Code Security Report: High Severity Findings & Remediation

This code security report delves into the findings of a static application security testing (SAST) scan conducted on the SAST-UP-DP-DEV-env repository. The scan, executed on November 27, 2025, at 10:56 PM, revealed a total of 11 findings, all of which are new. This report highlights the most relevant vulnerabilities, focusing on their severity, type, and potential remediation strategies. Understanding and addressing these findings is crucial for maintaining the security and integrity of the codebase.

Scan Metadata: A Snapshot of the Security Assessment

Understanding the scan metadata provides context for the findings. The latest scan was performed on 2025-11-27 10:56 PM, identifying a total of 11 findings. All 11 findings are new, indicating a fresh set of vulnerabilities that require attention. The scan covered 117 tested project files, demonstrating a thorough assessment of the codebase. Furthermore, the scan detected 3 programming languages: JavaScript / TypeScript, Python, and Secrets. This multi-language detection capability ensures a comprehensive security analysis across different parts of the project.

Delving into the Most Relevant Findings

The report identifies the 10 most relevant findings that demand immediate attention. Notably, automatic remediation is available for 3 of these findings, streamlining the process of fixing critical issues. These findings are presented in a detailed table, providing a clear overview of each vulnerability.

Let's break down some of the key findings:

1. High Severity: SQL Injection in libuser.py:12

This finding highlights a critical vulnerability: SQL Injection (CWE-89) in the libuser.py file at line 12. The severity is marked as High, indicating a significant risk to the application's security. This vulnerability has 7 detected data flows, meaning the potential impact is widespread. The vulnerability was detected on 2025-11-27 10:57 PM and violates the SAST-workflowa239de9c-3b83-41df-a6c1-1ae8ecf5bd74 workflow. The violation priority is HIGH, further emphasizing the urgency of addressing this issue.

Vulnerable Code Snippet

The report provides a direct link to the vulnerable code snippet on GitHub, allowing developers to quickly inspect the issue. The vulnerable code lies within the libuser.py file, specifically between lines 8 and 17. By examining the code, developers can understand how user input is being incorporated into SQL queries without proper sanitization, leading to the SQL Injection vulnerability.

Data Flows: Tracing the Vulnerability

Understanding the data flows is crucial for comprehending the scope and impact of the vulnerability. The report details 7 detected data flows, illustrating the path of the malicious input through the application. Each data flow is presented with links to the relevant code snippets, allowing developers to trace the vulnerability from its source to its point of execution. For example, Data Flow #1 shows the path through mod_user.py#L17, mod_user.py#L20, libuser.py#L5, and finally libuser.py#L12. This detailed tracing helps in identifying all potential entry points and affected components.

Secure Code Warrior Training Material

To facilitate learning and prevent future occurrences, the report includes links to Secure Code Warrior training materials. This includes training modules, videos, and further reading resources focused on SQL Injection. These resources provide developers with the knowledge and skills necessary to identify and mitigate SQL Injection vulnerabilities effectively. For instance, the report links to the Secure Code Warrior SQL Injection Training module and the OWASP SQL Injection Prevention Cheat Sheet, offering comprehensive learning opportunities.

Remediation Suggestion: Parameterized Queries

The report offers a specific remediation suggestion: using parameterized queries with the sqlite3 module. This technique safely injects user-provided parameters into SQL statements using placeholders, preventing SQL Injection attacks. The report includes a link to a diff file on GitHub, showcasing the proposed code changes. This practical guidance simplifies the remediation process, allowing developers to quickly implement the recommended solution. The remediation suggests using placeholders ('?') to safely inject the 'username' and 'password' parameters, a standard practice in secure coding.

2. High Severity: SQL Injection in libuser.py:25

Similar to the previous finding, this also highlights a High severity SQL Injection vulnerability (CWE-89), this time in libuser.py:25. This vulnerability has 2 detected data flows, detected on 2025-11-27 10:57 PM, and violates the SAST-workflowa239de9c-3b83-41df-a6c1-1ae8ecf5bd74 workflow with a HIGH priority.

The vulnerable code is located between lines 21 and 30 in libuser.py. Data flows are detailed, and the same Secure Code Warrior training materials and remediation suggestions (parameterized queries) apply here as well.

3. High Severity: SQL Injection in libuser.py:53

A third High severity SQL Injection vulnerability (CWE-89) is identified in libuser.py:53, with 1 detected data flow. The violation date, workflow, and priority are consistent with the previous SQL Injection findings.

Vulnerable code spans lines 49-58 in libuser.py. As with the previous findings, the report provides links to Secure Code Warrior training and suggests using parameterized queries for remediation.

4. Low Severity: Weak Hash Strength in skey.py:11

This finding points to a Low severity issue: Weak Hash Strength (CWE-328) in skey.py:11. While not as critical as SQL Injection, using weak hashing algorithms can compromise password security. The vulnerable code is between lines 7 and 16 in skey.py, with 1 detected data flow.

The report offers Secure Code Warrior training material related to Weak Hash Strength and further reading resources, including the OWASP Password Storage Cheat Sheet.

5-11. Medium Severity: Hardcoded Password/Credentials

The report identifies several instances of Medium severity vulnerabilities related to Hardcoded Password/Credentials (CWE-798). These are found in the following files and lines:

• libapi.py:10
• libapi.py:20
• libapi.py:45
• vulpy-ssl.py:13 (bad)
• vulpy-ssl.py:13 (good)
• vulpy.py:16

Each instance has 1 detected data flow. The report provides links to vulnerable code snippets, Secure Code Warrior training material, and videos on Hardcoded Password/Credentials.

Overview of Findings: A Consolidated Summary

To provide a clear overview of the vulnerabilities, the report includes a table summarizing the findings by severity, vulnerability type, CWE, and language. This table highlights the prevalence of SQL Injection and Hardcoded Password/Credentials vulnerabilities in the Python codebase.

Conclusion: Prioritizing Remediation Efforts

This code security report provides a comprehensive overview of the vulnerabilities identified in the SAST-UP-DP-DEV-env repository. The high severity SQL Injection vulnerabilities should be addressed with utmost priority, leveraging the provided remediation suggestions and Secure Code Warrior training materials. Addressing the medium severity Hardcoded Password/Credentials issues and the low severity Weak Hash Strength vulnerability will further enhance the security posture of the application.

By diligently addressing these findings, the development team can significantly reduce the risk of security breaches and ensure the integrity of the software. It's important to implement secure coding practices and utilize resources like the OWASP ( https://owasp.org/ ) to gain further insights into application security.