Data Loss Prevention Coverage Calculator
Score DLP coverage across email, web, endpoint, cloud and API egress paths, weighted by enforcement mode and classification quality.
Inputs
DLP Coverage Score
40.5/ 100
Weighted Path Coverage
73.7/ 100
Enforcement Strength
60.4/ 100
Residual Egress Exposure
59.5%
Coverage Rating
D — Weak
Weakest Egress Path
API and integration egress — bulk automated export is the least watched path
Step by step
Values used
Email egress covered = 95 %; Web and SaaS upload covered = 80 %; Endpoint — USB, print, clipboard = 65 %; Sanctioned cloud storage covered = 70 %; API and integration egress covered = 40 %; Coverage in blocking rather than monitor mode = 55 %; Sensitive data correctly classified = 60 %; Estimated unsanctioned SaaS use = 20 %; DLP alerts overturned as false positives = 35 %
Data Loss Prevention Coverage
pathCoverage = 0.26×email + 0.24×web + 0.20×endpoint + 0.16×cloud + 0.14×API; effective coverage then scales by enforcement mode (0.6–1.0) and classification quality (0.5–1.0), halves the credit for shadow IT, and is trimmed by the false-positive rate.
DLP Coverage Score
= 40.5 / 100
Weighted Path Coverage
= 73.7 / 100
Enforcement Strength
= 60.4 / 100
Residual Egress Exposure
= 59.5
Coverage Rating
= D — Weak
Weakest Egress Path
= API and integration egress — bulk automated export is the least watched path
How it works
DLP is only as good as the narrowest path an insider or attacker can use, so coverage is weighted across all five egress routes and monitor-only coverage earns half credit. The critical multiplier is classification: a policy that cannot recognise your sensitive data does nothing regardless of where it is deployed. Shadow IT discounts the result because unsanctioned destinations sit outside the policy entirely. Treat the score as a prioritisation estimate of egress exposure. Most DLP deployments cover email thoroughly and APIs barely at all, which is precisely inverted — bulk data leaves through integrations, not attachments.
Formula
Data Loss Prevention Coverage
pathCoverage = 0.26×email + 0.24×web + 0.20×endpoint + 0.16×cloud + 0.14×API; effective coverage then scales by enforcement mode (0.6–1.0) and classification quality (0.5–1.0), halves the credit for shadow IT, and is trimmed by the false-positive rate.
- blockingShare
- Coverage that actually blocks rather than only alerting
- classificationCoverage
- Sensitive data the DLP engine can recognise
- shadowItPct
- Unsanctioned SaaS the controls never see
Frequently Asked Questions
How is Data Loss Prevention Coverage calculated?
pathCoverage = 0.26×email + 0.24×web + 0.20×endpoint + 0.16×cloud + 0.14×API; effective coverage then scales by enforcement mode (0.6–1.0) and classification quality (0.5–1.0), halves the credit for shadow IT, and is trimmed by the false-positive rate. DLP is only as good as the narrowest path an insider or attacker can use, so coverage is weighted across all five egress routes and monitor-only coverage earns half credit. The critical multiplier is classification: a policy that cannot recognise your sensitive data does nothing regardless of where it is deployed. Shadow IT discounts the result because unsanctioned destinations sit outside the policy entirely. Treat the score as a prioritisation estimate of egress exposure.
Why does Data Loss Prevention Coverage matter?
Most DLP deployments cover email thoroughly and APIs barely at all, which is precisely inverted — bulk data leaves through integrations, not attachments.
What values do I need to enter?
This calculator takes 9 inputs: Email egress covered, Web and SaaS upload covered, Endpoint — USB, print, clipboard, Sanctioned cloud storage covered, API and integration egress covered, Coverage in blocking rather than monitor mode, Sensitive data correctly classified, Estimated unsanctioned SaaS use, DLP alerts overturned as false positives. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.
Why does monitor-only mode earn half credit?
Because it records the loss rather than preventing it. That has genuine investigative value, which is why it is not zero, but a monitor-only estate has not stopped a single byte from leaving.
Is a high false-positive rate really a coverage problem?
Indirectly, yes. Noisy policies get exceptions carved into them and alerts get bulk-closed, so real coverage erodes. The model applies a modest trim rather than a large one, because tuning is a fixable problem.
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