Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

We can't control the pace of AI-driven vulnerability discovery, but we can control how fast we respond. Last week, Thomas Ptacek published a piece arguing that vulnerability research is cooked. His thesis: AI agents are about to drown us in a steady stream of validated, exploitable, high-severity vulnerabilities, faster than anyone can patch them. But from where I sit, the more urgent question isn't whether the flood is coming, but whether the infrastructure we depend on can absorb it.

On April 7, 2026, a security researcher described an Adobe Reader zero-day vulnerability that has been exploited since at least December 2025. The vulnerability allows threat actors to execute privileged Acrobat APIs via specially crafted malicious PDF files that execute obfuscated JavaScript when opened. Exploitation allows attackers to steal sensitive user and system data and to potentially launch additional attacks and remotely execute code.

Everyone is calling Claude Mythos a watershed moment. I’d like to offer a slightly different take. Not because the capability isn’t real, it is. But if Mythos is the moment that finally convinced your organization that rapid vulnerability discovery is an existential threat, you’ve been watching the wrong thing. We saw this coming. Vulnerability Management has been moving in this direction for years, and we built Nucleus with this trajectory in mind. What surprises me is the surprise.

AI is changing how attacks happen, and how fast they happen. Seemplicity’s 2026 State of Exposure Management report shows why most security teams aren’t struggling to find risk, but to fix it quickly enough. Based on insights from 300 security leaders, it highlights where remediation breaks down, how AI is being used today, and why execution is becoming the real bottleneck.

A definitive guide to how automated and human-reviewed patch-in-place remediation solves both direct and transitive open source vulnerabilities - without forcing risky upgrades. Learn why traditional tools miss transitive risk, and how to evaluate modern platforms based on SLA, provenance, and CI/CD fit.

Hoppscotch is an open-source API development ecosystem, similar to Postman, with over 100,000 monthly users. Two weeks ago, we set up a self-hosted instance and ran our AI pentest agents against it. They found two high-severity vulnerabilities and one medium-severity vulnerability, all present in versions up to and including 2026.2.1, and all patched in 2026.3.0: All three were responsibly disclosed and have been resolved. Note: We accidentally grouped the XSS and an Access Control issue into one report.

In November, we shared our vision for the Future of Snyk Container, outlining a fundamental shift in how teams secure the modern container lifecycle. We promised a future where security doesn’t just “scan” but scales effortlessly with the speed of the AI-driven, agentic world. Today, we are thrilled to announce that we are moving from vision to reality.

For years, vulnerability management has followed a familiar pattern: discover assets, scan for CVEs, prioritize by severity, and remediate what you can. That model works, at least within the boundaries of systems you own. The problem is that most organizations no longer operate within those boundaries. Federal agencies especially depend on a complex ecosystem of SaaS platforms, software vendors, contractors, and open-source components.