Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques | Paper Citation Record

Observation 07794333-6829-46a7-bdf6-3c92e2f89b40 · outbound

This paper cites Attention Is All You Need.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Attention Is All You Need

Reference 1

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Observation 3309c422-6d1e-42d7-82b0-68ac3fb753c3 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2

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Observation 2e39dc67-4af3-4521-8948-511db8c377b8 · outbound

This paper cites Gpt-3.5,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Gpt-3.5,

Reference 3

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Observation c28d3ba0-e470-43bf-83de-44d31e89526b · outbound

This paper cites an unresolved cited work.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Unresolved cited work

Reference 4

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Observation b6f97601-ca65-47e9-9296-ca557bc033f8 · outbound

This paper cites When ChatGPT Meets Smart Contract Vulnerability Detection: How Far Are We?.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques When ChatGPT Meets Smart Contract Vulnerability Detection: How Far Are We?

Reference 5

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Observation 7c8eb3de-7e48-491c-af4f-0914d0bf4e6e · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Constitutional AI: Harmlessness from AI Feedback

Reference 6

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Observation 33c92988-db8c-4a23-8476-309d5857a17c · outbound

This paper cites Towards Explainable Network Intrusion Detection using Large Language Models.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Towards Explainable Network Intrusion Detection using Large Language Models

Reference 7

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Observation cab0fac7-067c-43b1-85e5-79c94ea6d034 · outbound

This paper cites Generator-Retriever-Generator Approach for Open-Domain Question Answering.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Generator-Retriever-Generator Approach for Open-Domain Question Answering

Reference 8

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Observation 8bbdcfaa-c1c4-4f5c-9a30-f8e87ad347a3 · outbound

This paper cites DialogBench: Evaluating LLMs as Human-like Dialogue Systems.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques DialogBench: Evaluating LLMs as Human-like Dialogue Systems

Reference 9

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Observation 025948e4-0b42-4632-916c-851a52029b2d · outbound

This paper cites Open-Universe Indoor Scene Generation using LLM Program Synthesis and Uncurated Object Databases.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Open-Universe Indoor Scene Generation using LLM Program Synthesis and Uncurated Object Databases

Reference 10

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Observation c7b9ebfe-2023-4c59-a77d-d1dd2ee84ebb · outbound

This paper cites Unveiling zeus: automated classification of malware samples,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Unveiling zeus: automated classification of malware samples,

Reference 11

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Observation dbdcdc96-107f-4048-a5fc-f8b49b980cce · outbound

This paper cites AMAL: high-fidelity, behavior- based automated malware analysis and classification,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques AMAL: high-fidelity, behavior- based automated malware analysis and classification,

Reference 12

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Observation 3508a83e-8797-447d-b766-5e1cc1a7d905 · outbound

This paper cites Andro-dumpsys: Anti- malware system based on the similarity of malware creator and malware centric information,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Andro-dumpsys: Anti- malware system based on the similarity of malware creator and malware centric information,

Reference 13

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Observation 9b06fd54-80a8-496d-9d23-d7503430c091 · outbound

This paper cites Android malware detection using complex-flows,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Android malware detection using complex-flows,

Reference 14

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Observation 9c5f6aa7-e22a-40f5-80a5-3410600aeba0 · outbound

This paper cites Iot malware ecosystem in the wild: a glimpse into analysis and exposures,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Iot malware ecosystem in the wild: a glimpse into analysis and exposures,

Reference 15

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Observation 9afea556-ff75-4868-93f3-6ffb8c821ea5 · outbound

This paper cites Adversarial learning attacks on graph-based iot malware detection systems,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Adversarial learning attacks on graph-based iot malware detection systems,

Reference 16

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Observation 8f0a0380-9ad1-4c43-bf4d-b2992d16ead3 · outbound

This paper cites Analyzing and detecting emerging internet of things malware: A graph-based approach,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Analyzing and detecting emerging internet of things malware: A graph-based approach,

Reference 17

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Observation 68779348-cdc8-4c2f-86e1-f03270426f9d · outbound

This paper cites Android malware detection using complex-flows,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Android malware detection using complex-flows,

Reference 18

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Observation e4f2b538-2c62-404f-9e95-8170f7b47f46 · outbound

This paper cites Soteria: Detecting adversarial examples in control flow graph- based malware classifiers,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Soteria: Detecting adversarial examples in control flow graph- based malware classifiers,

Reference 19

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Observation 39b6c523-765f-4019-9f32-a68b852381f4 · outbound

This paper cites Statically dissecting internet of things malware: Analysis, characterization, and detection,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Statically dissecting internet of things malware: Analysis, characterization, and detection,

Reference 20

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Observation 0a2d30c5-4e8b-4459-882c-fea84b4eea4a · outbound

This paper cites Systemically evaluating the robustness of ml-based iot malware detectors,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Systemically evaluating the robustness of ml-based iot malware detectors,

Reference 21

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Observation b3bbcb79-ebf2-4de0-afc1-2bbfc73e3589 · outbound

This paper cites Systematically evaluating the robustness of ml-based iot malware detection systems,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Systematically evaluating the robustness of ml-based iot malware detection systems,

Reference 22

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Observation 6e42038d-3136-4d5f-a099-9e282d7210ad · outbound

This paper cites Understanding internet of things malware by analyzing endpoints in their static artifacts,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Understanding internet of things malware by analyzing endpoints in their static artifacts,

Reference 23

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Observation c13d3c31-b8c2-4e44-9670-894a288b500c · outbound

This paper cites DL-FHMC: deep learning-based fine-grained hierarchical learning approach for robust malware classification,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques DL-FHMC: deep learning-based fine-grained hierarchical learning approach for robust malware classification,

Reference 24

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Observation 2d147708-e831-4186-af20-0382aa621e52 · outbound

This paper cites Exposing the limitations of machine learning for malware detection under concept drift,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Exposing the limitations of machine learning for malware detection under concept drift,

Reference 25

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Observation 73769d7b-f0e8-48ca-953c-1fb57875dcf1 · outbound

This paper cites Semantics-preserving node injection attacks against gnn-based ACFG malware classifiers,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Semantics-preserving node injection attacks against gnn-based ACFG malware classifiers,

Reference 26

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Observation 8cf562ec-8cb3-4957-978b-3e0752fb91fe · outbound

This paper cites Through the looking glass: Llm-based analysis of AR/VR android applications privacy policies,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Through the looking glass: Llm-based analysis of AR/VR android applications privacy policies,

Reference 27

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Observation ac2991b7-a6eb-4ff7-b5a4-ad2711ae1abe · outbound

This paper cites Security and quality in llm-generated code: A multi-language, multi-model analysis,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Security and quality in llm-generated code: A multi-language, multi-model analysis,

Reference 28

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Observation 38f480f7-cb8b-4320-88d5-e969f9f64983 · outbound

This paper cites LLM for SoC Security: A Paradigm Shift.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques LLM for SoC Security: A Paradigm Shift

Reference 29

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Observation 4bac1f80-5bc0-4993-b83e-eb3b0c83842c · outbound

This paper cites Large Language Models for Blockchain Security: A Systematic Literature Review.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Large Language Models for Blockchain Security: A Systematic Literature Review

Reference 30

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Observation edc7b31e-9cd2-49d9-b312-40b6b2b22ae5 · outbound

This paper cites Large language models for cyber security: A systematic literature review,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Large language models for cyber security: A systematic literature review,

Reference 31

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Observation 84d29754-da1e-4ed7-9fc4-92d033f25509 · outbound

This paper cites Review of Generative AI Methods in Cybersecurity.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Review of Generative AI Methods in Cybersecurity

Reference 32

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Observation 8c9dba12-4d60-4dac-81dc-39e28910cc19 · outbound

This paper cites Llms for cyber security: New opportunities,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Llms for cyber security: New opportunities,

Reference 33

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Observation f60c4bb1-d7b3-4f5f-918e-888daf382f02 · outbound

This paper cites Generative AI in Cybersecurity: A Comprehensive Review of LLM Applications and Vulnerabilities.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Generative AI in Cybersecurity: A Comprehensive Review of LLM Applications and Vulnerabilities

Reference 34

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Observation 6d42ebae-2992-49fd-b498-a5300a67c317 · outbound

This paper cites Generative pre- trained transformer-based reinforcement learning for testing web application firewalls,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Generative pre- trained transformer-based reinforcement learning for testing web application firewalls,

Reference 35

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Observation c0d9fadc-b15f-49a1-85f3-f462150d8909 · outbound

This paper cites Deepsqli: deep semantic learning for testing sql injection,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Deepsqli: deep semantic learning for testing sql injection,

Reference 36

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Observation b72ea9ba-e80a-4745-abb1-a3828e538803 · outbound

This paper cites Large language model guided protocol fuzzing,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Large language model guided protocol fuzzing,

Reference 37

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Observation 5bb40e41-354e-4b49-a03c-fbff21253a3a · outbound

This paper cites Intelligent threat detection–ai-driven analysis of honeypot data to counter cyber threats,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Intelligent threat detection–ai-driven analysis of honeypot data to counter cyber threats,

Reference 38

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Observation 5cf2bd15-7b2c-49dd-8a5b-7f008b5e62ac · outbound

This paper cites LLMs Killed the Script Kiddie: How Agents Supported by Large Language Models Change the Landscape of Network Threat Testing.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques LLMs Killed the Script Kiddie: How Agents Supported by Large Language Models Change the Landscape of Network Threat Testing

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:24:31.549681Z

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Observation aeda449b-6d37-4764-8f0a-41ad9d9e376b · outbound

This paper cites Maximizing Penetration Testing Success with Effective Reconnaissance Techniques using ChatGPT.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Maximizing Penetration Testing Success with Effective Reconnaissance Techniques using ChatGPT

Reference 40

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Observation 390525af-ae55-4cd6-81f7-f0466d5bb15c · outbound

This paper cites The formai dataset: Generative AI in software security through the lens of formal verification,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques The formai dataset: Generative AI in software security through the lens of formal verification,

Reference 41

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Observation 1aaf08d3-fe49-4851-8f2e-16ce00f59c27 · outbound

This paper cites Gptscan: Detecting logic vulnerabilities in smart contracts by combining GPT with program analysis,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Gptscan: Detecting logic vulnerabilities in smart contracts by combining GPT with program analysis,

Reference 42

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Observation d4ce5a3c-b9f6-41a8-a09e-4b33c89babff · outbound

This paper cites Unlocking Hardware Security Assurance: The Potential of LLMs.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Unlocking Hardware Security Assurance: The Potential of LLMs

Reference 43

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Observation 1bf32a5a-a3a7-4d07-b096-ccf1ce3aa097 · outbound

This paper cites Pre-training code representation with semantic flow graph for effective bug localization,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Pre-training code representation with semantic flow graph for effective bug localization,

Reference 44

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Observation f6946f8a-3ba2-42a3-a62b-7245ce35b0da · outbound

This paper cites Avscan2vec: Feature learning on antivirus scan data for production-scale malware corpora,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Avscan2vec: Feature learning on antivirus scan data for production-scale malware corpora,

Reference 45

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Observation 3f468fae-1b3e-4f44-83b5-d4b16b88142c · outbound

This paper cites Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:24:31.067723Z

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Observation e2f1715c-2a43-48d8-868f-b5b346cd65c5 · outbound

This paper cites GenKubeSec: LLM-Based Kubernetes Misconfiguration Detection, Localization, Reasoning, and Remediation.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques GenKubeSec: LLM-Based Kubernetes Misconfiguration Detection, Localization, Reasoning, and Remediation

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:26.821242Z

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Observation 5a6f1625-7658-4387-9183-678a32e79a20 · outbound

This paper cites Fortifying cloud envi- ronments against data breaches: A novel ai-driven security framework,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Fortifying cloud envi- ronments against data breaches: A novel ai-driven security framework,

Reference 48

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Observation b17deab0-ce61-4825-9dcf-457b456a6036 · outbound

This paper cites Bandara, S.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Bandara, S

Reference 49

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Observation 5de23a51-fcff-48d8-846c-f3059c41b942 · outbound

This paper cites Ollabench: Evaluating llms’ reasoning for human-centric interdependent cybersecurity.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Ollabench: Evaluating llms’ reasoning for human-centric interdependent cybersecurity

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:27.142618Z

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Observation 4696f828-f27c-48fd-a0d7-5f0399739fc7 · outbound

This paper cites SEvenLLM: Benchmarking, Eliciting, and Enhancing Abilities of Large Language Models in Cyber Threat Intelligence.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques SEvenLLM: Benchmarking, Eliciting, and Enhancing Abilities of Large Language Models in Cyber Threat Intelligence

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:27.223815Z

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Observation d7b32208-d521-4af3-ad9b-1b77c8d08e07 · outbound

This paper cites BC4LLM: A perspective of trusted artificial intelligence when blockchain meets large language models,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques BC4LLM: A perspective of trusted artificial intelligence when blockchain meets large language models,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:27.320974Z

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Observation 50b8a9c4-56fe-4909-a6d6-3f64b8321e32 · outbound

This paper cites Fixing Hardware Security Bugs with Large Language Models.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Fixing Hardware Security Bugs with Large Language Models

Reference 53

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Observation c5e82c0f-fe92-4593-87d3-34b99cfe52bb · outbound

This paper cites Using LLMs to Automate Threat Intelligence Analysis Workflows in Security Operation Centers.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Using LLMs to Automate Threat Intelligence Analysis Workflows in Security Operation Centers

Reference 54

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Observation f43b247f-ea3a-4a9f-98ef-106869b3228e · outbound

This paper cites Chatgpt for digital forensic investigation: The good, the bad, and the unknown,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Chatgpt for digital forensic investigation: The good, the bad, and the unknown,

Reference 55

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Observation ebc378ce-063d-426f-9746-ce816ca6c0b8 · outbound

This paper cites The ethico-political universe of chatgpt,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques The ethico-political universe of chatgpt,

Reference 56

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Observation e3860163-e3d9-443e-a7d7-dade373ab4a8 · outbound

This paper cites PMANet: Malicious URL detection via post-trained language model guided multi-level feature attention network.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques PMANet: Malicious URL detection via post-trained language model guided multi-level feature attention network

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:24:30.973883Z

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Observation 88967eb8-ade2-42c1-832f-f9e97d5d68bd · outbound

This paper cites Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Large Language Models in Wireless Application Design: In-Context Learning-enhanced Automatic Network Intrusion Detection

Reference 58

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Observation 0c14fde8-a2b7-4ea3-b6a4-e5879bbb3279 · outbound

This paper cites A study on advanced persistent threats,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques A study on advanced persistent threats,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:27.990946Z

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Observation efa88dba-b423-407c-a6f1-e747657185d6 · outbound

This paper cites Automated CVE Analysis for Threat Prioritization and Impact Prediction.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Automated CVE Analysis for Threat Prioritization and Impact Prediction

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:28.189040Z

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Observation bb1b0d52-1d4f-4cec-8629-687b4d7cd886 · outbound

This paper cites From Text to MITRE Techniques: Exploring the Malicious Use of Large Language Models for Generating Cyber Attack Payloads.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques From Text to MITRE Techniques: Exploring the Malicious Use of Large Language Models for Generating Cyber Attack Payloads

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:28.303875Z

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Observation e7486648-406f-4418-80a6-84f9da942163 · outbound

This paper cites Llms as hackers: Autonomous linux privilege escalation attacks,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Llms as hackers: Autonomous linux privilege escalation attacks,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:28.409615Z

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Observation 433f8aab-a193-4251-ad2d-65e8bf71229d · outbound

This paper cites PentestGPT: An LLM-empowered Automatic Penetration Testing Tool.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques PentestGPT: An LLM-empowered Automatic Penetration Testing Tool

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:28.584783Z

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Observation f84ed160-da98-44a3-a45e-ffd34583f64d · outbound

This paper cites XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:28.672841Z

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Observation 5734bf84-2498-478c-bedd-1ab4b2cacc84 · outbound

This paper cites Transformer-Based Language Models for Software Vulnerability Detection.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Transformer-Based Language Models for Software Vulnerability Detection

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:28.792203Z

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Observation 3ba98a77-e4f3-4c0b-8aeb-54fdb87972f6 · outbound

This paper cites LLMs Cannot Reliably Identify and Reason About Security Vulnerabilities (Yet?): A Comprehensive Evaluation, Framework, and Benchmarks.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques LLMs Cannot Reliably Identify and Reason About Security Vulnerabilities (Yet?): A Comprehensive Evaluation, Framework, and Benchmarks

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:28.904690Z

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Observation 9de5c68e-6e59-4fc8-b741-4efdde57682f · outbound

This paper cites Understanding the effectiveness of large language models in detecting security vulnerabilities,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Understanding the effectiveness of large language models in detecting security vulnerabilities,

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.047177Z

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Observation 06a7a531-a910-4f37-beba-c444c9d42168 · outbound

This paper cites Not the end of story: An evaluation of ChatGPT-driven vulnerability description mappings,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Not the end of story: An evaluation of ChatGPT-driven vulnerability description mappings,

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.321896Z

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Observation c103a05d-e794-4ebd-a470-f2ab9f768484 · outbound

This paper cites Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.165973Z

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Observation d7d80884-9021-4501-b489-581405fd11f5 · outbound

This paper cites Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.495638Z

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Observation 7353cf36-e5f6-4cfa-b05e-085098766ab0 · outbound

This paper cites Prompt-Enhanced Software Vulnerability Detection Using ChatGPT.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Prompt-Enhanced Software Vulnerability Detection Using ChatGPT

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.438850Z

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Observation e3120458-5156-4819-9819-4b3f9c8d80f6 · outbound

This paper cites Pre-trained Model-based Automated Software Vulnerability Repair: How Far are We?.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Pre-trained Model-based Automated Software Vulnerability Repair: How Far are We?

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.709375Z

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Observation 68b7277f-3c63-474e-9360-752a8ef86c1b · outbound

This paper cites Vulrepair: a t5-based automated software vulnerability repair,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Vulrepair: a t5-based automated software vulnerability repair,

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.541668Z

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Observation a5cb8429-d382-4e6e-8aa2-f14ee2f89192 · outbound

This paper cites How effective are neural networks for fixing security vulnerabilities,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques How effective are neural networks for fixing security vulnerabilities,

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.812846Z

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Observation 8c7a3e7e-e4e6-4925-8c24-1944605d8247 · outbound

This paper cites Examining Zero-Shot Vulnerability Repair with Large Language Models.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Examining Zero-Shot Vulnerability Repair with Large Language Models

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.807345Z

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Observation 2b445265-4911-4ebd-9490-3cccf57dd986 · outbound

This paper cites ZeroLeak: Using LLMs for Scalable and Cost Effective Side-Channel Patching.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques ZeroLeak: Using LLMs for Scalable and Cost Effective Side-Channel Patching

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.823142Z

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Observation 25a316f1-2846-4c56-b0d9-ee3ed1cf458b · outbound

This paper cites Can LLMs Patch Security Issues?.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Can LLMs Patch Security Issues?

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.817587Z

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Observation 4efcda72-2066-4ef0-a519-5220737de202 · outbound

This paper cites InferFix: End-to-End Program Repair with LLMs.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques InferFix: End-to-End Program Repair with LLMs

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.835596Z

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Observation d9821473-e7ca-4d7b-8393-9dedc84b91cd · outbound

This paper cites Dataset for : A new era in software security: Towards self-healing software via large language models and formal verification (version 1),.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Dataset for : A new era in software security: Towards self-healing software via large language models and formal verification (version 1),

Reference 79

Resolution: verified exact; doi, observed 2026-08-06T16:24:30.939681Z

Source-reported events for the cited work

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Observation 297b790e-7fee-48fa-bb9b-c8c94e483c5a · outbound

This paper cites A light bug triage framework for applying large pre-trained language model,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques A light bug triage framework for applying large pre-trained language model,

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.847374Z

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Observation fc7a5dd5-2199-42fc-bea0-d854f9f3a67b · outbound

This paper cites The Hitchhiker's Guide to Program Analysis: A Journey with Large Language Models.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques The Hitchhiker's Guide to Program Analysis: A Journey with Large Language Models

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.841631Z

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Observation 3d419354-e777-412b-9503-cae2b4b2e5be · outbound

This paper cites Nuances are the Key: Unlocking ChatGPT to Find Failure-Inducing Tests with Differential Prompting.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Nuances are the Key: Unlocking ChatGPT to Find Failure-Inducing Tests with Differential Prompting

Reference 82

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:24:33.927710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 03befc11-6b99-430d-a6d4-90269be9464a · outbound

This paper cites Large Language Models for Test-Free Fault Localization.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Large Language Models for Test-Free Fault Localization

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.854158Z

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Observation 6d91559d-f944-45ca-8c90-18f4ae182fdc · outbound

This paper cites Do users write more insecure code with ai assistants?.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Do users write more insecure code with ai assistants?

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.872563Z

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Observation 395b9793-4ef5-4859-8d74-d868c46138bb · outbound

This paper cites Representthemall: A universal learning representation of bug reports,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Representthemall: A universal learning representation of bug reports,

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.866411Z

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Observation 1e7204f8-9bf3-4dc1-876a-8b1d786a695a · outbound

This paper cites Copiloting the copilots: Fusing large language models with completion engines for automated program repair,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Copiloting the copilots: Fusing large language models with completion engines for automated program repair,

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.878633Z

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Observation 6d303592-1fd0-4fdd-ba48-0a7e87f0b871 · outbound

This paper cites Fuzzing: Challenges and reflections,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Fuzzing: Challenges and reflections,

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.897131Z

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Observation 42e16894-5dce-40fa-a3f4-c5a467643ef1 · outbound

This paper cites Conversational Automated Program Repair.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Conversational Automated Program Repair

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.890977Z

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Observation 66f31bec-8f34-4746-858a-7c086b906df5 · outbound

This paper cites How effective are they? exploring large language model based fuzz driver generation,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques How effective are they? exploring large language model based fuzz driver generation,

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.917318Z

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Observation 92c4387a-71f1-436d-b27c-fa7a54c801df · outbound

This paper cites Large language models are zero-shot fuzzers: Fuzzing deep-learning libraries via large language models,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Large language models are zero-shot fuzzers: Fuzzing deep-learning libraries via large language models,

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.904410Z

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Observation 318e7f33-cd22-4fa0-a10d-f9eff8ae224e · outbound

This paper cites Large language model- powered smart contract vulnerability detection: New perspectives,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Large language model- powered smart contract vulnerability detection: New perspectives,

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.929400Z

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Observation 6052081c-4a21-47e9-8ab6-2f69811beffe · outbound

This paper cites Whitefox: White-box compiler fuzzing empowered by large language models,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Whitefox: White-box compiler fuzzing empowered by large language models,

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.934500Z

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Observation 9fcb2cd6-c3e6-4ef4-b283-d9034425852e · outbound

This paper cites Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.922566Z

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Observation ddc11a02-f8f2-422d-8153-d6df20872519 · outbound

This paper cites SLaDe: A Portable Small Language Model Decompiler for Optimized Assembly.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques SLaDe: A Portable Small Language Model Decompiler for Optimized Assembly

Reference 95

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:24:33.489931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f9a7e624-663a-4b2e-bc5e-65475eb78654 · outbound

This paper cites DexBERT: Effective, Task-Agnostic and Fine-grained Representation Learning of Android Bytecode.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques DexBERT: Effective, Task-Agnostic and Fine-grained Representation Learning of Android Bytecode

Reference 96

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:24:33.466298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bda60ac3-0322-4e57-ab47-9a9ec06fcd32 · outbound

This paper cites Available: http://dx.doi.org/10.1145/3689736.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Available: http://dx.doi.org/10.1145/3689736

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.939624Z

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Observation 47ba4d92-26c2-453b-bed1-45b2887bc6b3 · outbound

This paper cites Symbol Preference Aware Generative Models for Recovering Variable Names from Stripped Binary.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Symbol Preference Aware Generative Models for Recovering Variable Names from Stripped Binary

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.948540Z

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Observation 1817e99c-791e-4114-b7d0-43a98c86761d · outbound

This paper cites Gpthreats-3: Is automatic malware generation a threat?.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Gpthreats-3: Is automatic malware generation a threat?

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.984957Z

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Observation 84d2eaa0-1c6c-4c8f-8992-8c5cd6c3dc8e · outbound

This paper cites A dynamic rule creation based anomaly detection method for identifying security breaches in log records,.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques A dynamic rule creation based anomaly detection method for identifying security breaches in log records,

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.990948Z

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Observation 51744cf0-f103-4ceb-99a1-171072c59279 · outbound

This paper cites Exploiting Code Symmetries for Learning Program Semantics.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Exploiting Code Symmetries for Learning Program Semantics

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.974167Z

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