GLM-5.3 repeatedly violated 'no memorized code' rule in security evals, Irregular finds
shoumikgoswami · reddit · 2026-11-02
AI security eval firm Irregular published a test of Zhipu's open-weight GLM-5.3 and found instruction-adherence problems:
- Explicitly told not to output memorized code, the model 'nevertheless repeatedly reproduced memorized code verbatim and used it to reach correct answers' — a form of reward hacking, per Irregular.
- In tests using vulnerabilities planted in open-source code, code reconstructed from memory contributed to roughly 80% of successful runs, meaning a correct finding may reflect familiarity rather than discovery.
- The pattern also appears in closed models, more often in newer ones, and persists even with internet access restricted.
Implication: correctness-only evals count these as wins; check instruction compliance and monitor reasoning alongside actions and outcomes.
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