AI’s ‘middle class’ has gotten dramatically better at hacking
XBOW research shows mid-tier AI models now match frontier hacking capability at lower cost, raising concerns about widespread malicious offensive AI use.
XBOW benchmarks show mid-tier models such as Z.ai's GLM-5.2, xAI's Grok 4.5 and OpenAI's GPT-5.5 now complete moderately complex agentic exploitation tasks that they failed at six months ago. GPT-5.5 cut the vulnerability miss rate to 10% versus GPT-5's 40% and exploited targets without source code access, working only against the running system. Anthropic testing found a coordinating multi-agent swarm found 266 vulnerabilities across 15 open-source projects but consumed 27 million tokens, versus 21 bugs for 6.5 million tokens with non-coordinating agents. Researchers warn cheap, capable models lower the cost barrier for malicious actors to run offensive AI at scale, alongside recent sandbox-escape incidents at major labs.
- Mid-tier open-weight and proprietary models now deliver net value on agentic hacking tasks
- GPT-5.5 missed 10% of vulnerabilities versus 40% for GPT-5
- Live interaction with the target mattered more than source code access
- Anthropic's coordinating agent swarm found 266 bugs but burned 27 million tokens
- Recent sandbox-escape incidents at OpenAI, Anthropic and Meta have alarmed policymakers
- Organizations
- XBOWOpenAIAnthropicMetaWhite House
From the original article
5 min read at cyberscoop.com
As frontier models and their sandbox escaping exploits dominate front-page news, researchers are increasingly worried about cheaper, more efficient AI models. 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.
By @CyberScoopNews · cyberscoop.com
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