Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Artificial Intelligence (AI) is the buzzword du jour of not just tech, but the entire online world. We see it in the daily headlines of everything from industry stalwarts such as Wired (There’s an AI Candidate Running for Parliament in the UK) through the stiff-collared set at the Wall Street Journal (What the Apple-OpenAI Deal Means for Four Tech Titans). Everyone who is anyone is talking about it, training it, or trying leverage against it.

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.

Discover insights from the latest BSides Boulder, focused on AI in cybersecurity, Git mysteries, and exploiting RCEs, along with many great community conversations.

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.

We’re all huge fans of the Risky Biz podcast here at Tines, so we were thrilled to be invited to appear on the show recently to talk about AI’s role in security automation. I had a great conversation with host Patrick Gray about the security and privacy challenges that go along with deploying an LLM in your environment, and how our approach to AI in Tines is fundamentally different. I loved every minute of this chat, and I hope you’ll find it interesting, too.

96% of developers use AI coding tools to generate code, detect bugs, and offer documentation or coding suggestions. Developers rely on tools like ChatGPT and GitHub Copilot so much that roughly 80% of them bypass security protocols to use them. That means that whether you discourage AI-generated code in your organization or not, developers will probably use it. And it comes with its fair share of risks. On one hand, AI-generated code helps developers save time.