Yes, there are several established and emerging security benchmarks for Large Language Models (LLMs). These benchmarks generally focus on different aspects of security, such as code generation safety, vulnerability detection, and resistance to adversarial attacks. Here are some notable examples and resources: * **BaxBench:** A specialized coding benchmark designed to evaluate how well LLMs generate both correct and secure backend code in realistic, security-critical scenarios. * **HardSecBench:** A benchmark specifically focused on the security awareness of LLMs, particularly in the context of hardware and firmware development, where functional correctness does not always equate to security. * **Rapticore LLM Security Benchmark:** An enterprise-grade framework that tests LLMs across multiple providers to evaluate their ability to identify and respond to security vulnerabilities in code. * **OWASP LLM Security Verification Standard:** While not a "benchmark" in the sense of a leaderboard, this is a critical industry standard that provides methodologies for security teams to conduct audits and penetration tests on LLM-backed systems. It also aims to establish and update security benchmarks. * **Industry-Specific Resources:** * **LLM Security 101 (2026 Edition):** A comprehensive guide that covers the OWASP Top 10 for LLMs and Agentic Applications, providing a foundational understanding of offensive and defensive security. * **Awesome-LLM4Cybersecurity:** A curated repository that includes various cybersecurity evaluation benchmarks for those looking to explore the field in depth. * **Infosecurity Magazine:** Often publishes lists of top benchmark suites for cybersecurity practices, which can be a good starting point for selecting tools relevant to your specific use case. When evaluating these benchmarks, it is important to consider whether they test for **safety** (e.g., the model refusing to generate malicious code) or **security** (e.g., the model's ability to write secure code or detect vulnerabilities). Many modern platforms, such as **splx.ai**, also offer commercial benchmarking services that test models against thousands of simulated attacks.