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NewSecurity Audit for AI-Built Apps. Fixed scope, clear report
GeekTech

Pillar 1

AI Security & Reliability

Make AI-built software safe to ship and reliable to run.

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  • Senior engineers only
  • NDA on request
  • Fixed-scope starting point

Is this you?

Sound familiar?

  • You shipped an app built largely with AI coding tools and have never had it reviewed.

  • You're adding LLM features and don't know how they could be attacked.

  • Your prototype got traction and now needs to handle real users and real data.

  • A customer or investor asked about your security posture.

Outcomes

What we solve

  • Exposed API keys and secretsOutcome: Secrets moved server-side, rotated and monitored.
  • Broken authentication and authorizationOutcome: Every route and record checks who is asking.
  • Open database access rulesOutcome: Row-level rules that match how your app is really used.
  • Vulnerable dependenciesOutcome: Known issues patched, with automated alerts for new ones.
  • Prompt injection and data leakage in LLM featuresOutcome: AI features tested against real attack patterns.
  • Missing monitoring, backups and incident responseOutcome: You know when something breaks, and how to recover.

Services

Services in this pillar

Start here

Begin with a fixed scope

A short, fixed-scope engagement shows exactly where you stand and what to do next. No long commitment.

Start here

Fixed scope · Price on request

Security Audit for AI-Built Apps

A fixed-scope review of your AI-built app, with a clear report and a prioritized fix list.

  • Code, configuration and data-access review
  • LLM feature testing
  • Report with severity ratings
  • Walkthrough call
What's included →

Ongoing support

AI Security & Reliability Retainer

Security isn't a one-off. New code, new features and new dependencies arrive every week. A retainer keeps reviewing them.

  • Essential

    Ongoing review for a stable product.

    Tailored to your scope

    • Monthly security review of new code
    • Dependency and secrets monitoring
    • Quarterly security report
    Reporting:
    Monthly

  • Growth

    For teams shipping AI features regularly.

    Tailored to your scope

    • Everything in Essential
    • LLM feature testing on each release
    • Monitoring and alerting
    • Priority response
    Reporting:
    Monthly + quarterly review

  • Partner

    Security built into how you deliver.

    Tailored to your scope

    • Everything in Growth
    • Incident response
    • Security architecture input
    • Embedded reviews in your delivery process
    Reporting:
    Weekly + quarterly review

Every retainer is scoped in a written proposal after a short call. Compare tiers on How we work.

Process

How an engagement runs

  1. 1

    Scope call

    We agree what's in scope, what access we need and what a good outcome looks like.

  2. 2

    Access & NDA

    NDA signed, least-privilege read access set up. Nothing is tested without written authorization.

  3. 3

    Review

    Senior engineers review code, configuration and AI features against a structured checklist.

  4. 4

    Report & walkthrough

    A written report with severity ratings and a prioritized fix list, walked through on a call.

  5. 5

    Fixes or retainer

    Fix it yourself with our report, have us deliver the fixes, or keep us on to review what's next.

FAQ

Frequently asked questions

Do you need our source code?

For the most thorough review, yes: read-only repository access or a code export. We can also start with the running app and configuration, but some issues are only visible in code.

Will the audit disrupt our app?

No. We review code and configuration and test against accounts you provide. Anything that could affect production is agreed in writing first, and we can work against a staging environment.

What do we get at the end?

A written report with every finding rated by severity, a prioritized fix list your team can act on, and a walkthrough call to answer questions.

Can you fix the issues too?

Yes. Many clients ask us to deliver the priority fixes after the audit, and some keep us on a retainer to review new code as it ships.

Do you test AI/LLM features specifically?

Yes. We test for prompt injection (direct and indirect), system-prompt and data leakage, unsafe tool or function calls, and how model output is handled downstream.

Insights

Related insights

All insights →

  • Vibe Coding

    Taking an AI-Built Prototype to Production

    Your AI-built prototype works and users are arriving. What to add before it holds real data: tests, CI/CD, environments, monitoring, backups, cost limits.

    5 min read

  • AI Security

    How to Secure AI Agents That Can Use Tools

    AI agents that call tools can take real actions. How to scope their permissions, contain prompt injection and test an agent before it touches production.

    6 min read

  • AI Security

    Prompt Injection Explained for Product Teams

    What prompt injection is, why it can't be solved with better prompts alone, and the design decisions that limit the damage in your AI features.

    7 min read

Free resource

Is your AI-built app leaking data?

Get our 25-point security checklist for apps built with AI tools.

  • 25 checks across 6 areas
  • Plain-language explanations
  • What to do if a check fails
See what's inside

Get in touch

Tell us what you're building.

Share a few details and a senior engineer will reply within 1 business day.

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