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

Paper recorded by Signals 4 on 2026-10-01 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-01 on arXiv · recorded by Signals 4 on 2026-10-02

Category: cs.AI · 人工智能 · first seen 2026-10-02

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, and do not directly measure LLMs' ability to generate executable commands for real-world cybersecurity tools. This gap is critical because cybersecurity operations rely

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#2 most recent of 500 cs.AI papers we have recorded · ↑ newer: One Basis to Animate Them All: Gaussian Blendshape Distillation for Re · ↓ older: Reconstruct, Practice, Go Real: Guided Self-Improvement for Embodied A
Cite this page: KaliBench: A Fine-Grained Benchmark for Cybersecurity Tool Use on Kali Linux with Runtime-Free Verifiable Rewards: the #2 most recent of 500 cs.AI papers we have recorded (as of 2026-10-01). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/kalibench-a-fine-grained-benchmark-for-cybersecurity-tool-use-on-kali-linux-with.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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