It’s now even easier to find—and exploit—vulnerabilities in computer systems using AI.
Last Friday, the Chinese AI company Z.ai announced a powerful open-weight model that it says is capable of automating cutting-edge coding and cybersecurity tasks almost as well as the best publicly available models from Anthropic and OpenAI.
The new model, GLM 5.3, could be a gift for companies looking to secure their systems against attacks, providing a cheaper way to scan for hidden bugs and other weaknesses. Open-weight—or free-to-download—models can be run on one’s own hardware and are often significantly less costly than closed models like Claude and GPT. Alongside the new model, Z.ai released OpenVuln, a service for scanning code repositories for vulnerabilities using GLM 5.3.
For now, the new model is in a limited release with trusted partners, but it shows how quickly open-weight models are gaining superhuman hacking skills. And that might pose problems if the model is harnessed by criminals and other bad actors.
That prospect is especially sobering following a string of startling incidents involving rogue AI agents with advanced cyber-skills. In recent weeks, OpenAI, Anthropic, and independent security researchers have revealed examples of agents escaping from testing environments and autonomously hacking into outside systems, including the research platform Hugging Face, to complete tasks.
On Monday, OpenAI president Greg Brockman warned in a blog post that the Hugging Face incident would go down as “a watershed moment for cybersecurity because it gave a peek into how the capabilities of a typical threat actor will evolve in upcoming months.”
Brockman argued that AI models are becoming so good at scouring codebases for unknown flaws and analyzing systems for misconfigurations that it’s crucial for organizations to use AI to scan their systems and identify issues before they can be exploited.
OpenAI would, of course, like companies to use its AI to do that. So far, it’s moving carefully in providing access to its most capable AI. Like Anthropic, OpenAI has made its most advanced models available to a limited number of partners prior to full release. The US government is also wrestling with the issue and now reviews frontier models as part of their releases.
Some believe that open-source AI will be crucial to shoring systems up from attack; Nvidia recently announced an alliance to promote the use of open AI for cybersecurity. A previous version of Z.ai’s GLM was used by Hugging Face to shore up its systems after an unreleased OpenAI model went rogue and broke them last month.
In a post on X, Guillermo Rauch, CEO of Vercel, a web design and hosting company, said his engineers had tested GLM 5.3 as a tool for scanning sites for bugs. “Given its lower costs, I expect this to be a boon for defensive security work,” Rauch wrote in his post. “It’s the new open frontier.”
Z.ai said in a post announcing GLM 5.3 that it had improved the model by “post-training,” which involves giving a model examples of solved problems and letting it learn through experimentation. The company cited coding and cybersecurity benchmark scores that show GLM 5.3 nearing or even exceeding the scores of Anthropic and OpenAI’s models in some cases, like one popular cybersecurity benchmark called CyberGym.
Z.ai also acknowledged the risk of releasing powerful open models in its post. “These capabilities can help defenders identify weaknesses earlier, validate risks, and accelerate remediation,” the company wrote. “They also create clear dual-use risks. We are therefore taking a staged approach to release. Selected security partners will first evaluate GLM-5.3 in controlled settings.” Z.ai says that full access to the model will be available in two weeks.
“This model looks exceptional, with a somewhat astounding increase in scores,” Nathan Lambert, a prominent AI expert, wrote in a post about GLM 5.3. “This is another step towards the inevitable proliferation of very strong cyber capabilities across the economy.”
Z.ai’s latest release also highlights China’s edge in open-weight models. Although the US has sought to restrict the country’s access to the most advanced chips for training AI models, recent months have seen the release of several extremely powerful open-weight models, including Qwen 3.8 Max from Alibaba and Kimi 3 from Moonshot AI. Z.ai has previously said that it used Chinese-made chips from Huawei to train some of its models. Meta, which appeared to have abandoned open-source AI, now seems poised to lead the US challenge with a powerful model called Muse Spark.
The US government is developing a framework designed to mitigate the impact of AI’s advancing cyber capabilities. A big remaining question is what it should do with open models—especially as they introduce more potential risk.
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