Fremont, CA – October 14, 2025 – IronSDN, the leader in risk management solutions for businesses, unveiled today the WhiteHaX AI-Attack Surface Management (AI-ASM), an enterprise platform designed to expose security, compliance, and performance risks in Generative AI, LLM, and Agentic-AI deployments before they impact customers or the business.

As enterprises rapidly deploy AI copilots, chatbots, and autonomous agents, many lack visibility into how these systems behave under adversarial conditions. Traditional application security tools were not built to test prompt manipulation, model abuse, agent tool misuse, or AI-specific denial-of-service scenarios. WhiteHaX AI-ASM fills this gap by automating large-scale adversarial testing across the full AI attack surface.

“AI systems introduce an entirely new class of failure modes that most organizations are not testing for,” said [Vimal Vaidya, CEO at IronSDN, “AI-ASM continuously attacks AI deployments the same way real adversaries do—across prompts, documents, APIs, agents, and MCP services—so teams can identify and fix issues before they reach production.”

Testing AI the Way Attackers Do

WhiteHaX AI-ASM simulates hundreds of thousands of AI-specific attacks per hour, validating security, compliance, and system resilience across nine core risk areas, including:

• Prompt Injection and Jailbreaks
  – Advanced prompt manipulation, backdoor triggers, and model hijacking attempts
• Agentic-AI and RAG Security
  – Multi-step attack chains, tool abuse, memory exhaustion, and cost amplification
• Data Leakage Detection
  – Identification of PII, proprietary data, and confidential information exposure
• Malicious File Uploads
  Weaponized PDFs, Office documents, images, QR codes, and embedded prompt attacks
• LLM API Abuse
  Token theft simulations, rate-limit bypass, and anomalous access patterns
• AI Denial-of-Service
  Resource exhaustion, token overflow, and high-concurrency stress testing
• Policy and Compliance Validation
  GDPR, HIPAA, EU AI Act readiness, and OWASP Top-10 for LLMs
• Performance and Latency Measurement
  End-to-end AI responsiveness and throughput monitoring
• MCP Service Security
  Protocol violations, tool abuse, session hijacking, and memory leak detection

Built for Enterprise AI Teams

The platform integrates into CI/CD pipelines, APIs, and developer workflows, enabling continuous validation as AI systems evolve. WhiteHaX AI-ASM combines SaaS management with on-prem deployment options and provides detailed remediation reports, audit-ready evidence, and centralized dashboards for tracking risk over time.

Who Is Using It

• Security and Red Teams testing AI attack surfaces
• Compliance and Risk teams preparing for regulatory scrutiny
• AI developers embedding security into DevSecOps pipelines
• Product teams shipping customer-facing AI features

Why It Matters
AI failures are no longer hypothetical. Prompt injections, data leaks, runaway inference costs, and agent misbehavior are already causing real-world outages and regulatory exposure. WhiteHaX AI-ASM gives enterprises a way to continuously verify AI deployments under real-world attack conditions—before those failures become public incidents.

WhiteHaX AI-Attack Surface Management is available now.

The WhiteHaX AI ASM platform is now available for business customers as a cloud-based, SaaS solutions and for MSSPs as subscription-based managed services.

About IronSDN IronSDN, Corp. specializes in cyber risk management solutions for businesses. It’s flagship WhiteHaX brand of solutions are specifically designed ground-up to help businesses identify and eliminate cyber risks across AI infrastructure, data and humans. Cloud-hosted WhiteHaX AI ASM platform offers businesses a quick, low-impact, low-cost AI attack surface risk management. WhiteHaX AI ASM helps businesses gradually improve their AI security posture through thorough AI risk verification and provides detailed reports with step-by-step recommendations on how to improve AI security risks. For more information on WhiteHaX AI ASM, visit
https://www.WhiteHaX.com