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Your Code Secret Belongs to Me: Neural Code Completion Tools Can Memorize Hard-Coded Credentials
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/j.1538-7305.1948.tb00917.xopenalex-snapshot
A Mathematical Theory of Communication
inferredcites →https://doi.org/10.1007/978-3-540-79228-4_1openalex-snapshot
Differential Privacy: A Survey of Results
inferredcites →https://doi.org/10.1109/apsec.2018.00040openalex-snapshot
An Empirical Study of SDK Credential Misuse in iOS Apps
inferredcites →https://doi.org/10.1109/ase56229.2023.00143openalex-snapshot
From Misuse to Mastery: Enhancing Code Generation with Knowledge-Driven AI Chaining
inferredcites →https://doi.org/10.1109/ase56229.2023.00193openalex-snapshot
CAT-LM Training Language Models on Aligned Code And Tests
inferredcites →https://doi.org/10.1109/comsnets48256.2020.9027350openalex-snapshot
Secrets in Source Code: Reducing False Positives using Machine Learning
inferredcites →https://doi.org/10.1109/csf.2018.00027openalex-snapshot
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting
inferredcites →https://doi.org/10.1109/cvpr41558.2019openalex-snapshot
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
inferredcites →https://doi.org/10.1109/icse48619.2023.00179openalex-snapshot
SkCoder: A Sketch-based Approach for Automatic Code Generation
inferredcites →https://doi.org/10.1109/icse48619.2023.00181openalex-snapshot
On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot
inferredcites →https://doi.org/10.1109/icse48619.2023.00207openalex-snapshot
ContraBERT: Enhancing Code Pre-trained Models via Contrastive Learning
inferredcites →https://doi.org/10.1109/intense59150.2023.00005openalex-snapshot
Study of Distractors in Neural Models of Code
inferredcites →https://doi.org/10.1109/intense59150.2023.00006openalex-snapshot
Probing Numeracy and Logic of Language Models of Code
inferredcites →https://doi.org/10.1109/msr.2013.6624029openalex-snapshot
Mining source code repositories at massive scale using language modeling
inferredcites →https://doi.org/10.1109/nlbse59153.2023.00008openalex-snapshot
The (ab)use of Open Source Code to Train Large Language Models
inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot
Membership Inference Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1109/sp46214.2022.9833571openalex-snapshot
Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions
inferredcites →https://doi.org/10.1109/sp46215.2023.10179300openalex-snapshot
Analyzing Leakage of Personally Identifiable Information in Language Models
inferredcites →https://doi.org/10.1145/2591971.2592003openalex-snapshot
A measurement study of google play
inferredcites →https://doi.org/10.1145/2766498.2766499openalex-snapshot
Harvesting developer credentials in Android apps
inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot
Deep Learning with Differential Privacy
inferredcites →https://doi.org/10.1145/2983990.2984041openalex-snapshot
Probabilistic model for code with decision trees
inferredcites →https://doi.org/10.1145/3368089.3417058openalex-snapshot
IntelliCode compose: code generation using transformer
inferredcites →https://doi.org/10.1145/3372297.3417880openalex-snapshot
Analyzing Information Leakage of Updates to Natural Language Models
inferredcites →https://doi.org/10.1145/3510003.3510150openalex-snapshot
Automated detection of password leakage from public GitHub repositories
inferredcites →https://doi.org/10.1145/3520312.3534862openalex-snapshot
A systematic evaluation of large language models of code
inferredcites →https://doi.org/10.1145/3540250.3549113openalex-snapshot
No more fine-tuning? an experimental evaluation of prompt tuning in code intelligence
inferredcites →https://doi.org/10.1145/3540250.3549162openalex-snapshot
NatGen: generative pre-training by “naturalizing” source code
inferredcites →https://doi.org/10.1145/3597926.3598036openalex-snapshot
Towards Efficient Fine-Tuning of Pre-trained Code Models: An Experimental Study and Beyond
inferredcites →https://doi.org/10.14722/ndss.2019.23418openalex-snapshot
How Bad Can It Git? Characterizing Secret Leakage in Public GitHub Repositories
inferredcites →https://doi.org/10.24963/ijcai.2023openalex-snapshot
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence
inferredcites →https://doi.org/10.5281/zenodo.5297715openalex-snapshot
GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Automatically Detecting Checked-In Secrets in Android Apps: How Far Are We?
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New frontiers in large code language model security: a review of emerging adversarial threats and countermeasures
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Model-Agnostic Empirical Evaluation of Test-Driven Prompt Engineering on Improving Accuracy and Efficiency in Large Language Models Python Code Generation
inferred← citeshttps://doi.org/10.1109/aiware69974.2025.00013openalex-snapshot
How Does Quantization Impact Privacy Risk on LLMS for Code?
inferred← citeshttps://doi.org/10.1109/ase63991.2025.00191openalex-snapshot
Effective Code Membership Inference for Code Completion Models via Adversarial Prompts
inferred← citeshttps://doi.org/10.1109/icoeins69996.2026.11605523openalex-snapshot
Addressing Dynamic and Socio-Technical Privacy Risks: A Position Paper on System Dynamics for Privacy-Risk Assessment
inferred← citeshttps://doi.org/10.1109/icse-nier66352.2025.00017openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icse55347.2025.00103openalex-snapshot
LibreLog: Accurate and Efficient Unsupervised Log Parsing Using Open-Source Large Language Models
inferred← citeshttps://doi.org/10.1109/icse55347.2025.00229openalex-snapshot
Decoding Secret Memorization in Code LLMs Through Token-Level Characterization
inferred← citeshttps://doi.org/10.1109/saner-c66551.2025.00016openalex-snapshot
Malicious and Unintentional Disclosure Risks in Large Language Models for Code Generation
inferred← citeshttps://doi.org/10.1109/saner60148.2024.00051openalex-snapshot
Assessing the Security of GitHub Copilot's Generated Code - A Targeted Replication Study
inferred← citeshttps://doi.org/10.1109/sp61157.2025.00009openalex-snapshot
The File That Contained the Keys Has Been Removed: An Empirical Analysis of Secret Leaks in Cloud Buckets and Responsible Disclosure Outcomes
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KeyChaser: Unveiling API Keys in Browser Extensions
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inferred← citeshttps://doi.org/10.1145/3691620.3695021openalex-snapshot
Promise and Peril of Collaborative Code Generation Models: Balancing Effectiveness and Memorization
inferred← citeshttps://doi.org/10.1145/3691620.3695503openalex-snapshot
Contextualized Data-Wrangling Code Generation in Computational Notebooks
inferred← citeshttps://doi.org/10.1145/3696630.3731473openalex-snapshot
Towards Privacy-Preserving Code Generation: Understanding and Mitigating Memorization in Code Large Language Models
inferred← citeshttps://doi.org/10.1145/3708525openalex-snapshot
Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead
inferred← citeshttps://doi.org/10.1145/3715784openalex-snapshot
Detecting and Reducing the Factual Hallucinations of Large Language Models with Metamorphic Testing
inferred← citeshttps://doi.org/10.1145/3719027.3765033openalex-snapshot
Leaky Apps: Large-scale Analysis of Secrets Distributed in Android and iOS Apps
inferred← citeshttps://doi.org/10.1145/3719027.3765065openalex-snapshot
It Should Be Easy but... New Users' Experiences and Challenges with Secret Management Tools
inferred← citeshttps://doi.org/10.1145/3729397openalex-snapshot
An Empirical Study of Code Clones from Commercial AI Code Generators
inferred← citeshttps://doi.org/10.1145/3748647openalex-snapshot
Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey
inferred← citeshttps://doi.org/10.1145/3796239openalex-snapshot
Unsupervised, Accurate, and Efficient Log Parsing Using Smaller Open Source Large Language Models
inferred← citeshttps://doi.org/10.3389/fdata.2024.1386720openalex-snapshot
A systematic literature review on the impact of AI models on the security of code generation
inferred← citeshttps://doi.org/10.70315/uloap.ulirs.2026.0301009openalex-snapshot
Accelerating Mobile Application Development and Testing with Artificial Intelligence: A Systematic Literature Review
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