Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Announcing Justification Coach: AI-Powered Guidance for Better Access Requests and Stronger Audits

Today, we’re introducing Justification Coach, a new AI-powered capability that helps users write better access request justifications in real time, so admins get the context they need for audits and investigations without having to chase people down after the fact.

New KnowBe4 Agent Risk Manager Addresses Pervasive AI Agent Risk

By Roger A. Grimes and Matthew Duren AI agents can deliver incredible productivity gains, but their operational complexity makes effective threat modeling harder than ever, including for developers, administrators and especially end users. At the same time, both developers and non-developers are increasingly vibe-coding, or using AI to generate functional software from natural language prompts.

Claude Mythos Changed Everything. Your APIs Are the First Target.

Anthropic just released Claude Mythos Preview. They did not make it publicly available. That decision alone should tell you everything you need to know about what this model can do. During internal testing, Mythos autonomously discovered and exploited zero-day vulnerabilities across every major operating system and web browser. It found a 27-year-old bug in OpenBSD. A 16-year-old vulnerability in a widely used media codec.

Why Securing AI Code Generation is Critical for AppSec

The revolution is here, but it’s not what we expected. AI coding assistants have transformed software development, with developers shipping code faster than ever before. GitHub Copilot, Amazon CodeWhisperer, and Claude Code have become as essential to modern development as Git itself. The productivity gains are undeniable; what once took hours now takes minutes. But there’s a dangerous blind spot in this revolution: security.

Observability and Security for the AI Era

Datadog has always been driven by a broader vision of helping teams understand and operate complex systems. In this session, you’ll hear from Yanbing Li, Chief Product Officer, and Shri Subramanian, Group Product Manager, as they share the latest updates across the Datadog product suite and discuss how that vision continues to shape the platform’s evolution and support the next generation of AI-driven applications.

A Look At GitGuardian's ML-Powered Contextual EnrichmentAnd Incident Scoring

In this quick introductory video, Mathieu Bellon, Senior Product Manager at GitGuardian, sits down with Dwayne McDaniel, Developer Advocate, to cover some of the advancements GitGuardian has made by integrating machine learning directly into the secrets security platform. Mathieu describes how engineers and responders can save serious time as by automating contextual analysis, geving the humans in the loop with the best information to be able to take an informed action when it comes to secrets leaks. They also discuss the security implications and where teams can look if they want to opt out or bring their own agents.

7 Generative AI Security Risks and How to Defend Your Organization

Generative AI creates new attack surfaces that traditional security tools were not designed to address. The biggest generative AI security risks include prompt injection, data leakage, shadow AI, compliance exposure, model poisoning, insecure RAG pipelines, and broken access control. Each one requires a specific defense, not a generic firewall or DLP rule.

Best Enterprise DLP Tools for AI Data Risk (2026 Comparison)

Employees move sensitive data into AI tools every day. Someone pastes customer records into ChatGPT to draft an email. A developer feeds proprietary source code into a coding assistant to fix a bug. A project manager drops a confidential contract into Gemini to summarize it for a meeting. According to research from Cyberhaven Labs, 39.7% of the data employees share with AI tools is sensitive, and enterprise adoption of endpoint-based AI agents grew 276% in the past year alone.