ML operations, data scientists, and developers currently face critical security challenges on multiple fronts. First, staying up to date with evolving attack techniques requires constant vigilance and security know-how, which can only be achieved by a dedicated security team. Second, existing ML model scanning engines suffer from a staggering rate of false positives.

Enterprises are racing to integrate AI into applications, yet transitioning from prototype to production remains challenging. Managing ML models efficiently while ensuring security and governance is a critical challenge. JFrog’s integration with NVIDIA NIM addresses these issues by applying enterprise-grade DevSecOps practices to AI development. Before exploring this solution further, let’s examine the core MLOps challenges it solves.

The Swiss Financial Market Supervisory Authority (FINMA) sets strict requirements to ensure that financial institutions operating in Switzerland maintain robust security and operational resilience. FINMA’s guidelines are crucial for protecting sensitive financial data, minimizing risks, and maintaining trust in the Swiss financial ecosystem. As part of that, software supply chain security plays an essential role in meeting these compliance requirements.

The Indian Computer Emergency Response Team (CERT-In) is the national agency responsible for addressing cybersecurity incidents in India. Established in 2004 and operating under the Ministry of Electronics and Information Technology (MeitY), CERT-In is dedicated to enhancing the security of India’s digital infrastructure.

The Network and Information Systems Directive 2 (NIS2) is the European Union’s effort to fortify cybersecurity across critical industries and services. Building on the original NIS Directive, NIS2 has broadened its scope, introduced stricter requirements, and placed greater emphasis on supply chain security. Now that the October 2024 transposition deadline has passed, organizations must focus on maintaining compliance and integrating robust cybersecurity measures into their operations.

In our previous round-up of security research for 2023, we mentioned our surprise at the large volume of 29,000 vulnerabilities that were reported two years ago. But that didn’t prepare us for the astounding 40% increase, reported by Cyber Press, resulting in over 40,000 CVEs that were published over the past year in 2024.

There is an increasing need for traceability and attestation of the actions taken as software moves across the SDLC. Emerging regulations and policies around secure software development are rapidly evolving, and it’s important to stay ahead of the changing landscape. Some organizations have taken a proactive approach with home-grown solutions or manual processes, but despite best efforts, these solutions often lack scale and eventually falter over time.

JFrog uses open source tools such as Kubernetes, Kubernetes Event-driven Autoscaling (KEDA), and Prometheus to develop its cloud development infrastructure and ensure tight integration with the three leading cloud providers AWS, GCP, and Azure. Let’s explore how JFrog cloud deployments leverage our cloud-native architecture to provide enhanced security and management capabilities for DevOps while ensuring high availability and a transparent user experience for developers.

On July 24th 2024, Curl maintainers announced a new stack buffer Use After Free (UAF) vulnerability – CVE-2024-6197. This type of vulnerability is very uncommon since UAF issues usually occur on the heap and not on the stack. While the vulnerability can be easily exploited for causing denial of service, in this blog we will show why we believe that it is almost impossible to exploit this vulnerability to achieve remote code execution in any real-world setup.