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With the rapid growth of research in trojaning deep neural models of sourcecode, we observe that there is a need of developing a benchmark trojaned modelsfor testing various trojan detection and unlearning techniques. In this work,we aim to provide the scientific community with diverse trojaned code models,that cover a variety of state-of-the-art architectures, on which they canexamine such techniques. We thus present TrojanedCM, a publicly availablerepository of clean and poisoned models of source code. We provide poisonedmodels for two code classification tasks (defect detection and clone detection)and a code generation task (text-to-code generation). We finetuned popularpretrained code models such as CodeBERT, PLBART, CodeT5, CodeT5+, on poisoneddatasets that we generated from benchmark datasets (Devign, BigCloneBench,CONCODE) for the above mentioned tasks. The repository also provides fullaccess to the architecture and parameters of the models, allowing practitionersto investigate different white-box analysis techniques. In addition to thepoisoned models, we also provide a poisoning framework using whichpractitioners can deploy various poisoning strategies for the different tasksand models of source code. All the material are accessible via this link:https://github.com/UH-SERG/TrojanedCM.

TrojanedCM: A Repository of Trojaned Large Language Models of Code