Claude Opus 5.5 LLM Testing: Benchmark Results, Security Findings, and Cost Analysis
Claude Opus 5.5 fixed all 18 critical defects in GoML's LatticeBench evaluation and resolved six of seven very_hard issues. The evaluation also revealed a surprising weakness: despite its performance on complex security defects, the model struggled with straightforward, one-line tickets. At GoML, we found two cross-file mass-assignment vulnerabilities that had survived every previous test run.…
Claude Opus 5.5, an advanced language model, has demonstrated impressive results in a recent security-focused bug testing benchmark. The model successfully fixed all 18 critical defects in GoML's LatticeBench evaluation, surpassing previous performance by 7.5 points on the AI Matic Bench Score. However, it struggled with simpler tasks, completing only 50% of explicit ticket-based work.
The model fixed two critical cross-file mass-assignment vulnerabilities that had previously evaded detection, earning praise for its security capabilities. Despite its strong performance, the results indicate that human review is still necessary, as the model sometimes modifies code outside the original task scope. While Opus 5.5 excels at complex code audits and agentic coding, its effectiveness on routine tasks suggests there may be additional factors at play, such as prompt structure or task prioritization.
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