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XekRung Technical Report

About

We present XekRung, a frontier large language model for cybersecurity, designed to provide comprehensive security capabilities. To achieve this, we develop diverse data synthesis pipelines tailored to the cybersecurity domain, enabling the scalable construction of high-quality training data and providing a strong foundation for cybersecurity knowledge and understanding. Building on this foundation, we establish a complete training pipeline spanning continued pre-training (CPT), supervised fine-tuning (SFT), and reinforcement learning (RL) to further extend the model's capabilities. We further introduce a multi-dimensional evaluation system to guide the iterative improvement of both domain-specific and general-purpose abilities. Extensive experiments demonstrate that XekRung achieves state-of-the-art performance on cybersecurity-specific benchmarks among models of the same scale, while maintaining strong performance on general benchmarks.

Jiutian Zeng, Junjie Li, Chengwei Dai, Jie Liang, Zhaoyu Hu, Yiliang Zhang, Ziang Weng, Longtao Huang, Dongjie Zhang, Libin Dong, Yang Ge, Yuanda Wang, Kaiwen Lv Kacuila, Bingyu Zhu, Jing Wang, Jin Xu• 2026

Related benchmarks

TaskDatasetResultRank
ReasoningHellaSwag (HS)
HellaSwag Accuracy77.43
209
ReasoningWinoGrande (WG)
Accuracy73.24
168
KnowledgeMMLU
Accuracy78.58
161
Commonsense ReasoningSocialIQA
Accuracy73.39
158
MathematicsMATH
MATH Accuracy73.5
136
Commonsense ReasoningCommonsenseQA
Accuracy (pass@1)80.59
108
Common Sense ReasoningPIQA
Accuracy86.4
100
Story completionStoryCloze
Accuracy97.42
80
Mathematical ReasoningTheoremQA
Accuracy41.63
64
Chinese KnowledgeCEval
Accuracy76.65
28
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