MLSecOps Community

Discover expert resources and best practices for securing AI & Machine Learning (ML) with this community. You're invited to join us as we drive forward the field of Machine Learning Security Operations, also known as MLSecOps.

Since its inception, the MLSecOps Community has been a leader in educating and promoting the integration of security practices throughout the entire AI/ML lifecycle. The transition from MLOps to MLSecOps introduces contemporary best practices, aligning with the rapid adoption of AI-powered technologies in our society. The community aims to assist its members in better understanding, identifying, and managing the risks associated with their AI systems.

Built on the solid foundation of traditional cybersecurity pillars—people, processes, and technology—the MLSecOps framework encompasses assurance categories such as supply chain vulnerabilities, model provenance, GRC, Trusted AI, and adversarial machine learning. The MLSecOps Community ethos revolves around teaching, learning, and sharing resources related to each of these categories.

Our materials are built for a diverse spectrum of roles, including ML practitioners, data scientists, security professionals, and policy makers; spanning various industries. The community is dedicated to propelling the field of MLSecOps through heightened awareness and by providing current, relevant, and high-quality educational resources. Additionally, it aims to offer access to the insights of today's AI security thought leaders and experts.

Read more here: "What is MLSecOps?"

Join us in our Slack groupThe MLSecOps Podcast and check out The MLSecOps Podcast as you grow your understanding of AI application threats, risks & security, and MLSecOps best practices with other security-minded professionals.