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Description
During a security scan of our Next.js application, we encountered several false positives that could lead to confusion and unnecessary concern. We'd like to report these to help improve the accuracy of the scanning tool.
False Positives Found
1. AWS Secret Access Key Detection
- Location:
app/(root)/page.tsx - Reported Issue: High severity AWS Secret Access Key detected
- Actual Code: The file contains only React components and imports, with no AWS credentials
- Impact: Could cause unnecessary alarm for developers
2. File Upload Vulnerability
- Location:
app/(root)/(admin)/admin/SearchUsers.tsx - Reported Issue: Potential file upload handling vulnerability
- Actual Code: The file uses
FormDatafor text search functionality, not file uploads - Impact: Misleads developers into thinking there's a file upload security issue
3. High Entropy String Warnings
- Locations: Multiple files including:
- Font files (
.otffiles) - Image files (
.webpfiles) - UI component files
- Font files (
- Reported Issue: High entropy strings detected
- Actual Code: These are binary files and UI components with no sensitive data
- Impact: Creates noise in the scan results, making it harder to identify real issues
Environment
- Next.js application
- TypeScript
- Various binary assets (fonts, images)
Expected Behavior
The security scanner should:
- Not flag binary files (fonts, images) as containing high entropy strings
- Better distinguish between
FormDatausage for file uploads vs. form submissions - Have more accurate detection of actual AWS credentials
Additional Context
The scan did correctly identify some valid security concerns (rate limiting, error logging), but the false positives made it more difficult to focus on the real issues.
Impact
These false positives:
- Create unnecessary concern for developers
- Make it harder to identify real security issues
- Could lead to wasted time investigating non-existent problems
Possible Solutions
- Add file type filtering for binary files
- Improve context analysis for
FormDatausage - Implement better heuristics for AWS credential detection
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