As the White House and federal agencies grapple with frontier AI models and their hacking capabilities, researchers are warning that the industry’s “middle class” of smaller models may end up posing a greater threat over the long term.
Research from XBOW this week shows that a growing class of both proprietary and open-source models are becoming strategically important in the offensive security ecosystem. Models like Z.ai’s open-weight GLM-5.2, xAI’s Grok 4.5, Anthropic’s Opus 4.7, Meta’s Muse Spark 1.1, still perform very strongly at many hacking and exploitation tasks that worry policymakers.
“It’s not even that the open-source variants or…not quite frontline competitors are catching up [to frontier models] as such,” said Albert Ziegler, head of AI at XBOW. It’s that they are crossing a certain threshold, which means that suddenly they are providing net value at a cheaper price.”
That wasn’t necessarily the case as recently as six months ago, when testing on mid-tier class models showed they struggled to complete “moderately complex” agentic tasks. Today’s middle class largely can. Their relative cheapness means users can spend many times more resources—running them repeatedly—to solve the same challenges.
“Because these models are cheaper, it’s okay to give them more time, and they come from behind and leapfrog the big frontier model,” said Ziegler. “Now, that didn’t work half a year ago because…if you wanted to run some open-source model on a complex task in an agentic way…on a long horizon, then it would just get lost.”
GPT 5.5, now considered a near-frontier model, delivered one of the best performances on exploitation benchmarks that XBOW has recorded to date.