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Suspicious User Activity
Predefined Policies and Classifiers | Forcepoint DLP | v8.4.x
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Detects data that is sent at an unusual time. You define what is considered an unusual time in the script classifier, Unusual Hours. Each rule in this policy target a different type of data, such as Office or archive files.
Example: If you define working days in the classifier as Monday-Friday and unusual hours as 9pm-5am, then data sent on Saturday, Sunday, or during the working week between 9 p.m. and 5 a.m. triggers this policy.
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Policy for detecting deep web URLs that appear in analyzed content such as textual documents or email messages and end with the pseudo-top-level domains .onion and .i2p. The deep web is a portion of World Wide Web content that is not indexed by standard search engines and that is intentionally hidden from the regular Internet, accessible only with special software, such as Tor. Such URLs are used for anonymous defamation, unauthorized leaks of sensitive information and copyright infringement, distribution of illegal sexual content, selling controlled substances, money laundering, bank fraud, credit card fraud and identity theft, among other things. The rules for this policy are:
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A policy for detecting email messages that are being sent from one's corporate email address to his or her personal email address. The rules for this policy are:
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Policy for detection of content suspected to be manipulated to avoid detection.This may cause false positives. The rules for this policy are:
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Detects content suspected to be a password in clear text. The rules for this policy are:
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Policy for detecting email messages that are being sent from one's corporate email address to his or her personal email address. The rules for this policy are:
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Detects when unencrypted binary files of unknown formats are being sent repeatedly over a period of time. For example, if 50 unencrypted files of an unknown format are sent during 1 hour, this policy is triggered. The rules for this policy are:
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Policy for detection of suspicious behavior of users by measuring the rate and type of transactions over time. This may cause false positives. The rules for this policy are:
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