You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion

5 July 2020

Papers citing "You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion"

36 / 36 papers shown

Title
SandboxEval: Towards Securing Test Environment for Untrusted Code Rafiqul Rabin Jesse Hostetler Sean McGregor Brett Weir Nick Judd ELM 41 0 0 27 Mar 2025
VeriLeaky: Navigating IP Protection vs Utility in Fine-Tuning for LLM-Driven Verilog Coding Zeng Wang Minghao Shao M. Nabeel P. Roy Likhitha Mankali Jitendra Bhandari Ramesh Karri Ozgur Sinanoglu Muhammad Shafique J. Knechtel 70 0 0 17 Mar 2025
Poisoned Source Code Detection in Code Models Ehab Ghannoum Mohammad Ghafari AAML 65 0 0 19 Feb 2025
Timber! Poisoning Decision Trees Stefano Calzavara Lorenzo Cazzaro Massimo Vettori AAML 30 0 0 01 Oct 2024
Learning Program Behavioral Models from Synthesized Input-Output Pairs Tural Mammadov Dietrich Klakow Alexander Koller Andreas Zeller 45 3 0 11 Jul 2024
An LLM-Assisted Easy-to-Trigger Backdoor Attack on Code Completion Models: Injecting Disguised Vulnerabilities against Strong Detection Shenao Yan Shen Wang Yue Duan Hanbin Hong Kiho Lee Doowon Kim Yuan Hong AAML SILM 43 17 0 10 Jun 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 31 16 0 02 Feb 2024
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit Yao Wan Yang He Zhangqian Bi Jianguo Zhang Hongyu Zhang Yulei Sui Guandong Xu Hai Jin Philip S. Yu 35 20 0 30 Dec 2023
Explaining high-dimensional text classifiers Odelia Melamed Rich Caruana 23 0 0 22 Nov 2023
An Empirical Study of AI Generated Text Detection Tools Arslan Akram DeLMO 34 29 0 27 Sep 2023
Trustworthy and Synergistic Artificial Intelligence for Software Engineering: Vision and Roadmaps David Lo 34 39 0 08 Sep 2023
On the Exploitability of Instruction Tuning Manli Shu Jiong Wang Chen Zhu Jonas Geiping Chaowei Xiao Tom Goldstein SILM 33 91 0 28 Jun 2023
Poisoning Web-Scale Training Datasets is Practical Nicholas Carlini Matthew Jagielski Christopher A. Choquette-Choo Daniel Paleka Will Pearce Hyrum S. Anderson Andreas Terzis Kurt Thomas Florian Tramèr SILM 31 182 0 20 Feb 2023
Backdoor Learning for NLP: Recent Advances, Challenges, and Future Research Directions Marwan Omar SILM AAML 33 20 0 14 Feb 2023
AI vs. Human -- Differentiation Analysis of Scientific Content Generation Yongqiang Ma Jiawei Liu Fan Yi Qikai Cheng Yong Huang Wei Lu Xiaozhong Liu DeLMO 4 56 0 24 Jan 2023
TrojanPuzzle: Covertly Poisoning Code-Suggestion Models H. Aghakhani Wei Dai Andre Manoel Xavier Fernandes Anant Kharkar Christopher Kruegel Giovanni Vigna David E. Evans B. Zorn Robert Sim SILM 23 33 0 06 Jan 2023
Backdoor Attacks Against Dataset Distillation Yugeng Liu Zheng Li Michael Backes Yun Shen Yang Zhang DD 42 28 0 03 Jan 2023
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice Giovanni Apruzzese Hyrum S. Anderson Savino Dambra D. Freeman Fabio Pierazzi Kevin A. Roundy AAML 31 75 0 29 Dec 2022
Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods Evan Crothers Nathalie Japkowicz H. Viktor DeLMO 38 107 0 13 Oct 2022
On the Robustness of Random Forest Against Untargeted Data Poisoning: An Ensemble-Based Approach M. Anisetti C. Ardagna Alessandro Balestrucci Nicola Bena Ernesto Damiani C. Yeun AAML OOD 32 10 0 28 Sep 2022
Don't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems Zhensu Sun Xiaoning Du Fu Song Shangwen Wang Mingze Ni Li Li 26 10 0 13 Sep 2022
PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning Hongbin Liu Jinyuan Jia Neil Zhenqiang Gong 25 34 0 13 May 2022
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets Florian Tramèr Reza Shokri Ayrton San Joaquin Hoang Minh Le Matthew Jagielski Sanghyun Hong Nicholas Carlini MIACV 38 107 0 31 Mar 2022
Spinning Language Models: Risks of Propaganda-As-A-Service and Countermeasures Eugene Bagdasaryan Vitaly Shmatikov SILM AAML 27 76 0 09 Dec 2021
A Survey on Machine Learning Techniques for Source Code Analysis Tushar Sharma M. Kechagia Stefanos Georgiou Rohit Tiwari Indira Vats Hadi Moazen Federica Sarro 25 61 0 18 Oct 2021
Spinning Sequence-to-Sequence Models with Meta-Backdoors Eugene Bagdasaryan Vitaly Shmatikov SILM AAML 38 8 0 22 Jul 2021
Evaluating Large Language Models Trained on Code Mark Chen Jerry Tworek Heewoo Jun Qiming Yuan Henrique Pondé ... Bob McGrew Dario Amodei Sam McCandlish Ilya Sutskever Wojciech Zaremba ELM ALM 78 5,082 0 07 Jul 2021
Programming Puzzles Tal Schuster Ashwin Kalyan Oleksandr Polozov Adam Tauman Kalai ELM 17 32 0 10 Jun 2021
Poisoning the Unlabeled Dataset of Semi-Supervised Learning Nicholas Carlini AAML 149 68 0 04 May 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 21 51 0 08 Feb 2021
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses Micah Goldblum Dimitris Tsipras Chulin Xie Xinyun Chen Avi Schwarzschild D. Song A. Madry Bo-wen Li Tom Goldstein SILM 27 270 0 18 Dec 2020
Concealed Data Poisoning Attacks on NLP Models Eric Wallace Tony Zhao Shi Feng Sameer Singh SILM 19 18 0 23 Oct 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 34 79 0 17 Sep 2020
Backdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review Yansong Gao Bao Gia Doan Zhi-Li Zhang Siqi Ma Jiliang Zhang Anmin Fu Surya Nepal Hyoungshick Kim AAML 36 220 0 21 Jul 2020
Model-Reuse Attacks on Deep Learning Systems Yujie Ji Xinyang Zhang S. Ji Xiapu Luo Ting Wang SILM AAML 134 186 0 02 Dec 2018
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 168 287 0 02 Dec 2018