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Improve scan engine error classification to reduce false positives and ambiguous results #1195

@S3DFX-CYBER

Description

@S3DFX-CYBER

During recent testing, some scan results were initially flagged as potential vulnerabilities but were later confirmed to be false positives due to environmental factors (intentional Docker behavior, outdated images, or network/SSL edge cases).

While these cases were handled correctly after manual investigation, the current scan engine does not clearly distinguish between:
genuine vulnerabilities
environmental misconfigurations
intentional design behavior
transient network or SSL handshake failures

This can lead to ambiguous results and additional manual verification effort for users.

Proposed improvement:
Improve error classification and reporting in the scan engine
Introduce clearer result states (e.g., confirmed issue, possible misconfiguration, environmental limitation)
Reduce false positives by improving exception handling and context-aware validation

Benefits:
Higher scan accuracy
Reduced false positives
Improved user trust in scan results
Better suitability for automated pipelines

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