Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

As the AI revolution accelerates, developers are being inundated with a dazzling array of new software packages and game-changing tools such as GitHub CoPilot, Sourcegraph, Qodo, Cursor, Goose, and others that promise incredible advances in productivity and impact. The excitement over this is high and just keeps on growing.

And that’s a wrap! Held in beautiful Napa Valley, swampUP 2025, JFrog’s annual customer conference brought together developers, operations, security, compliance, and AI/ML leaders – all facing the same burning challenges posed by the AI-driven quantum shift in software delivery. In the keynotes, breakout sessions, and side-conversations over wine and coffee, a common theme was made clear: a unified Software Supply Chain platform is essential to thrive in the new reality.

JFrog Security Research recently discovered and disclosed multiple CVEs in the highly popular Chaos engineering platform – Chaos-Mesh. The discovered CVEs, which we’ve named Chaotic Deputy are CVE-2025-59358, CVE-2025-59360, CVE-2025-59361 and CVE-2025-59359. The last three Chaotic Deputy CVEs are critical severity (CVSS 9.8) vulnerabilities which can be easily exploited by in-cluster attackers to run arbitrary code on any pod in the cluster, even in the default configuration of Chaos-Mesh.

The entire world of technology is abuzz about AI/ML. It’s arguably the most disruptive technology to society since the smartphone. In fact, Gartner estimates that the number of companies using open-source AI directly will increase tenfold by 2027.

Picture this: A new developer joins your team, excited to start contributing. On day one, they spend hours installing and configuring their IDE, searching for the “right” extensions. Their setup ends up being completely different from everyone else’s. Sound familiar? Worse yet, what if that “productivity-boosting” extension or new MCP server they just installed also secretly opened a backdoor in your codebase?

Most DevSecOps pipelines have a gap: source code security and binary security are handled in separate silos. This creates blind spots, slows teams down, and increases risk. At swampUP 2025, we’re unveiling the next evolution of the JFrog and GitHub integration, a deeply integrated DevSecOps experience that unifies best-of-breed code and binary platforms.

(Nov 26, 2025) JFrog continues to track, provide research and document a second wave of the Shai-Hulud Software Supply Chain Attack. Following the initial campaign, threat actors have returned with more advanced tactics, compromising an additional 621 new malicious packages across leading public registries.

Software supply chains are the attack vector for cybercriminals, and the challenge isn’t just finding vulnerabilities; it’s fixing them fast while ensuring security, compliance, and developer productivity. As supply chains grow in complexity, traditional tools aren’t enough; organizations need intelligent, autonomous assistance embedded directly into developer workflows.

The rapid pace of AI innovation is driving new possibilities for every organization. Yet, for many, the journey from inception to reliable, production-ready AI applications is riddled with hidden challenges: proliferation of models, security blind spots, and a desperate need for consistent governance. You want to harness the power of AI, but not at the expense of control, security, or compliance.

The pressure to deliver applications quickly has created a complex software supply chain that is vulnerable to more threats than ever before. New regulations are shifting the liability to software developers, demanding auditable proof of security across the entire product lifecycle. Caught between velocity and complexity, the critical question is this: Can you truly vouch for the integrity, security, and compliance of every application that leaves your pipeline? What about after it’s deployed?

AI agents are rapidly evolving from simple text generators into powerful autonomous assistants that can browse the web, book travel, and extract complex data on our behalf. This new “agentic” AI, which operates in a “sense-plan-act” loop, promises to revolutionize how we interact with the digital world.

The speed of software development today is driven by fierce competition and the constant demand for innovation. Organizations are launching software faster than ever to keep up with the market and drive growth. This need for speed has led to several key trends: These trends introduce a critical dilemma: How do you balance speed vs. trust? While fast releases are essential to meet market and user demands, sacrificing trust for speed can lead to severe business repercussions.