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harish93's avatar
harish93
Copper Contributor
Oct 31, 2025

Microsoft Default Credit Card Number is not working effectively.

Hi All,
I just observe that Microsoft default SIT for Credit Card is detecting more False Positives, it is detecting the 16 digit transaction numbers, tracking ID's, Receipt numbers and even Microsoft support ticket numbers also detecting as Credit Card Numbers. how can we finetune the Microsoft Default SIT to make sure it should detect only valid Credit Card Numbers.

1 Reply

  • Hey, that’s correct

    This causes false positives

    • Plain 16‑digit numbers with separators (spaces, hyphens) that pass the Luhn checksum.
    • Strings near generic words like “card,” “payment,” “visa,” “master,” “exp,” “cvv,” “mm/yy,” “billing,” etc.
    • Numbers embedded in structured layouts (tables, receipts) where proximity evidence is weak.

    You cannot modify the built‑in SIT, only adjust policy confidence or replace it with a custom SIT. This is the safest way to reduce false positives without losing protection.

     

    Few ways:

     

    Increase confidence level in DLP policy

    • In your DLP rule, set Confidence Level = High for Credit Card SIT.
    • High confidence requires Luhn + supporting keywords (e.g., “card number”, “expiry”, “cvv”), reducing false positives.

    Require more supporting evidence

    • In the policy, configure:
      • Proximity window: tighten from default (300 chars) to 64 chars.
      • Minimum supporting keywords: require at least 2 (e.g., “credit card” AND “expiry”).
    • This ensures detection only when the number appears in a realistic card context.

    Add negative keywords or exclusions

    • Use exceptions in the DLP rule for terms like:
    • tracking, ticket, receipt, order, reference, AWB, SR or any pattern you noticed a lot
    • This prevents IDs with those labels from triggering.

    Create a custom SIT (recommended)

    • Define:
      • Regex for card number format.
      • Luhn check (Purview supports Func_Luhn).
      • Supporting keywords: “cvv”, “expiry”, “cardholder”, “billing”.
    • Require expiry date pattern nearby for extra accuracy.

     

    Please let me know after trying if this reduces false results.

     

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