Use case · Teams building with AI coding agents
Your AI assistant asks. Vulkro answers.
Instead of reading your whole codebase, it gets back the finding, the path that proves it and what to change. It makes the fix, and Vulkro checks it again.
- Claude Code
- Cursor
- Codex
- GitHub Copilot
01The problem
Reading everything is a poor security check.
An AI assistant asked to review its own code usually reads file after file and reasons about what it saw.
- ExpensiveEvery review pays for the codebase in tokens again, and a bigger repository costs more each time.
- Not repeatableAsk twice and you can get two answers. A security check needs one.
- Marking its own workThe assistant that wrote the line is often the one deciding it is safe.
02How Vulkro helps
One question, one precise answer.
The assistant calls Vulkro, gets the proven problem on the exact line, and makes a fix you review. Vulkro scans it again. A guard can also check every file the assistant writes, before it moves on.
VS Code agent mode, calling the extension’s scan tool. Other assistants use the same engine through Vulkro’s MCP server.
03Why it holds up
Precise, and checkable.
- 0166% fewer tokensOn a security review, against an AI agent reading the code itself, finding as many real issues in total (238 of 280).Measured with vulkro 0.32.0 on 2026-10-07, on Vulkro's own test apps, which were used to develop Vulkro, so the result is flattered.
- 02No AI in detectionThe same code gets the same answer, every run. The assistant asks; the engine decides.No model is called during a scan
- 03Runs offlineYour code stays on your machine. The guard checks each write with no network call.The command-line tools and the VS Code extension