Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

How the Arctic Wolf Agentic SOC Delivers Faster, More Accurate Security Outcomes

Learn how Arctic Wolf Superintelligence Platform and the Swarm of Experts work together to deliver faster, more accurate outcomes for customers by leveraging unmatched telemetry, deterministic models, our golden data set and human expertise.

Treat Your AI Agents Like Humans or You Are Creating Risk

AI agents are about to act as humans inside your organization. Curtis Koenig, Head of Application Security at Gen, explains why treating them with the same identity and data controls is the single most important step to get ahead of AI risk. "We're going to give these agents the capability to do things as though they were humans. If we are not treating them like we treat our other human users in our organizations, that's where we're creating risk.".

If AI Can Build the Exploit, It Can Write the Patch

The window between an exploit being discovered and actively used is around eight hours. Curtis Koenig, Head of Application Security at Gen, explains why zero trust and a prepared incident response process remain the foundation for security teams navigating this new threat landscape. "The good news is that if the tool can find a vulnerability and create an exploit, it can find a vulnerability and write a patch as well.".

Which AI Signals Carry a Finding and Which Only Size It

A correlation rule joins several telemetry sources and fires when they agree. Guidance on writing them concentrates on thresholds, ordering and tuning for noise. ‍ The decision that determines whether a rule works is upstream of all of that. Each source in a rule plays one of three roles, and treating them interchangeably is what produces a rule that misses real events or fires on ones nobody can act on. ‍

Jev's Paradox: The hidden cost of cheap AI decisions

This article was first published on LinkedIn. Consider a cybersecurity alert for a potentially malicious PowerShell script that downloads and runs a file. An AI agent in a security operations center (SOC) can handle it by picking from a fixed set of actions: close the alert as benign, collect more evidence, or send it to an analyst. Before letting the agent act on such alerts, the SOC needs to know how often it picks correctly and whether its confidence helps identify its mistakes.

Gen's Curtis Koenig on treating AI agents like human users to prevent security failures

Your backlog of low and medium severity vulnerabilities just became a real threat. AI can now chain them into critical exploits, and the window between exploit discovery and active use is around eight hours. Curtis Koenig, Head of Application Security at Gen, joins the show to explain why treating AI agents like human users is the single most important step security teams can take this year. CHAPTERS.

AI Agent Security: The Hidden Threat Your Firewall Can't Stop

If your AI security strategy is focused on stopping copy-pastes into chatbots, you're fighting yesterday's war. AI agent security is now the real endpoint challenge — autonomous agents operating with your users' credentials. Traditional firewalls, CASBs, and DLP weren't built for agentic AI. They can't see delegated credentials, multi-step tool calls, or live runtime execution across IDEs, browsers, and local apps.

Introducing Salt Claude Connect: Continuous MCP Server Visibility for Claude Enterprise

As AI adoption accelerates inside enterprises, security and IT teams are increasingly asking a foundational question: what exactly is connected to our AI, and what can it access? For organizations running Claude Enterprise, Salt now has a direct answer. Salt Claude Connect links Salt to Claude’s Compliance API and provides continuous, read-only visibility into the MCP (Model Context Protocol) servers connected to your Claude Enterprise organization.