Verify the human behind every workforce interaction.
Detect when the wrong person is behind a trusted workforce identity across hiring, onboarding, account recovery and ongoing work.
Attackers can fake identity.
They still have to operate.
A stolen identity, valid account or enrolled device can make an interaction look legitimate. But the operator still creates an environment around that interaction: infrastructure, routing, endpoint conditions, tooling and behavior. That operating pattern is much harder to fake.
How imper.ai works
From operating signals to an impersonation decision.
imper.ai evaluates a deep set of signals across device, network, location, environment, tooling and behavior. Individual observations are not detections. The engine recognizes combinations that match how impersonation attacks operate, then produces an explainable risk score for policy and workflow action.
Evaluate the operating conditions
Browser-based, agentless telemetry captures the environment around the interaction, including on personal or unmanaged devices where browser telemetry is available.
Recognize impersonation patterns
Combine otherwise ambiguous observations into impersonation-specific detections informed by how attackers actually operate.
Turn detections into a decision
Use detections and relevant context to produce an explainable impersonation risk score that can drive policy and workflow action.
Why now
Workforce impersonation is no longer an edge case.
Across the workforce
The same security question appears at different moments.
Hiring fraud
Detect proxy candidates, location hiding, remote control and identity handoffs across interviews.
Explore hiring → OnboardingOnboarding and enrollment
Detect laptop farms, remote control and unexpected environment changes when corporate access is issued.
Explore the platform → Account recoveryHelp desk vishing
Detect impersonators during account recovery, MFA resets and other high-risk support requests.
Explore help desk security → Ongoing workShadow workforce
Detect when someone other than the expected worker is operating a trusted account or device.
Explore shadow workforce →Detect the attacker-controlled environment.
See beyond the account, credential, face or voice.
An attacker can disguise one artifact. Sustaining a believable identity across device, network, location, environment, tooling and behavior is much harder. imper.ai evaluates those conditions together to identify impersonation patterns around the interaction.
Explore the detection architecture
Step up with contextual verification
Add assurance for established employees when risk or policy requires it.
When imper.ai already knows the employee, dynamic work specific questions grounded in recent enterprise context can verify knowledge an impostor should not have. This is primarily for help desk and selected employee step up workflows.
Learn MoreBuilt into the workflows
where identity breaks
Surface impersonation detections, risk scores and policy outcomes directly inside ATS, ITSM and identity and access workflows.
Apply the control across interviews, onboarding and enrollment, account recovery, MFA resets and other workforce events where the human behind the identity matters.
View Integrations
Customers trust us with their data and their money, so protecting that is crucial. imper.ai gives us peace of mind that the person we’re speaking with is exactly who they say they are, without compromising anyone’s privacy.
Enterprise financial software and systems provider
Workforce impersonation crosses industries.
Anywhere people are hired, onboarded, supported and trusted, the same security problem can appear.
Banking
Healthcare
Manufacturing
Telecom
Technology
Financial Services
Insurance
Critical InfrastructureWorkforce Identity Impersonation Detection
Ready to verify the human behind the identity?
See how imper.ai detects impersonation across hiring, onboarding, help desk recovery and ongoing work.
