Max Justicz, the chief technology officer and co-founder of the startup Charge Robotics, used an OpenAI model to find a severe vulnerability that — if exploited — could allow hackers to take control of servers running Ubuntu, a widely used open source Linux-based operating system.
Justicz, who has a hobbyist’s interest in cybersecurity and previously found a vulnerability in the same codebase, told TechCrunch that he found this issue using GPT 5.6 Sol, released in July, through the AI maker’s Daybreak Blue, a program that gives cybersecurity defenders access to powerful frontier models.
“I literally just aimed ChatGPT at the same body of code and said ‘I found this bug previously that was fixed several years ago, please find bugs as bad or worse,’ and it came back in two hours with this,” Justicz said. “It’s extremely convoluted and hard for a human to find, but it works!”
He reported the issue to the Debian Project, which maintains the software in question and issued a patch to fix the vulnerability. There has been no known evidence of exploitation. Still, the ease with which he found it suggests that we’ve only seen the tip of the iceberg when it comes to potential exploits that even novice hackers can utilize with the help of AI models.
“I can only imagine what one could do with more time and access to less neutered models. We should expect some extremely crazy bugs to be found and exploited over the next few months,” Justicz wrote in a social media thread discussing his finding. “This might be obvious to most folks here, but there is currently huge alpha in taking some code or binary someone has not audited yet and just aiming a powerful AI model at it.”
OpenAI appears to have noticed. Today, the AI giant announced a new model focused on cybersecurity, ChatGPT Cyber, would be made available to the highest tier of users in the cybersecurity program, Daybreak Red, which allows offensive cybersecurity researchers tools for vulnerability hunting and development. Yesterday, OpenAI said that the same model had been used to scan and prepare patches for vulnerabilities in the Linux kernel, finding 948 potential issues. OpenAI also found 81 “novel” vulnerabilities in Firefox, the web browser.
“Our goal is to dramatically expand Daybreak, bringing advanced security research to organizations of every size, independent researchers, and open-source maintainers,” the frontier lab said in a statement.
OpenAI has insisted that there is a narrow window of time for the people who safeguard digital infrastructure to take action before AI models become even better at hacking and easier to access. For cyber defenders, however, it can feel like the frontier labs have unleashed a mountain of new work that outstrips their resources. Justicz said that he personally spent about $5,000 on subscriptions and tokens to find several exploits.
Besides Daybreak’s model access, OpenAI has also announced a $1 billion initiative to support cybersecurity professionals in the program who work on critical infrastructure like the electrical grid or water systems.
The Daybreak program has its own critiques. Justicz notes that the frontier lab appears to have recently “nerfed” Daybreak Blue to make it less useful at finding vulnerabilities. On one hand, it may be good to limit access from potential bad actors — Justicz said he just uploaded a photo of his driver’s license to join the program. On the other, cybersecurity professionals say they have one hand tied if they can’t use frontier technology while bad actors can deploy open-weight models with abliterated guardrails.
Still, OpenAI says just “thousands” of cybersecurity professionals are participating in the Daybreak program, versus a far larger number of potential hackers.
It’s unclear if frontier labs are devoting enough of their resources to this issue. Eric Wallace, a researcher on OpenAI’s technical staff, said that “we are now allocating a significant amount of our frontier compute towards discovering and patching vulnerabilities in open source codebases, fully pro bono.”
But the Linux bug hunt cost $1.2 million, which is significantly less than the approximate $6 million token spend the company invested in finding a potential solution to a famous problem of fluid dynamics.
If there is a narrow window of time to patch the digital infrastructure the world depends on, more urgency may be required.
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