Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI-Powered Human Risk Management Shifts the Focus to Adaptive, Behavior-Based Training

Human risk management (HRM) focuses on one of the most persistent cybersecurity vulnerabilities: humans. Social engineering attacks that trick users into taking risky actions are a factor in 98% of cyberattacks not because they are technically complex, but because they manipulate employee behavior. Unlike traditional, one-size-fits-all security awareness training, human risk management focuses on changing employee behavior through monitoring and targeted reinforcement.

Introducing the Datadog Code Security MCP

AI-assisted development helps teams write code faster, but that speed comes with added security risk. As agents generate more code, they can introduce vulnerabilities, insecure dependencies, or exposed secrets, often before a human reviewer ever sees the change. Security teams are left reviewing more code with the same resources, which makes it harder to catch issues early.

What is the NIST AI Risk Management Framework?

The NIST AI Risk Management Framework is a guide that helps organizations spot and reduce risks in AI systems. This framework was released in January 2023 by the U.S. National Institute of Standards and Technology. The framework is built around four key steps, namely: Govern, Map, Measure, and Manage, and is meant to help teams responsibly use AI. It doesn’t matter which industry you work in or which AI you use; this framework works everywhere.

How Weak AI Governance Is Creating A Security Disaster #cybersecurity #aisecurity

This episode explores why CTEM matters in a world of vibe coding, AI agents and rapidly expanding attack surfaces. It covers prompt injection, hidden threats, deepfakes, weak governance and the growing fear that businesses are deploying AI far faster than security teams can understand or control it.

IREX Upgrades FireTrack AI for Faster and More Accurate Fire Detection

WASHINGTON, DC - IREX has announced a major update to its FireTrack fire and smoke detection module, introducing significant improvements in speed, accuracy, and operational flexibility across a wide range of environments. According to an article on The Next Web, the updated solution is designed to work seamlessly with existing camera infrastructure, enabling organizations to enhance fire detection capabilities without deploying additional hardware.

What Is AI Data Exfiltration and How Do You Stop It?

AI adoption does not happen uniformly across an organization. Some employees have integrated generative AI (genAI) tools into core parts of their workflow. Others have barely opened one. Most are somewhere in between, experimenting on an ad hoc basis, without consistent visibility into what data those tools handle or where it goes. That variance is the problem. Security programs built around either universal AI adoption or zero AI adoption will miss most of the actual risk.

Using Agentic AI to Scale Threat Detection in Healthcare

For every human in a healthcare organization, there are 82 machine identities—service accounts, API keys, cloud functions, medical devices.2 That's the 82:1 ratio, and it means your team is fundamentally outnumbered. The Change Healthcare breach in 2024, which started with one unprotected Citrix credential and disrupted 40% of US claims processing,1 showed exactly what happens when that ratio goes unmanaged. The numbers back this up.

Everyone is Deploying AI Agents. Almost Nobody Knows What They're Doing

AI agents are operating inside your enterprise; querying databases, triggering workflows, and taking action through APIs. As AI agents are adopted, organizations cannot see, track, or control what these agents are actually doing. In this session, Roey Eliyahu, Co-Founder and CEO of Salt Security, challenges the industry’s narrow focus on LLM safety and exposes the much larger, invisible attack surface created by agentic systems.

Smishing AI

Cybercriminals are evolving—and so are their tactics. Smishing, or SMS phishing, has become one of the fastest-growing mobile threats. With AI, attackers can now create convincing, personalized messages in seconds—removing language barriers and making scams harder than ever to detect. That’s where Lookout Smishing AI comes in. Our advanced AI-powered detection goes beyond scanning for malicious links. It identifies the intent behind every message—stopping social engineering attacks before they reach you. Whether there’s a URL or not, Lookout keeps your mobile workforce protected.