets access and unpinned actions. Require explicit approval for workflow changes.

Check preview and production environment variables separately. A prototype that works with a public test key can become a production incident when the same key has broad access.

8. Do not let AI grade its own homework

A passing test suite generated by the same agent that wrote the code is not independent assurance. OWASP warns that agents can make CI green by deleting failing tests, weakening assertions, over-mocking dependencies or asserting the buggy behavior. OWASP Secure Coding with AI

Our checklist flags test deletions, assertion reductions and new mocks in security-sensitive tests. Write or review tests for authentication, authorization, input validation, payment state and data deletion independently. Add negative tests for expired tokens, malformed input, wrong tenants and replayed requests.

OWASP SAMM recommends deterministic verification such as static analysis, policy-as-code, automated tests and pipeline gates, because AI tools can ignore or misinterpret instructions. OWASP SAMM AI-assisted development

9. Run the normal security basics before launch

NIST's profile is explicit that it is not a checklist, but a starting point for a risk-based secure development approach. Our founder gate turns that principle into concrete release evidence: threat model, dependency scan, secret scan, test review, access review, logging review and rollback plan. Source

Run SAST, dependency scanning and secret scanning in CI. Test authentication, authorization, password reset, webhook signatures, file upload, rate limits, tenant isolation and admin paths. Review logs so tokens, passwords, personal data and full payment details are not stored.

Keep a rollback plan and an owner for the first 48 hours after launch. A fast prototype does not reduce the need for incident contact, backup restore or a way to disable a risky feature.

10. Use this pass-fail gate before users arrive

Our minimum pass-fail list is short enough to use before every launch:

• A named human reviewed the full diff and owns the change.

• Secrets are outside the repo and outside AI tool context.

• Every new package and version was verified and scanned.

• The agent ran without production credentials or broad network access.

• CI, Docker, package scripts and deployment files got explicit review.

• Security-critical tests were reviewed independently and still assert the intended behavior.

• Auth, tenant isolation, webhooks, uploads, rate limits and logging passed basic tests.

• Rollback, backups, monitoring and an incident owner are ready.

If you already have a generated MVP, our vibe-coded app audit guide covers the broader review sequence, and our vibe coding to production guide covers the rest of the launch path. For hands-on help, see Codesprint's Vibe Coding for Founders service.