Test gemini action

[adilshehzad786]

No description provided.

[github-actions]

Vulnerability Type	File	Line(s)	Description	Recommendation	Reference	Code Improvement
Hardcoded Secret	.github/workflows/code-scan.yml	17	The GEMINI_API_KEY is directly exposed in the workflow file. Although using GitHub secrets, referencing them directly in workflows exposes them in the workflow logs, which can be accessed if the repository is compromised.	Store the GEMINI_API_KEY as an encrypted secret within GitHub and access it securely during the workflow execution. Avoid direct usage like ${{ secrets.GEMINI_API_KEY }}. Use the key only within the action's internal logic.	Secrets	.github/workflows/code-scan.yml Line 16-18: Remove GEMINI_API_KEY and pass it to the action as an input parameter. Pass this value as input to the action and remove these lines. Access input parameters using the inputs context: api_key: ${{ inputs.gemini_api_key }} inside the action code.
Excessive Permissions	.github/workflows/code-scan.yml	6	permissions: write-all grants excessive permissions to the workflow. This poses a security risk if the workflow is compromised, as the attacker could gain full control over the repository.	Grant only the necessary permissions required by the workflow, such as pull-requests: write and contents: read.	Workflow permissions	.github/workflows/code-scan.yml Line 6: Replace write-all with specific required permissions. For example, permissions: { contents: read, pull-requests: write }
Insecure Logging	main.py	7	Logging sensitive data or exceptions without proper sanitization can expose sensitive information.	Ensure that logs do not contain sensitive data like API keys, tokens, or internal system paths. Implement proper sanitization before logging exceptions or user inputs. Consider using a dedicated security logging mechanism for sensitive events.	Logging Best Practices	main.py various lines: Review all logger calls and ensure no sensitive data is logged. Implement scrubbing of sensitive data before logging.

Summary:

• Total number of vulnerabilities found: 3
• High severity: 2 (🚨🚨)
• Medium severity: 1 (⚠️)
• Low severity: 0 (ℹ️)
• Overall status: Fail

It's crucial to address the hardcoded secret and excessive permissions issues immediately as they pose significant risks. The logging issue, while classified as medium, is also important for maintaining a secure and private environment. Remember that relying on AI for complete security analysis is not a substitute for proper code review and secure coding practices. These vulnerabilities should be addressed before deploying this action to production.