Guardiant is built on three research frameworks that formalize how AI coding assistants introduce structural security flaws. These frameworks are reproducible, applicable beyond Guardiant, and represent a new class of vulnerability detection.
Catalogs the specific vulnerability patterns AI tools introduce systematically.
Connects isolated medium-severity findings into critical attack paths.
Identifies where code trusts the wrong boundary — client, SDK, or frontend.
Vibe Code Vulnerability Fingerprinting catalogs the structural patterns that AI coding assistants introduce. Each pattern is reproducible across different AI tools and codebases.
AI tools generate UPDATE/DELETE endpoints with identical authorization logic as GET endpoints. No ownership verification.
// AI-generated: same auth check for all operations
router.delete('/api/users/:id', async (req, res) => {
if (!req.session.userId) return res.status(401).send();
// BUG: Any authenticated user can delete ANY user
await db.users.delete({ id: req.params.id });
res.send({ success: true });
});Pattern match: delete/update handlers with identical auth middleware as read handlers, no resource ownership check.
Individual medium-severity findings become critical when chained together. CVC identifies these attack paths automatically.
A table without RLS allows any client to query all rows. Combined with a client-side SDK, an attacker can exfiltrate the entire database.
Role checks only in the frontend. An attacker calls the API directly with a modified request, gaining admin access.
Update endpoint uses same auth as read. Attacker modifies user_id in the request body to take over any account.
Every application has trust boundaries. TIEF identifies where the code trusts the wrong boundary — and shows you the exploit path.
The code assumes the frontend is the security boundary. An attacker bypasses it by calling the API directly.
The code trusts the client SDK to enforce access control. Without RLS, the SDK is an open door.
Validation runs only in the browser. An attacker sends raw requests with malicious payloads.
The implementations, detection logic, and test cases are all available in the Guardiant repository. Use them, extend them, or build your own tools on top.