Data exfiltration
Protect sensitive information across transfer channels, from web uploads and email to suspicious DNS activity.
Controls for each exit channel
Data exfiltration prevention starts with the information being protected and the routes it can take. Content inspection by a DLP governs supported transfers; network analysis in AI Detection helps investigate less obvious routes such as DNS tunneling.
HTTPS uploads
An upload can come from a browser, desktop client or script. Network-level inspection by a DLP extends coverage beyond a browser extension, while evaluation establishes which applications and transfer paths the policy can inspect.
Generative AI
A prompt can contain the same confidential information as a document. Content inspection by a DLP on covered AI services lets the organization apply its handling rules to both text and uploaded files.
Email inspection by a DLP can check the message and its attachments before release. A sensitive match in a DLP can prompt correction, approval or blocking, helping prevent a mistaken recipient from becoming a data loss incident.
USB and print
DLP device and endpoint policies can govern removable media, printing and supported copy or capture actions. Apply the controls to the people and information involved, with a route for legitimate exceptions.
DNS tunneling
DNS analysis in AI Detection can reveal patterns associated with tunneling, beaconing and algorithm-generated domains. The finding should include the activity and historical context an analyst needs to assess whether it is suspicious.
Exceptions
A DLP rule can do more than block. It can log, ask the user for a reason, hold the file for a supervisor or encrypt it.
By scenario
Customer data uploaded through a desktop app
Inspect the covered application’s transfer against the DLP data-handling policy, with the user, destination and resulting decision recorded.
Spreadsheet attached for the wrong recipient
A DLP content check can catch the sensitive attachment before sending and give the user a chance to correct the transfer.
Confidential file sent to a printer
A DLP print rule blocks or logs it.
Script sends a file over SMTP
Mail inspection by a DLP can apply the same handling policy to supported script-generated traffic, rather than relying only on the user’s mail application.
Host resolving generated-looking domains
Review the domains against threat intelligence and the host’s DNS history. A suspicious pattern is a lead to investigate.
Questions
Can DLP inspect encrypted traffic?
It can on supported inspection paths, including relevant HTTPS, WebSocket, FTP and SMTP traffic. Coverage depends on the application and deployment, so evaluation should include the organization’s actual encrypted transfers.
Does it cover phones?
Gateway inspection by a DLP can cover mail and web traffic routed through supported services. It provides a different scope from an endpoint agent installed on a computer.
Will it stop legitimate work?
DLP policies can begin in monitoring mode and use justification or approval where a transfer may be legitimate. Review matches with the business before introducing broader blocks.
Which product blocks traffic?
DLP applies blocking policies on covered channels. AI Detection supplies findings for investigation and does not itself block the observed DNS traffic.
Guide
What is data exfiltration?
The unauthorized transfer of data out of an organization. MITRE ATT&CK tracks it as tactic TA0010.
What is DNS tunneling?
Using DNS queries and responses to carry data or commands beyond ordinary name resolution. It can support command and control or data exfiltration; MITRE ATT&CK describes DNS-based command and control under T1071.004.
What is shadow AI?
Using AI tools the company has not approved, which can send its data to services it does not control.
How ARRTECH takes care of data exfiltration
Connects security activity into a signed record, giving incident decisions and board reporting evidence that can be independently verified.
Protects intellectual property and customer trust, with content-aware controls that let organizations adopt AI on their own terms.
Expands response capacity through automation, with defined human authority and a record of who approved what.
Finds changes in behavior that predefined rules miss, connecting the signs of an attack so teams can understand what warrants action.
Investigates alerts, tests explanations and prepares the evidence, giving analysts more capacity while people retain authority over the response.
