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New KaliBench benchmark tests LLMs for cybersecurity CLI command generation

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced KaliBench, a new benchmark designed to evaluate the ability of large language models (LLMs) to generate precise command-line interface (CLI) commands for cybersecurity tools. The benchmark includes 8,504 query-command pairs across 1,642 tools, focusing on accurate tool selection and argument construction. Current open-weight models struggle with this task, achieving less than 42% exact-command accuracy. However, fine-tuning with KaliBench's verifiable rewards significantly improved an 8B model's performance. AI

IMPACT This benchmark could accelerate the development of more capable LLMs for cybersecurity operations by providing a standardized evaluation for CLI command generation.

RANK_REASON The cluster contains an academic paper introducing a new benchmark for evaluating LLM performance on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New KaliBench benchmark tests LLMs for cybersecurity CLI command generation

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The cluster contains an academic paper introducing a new benchmark for evaluating LLM performance on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Pengfei Li, Naufal Suryanto, Sicheng Zhang, Muzammal Naseer ·

    KaliBench: A Fine-Grained Benchmark for Cybersecurity Tool Use on Kali Linux with Runtime-Free Verifiable Rewards

    arXiv:2610.02206v1 Announce Type: cross Abstract: LLMs are increasingly applied to cybersecurity workflows, where they are expected to translate analysts' intent into tool invocations. However, existing evaluations focus on knowledge-based assessments or end-to-end agentic tasks,…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    KaliBench: A Fine-Grained Benchmark for Cybersecurity Tool Use on Kali Linux with Runtime-Free Verifiable Rewards

    LLMs are increasingly applied to cybersecurity workflows, where they are expected to translate analysts' intent into tool invocations. However, existing evaluations focus on knowledge-based assessments or end-to-end agentic tasks, and do not directly measure LLMs' ability to gene…

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