Evaluating the offensive utility of large language models in cyber threat generation

Bakhtiyorov, Mukhammadbek, Mattiev, Jamolbek

Innovative Multidisciplinary Journal of Applied Technology · 2026-yil

Annotatsiya

Large Language Models (LLMs) are increasingly integrated into cybersecurity workflows, creating both defensive opportunities and new forms of offensive enablement. Existing research demonstrates capabilities in threat modeling, attack-path construction, Cyber Threat Intelligence (CTI) processing, adversarial text generation, and automated penetration testing; however, these capabilities are commonly evaluated in isolation. This review synthesizes recent evidence and develops a methodological framework for evaluating offensive utility as a multidimensional construct encompassing technical capability, correctness, contextual grounding, reliability, operational relevance, temporal efficiency, and human-expertise compression. The review distinguishes linguistic plausibility from cyber validity and separates model capability from system-level utility. Evidence from recent studies indicates that LLMs can support attack-technique mapping and multi-stage reasoning, while retrieval-augmented architectures can improve contextualization. At the same time, hallucination, inconsistent reasoning, latency, safety restrictions, and retrieval dependence constrain practical utility. The proposed framework therefore treats offensive utility as an emergent property of the interaction among model, context, retrieval, tools, and human oversight rather than as a single model attribute. The framework provides a basis for reproducible comparative evaluation without requiring unauthorized real-world offensive activity.

Maqola ma’lumotlari
MualliflarBakhtiyorov, Mukhammadbek, Mattiev, Jamolbek
JurnalInnovative Multidisciplinary Journal of Applied Technology
NashriyotТДТУ Қўқон филиали
ISSN2995-486X, 2995-486x
Nashr sanasi2026-10-22
Jild4
Son10
Betlar172-179
TilIngliz
Ilmiy sohaTexnika
DOI10.51699/19p6pw96
Indeksga qo‘shilgan2026-10-23

DOI: 10.51699/19p6pw96 · Maqolaning asl sahifasi

Kalit so‘zlar

Large Language Models, cyber threat generation, offensive cybersecurity, Cyber Threat Intelligence, threat modeling, attack-path reasoning, retrieval-augmented generation, reliability, operational utility, cybersecurity automation

Ilmiy soha

Texnika

Iqtibos keltirish

APABakhtiyorov, Mukhammadbek, & Mattiev, Jamolbek (2026). EVALUATING THE OFFENSIVE UTILITY OF LARGE LANGUAGE MODELS IN CYBER THREAT GENERATION. Innovative Multidisciplinary Journal of Applied Technology, 4(10), 172-179. https://doi.org/10.51699/19p6pw96
GOST (OAK)Bakhtiyorov, Mukhammadbek, Mattiev, Jamolbek EVALUATING THE OFFENSIVE UTILITY OF LARGE LANGUAGE MODELS IN CYBER THREAT GENERATION // Innovative Multidisciplinary Journal of Applied Technology. – 2026. – T. 4, № 10. – P. 172-179. – DOI: 10.51699/19p6pw96.
MLABakhtiyorov, Mukhammadbek, and Mattiev, Jamolbek. “EVALUATING THE OFFENSIVE UTILITY OF LARGE LANGUAGE MODELS IN CYBER THREAT GENERATION.” Innovative Multidisciplinary Journal of Applied Technology, 4(10), 172-179, 2026. https://doi.org/10.51699/19p6pw96
ChicagoBakhtiyorov, Mukhammadbek, and Mattiev, Jamolbek. “EVALUATING THE OFFENSIVE UTILITY OF LARGE LANGUAGE MODELS IN CYBER THREAT GENERATION.” Innovative Multidisciplinary Journal of Applied Technology, 4(10), 172-179 (2026). https://doi.org/10.51699/19p6pw96
HarvardBakhtiyorov, Mukhammadbek, and Mattiev, Jamolbek (2026) ‘EVALUATING THE OFFENSIVE UTILITY OF LARGE LANGUAGE MODELS IN CYBER THREAT GENERATION’, Innovative Multidisciplinary Journal of Applied Technology, 4(10), 172-179. https://doi.org/10.51699/19p6pw96
BibTeX
@article{bakhtiyorovmukhammadbek2026,
  title = {EVALUATING THE OFFENSIVE UTILITY OF LARGE LANGUAGE MODELS IN CYBER THREAT GENERATION},
  author = {Bakhtiyorov, Mukhammadbek and Mattiev, Jamolbek},
  journal = {Innovative Multidisciplinary Journal of Applied Technology},
  year = {2026},
  volume = {4},
  number = {10},
  pages = {172-179},
  doi = {10.51699/19p6pw96},
  url = {https://doi.org/10.51699/19p6pw96}
}

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