Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Employee monitoring has become a standard practice for organizations seeking visibility into productivity, security, and operational efficiency. However, monitoring employees, especially in jurisdictions like California, requires careful alignment with privacy laws such as the California Consumer Privacy Act (CCPA) and its amendment, the California Privacy Rights Act (CPRA). This article provides a high level overview of how employee monitoring intersects with CCPA/CPRA requirements.

AI security compliance is the practice of applying security controls, data governance policies, and regulatory requirements specifically to how AI systems are deployed, used, and monitored within an organization.

In April 2026, Microsoft disclosed and patched a critical remote code execution vulnerability affecting the Windows Internet Key Exchange Service Extensions. Tracked as CVE-2026-33824, the issue was addressed as part of Microsoft’s April 2026 Patch Tuesday release. The affected component forms part of the Windows IPsec and IKEv2 stack, which is widely used to provide secure network connectivity.

When nation states target cloud infrastructure, MSSPs are at risk. Many security teams have quietly accepted this as someone else's problem. It isn't, and ignoring the problem only increases their risk exposure. A recent episode of the Cybersecurity Defenders Podcast featured a conversation on cloud infrastructure vulnerability between LimaCharlie Co-Founder Christopher Luft and Prophet Security R&D Guru, Matt Bromiley.

CrowdStrike has been selected for OpenAI's Trusted Access for Cyber (TAC) program. Today, OpenAI released GPT-5.4-Cyber, a frontier model designed for defensive cybersecurity, and expanded the TAC program to give verified, selected defenders governed access through identity verification and tiered controls. CrowdStrike continues to lead the market in secure AI adoption, trusted by AI leaders and organizations of all sizes to accelerate the world's AI revolution.

CVE-2025-53521 was first disclosed by F5 in October 2025 as part of their quarterly security advisory cycle. At that point, it was classified as a denial-of-service vulnerability with a CVSS v4 score of 8.7. Many security teams logged it and moved on, reasonably treating it as a lower-priority item in an already full patch queue.

If you hear that a product is 92% effective, you’d assume it’s operating as intended. It seems like a success story. But dig a little deeper, and the picture changes; only 51% say that their security information and event management (SIEM) is very effective. What does it mean when a majority of security relies on a tool that works, but doesn’t work well enough? Not broken, not exceptional. It’s somewhere in between.

Whether you’re a video editor, graphic designer, or marketer responsible for building key assets, you know how frustrating working on large-scale creative projects can get. Teams struggle to work with large video and design files, dealing with slow, incomplete renders, freezes, crashes, and misaligned content. When collaborating, those delays and inefficient version keeping lead to lost or overlapping work.

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.

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!