HiddenLayer has released version 25.12 of its AI Security Platform Console, introducing structural and operational updates designed to align security capabilities with AI development and deployment workflows. The update focuses on modularization, workflow-driven navigation, and enhanced reporting to support enterprise AI risk management.
Transition to Workflow-Aligned Modules
The release replaces the platform’s previous standalone products with three integrated modules, each corresponding to a distinct stage of the AI lifecycle. The former Model Scanner is now AI Supply Chain Security, Automated Red Teaming for AI is AI Attack Simulation, and AI Detection & Response (AIDR) has been rebranded as AI Runtime Security. This reorganization aims to clarify responsibilities, reduce tool fragmentation, and provide a unified operational view of AI risk.
Console and Dashboard Enhancements
Version 25.12 introduces a redesigned Console interface with workflow-driven navigation, intended to simplify movement between modules, policies, detections, and insights. A new unified Security Dashboard aggregates key metrics, charts, and summaries, giving both practitioners and leaders situational awareness of AI security posture.
All modules now include exportable data tables, facilitating analysis, integration with internal workflows, and compliance reporting. Additionally, the platform’s Learning Center has been expanded to centralize documentation and tutorials, supporting faster onboarding and ongoing enablement for security teams.
Incremental Operational Improvements
Additional updates in this release focus on day-to-day usability. These include default date ranges for detection logs, severity-based filtering for modules, improved table navigation and pagination, updated detection badges, and optional support for custom logout redirect URLs via SSO. These enhancements aim to improve efficiency, clarity, and enterprise readiness.
Implications for Enterprise AI Security
The update reinforces a structured, end-to-end approach to AI security, spanning supply chain assessment, attack simulation, and runtime monitoring. By aligning capabilities with operational workflows, organizations can achieve clearer ownership of security responsibilities, faster response times, and a more comprehensive understanding of AI risk across models, pipelines, and environments.
The release reflects ongoing investment in operational usability and enterprise-focused functionality, addressing practical needs in AI deployment and governance.