VulStyle: A Multi-Modal Pre-Training for Code Stylometry-Augmented Vulnerability Detection
We present VulStyle, a multi-modal software vulnerability detection model that jointly encodes function-level source code, non-terminal Abstract Syntax Tree (AST) structure, and code stylometry (CStyle) features. Prior work in code representation primarily leverages token-level models or full AST trees, often missing stylistic cues indicative of risky programming practices, or incurring high structural overhead. Our approach selects only non-terminal AST nodes, reducing input complexity while preserving semantic hierarchy, and integrates syntactic and lexical CStyle features as auxiliary vulnerability signals. VulStyle is pre-trained using masked language modeling on 4.9M functions across...
| Authors | Chidera Biringa, Ajmal Abbas, Vishnu Selvaraj et al. |
|---|---|
| Primary category | cs.CR |
| Published | 29 April 2026 |
| Last updated at source | 29 April 2026 |
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