Sensitive Data Scanner

Sensitive Data Scanner focuses on detect likely secrets in pasted git diffs using patterns.

Paste the relevant Git output or upload an existing text export, then inspect the structured result. The processing is intentionally transparent: the tool shows what it recognized and does not pretend to have access to a live repository.

Input validation is explicit. When the supplied data does not match the expected structure, the tool reports the problem rather than inventing missing values. Results are formatted for quick review and can be copied, downloaded or printed where appropriate.

Supporting information is specific to this Git task and is designed to help users interpret the result and avoid common workflow mistakes.

• Paste or upload: use an existing text export quickly.
• Focused parser: process the format expected by this tool.
• Validation: reject empty or unrecognized input with useful errors.
• Structured result: review important fields in a readable table or panel.
• Copy and download: reuse the generated result without retyping.
• Result-only print: create a clean printout of the useful output.
• Responsive design: the interface remains usable on mobile screens.
• Git-specific guidance: supporting tabs address the actual workflow behind the tool.

1. Paste the required Git output or upload a text export.
2. Check the sample format if you are unsure what the parser expects.
3. Run the analysis and read any validation message.
4. Review the structured result and its statistics.
5. Copy or download the result if you need it elsewhere.
6. Use the supporting Git guidance before acting on any generated command or recommendation.

Example 1: Use the included sample to understand the expected data shape.

Example 2: Replace the sample with a small real export and verify the parser before using a larger one.

Example 3: Use the output during repository maintenance or a pull-request review.

Example 4: Deliberately test an invalid line to confirm how the tool handles malformed data.

Example 5: Export the result as a small review artifact for a ticket or team note.

• Faster Git analysis: turn terminal output into useful information quickly.
• Less manual formatting: structured tables are easier to scan.
• Clear boundaries: invalid input is surfaced rather than guessed.
• Practical learning: task-specific guidance explains the Git concept involved.
• Reviewable commands: potentially destructive actions remain visible before execution.
• Flexible workflow: paste or upload existing data.