This invention discloses a
source code security analysis and
vulnerability verification system based on an AI-powered automated detection engine, relating to the field of
application security. The
system includes a candidate
vulnerability extraction module, a decompilation and path extraction module, an AI-powered judgment module, a sensitive data de-identification module, an interface reasoning module, a
verification request construction module, an
active detection module, and a multi-dimensional judgment module. These modules work collaboratively, relying on the AI-powered automated detection engine to construct a
fully automated closed loop. The AI-powered judgment module uses a large
language model with code understanding, semantic reasoning, and
text generation capabilities as its core reasoning unit, deeply participating in the entire process of
source code security analysis and
vulnerability verification. Combined with functions such as
JAR decompilation, path extraction, sensitive data de-identification, and multi-dimensional evidence constraints, it achieves automated verification from candidate risks to real vulnerabilities. This
system solves the problems of high false positives, reliance on manual labor, and low
automation in traditional code auditing. It possesses advantages such as high accuracy, high
automation, wide applicability, and
data security compliance, upgrading traditional code detection into a highly reliable and automated
source code security analysis and vulnerability
verification system, meeting the current technical needs of the source code security detection field. This invention also discloses the method and
computer configuration applied to this system.