Strengthening application resilience in an AI era
Detect and mitigate AI-specific risks like prompt injection and model misuse with security testing
purpose-built for AI
Analyst report
AppSec Strategy 2026: AI, DevSecOps and Platform Consolidation
Release secure, AI-powered software fast
Combine proven enterprise application security testing with intelligent auditing, agentic automation, and total protection across the new AI attack surface
AI logic security
Detect and fix AI-specific flaws
Identify and remediate vulnerabilities unique to AI-enabled code, including insecure model usage, unsafe outputs, and flawed AI decision logic.
Prompt & input abuse
Stop AI manipulation at the source
Detect prompt injection, malicious inputs, and unsafe data flows early, and guide remediation before AI behavior can be exploited.
AI-generated code risk
Secure code written by AI
Continuously detect and remediate vulnerabilities introduced by AI-generated code to ensure it meets enterprise security standards.
AI data exposure
Prevent AI-driven data leakage
Detect insecure data handling, overexposure, and unintended disclosure paths created by AI features—and remediate them before release.
Code security customer success
Find out how these organizations use OpenText enterprise application security solutions
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Application security
Empower developers with trusted, reimagined application security
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OpenText™ Static Application Security Testing
Find and fix security issues early with the most accurate results in the industry
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OpenText™ Application Security Aviator™
Secure smarter, not harder with AI code analysis and code fix suggestions
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OpenText™ Core Application Security
Unlock security testing, vulnerability management, and tailored expertise and support
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OpenText™ Core Software Composition Analysis
Take full control of open source security, compliance, and health
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Frequently asked questions
AI-enabled applications introduce new failure modes, such as prompt injection, unsafe model outputs, insecure AI logic, and unintended data exposure, that don’t exist in conventional code. These risks require security testing that understands how AI features behave, not just how code is written.
AI-focused security testing can identify issues like prompt injection paths, insecure handling of AI inputs and outputs, flawed AI decision logic, data leakage through AI responses, and vulnerabilities introduced by AI-generated code.
When AI-specific vulnerabilities are detected, remediation guidance is tailored to the AI context, helping teams fix insecure prompts, strengthen validation, correct unsafe logic, or remediate vulnerable AI-generated code without trial and error.
Yes. Even limited AI features, such as chat interfaces, recommendation logic, or AI-assisted workflows, can introduce new attack paths. Detecting and remediating AI-specific vulnerabilities is critical wherever AI influences application behavior.
AI-specific detection and remediation extend existing AppSec practices rather than replacing them. Organizations can address AI-driven risks alongside traditional vulnerabilities using familiar workflows, tools, and governance models.
OpenText brings decades of application security expertise into the AI era, extending proven detection and remediation capabilities to AI-specific risks. With security testing tuned for AI logic, AI-generated code, and emerging attack techniques, OpenText helps organizations adopt AI confidently, without compromising security, governance, or development velocity.
