Security for AI

High Tech

Enabling Safe and Scalable AI Adoption

The Challenges

Accelerating AI Adoption While Mitigating Risks

For technology companies, the rapid adoption of agentic, generative, and predictive AI creates competitive advantage but also presents a growing set of risks. Organizations face an increasingly complex threat landscape that includes adversarial manipulation, supply chain compromise, and model theft. Protecting AI applications against these evolving threats is essential to safeguarding intellectual property, ensuring resilience, and maintaining customer trust.

Adoption of Agentic & GenAI Applications

The rise of agentic and generative AI introduces new risks that necessitate innovative and proactive security measures. Emerging threats like indirect prompt injection, hidden prompt injections against coding agents, and function abuse in agentic systems highlight how adversaries exploit novel attack surfaces. Organizations need safeguards that protect innovation without increasing operational risk.

Navigating Regulations

Evolving frameworks for AI ethics, security, and privacy increase compliance pressure on technology providers. Aligning with standards like NIST AI RMF, ISO 42001, and the EU AI Act requires precise governance strategies that mitigate legal exposure while sustaining business agility.

Scale Safely with Speed

As AI operations expand, leaders must ensure consistent protection across diverse environments. Future-ready defenses enable organizations to maintain performance and resilience at scale—delivering security without slowing adoption.

Our Approach

Secure, Defend, & Automate

HiddenLayer’s AI Security Platform unifies supply chain security, runtime defense, posture management, and automated red teaming to protect agentic, generative, and predictive AI. The platform delivers scalable, automated defenses that detect malicious injections, prevent tampering, and monitor inputs and outputs in real time—empowering enterprises to adopt AI with confidence and resilience.

Adversarial Attack Prevention

Continuous, adaptive protection against prompt injection, model theft, and other adversarial threats ensures AI applications remain resilient from development through deployment.

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AI Governance

Integrates security frameworks and compliance controls into MLOps pipelines, aligning with NIST AI RMF, ISO 42001, and OWASP LLM Top 10 so governance is operationalized, not just a checkbox.

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Scalable Security Architecture

Enterprise-grade protection designed for growth, enabling organizations to secure expanding AI operations and agentic workloads without slowing innovation or performance.

As AI powers growth in the tech sector, safeguarding systems is essential to protect IP, maintain compliance, and enable innovation at scale.

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Key Capabilities

Excessive Agency Control — Governs agentic outputs and tool use to prevent backend exposure, privilege escalation, or unsafe execution that could disrupt operations.
Model Theft Prevention — Blocks reconnaissance and inference attacks aimed at stealing proprietary models, safeguarding intellectual property and competitive advantage.
Model Integrity — Validates AI models for tampering or corruption, preserving accuracy and protecting against manipulated outcomes that could undermine customer trust or compliance.
Prompt Injection Defense — Protects agentic and generative applications from adversarial input or output manipulation, reducing the risk of data leakage and unsafe system behaviors.
Malware Analysis — Detects malicious code hidden in AI applications before it can be weaponized as an infection vector, ensuring safe adoption of open-source and third-party models.

Recent News

Risks Related to the Use of AI

Why HiddenLayer

The most comprehensive security platform for AI

HiddenLayer, a Gartner-recognized AI Security company, is the only platform purpose-built to secure AI models and autonomous agents alike. Covering agentic, generative, and predictive AI applications, HiddenLayer protects the world’s most valuable technologies across the entire lifecycle—ensuring compliance, safeguarding IP, and strengthening enterprise resilience, while aligning with leading frameworks such as NIST RMF, MITRE ATLAS, ISO 42001, and the EU AI Act.

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Research 09.11.2025

Research

09.11.2025

How can we secure your AI?

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