Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI deepfakes are making fraud even more sophisticated. Learn how to stay safe from deepfake scams. Scammers are using deepfake technology to replicate your child's voice in a kidnapping hoax, catfish with AI-generated video dates, and impersonate executives to steal millions. Learn how to spot deepfake fraud, and use Avast Scam Guardian to help verify what's real before it's too late.

This is the final post in a three part series examining the past, present and future of workflows. In the first two posts, we explored where workflows came from and what defines an intelligent workflow. This final article looks ahead. The goal is to understand how workflows will evolve in the coming years and why they will become central to how organizations run, make decisions, and adapt.

Sha1-Hulud is back with a new evolution of its supply-chain attack that targets development environments via Node Package Manager (npm). npm is a very popular package manager for Node.js that provides millions of predeveloped packages of code to be used by JavaScript developers for access to millions of packages. This campaign trojans unsecured npm packages with malicious code that is automatically executed when developers using that package update to the trojaned version.

Modern organizations often use GitLab as a core version control system (VCS), making it one of the most essential systems for DevOps. Given the critical nature of the data stored here, thorough evaluation of risks and implementing data protection best practices are a must. According to the Shared Responsibility Model, GitLab provides security for the underlying infrastructure, while the user’s duty is to keep data protected. More about GitLab’s Shared Responsibility Model.

In the first installment of our Inside the Agent Stack series, we examined the design and security posture of agents built with Azure Foundry. Continuing the series, we now focus on Amazon Bedrock AgentCore, a managed service for building, deploying, and orchestrating AI agents on AWS.

According to our 2025 State of the Underground report, ransomware attacks rose by nearly 25% in 2024, and the number of ransomware group leak sites jumped 53%. This surge sets the stage for a critical question: if compromised, should you pay ransomware demands or not? The stakes are enormous, including downtime, data loss, brand damage, and legal risk all hang in the balance.

AI tools have proved their worth in the workplace. They help us write, research, code, plan, and automate. They’re making employees faster and more productive, and helping businesses move and innovate at a pace that wasn’t possible before. But AI’s rise wasn’t orchestrated by IT. It didn’t always arrive through formal adoption plans or procurement cycles. It turned up in shared links to popular GenAI and other tools, self-sanctioned and adopted by users in minutes.

Every security team I meet is dealing with the same pressure: more cloud, more AI, more data, more noise, and less time. The cloud promised speed and flexibility, and it delivered. However, customers are asking for an easier path to understanding what’s actually happening across that environment. That gap, between what teams can see and what they need to see, is where threats hide.

Endpoint Data Loss Prevention (DLP) solutions are critical tools for organizations looking to safeguard sensitive information from insider threats, unintentional leaks, and external attacks. These solutions monitor, detect, and block the transfer of valuable data outside company networks, ensuring compliance with data protection regulations. In this post, we’ll explore the top eight endpoint DLP solutions that offer robust security features, ease of use, and integration capabilities.