Data Loss Prevention (DLP)
Data loss prevention refers to tools and rules that detect and block sensitive information — credentials, personal data, financial identifiers — from being shared inappropriately, whether accidentally or maliciously.
Sensitive data leaking through a chat tool is usually not a dramatic breach — it's someone pasting a customer's data into the wrong channel, sharing a credential in plaintext to save time, or forwarding something to an external guest who shouldn't see it. Individually mundane, cumulatively a real compliance and security exposure, and hard to catch by relying on people to remember policy every time.
DLP tooling automates the catch: pattern-based rules (credit card numbers, tax IDs, API keys, custom regexes for an organization's specific sensitive formats) scan content as it's sent and can flag, block, or redact matches before they're delivered — turning a policy that depends on human vigilance into one enforced automatically. Native rule engines are usually paired with the option to integrate third-party DLP tools via a standard interface like ICAP for organizations with more specialized requirements.
Information barriers are a closely related control: rules preventing certain groups from communicating or sharing data with each other at all — relevant in regulated industries where two departments (say, research and trading) are legally required to be walled off from each other's information, regardless of intent.
Data Loss Prevention (DLP), in the product
Aanty includes native DLP rules with ICAP/third-party hooks on Business, plus information barriers for groups that must not see each other's data — part of the security spine rather than a bolted-on compliance add-on.
Related terms and pages
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