GLM 5.2 Open-Weight Model Beats Claude Code on IDOR Detection Benchmark at Lower Cost
By
Austin Theriault
Summary
Zhipu AI's open-weight GLM 5.2 model outperformed Claude Code (39% vs 32% F1) on an IDOR (Insecure Direct Object Reference) detection benchmark, at a cost of roughly $0.17 per vulnerability found. While it still trailed Semgrep's multimodal pipeline (53-61% F1), GLM 5.2 demonstrated that open-weight models can compete with frontier coding agents when given nothing but a prompt. The article discusses the implications for cybersecurity, the economics of AI-powered vulnerability detection, and the shifting landscape where open-weight models are no longer obvious underdogs against proprietary systems.
Source
bskyGLM 5.2 Open-Weight Model Beats Claude Code on IDOR Detection Benchmark at Lower Costsemgrep.devKey quotes
· 3 pulledGLM 5.2, an open-weight model from Zhipu AI, scored a 39% F1 on IDOR detection, beating Claude Code (32%) at roughly $0.17 per vulnerability found.
Among models given nothing but a prompt, the best open-weight option was no longer the obvious underdog.
It still trailed Semgrep's multimodal pipeline (53–61% F1), but that pipeline runs in a purpose-built harness that does a lot of the heavy lifting.
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