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Use cases / Secure AI Coding

Use case

Security rules runwhile the AI writes.

Adopt OWASP ASVS, OWASP Top 10, OWASP API Security Top 10, CWE Top 25, NIST SSDF and NIST SP 800-53 as rule packs, add your own in plain English, and Uzera holds the agent to them as it writes. A violation is denied before anything is saved, and every allow and deny is recorded. What is already in the repository is covered too: Code Health scans every repo for SQL injection, weak randomness, weak encryption, unsafe data loading and hardcoded secrets, and the findings are fixed in the review loop.

What Uzera does while the agent writes

Frameworks in. Your rules in. Violations denied. Proof out.

Guardrails holds the agent to your rules as it writes. Trust is the proof afterwards.

Guardrails

Frameworks as rule packs

Adopt the security frameworks you answer to as rule packs: OWASP ASVS, OWASP Top 10, OWASP API Security Top 10, CWE Top 25, NIST SSDF, NIST SP 800-53 and General Security Best Practices, plus coding standards for languages like C#, TypeScript, JavaScript and Node.js, with more added regularly. One click, applied to every agent in the workspace.

  • Applied as the agent writes
  • Scoped per repository or workspace-wide
  • Updated packs, adopted when you choose

Guardrails

Your rules, in plain English

Write the rule the way you would say it in a review. Uzera compiles it to an enforceable matcher, and rejects it if it can't, so a rule is never quietly ignored.

  • Plain English in, enforceable rule out
  • Rejected if it cannot be enforced
  • Block, warn or inform, your choice

Guardrails

Denied, not discovered

The violation never reaches the pull request. It is denied while the agent writes, so reviewers stop re-finding the same class of mistake.

  • Denied before anything is saved
  • Fewer security comments in review
  • What is already in the repo is found by Code Health and fixed in the loop

Trust

Proof for the security team

Every allow and deny is written to a hash-chained ledger, with the rule that decided it. Admin changes to rules and roles land in the audit log.

  • Every verdict, in order
  • Which rule decided it, and when
  • A database per customer

How the guard runs

Adopt. Enforce. Prove.

Three steps, and the team keeps working the way it does.

Step 01

Adopt

Pick the frameworks you answer to and adopt them as rule packs. Add the rules that are specific to you, in plain English.

Step 02

Enforce

The rules run while the AI writes. A violation is denied before anything is saved, with the rule named, so the agent corrects course on the spot. Code Health scans the code that is already there for the same class of problem, and those findings close themselves when the fix lands.

Step 03

Prove

Every allow and deny lands on the hash-chained ledger and every admin change in the audit log. The security team reads the record, not the rumour.

Where it fits

Your security team sets the bar. Uzera holds every agent to it.

Your team decides which frameworks and which rules apply. Uzera applies them to every agent as it writes, records every verdict, and gives the security team the ledger and the audit log they ask for.

Before the budget conversation

Questions security teams ask first.

01Does our source code leave the machine?

No clone of your repository is ever taken. Three things are sent: the diff of the change under review, the names and locations of the symbols it touches, and the agent's conversation for that session. Nothing else. The index of your codebase stays on your machine.

02How is this different from the SAST scanner we already run?

The scanner reads what is already committed. Uzera also runs while the agent writes, so a violation is denied before it is saved instead of queued as a finding. What is already in the repository is still scanned.

03Which frameworks can we adopt?

OWASP ASVS, OWASP Top 10, OWASP API Security Top 10, CWE Top 25, NIST SSDF and NIST SP 800-53, plus the rules you write in plain English. New templates arrive as packs you choose to adopt.

Governance for your coding agents

Every team adopted AI agents.
Few governed them well.

AI writes your code. You stay in charge.