AgenticSCR: An Autonomous Agentic Secure Code Review for Immature Vulnerabilities Detection

TL;DR

AgenticSCR is an autonomous AI system that improves pre-commit secure code review by effectively detecting and explaining immature vulnerabilities, outperforming traditional static analysis and LLM-based methods.

Contribution

This work introduces AgenticSCR, a novel autonomous AI approach combining LLMs with security-focused memories for immature vulnerability detection during pre-commit review.

Findings

AgenticSCR achieves 153% higher correct review comments than static LLM baselines.

It substantially surpasses SAST tools in detecting immature vulnerabilities.

It performs best in four out of five vulnerability types.

Abstract

Secure code review is critical at the pre-commit stage, where vulnerabilities must be caught early under tight latency and limited-context constraints. Existing SAST-based checks are noisy and often miss immature, context-dependent vulnerabilities, while standalone Large Language Models (LLMs) are constrained by context windows and lack explicit tool use. Agentic AI, which combine LLMs with autonomous decision-making, tool invocation, and code navigation, offer a promising alternative, but their effectiveness for pre-commit secure code review is not yet well understood. In this work, we introduce AgenticSCR, an agentic AI for secure code review for detecting immature vulnerabilities during the pre-commit stage, augmented by security-focused semantic memories. Using our own curated benchmark of immature vulnerabilities, tailored to the pre-commit secure code review, we empirically evaluate how accurate is our AgenticSCR for localizing, detecting, and explaining immature vulnerabilities. Our results show that AgenticSCR achieves at least 153% relatively higher percentage of correct code review comments than the static LLM-based baseline, and also substantially surpasses SAST tools. Moreover, AgenticSCR generates more correct comments in four out of five vulnerability types, consistently and significantly outperforming all other baselines. These findings highlight the importance of Agentic Secure Code Review, paving the way towards an emerging research area of immature vulnerability detection.