MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202611101717 A) filed by Panipat Institute Of Engineering And Technology Piet on August 22, 2026, for System And Method For Ai-Driven Source Code Vulnerability Detection Using Contextual Program Flow Analysis.
Inventors include Anju Arya; Neha Tuteja; and Shruti Jindal.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: [051] The present invention discloses a system and method for AI-driven source code vulnerability detection using contextual program flow analysis. Source code, dependency information, and software artifacts are collected and transformed into unified semantic representations preserving execution behavior. Integrated contextual execution graphs comprising control flow, data flow, dependency, and call relationships are generated for comprehensive software understanding. Artificial intelligence models including graph neural networks, transformer-based semantic reasoning engines, probabilistic inference mechanisms, and contextual vulnerability classifiers analyze execution behavior to identify security weaknesses across complete program flows. A vulnerability inference engine correlates contextual evidence with vulnerability knowledge bases and assigns confidence scores, severity rankings, and remediation recommendations. An explainable security analysis module generates execution traces supporting detected vulnerabilities while providing developer guidance for secure code correction. The invention integrates with continuous software development pipelines, supports multiple programming languages, reduces false positives, improves contextual vulnerability detection accuracy, and enables adaptive learning through continuous developer feedback, thereby providing an intelligent and scalable software security assessment framework. Accompanied Drawing [FIGS. 1-2]
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