Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Claude Mythos Explained: AI Finding Zero-Day Vulnerabilities and Chaining Exploits

Claude Mythos is an AI model capable of finding and chaining zero-day vulnerabilities at scale. That changes how attacks happen, especially in environments where you can’t patch fast enough. The Forescout 4D Platform with VistaroAI helps organizations respond with real-time visibility and dynamic control across all connected devices.

Exposed LLM Infrastructure: How Attackers Find and Exploit Misconfigured AI Deployments

Someone is scanning your LLM infrastructure right now. They are not waiting for you to finish your security review. Between October 2025 and January 2026, GreyNoise’s honeypot infrastructure captured 91,403 attack sessions targeting exposed LLM endpoints. These were two distinct campaigns systematically mapping the expanding attack surface of misconfigured AI deployments. Your team is moving fast on AI. LLM servers are going live, inference APIs are being connected, MCP endpoints are being spun up.

Cybersecurity AI Explained: Agentic AI, PQC, and Real-World Security Challenges

At the 2025 RSA Conference, Justin Foster joins Zeus Kerravala to break down where AI in cybersecurity is actually delivering value and where it’s falling short. As security teams deal with growing complexity, many are finding that today’s AI tools create as much friction as they solve. This conversation explores how a shift toward agentic, skills-based AI can help teams move faster, reduce noise, and focus on what really matters.

Navigating the Post-Mythos Landscape with Bitsight

The rise of AI-driven vulnerability discovery using Anthropic's Claude Mythos, as well as similar tools from Google and OpenAI, is completely changing the calculus of cyber risk. The number of vulnerabilities is exploding. The time it takes for exploits to appear is shrinking. The patching cadences and scan intervals, assessments and risk registers that many organizations still rely on are rapidly becoming ineffective.

What Is AI Context Security?

Every enterprise wants to use AI on its most valuable data — customer records, financial documents, clinical notes, legal files, engineering IP. The problem is simple: the moment that data enters an AI workflow, traditional security stops working. Firewalls protect the network. Encryption protects data at rest. Access controls protect the database. But none of them protect what happens when an AI agent retrieves five documents, synthesizes an answer, and delivers it to a user.

Autonomous AI Agents Explained: Risks, Capabilities & Security Gaps

Autonomous AI agents are no longer experimental—they’re writing code, executing commands, and making decisions in real time. But as AI coding agents become more powerful, they’re also introducing a new and often invisible attack surface. In this video, we break down: AI agents can install packages, run scripts, and modify systems instantly—often without traditional visibility. That means security teams need to rethink how they monitor and protect their environments.

7 Practical Ways to Shrink Your Digital Footprint in 2026

The average internet user now leaks more personal data in a single day of routine browsing than most people disclosed in a decade two generations ago. Ad networks track page views, data brokers aggregate public records into sellable dossiers, and AI systems ingest everything from social posts to leaked databases to build inferred profiles of individuals. Privacy Rights Clearinghouse has catalogued more than 750 data brokers operating in the United States alone, and industry analysts estimate the broader data-broker economy will grow past half a trillion dollars by the end of the decade.