HiddenLayer Raises $100M as Enterprises Rush to Secure AI Deployments

Three years ago, when AI security startup HiddenLayer raised its $50 million Series A, a key question loomed: would AI-specific threats materialize at scale, justifying a dedicated market? At the time, concrete examples of large-scale AI attacks were scarce. How quickly the landscape has shifted. Security vendors now scramble to build tools that monitor not only AI agents but also the tools and add-ons they rely on. While headlines about exploited agents remain rare, the risk of agents malfunctioning in production is very real. This urgency has fueled explosive market growth: Gartner estimates companies will spend $2.83 billion on AI security products this year, an 83% increase from 2025, with spending projected to reach nearly $4.78 billion in 2027. HiddenLayer, which protects AI models, agents, and workflows from adversarial attacks, vulnerabilities, and malicious code injections, has capitalized on this shift. Co-founder and CEO Chris Sestito told TechCrunch that annual recurring revenue grew more than tenfold over the past year. While he declined to disclose exact figures, he confirmed ARR is now in the "tens of millions," with over 90% of that growth driven by new customers in the last twelve months. Financial services and large tech firms building AI products are the company's largest verticals. HiddenLayer also holds contracts with the Department of Defense and the intelligence community. Notably, one customer is a "leading frontier model provider" with over 700 million weekly users—which strongly suggests OpenAI or Anthropic. To build on this momentum, HiddenLayer has raised $100 million in a Series B round led by Delta-v Capital, with participation from Ten Eleven Ventures, Morgan Stanley, Microsoft's M12, and Booz Allen Hamilton, among others. The Austin-based startup continues to sell its core offerings—discovery, runtime protection, attack simulation, and supply chain security—but has extended them to address prompt injection, agent manipulation, and malicious tool use. Sestito explained, "Inference is still inference. Whether it's a traditional machine learning model, Gen AI, or an agentic work stream, much of our technology still applies. We haven't had to pivot, but we've had to grow our scope from traditional modeling to Gen AI to agentic." Runtime security has become a particular priority as AI deployments proliferate across businesses. Sestito likens it to endpoint detection and response (EDR) solutions, but tailored specifically for AI. The company's new products reflect this evolution. Sestito highlighted a growing attack vector: exploitation of open-source models. "We parse and scan about 50 different AI file frameworks to ensure that, especially with open-source and open-weight models, they are free of hidden threats," he said, emphasizing the need for vigilance in a rapidly expanding AI ecosystem.

via TechCrunch AI