Insider threat
Protect sensitive information and investigate misuse of authorized access with evidence people can examine.
How ARRTECH handles insider risk
Insider risk begins with access people already have. Data loss prevention helps control sensitive transfers, while AI Detection brings unusual account activity to the team’s attention. A clear record helps security, HR and legal review what happened fairly.
Negligent insiders
A mistake can expose information just as easily as deliberate misuse. DLP content checks can identify a sensitive attachment, upload or AI prompt before it leaves through a covered channel. The policy can block the transfer, request a reason or route it for approval, so legitimate work has a way forward.
Departing employees
A departure is a reason to review access and information handling, not a conclusion about the person. Focus DLP policies on the relevant accounts and sensitive files, record unusual transfers and provide a controlled exception for work that still needs to be completed.
Compromised accounts
An attacker using stolen credentials may appear to be a trusted user. Comparing sign-ins, hosts and destinations with the account’s history, as AI Detection does through UEBA, can reveal changes worth investigating. The finding should show the underlying events, and AI Investigation can gather them into a case so the team can distinguish misuse from legitimate work.
Signed evidence
HR and legal need records they can examine independently of the investigation’s conclusion. Signed logs from a SIEM help show whether a record has changed after collection. Access history, transfer events and documented exceptions provide the context needed to assess what that record means.
Approval
Disabling an account, preserving a mailbox or restricting a transfer needs clear authority. Response workflows in a SOAR can gather the evidence and route the decision to the responsible person. The record should show the action, its reason and who approved it.
By scenario
Client list emailed to a personal address
Content inspection by a DLP can identify a client list in an outbound message and apply the organization’s sharing policy. A blocked or approved exception leaves a record the team can review.
Source code pasted into an AI chatbot
Prompt and upload inspection by a DLP can identify protected code on covered AI channels before it is shared. The policy should make clear which tools and information are approved for work.
Files copied to USB before resignation
DLP device and content policies can restrict removable storage and record file transfers. Review the activity alongside the employee’s work and any approved exception before drawing a conclusion.
Screenshots of a confidential document
DLP screen capture controls can restrict or record supported capture activity. Watermarks can add user context to a copy, helping an investigation follow the evidence.
Contractor signs in at 3 a.m. from a new host
The unusual time and host are useful AI Detection leads. Compare them with approved maintenance, the contractor’s role and the actions EDR recorded on the host after the sign-in.
Administrator queries an unfamiliar database
A new destination flagged by AI Detection can deserve review even when the account has permission to reach it. Examine the query activity, access history and business purpose together.
Questions
Can an employee get an exception?
Yes. A DLP policy can allow a user to explain the transfer or ask an authorized reviewer to approve it. The exception should apply to the specific need and remain on record.
Does detection work with our existing SIEM?
A supported SIEM export can provide the records for AI Detection. Evaluation confirms the required sources and history before the team adds it to its workflow.
Does it block as it happens?
DLP policies can block a transfer during inspection on covered channels. AI Detection analyzes recorded activity and supplies findings for review; its timing depends on collection and processing.
How do HR and legal use the findings?
They examine the source events, relevant policy and explanations alongside the AI Investigation assessment. An AI Detection risk score helps prioritize review; it does not establish intent or misconduct.
Guide
What is an insider threat?
The potential for anyone with authorized access to use that access to cause harm, intentionally or not. That includes employees, contractors, suppliers and an outsider using their credentials.
What are the types of insider threat?
Negligent insiders make mistakes, malicious insiders misuse access on purpose, and compromised insiders have credentials an attacker holds.
How is an insider threat different from an external attack?
Insider threats involve access that a person or account already holds. That access can be misused, compromised or extended through an exploit. Detection therefore considers sensitive content with DLP and account behavior with AI Detection, as well as the malware and intrusion signs that EDR and XDR look for.
How ARRTECH takes care of insider risk
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.
