Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The revolution is already inside your organization, and it's happening at the speed of a keystroke. Every day, employees turn to generative artificial intelligence (GenAI) for help with everything from drafting emails to debugging code. And while using GenAI boosts productivity—a win for the organization—this also creates a significant data security risk: employees may potentially share sensitive information with a third party.

What if just one line in a chatbot prompt could turn into a regulatory nightmare? That’s the reality enterprises face today. In fact, Gartner predicts the average data breach will exceed $5M by 2025—and AI-driven systems multiply those risks in ways traditional IT never prepared us for. Unlike legacy apps, AI doesn’t just use data—it feeds on it, reshapes it, and sometimes leaks it right back out.

Generative AI can deliver great improvements in work productivity and quality. But business users must be able to rely on the dependability of the responses their AI tools generate for them. That’s only possible with sophisticated, often complex prompts. In addition, companies want AI solutions that ensure a high level of consistent results across teams. With gen AI, when 10 users ask the same questions using their own prompts, they get 10 different responses.

Trustwave, A LevelBlue Company, is a huge proponent of employing offensive security tactics to ensure a client is properly protected. For Trustwave, the reason is obvious. Offensive security is an effective approach to evaluate and enhance an overall security posture. We’ve written about this before (just check here, here, and here), but today we will explore the difference between an Authenticated Scan and an Unauthenticated Scan. Let’s set the stage by defining the two types of scans.

As AI and automation increasingly become embedded into healthcare operations, securing these technologies becomes critical, especially for organizations managing protected health information (PHI), which are frequent targets for cybersecurity threats such as data breaches and unauthorized access. ‍ To safeguard this sensitive data, regulatory agencies like the U.S. Department of Health and Human Services (HHS) enforces strict cybersecurity and privacy regulations under HIPAA.

In a rare and unprecedented incident, a massive operational dump belonging to the North Korean Kimsuky APT group was leaked on a dark web forum. The leak containing virtual machine images, VPS dumps, phishing kits, rootkits, and thousands of credentials offers an unparalleled look into the inner workings of one of Pyongyang’s most prolific cyber espionage groups.

In this article Shadow IT used to be a fringe problem, a rogue Dropbox account here, a personal Gmail there. Now, it’s everywhere. One customer said it best: “We don’t have a Shadow IT problem. We are Shadow IT.” That stuck. It’s not malice. It’s urgency. People move fast. Procurement doesn’t. So teams swipe cards, spin up tools, and get on with it. The intentions are good. The risks are massive. We’ve seen it firsthand.

Endpoints play a vital role in any organization’s operations. However, endpoints are susceptible to a variety of cyber attacks, particularly malware and ransomware – threats that remain highly popular among threat actors. Additionally, many social engineering attacks seek to gain access to individual users’ endpoints.

If your company collects, stores, or shares consumer financial data, there’s a good chance the Gramm–Leach–Bliley Act (GLBA) applies to you. But here’s the catch: many businesses outside of traditional banks—like fintech apps, insurance providers, and mortgage tech platforms—don’t realize they fall under GLBA oversight.