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New benchmark tests LLMs on extracting threat intelligence from malware

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced SCRIPTIOC-BENCH, a new benchmark designed to evaluate the capability of large language models (LLMs) in extracting actionable threat intelligence from script-based malware. The benchmark includes 634 verified samples of JavaScript, PowerShell, and VBScript, focusing on four types of indicators of compromise (IOCs): URLs, domains, IP addresses, and filesystem artifacts. Evaluations showed that even the best-performing LLMs struggled with static IOC recovery, achieving a maximum F1 score of 65.4, highlighting the ongoing challenges in this area. AI

IMPACT This benchmark could drive improvements in LLM capabilities for cybersecurity threat detection and analysis.

RANK_REASON The cluster describes a new academic benchmark for evaluating LLMs on a specific security task, published on arXiv.

Read on Hugging Face Daily Papers →

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

New benchmark tests LLMs on extracting threat intelligence from malware

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The cluster describes a new academic benchmark for evaluating LLMs on a specific security task, published on arXiv.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Hanna Kim, Jian Cui, Minkyoo Song, Hwanjo Heo, Seungwon Shin, Kimin Lee, Xiaojing Liao ·

    SCRIPTIOC-BENCH: A Benchmark for Recognizing Actionable Threat Intelligence from Script-Based Malware using LLMs

    arXiv:2609.06149v1 Announce Type: cross Abstract: Script-based malware remains a prevalent attack technique. These scripts often contain indicators of compromise (IOCs) that provide actionable threat intelligence. However, statically recovering such indicators is challenging, as …

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

    SCRIPTIOC-BENCH: A Benchmark for Recognizing Actionable Threat Intelligence from Script-Based Malware using LLMs

    Script-based malware remains a prevalent attack technique. These scripts often contain indicators of compromise (IOCs) that provide actionable threat intelligence. However, statically recovering such indicators is challenging, as relevant values may be dispersed or transformed wi…

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