Krytho
Security review for AI-generated code

Your AI wrote it. Nobody read it.

A person reads the code you shipped and works the running app, looking for the things generated code gets wrong. Not a scanner run and summarised, and not a model asked for a second opinion. You get the findings and the pull request that fixes them, from $250.

app/api/auth/reset-password.tsCritical
An example of the class. Both of our first two reviews found a critical account takeover.

What Krytho does, and who does it

  • A senior developer reads your codeAvailable now
    Done by a person

    Not a scanner run and summarised, and not a model asked for an opinion. Someone experienced reads the code you shipped and works the running app, looking for the things generated code gets wrong.

  • Account takeover and auth logicAvailable now
    Done by a person

    Broken authentication is the flaw we find most and the one automated tools miss most, because it lives in logic rather than in a known-bad pattern. Both of our first two reviews found a critical one.

  • The pull request that fixes itAvailable now
    Done by a person

    Findings come with the code that resolves them, opened as a PR against your repo. A machine drafts the change; the developer who found the problem checks it before it reaches you.

  • Findings you can act onAvailable now
    Done by a person

    Each issue with its severity, how to reproduce it, and what it would cost you if someone found it first. No CVSS scores without context.

  • Security Reviewed sealAvailable now
    Done by a person

    A badge that names the commit it covers and the date it was reviewed, linking to a page you do not control. It expires, and only another human review renews it.

  • Drift and staleness alertsAvailable now
    Done by software

    Automated watching of the codebase a human reviewed, so you hear when your auth code changes or your seal is going stale. It reports; it never certifies.

  • Continuous checks on every pushAvailable now
    Done by software

    Exposed secrets, vulnerable dependencies and dangerous patterns, checked on a schedule between reviews. Finds the known-bad shapes; a person is still what finds broken logic.

  • AI-readiness reportAvailable now
    Done by software

    Whether the crawlers that feed AI answers can actually read your app: what robots.txt lets through, whether the page has content before JavaScript runs, and whether it says what it is.

  • Supply chain verificationAvailable now
    Done by software

    Install scripts, git and non-registry sources, missing integrity hashes, and dependencies that were invented rather than published.

How a review works

  1. 01

    You give us access

    A repo, the URL it runs at, and written permission to test it. We prove you control the domain before any traffic is sent, because a signature from someone who does not own the target protects nobody.

  2. 02

    Someone reads it

    A senior developer goes through the code and works the running app. Broken authentication is what we find most, and it is what scanners miss most, because it lives in logic rather than in a known-bad pattern.

  3. 03

    You get a PR, not a PDF

    Findings arrive with the code that resolves them, opened against your repo. Review and merge. Then a seal that names the reviewed commit and the date.

What we look for
  • CriticalAccount takeoverAuth logic that lets one user end up holding another user's session.
  • CriticalBroken access controlAn endpoint that checks you are signed in but never checks the record is yours.
  • HighExposed secretsKeys that reached the client bundle, the repo history, or a log line.
  • HighInjectionInput reaching a query, a shell, or a template without being separated from it.
  • MediumDependency contaminationPackages the model invented, typosquats, and install scripts nobody read.

Severity shown is the rating each class usually carries, not a prediction about your app. Findings come with the fix, not just the diagnosis.

Frequently asked questions

A person reads your code and works the running app, then opens a pull request against your repo fixing what they found. You also get the findings written up with how to reproduce each one, and a seal naming the commit that was reviewed.

Find out what your AI left open.