HiddenLayer

Founded by Christopher Sestito in 2022

Comprehensive AI security platform safeguarding models and assets across their entire lifecycle.

Pricing model

Demo

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use HiddenLayer to protect your AI models and assets from a wide range of threats, including prompt injections, data poisoning, model theft, and supply chain compromises. Designed for professionals like Machine Learning Engineers and AI Research Scientists, it offers runtime defense, supply chain protection, and automated red teaming to ensure the integrity and compliance of your AI deployments. With seamless integration into existing infrastructures, HiddenLayer enables secure AI adoption without disrupting your workflows.

What HiddenLayer does

Implement runtime defenses to detect and block AI-specific threats.Conduct automated red teaming exercises to test AI model security.Monitor AI model interactions for signs of adversarial manipulation.Validate and secure third-party AI models before deployment.Enforce compliance and governance policies for AI assets.Integrate AI security measures into existing DevOps pipelines.Analyze threat intelligence to stay ahead of emerging AI risks.Generate AI Bills of Materials to maintain an inventory of model components.Runtime Defense: Real-time protection against prompt injections, data poisoning, and model theft.Supply Chain Protection: Safeguards against malware in pre-trained models and tampered third-party artifacts.Automated Red Teaming: Continuous testing to uncover vulnerabilities before attackers do.Agentic AI Control: Governs tool use, permissions, and task execution to prevent malicious redirection.Posture & Governance: Enforces model signing and compliance policies across environments.Seamless Integration: Compatible with platforms like AWS, Azure, and GCP for easy deployment.Comprehensive Threat Intelligence: Aggregates data from public sources enriched with expert analysis.AI Bill of Materials (AIBOM): Provides an auditable inventory of model components and dependencies.