Know when your IP leaves, and whether it was meant to.
Data Exfiltration Detection & IP Protection
Know when source code, designs, customer records, or models leave, and whether they were meant to.
Know when your IP leaves, and whether it was meant to.
Know when source code, designs, customer records, or models leave, and whether they were meant to.
The object moves. The story leaves with it.
MCP creates new paths for covert exfiltration. Data also leaves through AI tools, browser uploads, and git clones to personal machines. DLP can follow a file. It struggles to follow the full exit: who moved it, where it went, what channel carried it, and whether the action belonged. The signal is there. The intent is not.
Legacy DLP scans for patterns: card numbers, social security numbers, keywords. But your most valuable data rarely carries a pattern to match. To a content scanner, source code, model weights, and a board deck all look like ordinary text.
No card number, no keyword. A scanner sees plain text and misses that this is your core repository.
Binary CAD and design formats carry no scannable pattern at all, and often no text at all.
Weights and embeddings are just numbers. Their value is invisible to a content rule.
Forecasts and strategy decks read as ordinary documents to a pattern matcher.
Audio and video hold no text to inspect, yet often carry the most sensitive context.
Even structured records slip through once they are renamed, zipped, or pasted in pieces.
Anzenna judges data by its provenance. It reconstructs the full journey of a sensitive dataset across your systems and ties every hop to a person. Importance comes from where data has been and who touched it, not from whether a regular expression happened to match.
Where it came from and how it is classified. A row from CUSTOMER_FACTS, a clone of the core repo, an export from Salesforce.
Every system it crossed on the way out. Warehouse to laptop to browser to a personal account, reconstructed end to end.
Who moved it, measured against their peers. An export that is routine for data engineering is a flag for a departing sales rep.
Anzenna watches MCP activity and browser AI flows as they happen. Every movement is tied back to an identity, giving security teams clear visibility into what is entering AI systems, through which path, and under whose hand.
The browser is often where the quiet exit begins. Anzenna captures file uploads and movements there, then connects them back to sensitive company data so the full exfiltration lineage comes into view.
Anzenna correlates git operations, Salesforce exports, and other data movements with identity context, HR status, and peer behavior. What looks like a simple export on the surface becomes a complete investigation, with the context and reporting security teams need to find real threats.
Anzenna caught one of our engineers uploading sensitive source code into their personal github repo.
Fifteen-minute install. Read-only by default. No agents on endpoints.
Thirty minutes. Your environment, not our slides.
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