Shadow IT | Breaking Cybersecurity News | The Hacker News

In a matter of months, AI became a tool relied on for daily critical tasks. Now, we are seeing it used just as easily to attack systems, deceive users, or even manipulate data. While full capabilities are still being explored, the most significant threats posed by AI are yet unknown. Even without knowing exactly what's coming, organizations can take meaningful steps now and develop identity security strategies to defend against AI-driven threats to avoid being an easy target. Suggestion 1: Start with the basics In the face of unknown AI-driven threats, one of the best places to start is with an identity security strategy that addresses the fundamentals.  When it comes to identity and access management, solutions that offer 'Preemptive Defense' (a term coined by Gartner) allow detection and protection before a user even authenticates to your systems. Think IP reputation checks, web application firewalls, machine learning-based risk scoring, user policies and app policies. Risky...

Device and software vulnerabilities pose an increasing risk to modern security. However, patch management is an infamously difficult (and downright Sisyphean) task for IT and security teams, who are faced with an ever-growing list of CVEs to remediate. This task was difficult enough in the days of on-premise environments, but a modern distributed workforce has to contend with all the users, devices, and applications that may exist outside the purview of traditional security solutions, like MDM. Overall, with the ever-growing number of CVEs and the ever-growing sprawl of shadow IT, patch management has become both more urgent and more daunting than ever. IT and security teams need to adopt zero trust methods to ensure that only healthy and patched devices are able to access their critical systems. With the help of SaaS management and employee-remediation tactics, teams can do even more to improve efficacy and support for their company-wide patch management programs.  French philo...

Generative AI has quietly become a part of the SaaS ecosystem that businesses use every day. Platforms like Zoom, Slack, Microsoft 365, and Salesforce now have AI assistants. You can use these tools to do things like write summaries of meetings or perform routine tasks. A recent  survey found that 95% of U.S. businesses now use generative AI. This is a big increase from last year. But this quick growth of AI features is making security leaders worried. Sensitive information could be leaked or used in the wrong way if there aren't enough controls in place. Shadow AI and Its Far-Reaching Risks When employees use AI apps without the knowledge or approval of IT, it creates shadow AI . This is akin to the shadow IT problem of unsanctioned cloud apps, but now with AI services. The unauthorized use of AI platforms can unknowingly expose organizations to data privacy issues, compliance violations, and even disinformation risks. We're already seeing these risks play out. Samsung engin...

The Perfect Recipe for Endpoint Security Calls for Privilege Control Today's most effective ransomware attacks don't require malware; they require a login. Modern threat actors don't need to break in. They can leverage legitimate identities and their privileges to gain a foothold, then continue to capitalize on them, moving laterally to probe for more opportunities and manipulate vulnerabilities and exploits to spread ransomware and spyware. A vulnerable identity or account tied to an endpoint can quickly become an attacker's ticket to your most valuable assets and controls.  With legitimate identities being used as the initial foothold in more attacks, we're seeing less 'anomalous' activity and far more seemingly normal actions performed by a trusted, privileged user. And attackers are keenly aware of how easily they can 'hide' behind these legitimate user accounts.  This is why Endpoint Detection and Response (EDR) is really only one piece of the endpoint protection puzz...

When generative AI tools became widely available in late 2022, it wasn't just technologists who paid attention. Employees across all industries immediately recognized the potential of generative AI to boost productivity, streamline communication and accelerate work. Like so many waves of consumer-first IT innovation before it—file sharing, cloud storage and collaboration platforms—AI landed in the enterprise not through official channels, but through the hands of employees eager to work smarter. Faced with the risk of sensitive data being fed into public AI interfaces, many organizations responded with urgency and force: They blocked access. While understandable as an initial defensive measure, blocking public AI apps is not a long-term strategy—it's a stopgap. And in most cases, it's not even effective. Shadow AI: The Unseen Risk The Zscaler ThreatLabz team has been tracking AI and machine learning (ML) traffic across enterprises, and the numbers tell a compelling story. In 2024 ...

There's a war raging in the heart of every developer. On one side, you have the id: the impulse-driven creative force that wants to code at the speed of thought and would prefer to deploy first and ask questions later. On the other side, there's the superego, which wants to test every line of code and would push a release by a month if it meant catching one extra bug.  Experienced developers know how to act as a referee between these two forces and find the right balance between speed and security. But inexperienced or overworked devs often put their id in the driver's seat, which leads (among other things) to accidentally leaking developer secrets. These secrets include things like API and SSH keys, unencrypted credentials, and authentication tokens. Calling developer secrets "the keys to the kingdom" is something of a cliche, but it's tough to think of another phrase that accurately captures the unique power of this data. Unfortunately, the people who most appreciate the pow...

I have been a Star Wars fan since the moment I took my seat in the theatre and saw Princess Leia's rebel ship trying to outrun an Imperial Star Destroyer. It's impossible to see that movie (or its greatest successor, Andor ) and not take the side of the underdog rebels, who are determined to escape the iron fist of imperial control. Of course, in my work as a security professional, "control" is the name of the game. I've spent as much of my career trying to stop my own end-users from going outside the lines as I have trying to guard against malicious outsiders. I personally still think I'm the good guy, since my ultimate goal is to protect sensitive data, but I understand why IT and security teams are often seen as the bad guys. After all, we do operate according to something called the "rule of no." It's not great branding, and increasingly, it just isn't working. Here's the situation in 2025: we have a galaxy's worth of diverse applications, devices, and user identities accessing...

Shadow AI is presenting new challenges for security leaders. While AI tools have already revolutionized how we work, they've also created unprecedented security challenges that our traditional strategies or tools simply weren't designed to handle. I've spent the last decade working with organizations grappling with emerging tech risks, and I can tell you that this is different. In this post, we'll talk about why, and more importantly, what you can do about it. The Hidden Risks of AI Adoption: Shadow AI The Wiz research team recently uncovered a publicly exposed DeepSeek production ClickHouse database , leaking chat history, API secrets, and other sensitive data—raising serious concerns for any organization using DeepSeek's models. Truth is that many teams rushed to try out DeepSeek given the hype around its truly advanced technologies. While the DeepSeek situation has been surrounded by FUD, drama, and misinformation, it has also set important precedents for privacy ...