Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

After speaking to a wide spectrum of customers ranging from SMBs to enterprises, three things have become clear: Add that together, and we get Shadow AI. This refers to AI usage that is not known or visible to an organization’s IT and security teams. Shadow AI comes in many forms, but in this blog we’ll stick to a discussion of Shadow AI as it pertains to applications. Application security teams are well aware that AI models come with additional risk.

I’m back from another Black Hat! It was great seeing everyone. I put out a message on LinkedIn for people to come find me and, boy, did they. The hallway conversations were so engaging, I was sometimes late getting to the official talks, but I’m getting ahead of myself. AI was everywhere, as we’d expect, but I also sat down to listen to experts on other topics like critical infrastructure, cyber insurance, and the root causes of cybersecurity failure.

This is a public service announcement: The not-so-simple act of securing applications produces a lot of documentation, including playbooks and policies, that isn’t typically needed on a daily basis. But when a zero-day event occurs, such as the recent Crowdstrike incident, application security teams better be able to find everything they need—and fast. Sadly, in both big and small companies, missing and outdated documentation is rampant.

Large language models are fascinating tools for cybersecurity. They can analyze large quantities of text and are excellent for data extraction. One application is researching and analyzing vulnerability data, specifically Common Vulnerabilities and Exposures (CVE) information. As an application security company with roots in open source software vulnerability detection and remediation, the research team at Mend.io found this a particularly relevant area of exploration.

Open source software (OSS) is software for which the original authors have granted express copyright and usage permissions to allow all users to access, view, and modify the source code of these programs however they see fit and without the need to pay royalties. This is in contrast to proprietary, closed source software, which typically requires a paid license and cannot be added to, modified, or distributed by anyone except the owner of the rights to the software.

Managing dependencies isn’t always easy, but it’s critical for protecting your code. In this guide, we’ll explore what dependencies are and how they can be checked for known vulnerabilities, compatibility, licensing requirements, and more. We’ll then learn that dependency checks should be part of a dependency management strategy to keep applications up to date and reduce security risks and technical debt.

Polyfill.js is a popular open-source project that provides modern functionality on older browsers that do not support it natively; users embed it using the cdn.polyfill.io domain. On February 24, 2024, a Chinese company named Funnull acquired both the domain and the Github account. Following that acquisition, the developer, Andrew Betts, tweeted on his X account a warning for all of his service’s users urging them to remove any reference to polyfill from their code.

It’s not uncommon to hear people refer to updating dependencies as “dependency management”. They’re not wrong; keeping dependencies up to date is a big part of dependency management, but it’s not everything. Read on to learn more about the differences between the two.

AI promises many advantages when it comes to application development. But it’s also giving threat actors plenty of advantages, too. It’s always important to remember that AI models can produce a lot of garbage that is really convincing—and so can attackers. “Dark” AI models can be used to purposely write malicious code, but in this blog, we’ll discuss three other distinct ways using AI models can lead to attacks.

Only about 35 percent of the models on Hugging Face bear any license at all. Of those that do, roughly 60 percent fall under traditional open source licenses. But while the majority of licensed AI models may be open source, some very large projects–including Midjourney, BLOOM, and LLaMa—fall under that remaining 40 percent category. So let’s take a look at some of the top AI model licenses on Hugging Face, including the most popular open source and not-so-open source licenses.