Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A new CVE drops into a package you depend on. With the JFrog power for Kiro installed, your next move is a single prompt in your IDE, not a tab switch to the JFrog UI and thirty minutes of hand-rolled REST calls. This is what governed agentic development looks like in practice.

In late May and early June 2026, Arctic Wolf began observing increased exploitation of CVE-2026-0257, a high-severity authentication bypass vulnerability affecting Palo Alto Networks PAN-OS GlobalProtect and Prisma Access. The increase in CVE-2026-0257 exploitation began on May 30, 2026, following a smaller initial wave that had taken place between May 17 and May 21.

A CVE lands in the morning. Hours later, attackers are exploiting it in the wild. The patch is not ready, the change window is days away, and the clock is already running. None of this is new. What changed is that vulnerability exploitation is now the most common path into organizations.

AI agents can investigate a single vulnerability brilliantly, but that is only about 20% of vulnerability remediation. This post breaks down the other 80%: the data normalization, cross-tool asset identity, SLA enforcement, exception governance, and audit evidence that turn individual agent outputs into a governed, provable remediation program, and why AI and a platform like Seemplicity work better together than apart.

Agent skills are the newest piece of plumbing quietly making its way onto developer machines. They're easy to install, they get to call into the user's tools on the agent's behalf, and once they're in place they tend to stay in place. While auditing the popular installer vercel-labs/skills, we saw several ways a bad actor can make the tool install something other than what the user thought they were installing.

Security teams are not struggling to find vulnerabilities. They are struggling to deal with them in a way that actually reduces risk. Most environments generate thousands of new findings every month. While vulnerability scanners, cloud tools, and endpoint platforms all contribute, that data does not come together in a way that is actionable. Teams end up with long lists of vulnerabilities, limited context, and no clear way to determine what should be fixed first.

Cato CTRL researchers recently identified an undocumented, active phishing campaign targeting Brazilian organizations with fake business-document lures, downloading a NinjaOne Remote Monitoring and Management (RMM) agent. The use of NinjaOne is particularly significant, underscoring how attackers no longer need exotic malware to penetrate an enterprise. Familiar business workflows and software is enough.