Nightfall Sample Data Sets
Use sample data sets provided by Nightfall to test Nightfall's detection capabilities.
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Use sample data sets provided by Nightfall to test Nightfall's detection capabilities.
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The following datasets can be used to test Nightfall's advanced AI-based detection capabilities. The data has been fully de-identified and can be used to test any data loss prevention (DLP) platform.
Nightfall's genAI-based model outperforms traditional entity-based detectors by detecting PHI entities in patient healthcare-related documents.
Nightfall AI's fine-tuned API key detection LLM detects secrets with high precision and dramatically reduces false positives.
Testing note: If a key status is marked as ‘Active’, please rotate the key immediately. Not all vendors provide an "Inactive" response code. In these cases or if the vendor service is offline, the finding status will be marked ‘Unverified’.
Nightfall AI detects passwords shared in conversational text and code.
This sample dataset demonstrates Nightfall's ability to detect cryptographic keys.
This sample dataset demonstrates Nightfall's ability to detect PII with high precision and low noise in text, spreadsheets, and screen grabs. Samples include names, U.S. social security numbers, and driver's licenses.
This sample dataset demonstrates Nightfall's ability to detect sensitive banking and payment information with high precision and low noise in text, spreadsheets, and screen grabs. Samples include positive and negative examples of credit card numbers, routing numbers, IBAN codes, and SWIFT codes.
Nightfall’s computer vision (CV) transformer model outperforms legacy Optical Character Recognition (OCR) text scanning to identify driver’s licenses, passports, credit cards, and US social security cards even though images may be degraded (rotated, glossy, low contrast, blurry, skewed, or cropped).
