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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
01

Prompt

Instructions, context, extensions, terminals, and connected tools.

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

Every engagement produces a decision-ready assessment package: an executive Go/No-Go memo, technical findings register, architecture/trust-boundary review, abuse-case matrix, and prioritized remediation roadmap.

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

Principal-led, architecture-level review for high-stakes agent deployments.

Use this when a specific system boundary needs senior technical judgment before production access, customer review, or executive approval.

Next step

Decide whether this is the right review for your next decision.

Request an AI coding security review