We are committed to ensuring the security and robustness of AI/ML systems.
Our services address the novel challenges of AI/ML and provide clients with the assurance
they need in a rapidly advancing industry.
Book a complimentary one-hour meeting with one of our engineers to dive into a challenging
technical issue, explore tooling options, and gain valuable insights directly from our experts.
This session is purely technical—no sales talk, just a focused discussion that showcases our
depth, talent, and capabilities.
We offer custom training solutions based on specific client needs. Our courses cover comprehensive security training for understanding and evaluating AI-based system risks, including AI failure modes, adversarial attacks, AI safety, data provenance, pipeline threats, and risk mitigation.
Learn more about our trainingOur assessments address the entire AI/ML pipeline:
Machine learning operations (MLOps) introduce novel attack vectors that differ from traditional software backdoors and vulnerabilities that impact ML-based systems and their operations. This service uncovers categories of vulnerabilities that can lead to ML-specific failure modes and degraded model performance or implicit and explicit access to and changes in data, model parameters, and the IP, increasing the system’s overall attack surface.
Our offerings include threat modeling, applying operational design domains, and analyzing scenarios to identify functional risks. We also assess existing risk frameworks associated with AI adoption.
We help organizations measure and validate the capabilities of the AI models their systems employ
(both first- and third-party). Specifically, we specialize in assessing models’ offensive
and defensive cyber capabilities by benchmarking their performance against experts,
state-of-the-art tools, and novices using AI/ML tools.
Our services are informed by our
first-hand experience assessing cybersecurity threats posed by models (AI red teaming) and building
automated, AI-based systems for detecting and patching software vulnerabilities
(as part of DARPA’s AI Cyber Challenge). We help our customers integrate only the
most effective AI tools into their internal software security processes.
Our AI/ML team develops and maintains multiple open-source tools, such as Differ, which we use in our internal assessments. Click to view our custom tools on Github.
We are committed to sharing our knowledge with the community. We share our research and expertise whenever possible through our blog. Read our favorite AI blog: We need a new way to measure AI security.
Our AI/ML team focuses on advancing technology with a strong emphasis on safety and security. Learn about our latest vulnerability discovery: Leftoverlocals
Unlike many firms that follow a predefined checklist that limits the scope and capabilities, our assessments don't look to check boxes but discover the root causes of security weaknesses identified. This approach allows us to provide nuanced, actionable insights that do more than fix the immediate problems—they also enhance the system's overall resilience and security for the future. By focusing on the root causes and broader implications of security vulnerabilities, we empower our clients to not just respond to bugs but to develop stronger, more resilient software design, development, and coding practices.
Read our assessment of Hugging FaceWe believe in the power of collaboration and the synthesis of knowledge across various fields to deliver unparalleled services to our clients. Our diverse company lines are not isolated silos of expertise. Instead, they represent a spectrum of capabilities that we seamlessly blend to meet the unique needs of each project.