HiddenLayer, a Gartner recognized Cool Vendor for AI Security, is the leading provider of Security for AI. Its security platform helps enterprises safeguard the machine learning models behind their most important products. HiddenLayer is the only company to offer turnkey security for AI that does not add unnecessary complexity to models and does not require access to raw data and algorithms. Founded by a team with deep roots in security and ML, HiddenLayer aims to protect enterprise’s AI from inference, bypass, extraction attacks, and model theft. The company is backed by a group of strategic investors, including M12, Microsoft’s Venture Fund, Moore Strategic Ventures, Booz Allen Ventures, IBM Ventures, and Capital One Ventures.
Biden Executive Order on Standards for AI Safety and Security
“Require(s) that developers of the most powerful AI systems share their safety test results and other critical information with the U.S. government.”
NIST AI Risk Management Framework
“Common security concerns relate to adversarial examples, data poisoning, and the exfiltration of models, training data, or other intellectual property through AI system endpoints. AI systems that can maintain confidentiality, integrity, and availability through protection mechanisms that prevent unauthorized access and use may be said to be secure.”
European Union Artificial Intelligence Act
“If models meet certain criteria they will have to conduct model evaluations, assess and mitigate systemic risks, conduct adversarial testing, report to the Commission on serious incidents, ensure cybersecurity, and report on their energy efficiency.”
Service Offerings
AI Risk Assessment
A detailed analysis of your ML Operations lifecycle and an in-depth review of your most critical AI models to determine the risk your AI investments currently pose to the organization. Findings are mapped to industry best practices such as NIST, MITRE ATLAS, and OWASP to provide actionable guidance for reducing organizational risk.
Adversarial ML Training
Two-day training to provide data science and security teams with an understanding of Adversarial Machine Learning TTPs and the most effective countermeasures to protect against them. Determine appropriate next steps and modifications required for internal testing processes to include ML models and an overview of offensive AI tooling, including Adversarial Robustness Toolbox (ART), Counterfit, CleverHans, Augly, Foolbox, and more.
Red Team Assessment
The Adversarial Machine Learning Research (AMLR) Team will leverage the same TTPs used by attackers to assess how well the attacks are currently detected and prevented by your existing people, processes, and controls. The red teaming engagement will focus on the following attack techniques to ascertain each model’s robustness to Attack: Reconnaissance, Inference, Bypass, Insider Threat, Prompt Injection, Code Audit, and Model Compromise.
AI Detection & Response (AIDR) Implementation Services
Professional implementation and integration of HiddenLayer’s AI Detection & Response (AIDR) product into the AI environment. It provides the data science and security teams with the functionality and visibility required to prevent attacks, improve responsiveness, and maximize model effectiveness.
Security for AI Retainer Service
An annual retainer service led by our Adversarial Machine Learning Research (AMLR) Team for full-service MLOps Lifecycle support, including an incident response plan, regular risk assessments, and adversarial ML team training.
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