Cheat Detection
HeyMilo's Cheat Detection helps recruiters identify potential cheating behaviors during candidate interviews. This guide explains how to configure the system and interpret the results.
System Requirements
Before enabling cheat detection, ensure:
Cheat detection is enabled for your workspace
Candidates use a supported browser for web interviews
Camera and microphone permissions are granted
If cheat detection is not available, contact [email protected].
Supported Browsers
Recommended (best experience) We recommend using one of these browsers, kept up to date:
Google Chrome: Latest stable version. Best tested; recommended for the most reliable experience.
Microsoft Edge: Latest stable version. Full support and regularly tested.
Mozilla Firefox: Latest stable version. Full support.
Safari: Latest version on macOS and iOS. Use the latest Safari your device supports.
Also supported These browsers use the same or similar engines as the recommended ones and should work when up to date:
Opera: Current stable version (Chromium-based).
Opera GX: Current stable version (Chromium-based).
Brave: Current stable version (Chromium-based).
Samsung Internet: Recent versions on Android (Chromium-based; keep the app updated).
Vivaldi: Current stable version (Chromium-based).
Arc: Current stable version (Chromium-based on macOS/Windows).
Not supported
Internet Explorer (all versions): Not supported; use Edge or another modern browser.
Very old or unpatched browsers: Browsers that are no longer receiving security updates are not supported.
General guidance
Desktop: Chrome, Edge, or Firefox on Windows/macOS/Linux, or Safari on Mac.
Mobile: Safari on iOS or Chrome/Firefox/Samsung Internet on Android.
Keep your browser updated to the latest version for the best experience.
Where Cheat Detection Is Configured
Cheat detection can be configured in two places, depending on your workflow.
Option 1: Workspace-Level Settings (Recommended Default)
Use this if you want consistent integrity settings across all interviews.

Path:
AI → Interview Integrity
Settings Available
Enable Cheat Detection
Turns integrity monitoring on for all new interviews in the workspace.
Detection Threshold (0–100)
Controls how strict the system is when flagging events.
Lower values = less sensitive (fewer flags)
Higher values = more sensitive (flags more signals)
Recommended starting point: 70
Detection Types
Select which signals to monitor:
Facial Behaviour
Multiple People
Phone Detection
AI / Scripted Answer
Unusual Delays
Tab Switching
Click Save Settings to apply changes.
Option 2: Interview-Level Settings (Per Agent)
Use this if you need role-specific control.

Path:
Create or Edit Interviewer → Voice/Video Interview (workflow step) → Settings tab
You’ll see the same options as workspace-level settings:
Enable Cheat Detection
Detection Threshold
Detection Types
These settings apply only to that interviewer and override workspace defaults.
What Each Detection Type Means
These signals are observational, not judgments.

Facial Behaviour
Flags repeated or sustained face movement away from the screen that may indicate reading notes or external prompts.
AI / Scripted Answer
Identifies response patterns that strongly resemble pre-written or AI-generated text, based on structure and delivery timing.
Viewing Cheat Detection Results
Path:

Interviewers → Candidate → Diagnostics & Analysis
Scroll down to Cheat Detection Overview and you’ll see:
Events grouped by detection type
Timestamps for each flagged moment
Confidence scores per event
A synced player to jump directly to flagged points
Understanding Confidence Scores
Confidence scores indicate how strongly a signal was detected, not intent.
80–100: Strong signal, review recommended
60–79: Moderate signal, check context
Below 60: Likely environmental or accidental
Always review video and transcript context before drawing conclusions.
Patterns Matter More Than Single Events
More weight should be given to:
Repeated signals across the interview
Multiple detection types occurring together
Signals aligned with complex or high-stakes questions
Single, low-confidence events are often caused by lighting, camera angle, or natural movement.
What Cheat Detection Does Not Do
It does not automatically fail or reject candidates
It does not score candidates higher or lower
It does not analyze facial features, expressions, accent, or appearance
It does not make hiring decisions
These signals exist to support review, not replace judgment.
Best Practices
Start with a threshold around 70
Enable only the detection types you actually plan to review
Always pair integrity signals with interview content
Document how your team interprets signals
Revisit settings as roles or hiring volume change
Troubleshooting
No cheat detection data
Feature may be disabled
Interview may have been too short
Camera permissions may not have been granted
Too many flags
Decrease detection threshold
Review candidate setup instructions
Inconsistent results
Check browser compatibility
Review lighting and camera placement
Example: A candidate with consistent 100% confidence “Eye Movement” detections from 1:20 to 8:03 likely looked away repeatedly, possibly at a phone or notes.
Red Flags vs. False Positives
💡 High Risk
Multiple detection types, repeated high-confidence incidents, aligned with tough questions.
Additional resources
If you need help enabling or configuring cheat detection, contact [email protected] or use in-app chat.
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