Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Why Claude Mythos Changes AppSec Research, Not Your Scanning Stack

If you’re like our team, the morning after the Claude Mythos announcement brought more questions than answers. Among them: “Serious question. Do customers still need SAST?” It’s a fair question if you stop at the headline. Claude Mythos, Anthropic’s frontier AI model currently gated to vetted partners through Project Glasswing, had autonomously identified thousands of zero-day vulnerabilities across major operating systems and browsers . No rule books, no checklists.

Why the Biggest Breaches Still Come Down to the Basics | Nicole Perlroth at Black Hat

At Black Hat last year, Garrett Hamilton asked Nicole Perlroth what she wanted the next five years of security to look like. She didn't give the optimistic answer. She said she was genuinely terrified. Zero-day exploitation at scale, fully automated. Attackers turning AI into infrastructure of their own. A year isn't five. But it's enough to check the tape.

Securing the Agentic Enterprise with Behavioral Analytics and AI Visibility

By mid-2026, the question is no longer whether AI belongs in the enterprise. It’s already embedded in daily work, supporting research, development, customer engagement, and operations. AI agents now act on behalf of employees, automate decisions, and interact directly with enterprise data and systems. This shift creates a new security challenge.

Agentic AI is Calling Your APIs: Why Autonomous Agents are the New Attack Surface

On April 27, 2026, a threshold was crossed that the internet had never hit before. Cloudflare Radar data confirmed that automated systems, such as bots, crawlers, and autonomous AI agents, now generate 57.4% of all HTTP requests for web content. Human traffic accounts for just 42.6%. What is accelerating this transformation is agentic AI: autonomous systems that browse, search, authenticate, and transact on behalf of users without any human intervention mid-task.

How AI Is Changing Both Cyberattacks and Cyber Defense

Artificial intelligence is changing cybersecurity because it gives both attackers and defenders more speed, scale, and flexibility. Attackers can use AI to write better messages, test code, scan targets, and move through stolen data faster. Security teams can use similar technology to detect odd behavior, sort alerts, and respond before a small incident becomes a serious breach. The biggest shift is not that AI replaces every hacker or every analyst. Work that once required hours, special training, or a larger team can now be assisted by software.
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The Control Paradox: Why Regulated Industries Must Rethink AI in Security Operations

For decades, highly regulated sectors have taken a cautious approach to cybersecurity, and for organisations in industries such as banking and finance, healthcare, insurance and critical national infrastructure, the instinct has been to retain ownership of security operations. That model is now under strain. Escalating cyber threats, regulatory scrutiny, and a growing skills shortage are exposing the limits of traditional Security Operations Centres (SOCs). At the same time, AI-driven technologies are maturing rapidly and forcing a strategic rethink.

What is AI Policy Enforcement and How Do You Implement It?

Here’s the reality that most security teams are already living: Over 80% of employees are using unapproved AI tools at work, and nearly half are actively hiding them from IT. The question facing every organization is no longer whether to adopt artificial intelligence — it’s how to secure the sensitive data flowing into it every single day. This is the governance gap.

Report: AI-Enabled Social Engineering Attacks Are on the Rise

Threat actors are increasingly using AI-enabled social engineering to get around technical security measures, according to a new report from Visa. Social engineering attacks were behind the largest number of losses in the second half of last year. “From July to December 2025, Visa identified nearly $1 billion in scam-related activity, making scams the single largest category of consumer payment fraud,” Visa says.

AI Gateway vs. MCP Gateway: Model Control Tool Control

As enterprises adopt AI agents, two control points are becoming common: AI Gateways and MCP Gateways. They sound similar, but they solve different problems. An AI Gateway controls how applications interact with AI models. An MCP Gateway controls how AI agents interact with tools, systems, and data exposed through MCP. Both are useful. Neither is enough on its own.

Monitor Claude Enterprise activity with Datadog Cloud SIEM

As Claude adoption expands across enterprises and workflows, security and compliance teams need to understand who is using Claude Enterprise, how it is accessed, and how it is administered and configured across the organization. The Claude Compliance API gives organizations access to valuable activity data that supports security monitoring, investigations, and governance initiatives.