[ AutoFiC ] Security Patch 2025-07-28 #19
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Security Fixes Suggested via Pull Request – Powered by Autofic 🛠️ Dear Esteemed Developer, My name is Jeongmin Oh, an undergraduate student majoring in Information Security at Gachon University 🇰🇷. I'm currently participating in a university project focused on enhancing software security using a combination of static analysis (SAST) and large language models (LLMs). As part of this initiative, we developed a tool called Autofic, which analyzes public code repositories to detect security vulnerabilities using SAST tools and then generates suggested fixes with the support of LLMs. 🔐 During a recent analysis of your repository, our system identified a few areas that may pose security risks. To assist in addressing them, we have submitted a Pull Request containing proposed patches automatically generated by Autofic. Since this work is part of an academic research project, your review and potential approval would be immensely valuable to us. 🙏 If you have any questions or would like to learn more about how Autofic works, please don’t hesitate to reach out. Thank you for your time and for your valuable contribution to the open-source community. Best regards, |
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🔧 About This Pull Request
This patch was automatically created by AutoFiC ,
an open-source framework that combines static analysis tools with AI-driven remediation.
Using Semgrep, CodeQL, and Snyk Code, AutoFiC detected potential security flaws and applied verified fixes.
Each patch includes contextual explanations powered by a large language model to support review and decision-making.
🔐 Summary of Security Fixes
Overview
server/app.jsserver/util/util.jsserver/database.jsserver/routes/backend.jsserver/routes/frontend.jsserver/routes/users.js1.
server/app.js🧩 SAST Analysis Summary
📝 LLM Analysis
🔸 Vulnerability Description
The application leaks error information to the client, which can disclose sensitive information about the server. Additionally, the
X-Powered-Byheader is enabled, which reveals the use of Express, potentially aiding attackers in crafting specific attacks.🔸 Recommended Fix
Handle errors without exposing sensitive information and disable the
X-Powered-Byheader using the Helmet middleware.🔸 Additional Notes
Consider using the Helmet middleware for additional security enhancements, such as setting various HTTP headers to protect the app from well-known web vulnerabilities.
2.
server/util/util.js🧩 SAST Analysis Summary
📝 LLM Analysis
🔸 Vulnerability Description
The code contains two vulnerabilities: a hardcoded secret key used in the
jsonwebtoken.signfunction and the use of an insecure hashing algorithm (md5) in thecrypto.createHashfunction.🔸 Recommended Fix
md5hashing algorithm with a more secure algorithm likesha256.🔸 Additional Notes
The secret key for JWT should ideally be stored in an environment variable or a secure configuration file, rather than being generated at runtime. This change is made here for demonstration purposes, and a more secure method of key management should be implemented in a production environment.
3.
server/database.js🧩 SAST Analysis Summary
📝 LLM Analysis
🔸 Vulnerability Description
The code contains hardcoded credentials for connecting to a MySQL database. This includes the database host, user, and password, which are directly embedded in the source code.
🔸 Recommended Fix
Use environment variables to store sensitive information like database credentials. This will prevent hardcoding credentials directly in the source code.
🔸 Additional Notes
Ensure that the environment variables (
DB_HOST,DB_USER,DB_PASSWORD,DB_PORT) are set in your environment where this script is executed. This approach enhances security by keeping sensitive information out of the source code.4.
server/routes/backend.js🧩 SAST Analysis Summary
📝 LLM Analysis
🔸 Vulnerability Description
The code is vulnerable to SQL Injection due to unsanitized input from HTTP parameters and request bodies being directly used in SQL queries.
🔸 Recommended Fix
Use parameterized queries or prepared statements to safely include user input in SQL queries, preventing SQL Injection.
🔸 Additional Notes
The changes involve using parameterized queries by passing the user inputs as parameters to the
db.Queryfunction. This helps in preventing SQL Injection by ensuring that user inputs are safely included in SQL queries.5.
server/routes/frontend.js🧩 SAST Analysis Summary
📝 LLM Analysis
🔸 Vulnerability Description
The code contains SQL Injection vulnerabilities due to unsanitized input from HTTP parameters and request bodies being directly used in SQL queries.
🔸 Recommended Fix
Use parameterized queries or prepared statements to ensure that user inputs are properly sanitized before being included in SQL queries.
🔸 Additional Notes
The changes involve using parameterized queries by passing parameters as an array to the
db.Querymethod, which helps prevent SQL injection by ensuring that inputs are properly escaped.6.
server/routes/users.js🧩 SAST Analysis Summary
📝 LLM Analysis
🔸 Vulnerability Description
The code is vulnerable to SQL Injection because it directly uses user input in SQL queries without proper sanitization or parameterization.
🔸 Recommended Fix
Use parameterized queries or prepared statements to safely include user input in SQL queries, preventing SQL injection attacks.
🔸 Additional Notes
Ensure that the
db.Querymethod supports parameterized queries. If not, you may need to refactor the database interaction layer to support them. Additionally, always validate and sanitize user inputs as an extra layer of security.🛠 Fix Summary
All identified vulnerabilities have been remediated following security best practices such as parameterized queries and proper input validation. Please refer to the diff tab for detailed code changes.
If you have questions or feedback regarding this automated patch, feel free to reach out via AutoFiC GitHub.