Mike Bruchanski, Chief Product Officer at HiddenLayer, brings over two decades of experience in product development and engineering to the company. In his role, Bruchanski is responsible for shaping HiddenLayer’s product strategy, overseeing the development pipeline, and driving innovation to support organizations adopting generative and predictive AI.
HiddenLayer 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 AI from inference, bypass, extraction attacks, and model theft.
You’ve had an impressive career journey across product management and AI security. What inspired you to join HiddenLayer, and how does this role align with your personal and professional goals?
I’ve always been drawn to solving new and complex problems, particularly where cutting-edge technology meets practical application. Over the course of my career, which has spanned aerospace, cybersecurity, and industrial automation, I’ve had the opportunity to pioneer innovative uses of AI and navigate the unique challenges that come with it.
At HiddenLayer, those two worlds—AI innovation and security—intersect in a way that’s both critical and exciting. I recognized that AI’s potential is transformative, but its vulnerabilities are often underestimated. At HiddenLayer, I’m able to leverage my expertise to protect this technology while enabling organizations to deploy it confidently and responsibly. It’s the perfect alignment of my technical background and passion for driving impactful, scalable solutions.
What are the most significant adversarial threats targeting AI systems today, and how can organizations proactively mitigate these risks?
The rapid adoption of AI across industries has created new opportunities for cyber threats, much like we saw with the rise of connected devices. Some of these threats include model theft and inversion attacks, in which attackers extract sensitive information or reverse-engineer AI models, potentially exposing proprietary data or intellectual property.
To proactively address these risks, organizations need to embed security at every stage of the AI lifecycle. This includes ensuring data integrity, safeguarding models against exploitation, and adopting solutions that focus on protecting AI systems without undermining their functionality or performance. Security must evolve alongside AI, and proactive measures today are the best defense against tomorrow’s threats.
How does HiddenLayer’s approach to AI security differ from traditional cybersecurity methods, and why is it particularly effective for generative AI models?
Traditional cybersecurity methods focus primarily on securing networks and endpoints. HiddenLayer, however, takes a model-centric approach, recognizing that AI systems themselves represent a unique and valuable attack surface. Unlike conventional approaches, HiddenLayer secures AI models directly, addressing vulnerabilities like model inversion, data poisoning, and adversarial manipulation. This targeted protection ensures that the core asset—the AI itself—is safeguarded.
Additionally, HiddenLayer designs solutions tailored to real-world challenges. Our lightweight, non-invasive technology integrates seamlessly into existing workflows, ensuring models remain protected without compromising their performance. This approach is particularly effective for generative AI models, which face heightened risks such as data leakage or unauthorized manipulation. By focusing on the AI itself, HiddenLayer sets a new standard for securing the future of machine learning.
What are the biggest challenges organizations face when integrating AI security into their existing cybersecurity infrastructure?
Organizations face several significant challenges when attempting to integrate AI security into their existing frameworks. First, many organizations struggle with a knowledge gap, as understanding the complexities of AI systems and their vulnerabilities requires specialized expertise that isn’t always available in-house. Second, there is often pressure to adopt AI quickly to remain competitive, but rushing to deploy solutions without proper security measures can lead to long-term vulnerabilities. Finally, balancing the need for robust security with maintaining model performance is a delicate challenge. Organizations must ensure that any security measures they implement do not negatively impact the functionality or accuracy of their AI systems.
To address these challenges, organizations need a combination of education, strategic planning, and access to specialized tools. HiddenLayer provides solutions that seamlessly integrate security into the AI lifecycle, enabling organizations to focus on innovation without exposing themselves to unnecessary risk.
How does HiddenLayer ensure its solutions remain lightweight and non-invasive while providing robust security for AI models?
Our design philosophy prioritizes both effectiveness and operational simplicity. HiddenLayer’s solutions are API-driven, allowing for easy integration into existing AI workflows without significant disruption. We focus on monitoring and protecting AI models in real time, avoiding alterations to their structure or performance.
Additionally, our technology is designed to be efficient and scalable, functioning seamlessly across diverse environments, whether on-premises, in the cloud, or in hybrid setups. By adhering to these principles, we ensure that our customers can safeguard their AI systems without adding unnecessary complexity to their operations.
How does HiddenLayer’s Automated Red Teaming solution streamline vulnerability testing for AI systems, and what industries have benefited most from this?
HiddenLayer’s Automated Red Teaming leverages advanced techniques to simulate real-world adversarial attacks on AI systems. This enables organizations to:
- Identify vulnerabilities early: By understanding how attackers might target their models, organizations can address weaknesses before they are exploited.
- Accelerate testing cycles: Automation reduces the time and resources needed for comprehensive security assessments.
- Adapt to evolving threats: Our solution continuously updates to account for emerging attack vectors.
Industries like finance, healthcare, manufacturing, defense, and critical infrastructure—where AI models handle sensitive data or drive essential operations—have seen the greatest benefits. These sectors demand robust security without sacrificing reliability, making HiddenLayer’s approach particularly impactful.
As Chief Product Officer, how do you foster a data-driven culture in your product teams, and how does that translate to better security solutions for customers?
At HiddenLayer, our product philosophy is rooted in three pillars:
- Outcome-oriented development: We start with the end goal in mind, ensuring that our products deliver tangible value for customers.
- Data-driven decision-making: Emotions and opinions often run high in startup environments. To cut through the noise, we rely on empirical evidence to guide our decisions, tracking everything from product performance to market success.
- Holistic thinking: We encourage teams to view the product lifecycle as a system, considering everything from development to marketing and sales.
By embedding these principles, we’ve created a culture that prioritizes relevance, effectiveness, and adaptability. This not only improves our product offerings but ensures we’re consistently addressing the real-world security challenges our customers face.
What advice would you give organizations hesitant to adopt AI due to security concerns?
For organizations wary of adopting AI due to security concerns, it’s important to take a strategic and measured approach. Begin by building a strong foundation of secure data pipelines and robust governance practices to ensure data integrity and privacy. Start small, piloting AI in specific, controlled use cases where it can deliver measurable value without exposing critical systems. Leverage the expertise of trusted partners to address AI-specific security needs and bridge internal knowledge gaps. Finally, balance innovation with caution by thoughtfully deploying AI to reap its benefits while managing potential risks effectively. With the right preparation, organizations can confidently embrace AI without compromising security.
How does the recent U.S. Executive Order on AI Safety and the EU AI Act influence HiddenLayer’s strategies and product offerings?
Recent regulations like the EU AI Act highlight the growing emphasis on responsible AI deployment. At HiddenLayer, we have proactively aligned our solutions to support compliance with these evolving standards. Our tools enable organizations to demonstrate adherence to AI safety requirements through comprehensive monitoring and reporting.
We also actively collaborate with regulatory bodies to shape industry standards and address the unique risks associated with AI. By staying ahead of regulatory trends, we ensure our customers can innovate responsibly and remain compliant in an increasingly complex landscape.
What gaps in the current AI security landscape need to be addressed urgently, and how does HiddenLayer plan to tackle these?
The AI security landscape faces two urgent gaps. First, AI models are valuable assets that need to be protected from theft, reverse engineering, and manipulation. HiddenLayer is leading efforts to secure models against these threats through innovative solutions. Second, traditional security tools are often ill-equipped to address AI-specific vulnerabilities, creating a need for specialized threat detection capabilities.
To address these challenges, HiddenLayer combines cutting-edge research with continuous product evolution and market education. By focusing on model protection and tailored threat detection, we aim to provide organizations with the tools they need to deploy AI securely and confidently.
Thank you for the great interview, readers who wish to learn more should visit HiddenLayer.
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