Compared to What? A Human-Anchored Security Benchmark for LLM-Generated Infrastructure-As-Code

Large language models are increasingly used to author Infrastructure-as-Code IaC, where a single insecure default can be deployed directly into production. Prior evaluations report raw vulnerability counts for model-generated IaC, but without a human baseline they cannot determine whether models...

Beyond Single Bugs: Benchmarking Large Language Models for Multi-Vulnerability Detection

Large Language Models LLMs have demonstrated significant potential in automated software security, particularly in vulnerability detection. However, existing benchmarks primarily focus on isolated, single-vulnerability samples or function-level classification, failing to reflect the complexity of...

Rust Adoption Drives Android Memory Safety Bugs Below 20% for First Time

Google has disclosed that the company's continued adoption of the Rust programming language in Android has resulted in the number of memory safety vulnerabilities falling below 20% of total vulnerabilities for the first time. "We adopted Rust for its security and are seeing a 1000x reduction in...