File Classifiers
File Classifiers
File Classifiers use machine-learning technology to match documents and images that are part of a group. There are 28 predefined file classifiers. You can also upload a group of images that will be used to train a custom ML-based image classifier. Only images can be uploaded at this time. Alerts and Incidents will be generated similar to any other classifiers. File classifiers can be referenced as part of creating or editing a Custom DLP Profile.
Create a File Classifier
To create a File Classifier:
- Go to Policies > Profiles > DLP > File Classifiers in the Netskope UI.
- Click New File Classifier.
- Under Upload Training Files, drag & drop files into the box or Select Files to be added to the classifier
- Click Save.
Positive training data trains the model to identify files that are similar to the ones being uploaded.
Negative training data trains the model to identify what is not considered a match to the classifier’s model. This functionality is only available after the custom classifier has been successfully setup and trained.
Percent Match specifies what percent of the file has to match the file classifier in order for it to evaluate the file.
If your model’s efficacy is below the Netskope standard, a warning will be provided with an explanation.

There are 5 scenarios which will elicit a warning:
- False positive rate is too high
- True positive rate is too low
- Maximum number of tests met
- The model evaluation is currently running
- The model efficacy must be evaluated
Edit a File Classifier
When a File Classifier has been successfully created, it can be edited to include Positive training data or Negative training data. The Percent Match value can also be changed. This is also known as Training Your Own Classifier (TYOC).
To edit an existing File Classifier:
- Click … on an existing File Classifier.
- Click Edit.
Delete a File Classifier
To delete an existing File Classifier.
- Click … on an existing File Classifier.
- Click Delete.
Edit a Predefined File Classifier
Editing a predefined file classifier allows you to modify the behavior of predefined classification matches with the goal of reducing false positives (by uploading a false positive file or by increasing the match threshold) or in some cases properly detecting false negatives (by reducing the threshold level).
- Click … on an existing File Classifier in the Predefined section.
- Click Edit.
- Select your Confidence Level.
- Select your files or drag and drop them to the False Positive Files section.
- Click Save.
Confidence Level – This setting allows you to modify the model’s sensitivity level/threshold. A lower confidence level will cause the classifier to have a higher recall. This means the classifier’s model will match on a higher number of true positives, but is also subject to having more false positives. A higher confidence level will cause the classifier to have a higher precision. This means the classifier’s model will result in fewer false positives but will also have fewer true positives.
Predefined Classifiers
List of Document Classifiers
Bank Statement, Loan Agreement, Loan Application, Stock Purchase Program, Tax Form (US), Offer Letter, *Resume, Consulting Agreement, Merger and Acquisitions Form (M&A), NDA (English), Partner Agreement, Patent, Medical Form, Medical Power of Attorney (POA), *Source Code (All)
List of Image Classifiers
Check, Payment Card (Credit, Debit), Medical Image, Screenshot, Whiteboard, Driver’s License (All), Driver’s License (US), Health ID Card, Passport Book, Photo ID, Social Security Card (US)