ThreatDetect-C-Cpp

Model Card for ThreatDetect-C-Cpp

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This is a derivative version of answerdotai/ModernBERT-base. <br> We fine-tuned ModernBERT-base to detect vulnerability in C/C++ Code. <br> The actual version has an accuracy of 86% <br>

Model Details

Model Description

ThreatDetect-C-Cpp can be used as a code classifier. <br> Instead of binary classification ("safe", "unsafe"), The model classifies the input code into 7 labels: 'safe' (no vulnerability detected) and six other CWE weaknesses:

• Developed by: lemon42-ai
• Contributers Abdellah Oumida & Mohammed Sbaihi
• Model type: ModernBERT, Encoder-only Transformer
• Supported Programming Languages: C/C++
• License: Apache 2.0 (see original License of ModernBERT-Base)
• Finetuned from model: answerdotai/ModernBERT-base.

Model Sources [optional]

• Repository: The official lemon42-ai Github repository
• Technical Blog Post: Coming soon.

Uses

ThreadDetect-C-Cpp can be integrated in code-related applications. For example, it can be used in pair with a code generator to detect vulnerabilities in the generated code.

Bias, Risks, and Limitations

ThreadDetect-C-Cpp can detect weaknesses in C/C++ code only. It should not be used with other programming languages.<br> The model can only detect the six CWEs in the table above.

Training Details

Training Data

The model was fine-tuned on a minified, clean and deduplicated version of DiverseVul dataset. <br> This new version can be explored on HF datasets HERE

Training Procedure

The model was trained using LoRA applied to Q and V matrices.

Training Hyperparameters

Evaluation

ThreatDetect-C-Cpp reaches an accruacy of 86% on the eval set.

Technical Specifications

Hardware

The model was fine-tuned on 4 Tesla V100 GPUs for 1 hour using torch + accelerate frameworks.