
HiddenLayer is an AI security platform for organizations building or adopting generative, predictive, and agentic systems. It combines asset discovery, model supply-chain analysis, adversarial testing, and runtime defenses. Security teams can assess a model before deployment and continue monitoring the application that uses it.
HiddenLayer brings several stages of AI security into one platform. A model-scanning result, an attack simulation, and a production alert answer different questions; the platform gives security teams tools for each stage rather than treating a prompt filter as the entire assessment.
Its coverage includes agentic and MCP workflows, where an unsafe action may involve connected tools as well as generated text.
Use discovery to build an inventory, then examine models for malware, vulnerabilities, or supply-chain concerns. Attack simulations test how applications behave under adversarial input and help teams validate their defenses before broader deployment.
Runtime controls monitor deployed AI applications for misuse, data leakage, and other adversarial activity. Integrations connect this work to CI/CD pipelines, data platforms, and SIEM/SOAR systems. Match the selected controls to the models, tools, and data access in your own environment.
Vendor-selected endorsements from security leaders emphasize lifecycle coverage, visibility, and integration with enterprise security responsibilities. They describe individual professional perspectives rather than a measured success rate for every customer. An evaluation should include representative attacks and the response workflow your team needs.
HiddenLayer uses sales-led pricing for enterprise deployments. Request a commercial proposal covering the capabilities and deployment scope you need.
Compare discovery, model scanning, attack simulation, and runtime coverage separately when defining the evaluation. A useful purchase decision depends on which AI assets can be assessed and how findings reach the teams responsible for fixing them.
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