Awesome Vulnerability Detection

Key papers

• Vuldeepecker: A Deep Learning-based System For Vulnerability Detection (2018)
  Zhen Li, Deqing Zou, Shouhuai Xu, et al.
  21.76
• Adversarial Malware Binaries: Evading Deep Learning For Malware Detection In Executables (2018)
  Bojan Kolosnjaji, Ambra Demontis, Battista Biggio, et al.
  17.71
• Diversevul: A New Vulnerable Source Code Dataset For Deep Learning Based Vulnerability Detection (2023)
  Yizheng Chen, Zhoujie Ding, Lamya Alowain, et al.
  16.95
• Bayesian Optimization With Machine Learning Algorithms Towards Anomaly Detection (2020)
  Mohammadnoor Injadat, Fadi Salo, Ali Bou Nassif, et al.
  15.67
• An Empirical Study Of Deep Learning Models For Vulnerability Detection (2022)
  Benjamin Steenhoek, Md Mahbubur Rahman, Richard Jiles, et al.
  15.13
• Predicting Exploitation Of Disclosed Software Vulnerabilities Using Open-source Data (2017)
  Benjamin L. Bullough, Anna K. Yanchenko, Christopher L. Smith, et al.
  13.74
• Security Vulnerability Detection Using Deep Learning Natural Language Processing (2021)
  Noah Ziems, Shaoen Wu
  13.55
• Redundancy Coefficient Gradual Up-weighting-based Mutual Information Feature Selection Technique For Crypto-ransomware Early Detection (2018)
  Bander Ali Saleh Al-Rimy, Mohd Aizaini Maarof, Syed Zainudeen Mohd Shaid
  12.99
• Llms In Software Security: A Survey Of Vulnerability Detection Techniques And Insights (2025)
  Ze Sheng, Zhicheng Chen, Shuning Gu, et al.
  11.54
• Poisonprompt: Backdoor Attack On Prompt-based Large Language Models (2023)
  Hongwei Yao, Jian Lou, Zhan Qin
  11.19
• Trojanpuzzle: Covertly Poisoning Code-suggestion Models (2023)
  Hojjat Aghakhani, Wei Dai, Andre Manoel, et al.
  10.97
• Securefalcon: Are We There Yet In Automated Software Vulnerability Detection With Llms? (2023)
  Mohamed Amine Ferrag, Ammar Battah, Norbert Tihanyi, et al.
  10.97
• Enhancing Threat Detection Using Artificial Intelligence in Modern Cybersecurity Systems Using SPSS Statistics (2026)
  Rajendar Dommeti
  10.82
• Challenging Machine Learning Algorithms In Predicting Vulnerable Javascript Functions (2024)
  Rudolf Ferenc, Péter Hegedűs, Péter Gyimesi, et al.
  10.61
• Transfer Learning In Pre-trained Large Language Models For Malware Detection Based On System Calls (2024)
  Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Gérôme Bovet, et al.
  10.48
• Multi-target Backdoor Attacks For Code Pre-trained Models (2023)
  Yanzhou Li, Shangqing Liu, Kangjie Chen, et al.
  9.59
• Anomaly Detection For Scenario-based Insider Activities Using CGAN Augmented Data (2021)
  R G Gayathri, Atul Sajjanhar, Yong Xiang, et al.
  9.03
• Backdooring Neural Code Search (2023)
  Weisong Sun, Yuchen Chen, Guanhong Tao, et al.
  8.82
• Nlp-based Cross-layer 5G Vulnerabilities Detection Via Fuzzing Generated Run-time Profiling (2023)
  Zhuzhu Wang, Ying Wang
  7.81
• An Unbiased Transformer Source Code Learning With Semantic Vulnerability Graph (2023)
  Nafis Tanveer Islam, Gonzalo de La Torre Parra, Dylan Manuel, et al.
  7.50
• Phishguard: A Multi-layered Ensemble Model For Optimal Phishing Website Detection (2024)
  Md Sultanul Islam Ovi, Md. Hasibur Rahman, Mohammad Arif Hossain
  7.50
• MANDERA: Malicious Node Detection in Federated Learning via Ranking (2021)
  Wanchuang Zhu et al.
  7.16
• Feasibility Study For Supporting Static Malware Analysis Using LLM (2024)
  Shota Fujii, Rei Yamagishi
  7.16
• A Hierarchical Deep Neural Network For Detecting Lines Of Codes With Vulnerabilities (2022)
  Arash Mahyari
  7.16
• Leveraging Large Language Models To Detect Npm Malicious Packages (2024)
  Nusrat Zahan, Philipp Burckhardt, Mikola Lysenko, et al.
  7.16
• Models Are Codes: Towards Measuring Malicious Code Poisoning Attacks On Pre-trained Model Hubs (2024)
  Jian Zhao, Shenao Wang, Yanjie Zhao, et al.
  7.16
• Multi-instance Adversarial Attack On Gnn-based Malicious Domain Detection (2023)
  Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah, et al.
  6.77
• Genxss: An Ai-driven Framework For Automated Detection Of XSS Attacks In Wafs (2025)
  Vahid Babaey, Arun Ravindran
  6.64
• Leveraging Large Language Models And Machine Learning For Smart Contract Vulnerability Detection (2025)
  S M Mostaq Hossain, Amani Altarawneh, Jesse Roberts
  6.64
• Large Language Models For In-file Vulnerability Localization Can Be "lost In The End" (2025)
  Francesco Sovrano, Adam Bauer, Alberto Bacchelli
  6.39
• Vulscriber: Exploring Rag-based Vulnerability Augmentation With Llms (2024)
  Seyed Shayan Daneshvar, Yu Nong, Xu Yang, et al.
  6.34
• Mitigating Adversarial Vulnerability Through Causal Parameter Estimation By Adversarial Double Machine Learning (2023)
  Byung-Kwan Lee, Junho Kim, Yong Man Ro
  6.34
• P3GNN: A Privacy-preserving Provenance Graph-based Model For APT Detection In Software Defined Networking (2024)
  Hedyeh Nazari, Abbas Yazdinejad, Ali Dehghantanha, et al.
  6.34
• FDI: Attack Neural Code Generation Systems Through User Feedback Channel (2024)
  Zhensu Sun, Xiaoning Du, Xiapu Luo, et al.
  6.34
• Eliminating Backdoors In Neural Code Models For Secure Code Understanding (2024)
  Weisong Sun, Yuchen Chen, Chunrong Fang, et al.
  5.84
• Automatically Generating Rules Of Malicious Software Packages Via Large Language Model (2025)
  Xiangrui Zhang, Haoyu Chen, Yongzhong He, et al.
  5.82
• A Sample-Based, Multistage Machine Learning Pipeline for Scalable IoT Threat Detection (2026)
  Marcelo V. C. Aragão et al.
  5.58
• Leveraging LLM To Strengthen Ml-based Cross-site Scripting Detection (2025)
  Dennis Miczek, Divyesh Gabbireddy, Suman Saha
  5.46
• Toward Malicious Clients Detection in Federated Learning (2025)
  Zhihao Dou et al.
  5.40
• ML-FEED: Machine Learning Framework For Efficient Exploit Detection (2023)
  Tanujay Saha, Tamjid Al-Rahat, Najwa Aaraj, et al.
  5.24
• Fine-tuning Large Language Models For DGA And DNS Exfiltration Detection (2024)
  Md Abu Sayed, Asif Rahman, Christopher Kiekintveld, et al.
  5.24
• Backdoorbench: A Comprehensive Benchmark And Analysis Of Backdoor Learning (2024)
  Baoyuan Wu, Hongrui Chen, Mingda Zhang, et al.
  5.24
• IRIS: Llm-assisted Static Analysis For Detecting Security Vulnerabilities (2024)
  Ziyang Li, Saikat Dutta, Mayur Naik
  5.13
• A Defensive Framework Against Adversarial Attacks On Machine Learning-based Network Intrusion Detection Systems (2025)
  Benyamin Tafreshian, Shengzhi Zhang
  5.04
• Securing Code Understanding: Detecting Natural Backdoor Vulnerability in Code Language Models (2026)
  Yuchen Chen et al.
  5.01
• Comparative Analysis of Inference-Time Defense Methods for Multimodal Large Language Models (2026)
  Bulat Nutfullin et al.
  5.01
• Do Transformers Actually Help Intrusion Detection? A Temporal Sequence Evaluation on CIC-IDS2017 (2026)
  Zach Moczkodan (Royal Military College of Canada et al.
  5.01
• MAStrike: Shapley-Guided Collusive Red-Teaming on Multi-Agent Systems (2026)
  Chejian Xu et al.
  5.01
• Backdoorllm: A Comprehensive Benchmark For Backdoor Attacks And Defenses On Large Language Models (2024)
  Yige Li, Hanxun Huang, Yunhan Zhao, et al.
  4.95
• MalDataGen: A Modular Framework for Synthetic Tabular Data Generation in Malware Detection (2025)
  Kayua Oleques Paim and Angelo Gaspar Diniz Nogueira and Diego Kreutz and Weverton Cordeiro and Rodrigo Brandao Mansilha
  4.80
• Can Indirect Prompt Injection Attacks Be Detected And Removed? (2025)
  Yulin Chen, Haoran Li, Yuan Sui, et al.
  4.53
• VISION: Robust And Interpretable Code Vulnerability Detection Leveraging Counterfactual Augmentation (2025)
  David Egea, Barproda Halder, Sanghamitra Dutta
  4.53
• Detecting Code Vulnerabilities With Heterogeneous GNN Training (2025)
  Yu Luo, Weifeng Xu, Dianxiang Xu
  4.53
• Robust Intrusion Detection System With Explainable Artificial Intelligence (2025)
  Betül Güvenç Paltun, Ramin Fuladi, Rim El Malki
  4.53
• Show Me Your Code! Kill Code Poisoning: A Lightweight Method Based On Code Naturalness (2025)
  Weisong Sun, Yuchen Chen, Mengzhe Yuan, et al.
  4.53
• Level Up With ML Vulnerability Identification: Leveraging Domain Constraints In Feature Space For Robust Android Malware Detection (2022)
  Hamid Bostani, Zhengyu Zhao, Zhuoran Liu, et al.
  4.52
• Peftguard: Detecting Backdoor Attacks Against Parameter-efficient Fine-tuning (2024)
  Zhen Sun, Tianshuo Cong, Yule Liu, et al.
  4.52
• Boosting Vulnerability Detection Of Llms Via Curriculum Preference Optimization With Synthetic Reasoning Data (2025)
  Xin-Cheng Wen, Yijun Yang, Cuiyun Gao, et al.
  4.51
• Iron Sharpens Iron: Defending Against Attacks In Machine-generated Text Detection With Adversarial Training (2025)
  Yuanfan Li, Zhaohan Zhang, Chengzhengxu Li, et al.
  4.46
• Toward a Generalized Defense Across Sparse, Continuous, and Structured Parameter Attacks (2026)
  Bin Duan et al.
  4.39