Artificial Intelligence models are rapidly improving their ability to find vulnerabilities in software systems, leading some experts to warn that the tech industry may need to rethink its approach to building secure code. As these AI models become increasingly sophisticated, they can identify previously unknown weaknesses and potential entry points for hackers.
The situation has reached an "inflection point," according to Dawn Song, a computer scientist at UC Berkeley who specializes in both AI and security. Recent advances in AI have produced models that are better than ever at finding flaws, including simulated reasoning and agentic AI. These capabilities have dramatically increased the cyber abilities of frontier models.
In fact, a benchmark called CyberGym, which includes 1,507 known vulnerabilities found in 188 projects, has shown that some large language models can identify up to 30 percent of these vulnerabilities. This is particularly concerning, as it suggests that hackers could potentially exploit previously unknown weaknesses.
To counter this trend, experts are calling for new approaches to security, including sharing AI models with security researchers before launch and using them to find bugs in systems prior to a general release. Another idea is to rethink how software is built in the first place, using AI to generate code that is more secure than what most programmers use today.
However, some experts warn that the coding skills of AI models could also give hackers an upper hand. If these capabilities accelerate, it means that offensive security actions will also accelerate, potentially leading to a cat-and-mouse game between cybersecurity experts and hackers.
As the tech industry continues to grapple with this challenge, one thing is clear: the future of software security will require innovative solutions and new approaches to building secure code.
The situation has reached an "inflection point," according to Dawn Song, a computer scientist at UC Berkeley who specializes in both AI and security. Recent advances in AI have produced models that are better than ever at finding flaws, including simulated reasoning and agentic AI. These capabilities have dramatically increased the cyber abilities of frontier models.
In fact, a benchmark called CyberGym, which includes 1,507 known vulnerabilities found in 188 projects, has shown that some large language models can identify up to 30 percent of these vulnerabilities. This is particularly concerning, as it suggests that hackers could potentially exploit previously unknown weaknesses.
To counter this trend, experts are calling for new approaches to security, including sharing AI models with security researchers before launch and using them to find bugs in systems prior to a general release. Another idea is to rethink how software is built in the first place, using AI to generate code that is more secure than what most programmers use today.
However, some experts warn that the coding skills of AI models could also give hackers an upper hand. If these capabilities accelerate, it means that offensive security actions will also accelerate, potentially leading to a cat-and-mouse game between cybersecurity experts and hackers.
As the tech industry continues to grapple with this challenge, one thing is clear: the future of software security will require innovative solutions and new approaches to building secure code.
can't believe it's gonna be a cat-and-mouse game between hackers and cybersecurity experts!!! we need to think outside the box and come up with some serious solutions stat! 
sharing ai models with security researchers is a great idea, but what if hackers just adapt and find new ways to exploit? 
anyway, I'm all for rethinking how software is built in the first place - AI generated code could be the answer?! 
let's get creative and make secure coding a thing of the past! 
. Now these big language models can find like 30% of the known vulnerabilities 
. we need to rethink how we build software from scratch, maybe use AI to generate more secure code, but not just rely on them to find flaws after the fact. what if these models become the new weakest link in our cybersecurity 
. We can't just rely on these AI models to find bugs and vulnerabilities for us anymore. That just creates more opportunities for hackers to exploit. 
We need to collaborate with security researchers and experts to develop new ways of building software that's inherently more secure.
. We can't just sit around waiting for hackers to find weaknesses in our systems before we act. We need to be proactive about it 
. Time to get creative and think outside the box 
But on the other hand, if these models can spot weaknesses that hackers haven't even thought of yet... we might be looking at a whole new level of cat-and-mouse games 
. And let's not forget, cybersecurity is all about trade-offs: do we prioritize speed and progress or focus on building secure systems from the ground up? 
) about how we're gonna balance these competing interests. After all, if the private sector isn't willing to invest in security, who will be? 
but what about the potential risks? If hackers get their hands on this tech, it's like they have a superpower 
. We need to stay ahead of the game and come up with some creative solutions to keep our software safe 
. Need to think outside the box (or in this case, the codebase) 
. Like, seriously, these models can find vulnerabilities that we didn't even know existed yet? It's like having a mole in the lab working against us 
. We need to get creative here and start thinking of new ways to build security into our code from the ground up. Sharing AI models with security researchers is a good start, but it's only half the battle. We also need to rethink how we write code in the first place. Maybe we can use AI to generate code that's like a super-strong firewall for our software 
. But at the same time, I'm a bit worried about these models being used by hackers too. It's like a game of cat and mouse where both sides are getting way smarter 
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. But seriously, I think it's time to upgrade our coding skills from "good enough" to "AI-approved". Maybe we can even hire some AIs as consultants, they're already better at finding flaws than most humans! 
. We need more automation not less. Let the AI do all the grunt work so we can focus on making the code even more secure 
. Sharing AI models with security researchers is just gonna spread the problem around 
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. The more they learn, the harder it gets for us to keep up. I mean, I've heard of these CyberGym benchmarks before, but now it's crazy to think that language models can spot 30% of vulnerabilities. What's next? AI-generated malware? 
. We need innovative solutions ASAP or we'll be living in a world where hackers are like super ninjas 
. Sharing AI models with security researchers before launch is a good start but we also need to consider using them to generate code that's way more secure than what most programmers use today