HiddenLayer, a cybersecurity startup based in Austin, Texas, emerged in response to a cyberattack that exploited machine learning code at the founders’ previous company. Today, HiddenLayer has announced a successful $50 million Series A funding round aimed at bolstering the defenses of the ever-expanding array of AI models adopted by enterprises.
This funding round was spearheaded by M12, Microsoft’s Venture Fund, and Moore Strategic Ventures, with participation from Booz Allen Ventures, IBM Ventures, Capital One Ventures, and Ten Eleven Ventures.
HiddenLayer’s CEO and Co-Founder, Chris Sestito, expressed, “The rapid adoption of AI inspires us to accelerate our mission, ensuring that every security professional possesses the necessary tools and expertise to embrace AI securely.”
HiddenLayer already plays a crucial role in safeguarding AI/ML models for numerous Fortune 100 companies across various sectors, including finance, government, defense, and cybersecurity.
What HiddenLayer Offers:
Previously covered by VentureBeat, HiddenLayer has developed a suite of tools as part of its “MLSec” Platform, designed to safeguard enterprise machine learning (ML) and AI models. These tools do not directly access the models or compromise clients’ proprietary data and technology. Instead, they actively monitor the performance and operations of enterprise ML/AI models and associated applications in real-time. They scan for overarching vulnerabilities, provide recommendations for fortifying security, and detect the injection of malicious code/malware. Furthermore, they deploy defense mechanisms to thwart attackers and isolate intrusions.
HiddenLayer’s MLSec Platform includes an intuitive yet powerful dashboard, granting security managers immediate access to essential information about the security status of their enterprise ML/AI models. It automatically lists security issues and alerts in order of priority based on severity and stores data for compliance, auditing, and reporting purposes.
Additionally, HiddenLayer offers consulting services provided by their team of Adversarial Machine Learning (AML) experts, who remain up-to-date with the latest security trends and threats. These services encompass threat assessments, training for cybersecurity and DevOps personnel, and “red team” exercises to verify the effectiveness of clients’ defenses.
Earlier this year, HiddenLayer established a partnership with the prominent enterprise data lakehouse provider, Databricks. This collaboration enables Databricks enterprise customers to directly utilize HiddenLayer’s MLSec Platform for their models running on Databricks’ lakehouses. The integration is model-agnostic and covers model scanning, detection, and response. It empowers Data Scientists and ML Engineers to enhance their models’ security without altering their code or environment. As models are loaded, HiddenLayer’s model scanner ensures integrity and security. If an attack is detected, the integration responds automatically without human intervention.
Future Goals for Enterprise AI Security:
HiddenLayer’s inception traces back to an incident at its co-founders’ prior company, Cylance, where ML models fell victim to a cyberattack. Attackers exploited Cylance’s Windows executable ML model, revealing vulnerabilities and enabling the production of evasive binary files. While this event was concerning, it prompted the realization that attacks on ML/AI would escalate as more enterprises adopted generative AI to boost efficiency and performance.
Presently, HiddenLayer is experiencing rapid growth, having quadrupled its workforce in the past year. With the Series A funding secured, the company plans to hire an additional 40 personnel by year-end and continue expanding its client base.