HiddenLayer in the News
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HiddenLayer Raises $100M Series B to Advance Trustworthy AI
HiddenLayer raises $100M in Series B funding to advance AI security, expand agentic runtime protection, and meet growing enterprise demand.
The investment comes as enterprises race to secure a rapidly expanding AI attack surface, from foundation models to the autonomous agents now writing and shipping code on their behalf.
September 2, 2026 – Austin, TX – HiddenLayer, the leading AI security company that secures agentic, generative, and predictive AI applications, today announced a $100 million Series B funding round led by Delta-v Capital, with participation from Ten Eleven Ventures, Morgan Stanley, M12, Microsoft's Venture Fund, and Booz Allen Ventures.
The company will use the funding to deepen its enterprise platform, including its Agentic Runtime Security capabilities, and Agent Harness Security, a new solution that extends the Runtime Security module to secure AI coding agents at runtime and protect enterprises adopting autonomous coding agents into their stack.
"We set out to pioneer trusted, secure use of AI for enterprises, long before most organizations saw the urgency we do today. This funding lets us keep growing the purpose-built team and platform required to meet that moment as agentic AI becomes core to how enterprises operate,” said Chris Sestito, CEO and Co-Founder of HiddenLayer.
The raise follows a standout year: HiddenLayer's annual recurring revenue grew more than 10x, and the company signed more than 50 new platform customers, including some of the largest names in securities brokerage, banking, insurance, accounting, government, technology, IT services, pharmaceuticals, airlines, and the US defense and intelligence communities. Internationally, new customers included one of the world's largest pharmaceutical companies, along with several premium automotive brands and food and beverage providers. HiddenLayer also supports a leading frontier model provider in securing more than 700 million weekly users.
This growth is underpinned by a world-class research team that has directly influenced how leading organizations protect their AI systems. HiddenLayer's researchers hold 39 granted patents and 65 pending patents spanning adversarial detection, model protection, and AI threat analysis. The team developed the first comprehensive Adversarial Prompt Engineering (APE) Taxonomy and continues to research emerging threats across generative, predictive, and agentic AI, identifying dozens of vulnerabilities across the AI ecosystem, from foundation models to the tools and infrastructure that support them. HiddenLayer's researchers also contribute to the broader AI security community through work with organizations and initiatives including CISA/JCDC, MITRE, NIST, OWASP, and OpenSSF, improving red teaming methodologies and informing global discussions on AI governance and safety.
"Traditional security tools were built for code and infrastructure, not for models that can be poisoned, hijacked, or manipulated through their own inputs,” said Dan Williams, Partner at Delta-v Capital. "HiddenLayer built a platform from the ground up to secure AI across its full lifecycle, from the model at its core to the agentic systems being layered on top and whatever architecture comes next. We’ve watched this team turn deep adversarial-AI research into a product CISOs actually rely on, and we're proud to partner with them."
The funding allows HiddenLayer to focus on the three fronts where enterprises are most exposed: Agentic Runtime Security, giving organizations visibility into how their AI agents behave in production, flagging and stopping manipulation, tool misuse, and unauthorized actions as they happen, and securing Agentic Harnesses and Autonomous Coding Agents that write, review, and ship code with much less human oversight than traditional development tools. As AI cannot be made trustworthy through design-time principles alone, there is no trustworthy AI without end-to-end AI-native security. Trust has to be continuously tested and proven at runtime. These capabilities are designed to give enterprises the confidence to trust their AI, with 96% of organizations already considering AI critical to their core operations, but nearly a third unable to say with certainty whether they've experienced an AI-related breach, according to HiddenLayer’s 2026 AI Threat Landscape Report.
“Enterprises don't shift budgets at this pace unless a problem is urgent. HiddenLayer's growth over the past year across defense, financial services, and some of the most sensitive AI deployments in the world demonstrates that security teams have concluded that AI needs its own category of protection,” said Mark Hatfield, Co-Founder and Partner at Ten Eleven Ventures. “We expect that conviction to continue to grow as autonomous systems become more and more integral to the enterprise."
“HiddenLayer was early to recognize that enterprise security is critical to the safe deployment of AI, and its buildout of an end-to-end platform to enable compliant AI adoption is an important contribution to addressing this market need,” said Zheng Wang, Head of Strategic Investments at Morgan Stanley. “We are delighted to be investing in HiddenLayer to foster its next phase of growth and innovation.”
HiddenLayer is also strengthening its leadership team, recently naming Mike Gesnaldo as Chief Revenue Officer. More hires are on the way as the company deepens its channel relationships, keeps pace with enterprise customer demand, and pushes further into international markets, beginning with Europe and the wider EMEA region.
About HiddenLayer
HiddenLayer secures agentic, generative, and predictive AI applications across the entire AI lifecycle, from discovery and AI supply chain security to attack simulation and runtime protection. Backed by patented technology and industry-leading adversarial AI research, our platform is purpose-built to defend AI systems against evolving threats. HiddenLayer protects intellectual property, helps ensure regulatory compliance, and enables organizations to safely adopt and scale AI with confidence.
About Delta-v Capital
Delta-v Capital (“Delta-v”) partners with visionary leaders of technology companies to accelerate their next phase of growth. Delta-v is a sector-focused investor with expertise in infrastructure software, cloud services, vertical software, and digital infrastructure. The firm provides flexible growth capital to support organic growth, strategic acquisitions, and shareholder liquidity, partnering with management teams and existing investors as companies scale. Delta-v currently manages over $1.6B in assets on behalf of institutional and individual investors. For more information, please visit www.deltavcapital.com or follow Delta-v Capital on LinkedIn.
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HiddenLayer Launches the First Security Solution to Protect AI-Powered Products
AUSTIN, Texas, July 19, 2022 HiddenLayer, the developer of a unique security platform that safeguards the machine learning models enterprise organizations use behind their most important products, today emerged from stealth mode to launch its flagship product, purpose-built to detect and prevent cyberattacks that target machine-learning-powered systems. The HiddenLayer Platform’s primary product is the industry’s first and only Machine Learning Detection & Response (MLDR) solution that protects enterprises and their customers from this emerging attack vector.
Startup emerges from stealth mode after raising $6 million in seed funding led by Ten Eleven Ventures
AUSTIN, Texas, July 19, 2022 - HiddenLayer, the developer of a unique security platform that safeguards the machine learning models enterprise organizations use behind their most important products, today emerged from stealth mode to launch its flagship product, purpose-built to detect and prevent cyberattacks that target machine-learning-powered systems. The HiddenLayer Platform’s primary product is the industry’s first and only Machine Learning Detection & Response (MLDR) solution that protects enterprises and their customers from this emerging attack vector.
Organizations across virtually all industries are incorporating artificial intelligence (AI) technology into their hardware and software products that make machine learning (ML) inputs and outputs available to their customers, and bad actors have taken notice. Gartner predicts that 30 percent of all AI cyberattacks in 2022 will leverage training-data poisoning, model theft, or adversarial samples to attack machine learning-powered systems.
When ML inputs and decisions are publicly exposed, attackers can reverse-engineer the IP to steal trade secrets and tamper with production systems. These state-of-the-art attacks can destroy multi-million dollar investments, delay product releases, and leave victim organizations legally and financially liable.
According to HiddenLayer (founders Chris “Tito” Sestito, Tanner Burns, and James Ballard) companies unknowingly create vulnerabilities in their ML models for which there are no known commercially-available security controls. It’s a lesson they learned first-hand while working together at Cylance, an endpoint security software developer that pioneered the application of machine learning in anti-virus.
“We led the relief effort after our machine learning model was attacked directly through our product, and realized this would be an enormous problem for any organization deploying ML models in their products,” said Chris Sestito, CEO of HiddenLayer. “We decided to found HiddenLayer to both educate enterprises about this significant threat and help them defend against it.”
HiddenLayer’s MLDR solution uses a patent-pending ML-based approach to analyze billions of model interactions per minute to identify malicious activity without any access to or prior knowledge of the user’s ML model(s) or sensitive training data. It detects and responds to attacks against ML models to protect intellectual property and trade secrets from theft or tampering and ensure users are not exposed to attacks.
HiddenLayer’s MLDR is a non-invasive and easy-to-use security solution that does not require access to raw data or algorithms. It identifies patterns in ML model traffic through contextless vectorized data points to provide comprehensive defense from adversarial attacks targeting the deployed ML model in production.
HiddenLayer is using the MITRE ATLAS framework to structure their platform to align with the industry’s leading authority on adversarial threats targeting artificial-intelligence systems. “AI assurance and security is critical for consequential uses of AI and broader adoption,” said Christina Liaghati, a leading team member of MITRE ATLAS. “Collaboration between the government, academia, and industry will lead to a healthy ecosystem and unique perspectives to address these crucial challenges.”
“Machine learning algorithms are rapidly becoming a vital and differentiating aspect of more and more of the technology products we depend on every day. As dedicated cybersecurity investors, we know that protecting the algorithms at the very center of a company’s competitive advantage will become an essential part of a company’s cyber defenses - these algorithms will become the new “crown jewels.” Tito, Jim, and Tanner have the unique experience and skill set to solve this growing problem, making HiddenLayer the company best positioned to lead this important new category of security,” said Todd Weber of Ten Eleven Ventures.
To learn more and request a demonstration of the solution, visit HiddenLayer’s website and follow the company on LinkedIn or Twitter.
About HiddenLayer
HiddenLayer helps enterprises safeguard the machine learning models behind their most important products with a comprehensive security platform. Only HiddenLayer offers turnkey AI/ML security that does not add unnecessary complexity to models and does not require access to raw data and algorithms. Founded in March of 2022 by experienced security and ML professionals, HiddenLayer is based in Austin, Texas, and is backed by cybersecurity investment specialist firm Ten Eleven Ventures. For more information, visit www.hiddenlayer.com and follow us on LinkedIn or Twitter.
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