On 7th April 2026, Anthropic published a system card for an AI model we may never be allowed to use: Claude Mythos. This preview demonstrated a significant leap in capability over Anthropic’s previous Claude Model (Opus 4.6), and their Responsible Scaling Policy (RSP) v3.1 led to them making the decision to withhold it from general availability, serving as a "defensive only" asset.

SAST, or Static Application Security Testing, is a method of analyzing source code to find vulnerabilities before the application is deployed. It's a type of white box testing that scans the code without executing it, looking for weaknesses that could be exploited. SAST helps developers identify and fix security issues early in the Software Development Life Cycle (SDLC), potentially reducing costs and improving the overall security posture of the application.

When Anthropic revealed the existence of Mythos, the frontier AI model they deemed too dangerous for public release, the security community was alarmed. And it’s not hard to see why: Mythos is capable of detecting software vulnerabilities at a previously unimaginable scale, and autonomously crafting exploits to weaponize these flaws. According to Anthropic, Mythos created 181 exploits of Firefox in testing, ninety times more than the company’s previous model (Claude Opus 4.6).

Modern development teams move fast; security must keep pace. As organizations increasingly rely on GitLab to power CI/CD pipelines, integrating application security directly into the workflow is no longer optional — it’s essential. The Veracode GitLab Workflow Integration embeds automated security testing directly into GitLab pipelines, enabling teams to shift security left without disrupting delivery.

You often hear companies touting that they are AI enabled. But most do not give you the results of how that new AI stacks up with their previous non-AI offerings. We have some early data and want to share it. KnowBe4 was the first Human Risk Management (HRM) vendor to use AI. While our competitors have been touting the use of AI only since 2023 at the earliest, we have been using machine learning (ML), the backbone workhorse of AI, since early 2016 – for a decade!

Proofpoint DLP and Trellix DLP are two notable data loss prevention solutions. In this blog, we’ll analyze both platforms in depth and see how they compare. We’ll also introduce Teramind as a compelling alternative that combines the best aspects of Proofpoint and Trellix, while offering additional tools that could increase your workforce’s safety and productivity.

Anthropic’s latest Claude news shows how AI is compressing the time from vulnerability discovery to credentialed lateral movement, and why security teams need behavior-based detection across humans and AI agents. Anthropic’s Project Glasswing, announced on April 7, 2026, gives selected partners early access to Claude Mythos Preview for defensive cybersecurity work. Anthropic says the model has already identified thousands of zero-day vulnerabilities across critical infrastructure.