As the volume of code continues to grow exponentially, software developers, DevOps engineers, operations teams, security specialists, and everyone else who touches code are increasingly spending their time in the weeds of securing, delivering, and scaling software. This bottles up creativity and ultimately slows software development for every organization.

With the rapid adoption of AI-enabled services into production applications, it’s important that organizations are able to secure the AI/ML components coming into their software supply chain. The good news is that even if you don’t have a tool specifically for scanning models themselves, you can still apply the same DevSecOps best practices to securing model development.

The impact of the 2024 RSA Conference on security in San Francisco was beyond expectations. It was really a fantastic opportunity to meet an amazing group of individuals from all stages of the software supply chain from CISOs to researchers to development and security teams.

An organization’s software supply chain includes all the elements involved in developing and distributing software, such as components, tools, processes, and dependencies. Each link in this important chain presents the potential for security threats. Recent research conducted by Gartner shows a major increase in attacks targeting code, tools, open-source components, and development processes, particularly in areas where organizations lack visibility.

It’s a wrap! RSA 2024 brought together cybersecurity experts, industry leaders, and innovators to delve into critical topics defining the future of digital security. One of the key themes that garnered significant attention at RSA 2024 was software supply chain security.

Removing friction between DevOps and Security teams can only lead to good things. By pulling in the same direction, DevOps can make sure developers continue to work with minimum interruption, while automation and background processes make security more effective and consistent than before. And, security teams have the visibility and understanding of the software development life cycle (SDLC), to improve developer experience and reduce risks and incidents for the organization.

Despite organizations’ best efforts, security threats are on the rise, with malicious actors continuously evolving their tactics. Unfortunately, the situation is only intensifying as hackers from all walks of life leverage artificial intelligence (AI) and machine learning (ML) techniques. To combat these threats, security teams need to implement gates and controls throughout their entire software development lifecycle.