01
Prompt
Instructions, context, extensions, terminals, and connected tools.
AI Coding Security Review
Before AI-assisted development can change production, know its blast radius.
A focused review for teams using Cursor, Copilot, Claude Code, or other AI coding workflows with repository, CI/CD, secrets, or deployment access.
Buyer problem
Your AI coding tools can read or change source, pull requests, CI/CD, secrets, or developer machines, but your team has not yet validated the workflow trust boundaries and release controls.
Best fit: Engineering, security, platform, and product leaders using AI coding tools in repositories or delivery pipelines.
Scope
Repository and branch permissions, issue and pull-request trust, workflow triggers, secrets and tokens, generated code and commands, package and dependency paths, deployment influence, approvals, logging, and recovery.
Deliverable
A concrete work product tied to the decision.
A coding-workflow package with a trust-boundary map, permission matrix, abuse-case scenarios, prioritized findings register, remediation backlog, and engineering leadership memo.
Timeline
Typically 10 business days from kickoff and access confirmation.
Signature view / release path
Follow an AI-generated change until it meets production authority.
The review maps the path from developer prompt to deployed change, identifying where generated work can cross a permission boundary or bypass a human decision.
ai-coding-review / release-path
02
Worktree
Local files, credentials, packages, commands, and developer-machine access.
03
Pull request
Reviewers, branch protections, generated diffs, comments, and merge authority.
04
CI/CD
Workflow triggers, build jobs, test output, secrets, and environment access.
05
Deploy
Release approvals, production credentials, rollback, and post-change visibility.
> rollout_condition: validate authority before increasing autonomy
Sample assessment package
Agree the review boundary, authorized methods, and decision the work must support before starting. The scoped package draws from the outputs below and identifies untested paths and unresolved assumptions alongside the findings.
Repository and Branch Authority Map
Map of AI coding tools, identities, repository permissions, branch protections, pull-request actions, and merge authority.
CI/CD Trust-Boundary Review
Review of workflow triggers, generated changes, build jobs, deployment credentials, environments, and release approvals.
Secrets and Token Exposure Review
Assessment of how prompts, context windows, logs, extensions, terminals, and agents can reach sensitive credentials.
AI-Generated Change Abuse Cases
Scenarios covering malicious instructions, dependency changes, unsafe commands, hidden workflow edits, and review bypasses.
Remediation Backlog
Sequenced controls for least privilege, sandboxing, review gates, secret handling, logging, and recovery validation.
Risk addressed
Tool, data, and trust-boundary risk in one review.
- Covers AI coding tools and agentic development workflows, not only generated-code quality
- Connects developer-machine authority to repository, CI/CD, and deployment impact
- Produces rollout conditions and engineering actions that can be validated
When to use it
Technical review before a consequential decision.
Use this before allowing AI-assisted workflows to write code, open or approve pull requests, trigger CI/CD, or influence release decisions.
Next step