Next-Generation AI Vulnerability Scanning

Stop zero-day exploits before they happen. Our proprietary neural networks identify complex logic flaws that traditional scanners miss.

Check Your Web App With AI Vulnerability Scanning

Traditional vulnerability scanners rely on static signatures and pattern matching. While effective for known CVEs, they are completely blind to novel, zero-day logic flaws specific to your application's architecture.

FortPilot's AI Vulnerability Scanner actively learns the expected behavior of your APIs and web forms to uncover deep-seated authentication bypasses, broken access controls, and injection flaws before attackers do.

What is AI Vulnerability Detection?

AI vulnerability detection goes beyond simple payload injection. By utilizing neural networks and machine learning models, the scanner maps the logical flow of your application. It understands what a "normal" request looks like and intelligently mutates data to find unexpected edge cases.

Why is AI Scanning Important?

Zero-Day Logic Flaws

Because every web application is uniquely coded, business logic flaws don't have a CVE number. AI scanning is the only automated way to detect these unique, zero-day vulnerabilities without expensive manual penetration testing.

Automated Credential Stuffing Defense

Our scanners simulate sophisticated botnets attempting credential stuffing attacks. We analyze your rate limiting, CAPTCHA implementation, and session management to ensure your login endpoints are fortress-grade.

How to Use the AI Vulnerability Scanner

Enter your application URL: Input the target web application above.
Start the scan: The AI engine will begin crawling and mapping your application's logic.
Review findings: Analyze the detailed report highlighting logic flaws, false positives, and mitigation steps.
Remediate: Apply the suggested architectural changes and rescan to verify the fix.

AI Vulnerability Scanning FAQ

How does AI differ from traditional scanning?

Traditional scanners match known signatures. AI scanners understand application logic and dynamically generate unique payloads to test for novel vulnerabilities.

Does the AI engine produce false positives?

While no scanner is perfect, AI contextual analysis drastically reduces the noise of false alarms by verifying exploitability before reporting.

Can it test authenticated areas?

Yes. You can configure the scanner with test credentials or authentication headers to map the logic of secured dashboard areas.

Key Capabilities

Zero-Day Logic Detection

Identifies completely new attack vectors and business logic flaws without needing a CVE database update.

Low False Positives

AI contextual analysis drastically reduces the noise of false alarms by validating exploits.

Continuous Learning

The model adapts to your architecture as your application grows and changes.

Credential Stuffing Simulation

Tests your authentication endpoints against massive, automated brute-force attacks.

Intelligent Payload Mutation

Dynamically alters payloads based on server responses to bypass WAFs and simple filters.

Session State Analysis

Detects broken access controls and improper session invalidation logic.