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AI Attack Surface Mgmt

One of Industry’s First AI-specific Threat Verification, Analysis & Remediation Platform

WhiteHaX AI-ASM Platform is an enterprise-grade, attack-surface risks detection platform designed to verify business deployed Generative AI and Large Language Model (LLM) applications against a comprehensive spectrum of security threats and compliance risks.

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WhiteHaX AI-ASM Platform

Continuously Verify AI-deployment before it becomes a Business Risk

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AI Attack Surface Management

WhiteHaX® AI-ASM Platform

Continuously verify GenAI, Agentic-AI and RAG deployments against real-world breach scenarios, data leakage risks, and policy violations — before they become business incidents.

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Built for Security & Red Teams • Compliance • DevSecOps • Product teams

Clarity

See where AI is exposed across apps, APIs, uploads, agent tools, and RAG pipelines.

Control

Run repeatable verification continuously with built-in and custom scenarios.

Confidence

Get prioritized findings, evidence, and audit-friendly reporting for remediation.

Four pillars of AI-ASM verification

Attack Surface

See where AI is exposed across apps, APIs, uploads, agent tools, and RAG pipelines.

Adversarial Testing

Run repeatable verification continuously with built-in and custom scenarios.

Data & Policy

Get prioritized findings, evidence, and audit-friendly reporting for remediation.

Data & Policy

Get prioritized findings, evidence, and audit-friendly reporting for remediation.

How it works

1) Connect

Point WhiteHaX at your chatbot, copilot, API, RAG or agent workflow.

2) Verify

Run continuous security, policy, and resilience validation at scale.

3) Remediate

Use evidence-backed findings and guidance to harden deployment quickly.

Technical specifications
  • Deployment: SaaS management + on-prem WhiteHaX app (Win/Linux/macOS)
  • Integration: REST API, CLI, CI/CD (SAST/DAST-friendly)
  • Scale: High-volume test execution per target system
  • Reporting: PDF/HTML reports + dashboard trends
Who it’s for
  • Deployment: SaaS management + on-prem WhiteHaX app (Win/Linux/macOS)
  • Integration: REST API, CLI, CI/CD (SAST/DAST-friendly)
  • Scale: High-volume test execution per target system
  • Reporting: PDF/HTML reports + dashboard trends
Key testing modules

WhiteHaX's AI testing modules are organized into Nine Core pillars of AI security:

  • 1.1. Malicious Prompt Injection & Jailbreak Testing:Direct Prompt Injection,Indirect (Jailbreak) Attacks,Backdoor Triggers, Model Hijacking
  • 1.2. AI User-Based Behavioral & Model Threat Testing :Model Drift Simulation, Model Poisoning Attempts, Multi-Step Malicious Intent, Bias & Influence Detection
  • 1.3. Input/Output Data Leakage & Integrity Testing:PII Leakage Detection,Confidential Data Leakage, Output Bias Analysis, Toxicity Analysis
  • 1.4. Malicious Document Upload Testing
    • File Format Fuzzing: MS-Office Docs (Word, Excel, PPT etc.), PDFs, Images (JPG, PNG, SVG, etc.), QR Codes
  • 1.5. LLM API Misuse & Abuse Testing:Invalid API Request Flooding, Key/Token Abuse Simulation, Anomalous Access Pattern Detection, Access Rights Abuse
  • 1.6. Agentic-AI specific Denial-of-Serice Attacks: Resource Exhaustion, Cost Amplification, Memory Exhaustion, Token Overflow & Rate Limit Bypass
  • 1.7. Policy & Compliance Enforcement:GDPR Privacy Tests, HIPAA Tests, OWASP Top-10 for LLM Checks, Custom Regulatory Frameworks
  • 1.8. Performance & Responsiveness Measurement: Response time for Prompt Inputs, Response time of Document Processing, Overall System Performance
  • 1.9. Stress test MCP Services: Protocol Violation, MCP Tool Abuse, Resource Exhaustion, Memory Leak, Session Hijack, Additional MCP Tests

Ready to verify your AI deployment?

Request a trial and get an AI-ASM readiness walkthrough.

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Technical Specs