CodeOne
Fortify Aviator Ent.
What is Fortify Aviator Ent.?
Fortify Aviator Ent. (AI-Powered Application Security Diagnostic Assistant)
Fortify Aviator Ent. is a next-generation, on-premise security diagnostic solution that combines OpenText Fortify's Static Application Security Testing (SAST) capabilities with generative AI.
From the moment a developer writes code to a security officer's vulnerability audit and penetration-test-level logic flaw diagnosis, a single AI engine supports the entire application security lifecycle.
AI that reads code context together with data flow filters out false positives and provides secure-coding solutions that let you focus only on real threats.
Product Overview
Key Features
SHIFT-LEFT
For Developers
The moment code is written in the IDE, AI diagnoses vulnerabilities in real time and suggests secure-coding fixes directly on the code line.
VALIDATION
For Fortify
AI re-analyzes Fortify SAST scan results to accurately distinguish true positives from false positives, dramatically reducing the audit time required from security experts.
DISCOVERY
For Pen Testers
Scans a project standalone, even without Fortify, to diagnose penetration-test-level authentication/authorization bypasses and business logic flaws, and provides immediate secure-coding solutions.
Product Overview
Benefits
Increased Productivity
AI re-judgment shortens audit time and reduces the burden of repetitive review.
Risk Prevention
Immediate diagnosis and fixes at the moment code is written eliminate vulnerabilities before deployment.
Expanded Security Coverage
Integrates every stage of development and security into a single AI engine.
Product Overview
Why Fortify Aviator Ent.?
Multi-Agent Cross-Validation: Two or more AI models make independent judgments, then go through a process of mutual rebuttal and consensus to refine and report only real threats (true positives). This greatly reduces the fatigue caused by false positives.
Flexible Deployment Options: Supports both commercial cloud APIs (Claude, GPT, etc.) and closed-network on-premise deployment (open-weight LLMs), satisfying even the network-separation requirements of financial institutions and public agencies.
Precision Analysis Based on Code Context: Based on data flow and call graph analysis rather than simple text matching, it provides well-founded vulnerability judgments and fix code.