# Secure coding for web applications: Frameworks, challenges, and the role of LLMs

arXiv: https://arxiv.org/abs/2507.22223 · HTML: https://mlsanity.com/paper/2507.22223/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jul 2025.

## Built on by (most cited first, 3 of 3)

- [LLM-Driven Adaptive 6G-Ready Wireless Body Area Networks: Survey and Framework](https://mlsanity.com/paper/2508.08535/) (2025)
- [LLM-Generated Counterfactual Stress Scenarios for Portfolio Risk Simulation via Hybrid Prompt-RAG Pipeline](https://mlsanity.com/paper/2512.07867/) (2025)
- [The Illusion of Secure LLM Code: Closing the Security Gap via Iterative Reprompting](https://mlsanity.com/paper/2607.23710/) (2026)

## Abstract (arXiv)

Secure coding is a critical yet often overlooked practice in software development. Despite extensive awareness efforts, real-world adoption remains inconsistent due to organizational, educational, and technical barriers. This paper provides a comprehensive review of secure coding practices across major frameworks and domains, including web development, DevSecOps, and cloud security. It introduces a structured framework comparison and categorizes threats aligned with the OWASP Top 10. Additionally, we explore the rising role of Large Language Models (LLMs) in evaluating and recommending secure code, presenting a reproducible case study across four major vulnerability types. This paper offers practical insights for researchers, developers, and educators on integrating secure coding into real-world development processes.