18 Tips for Recruiters to Identify Fake & Dishonest Candidates in Remote Job Interviews

Remote interviews make hiring faster and more flexible — but they also open doors to impersonation, proxy interviews, deepfakes, and other dishonest behaviors. The good news: many of these risks are detectable if you know what to look for and follow disciplined verification steps. Below are 18 practical tips you can start using today, plus sample scripts and follow-up checks.

The 18 Tips

1. Review the candidate’s digital footprint beforehand
   
   • Check LinkedIn, GitHub, personal websites, and public portfolios for consistency. Look for patterns in writing, timing of contributions, and public project history that match what the candidate claims.
   • Remote interviews make hiring faster and more flexible — but they also open doors to impersonation, proxy interviews, deepfakes, and other dishonest behaviors. The good news: many of these risks are detectable if you know what to look for and follow disciplined verification steps. Below are 18 practical tips you can start using today, plus sample scripts and follow-up checks.
2. Verify identity documents before the interview (if policy allows)
   
   • Require a scanned government ID or corporate email verification ahead of time when appropriate, and confirm that names, roles, and locations line up with public profiles.
3. Ask for a short pre-interview task delivered live
   
   • Send a 10–15 minute micro-task (coding, problem-solving, or a short written prompt) to be completed at the start of the interview. Time pressure reduces the chance of outside help.
4. Require the candidate to join from a device with video + mic
   
   • Prefer candidates who use a single device for video and audio. Multiple devices or screen-sharing from odd setups can be a sign of proxying or external assistance.
5. Ask them to share their entire screen at the start
   
   • If your platform supports it, require full-screen sharing (not just app window). Tell them why: transparency builds trust and captures overlays that normal app windows can hide.
6. Check network indicators after they share the screen
   
   • Look at their network speed, latency, and connection metadata (if visible). High round-trip times, proxies, or sudden IP/region changes during session can be suspicious.
7. Scan for VPN/proxy use and inconsistent IP locations
   
   • If your tool shows IP location, verify it against the candidate’s stated location. Repeated or abrupt location hops during an interview are red flags.
8. Observe video and audio quality for anomalies
   
   • Watch for mismatched lip-sync, odd lighting on the face vs background, or compressed/artificial audio. These are typical of deepfake or voice-modulation attempts.
9. Use live verification gestures
   
   • Ask the candidate to perform a quick physical verification: raise their right hand, tilt their head, or hold up an ID next to their face. Watch for lag or inconsistent overlays.
10. Ask unexpected, process-based follow-ups
    
    • After a candidate answers, follow up with “How did you arrive at that?” or “Can you show me the steps?” Honest candidates can explain their process; someone fed answers often cannot.
11. Ask them to explain code or diagrams line-by-line
    
    • For technical roles, have candidates walk through their code or architecture reasoning. Request live edits or refinements. Proxy solvers will struggle to justify choices.
12. Listen for unnatural conversational pacing
    
    • Instant, perfectly formed answers or responses that arrive with exact timing may indicate an assistant reading outputs. Natural candidates pause, think aloud, and revise answers.
13. Require intermittent environment checks
    
    • At random points, ask the candidate to pan the camera, show the room corners, or confirm who else is present. Repeating checks makes proxying harder.
14. Use proctoring tools (e.g., Hyproctor) as evidence-gathering, not automatic judges
    
    • Tools can flag virtual cams, remote-control software, IP anomalies, and hidden overlays — present these as evidence for human review rather than automatic disqualification.
15. Keep a documented audit trail
    
    • Note down timestamps of suspicious events: screen shares started/ended, verification gestures, and any technical anomalies. This helps with internal reviews and escalations.
16. Train interviewers on red flags and standardized policies
    
    • Ensure your team has a consistent, written policy about acceptable use of AI, external help, and what steps to take when cheating is suspected.
17. Balance security with candidate experience
    
    • Be transparent in advance: tell candidates what checks you’ll perform and why. Friction reduces fraud but unnecessary suspicion can harm employer brand.
18. Follow up with reference and technical checks after the interview
    
    • If you’re unsure, do a live pair-programming session, a longer technical interview, or call references to confirm claims about past projects and responsibilities.

Red Flags to Watch For (Quick List)

• Perfectly polished answers delivered with no visible thinking time.
• Inconsistent public profile vs interview claims (job titles, dates, repos).
• Lip-sync issues, mismatched lighting, or audio artifacts.
• Candidate refuses to share screen or to perform simple verification gestures.
• Sudden changes in network IP or multiple device use not previously indicated.
• Candidate won’t explain how they solved a problem or gives vague high-level responses.

Sample Scripts & Prompts

Pre-interview email / instruction:

‍“Hi [Name], to keep our process fair for everyone, please join from a single device with camera and mic enabled and be prepared to share your full screen for a short environment check at the start of the interview.”

Live verification scripts:

‍“Can you please pan your camera slowly to show the room for 5 seconds?”

“Please raise your right hand and say your full name.”

“Can you walk me through how you tested that code — what tools did you run, and what output did you observe?”

If you suspect cheating:

‍“Thanks for your time. Before we proceed, we noticed [X]. Can you clarify what software you were using and why [Y] appeared? We’ll pause and review.”

‍

“We need a company-wide point of view. I’m worried that we’re letting each recruiter or hiring manager or interviewer decide what cheating is — and isn’t.”
— John Vlastelica, Founder of Recruiting Toolbox

Post-Interview Verification Steps

• Run a short follow-up technical or practical session (pair-programming or whiteboard explanation).
• Ask for raw artifacts (repositories with commit history, screen recordings of past work) to verify ownership.
• Contact references and ask specific, technical questions about the candidate’s role and deliverables.
• If impersonation is strongly suspected, consider escalation to security or legal teams and preserve any evidence collected.

Ethical & Legal Considerations

• Always notify candidates about what data will be checked and why. Transparency is both ethical and legally prudent.
• Avoid invasive biometric collection unless you have clear legal basis and consent.
• Be careful about discrimination risk — verification methods must be applied consistently and fairly.

Closing Thoughts

Detecting dishonesty in remote interviews is a mix of smart tooling, disciplined processes, and good interviewer instincts. No single tip is foolproof — but combining pre-interview checks, live verification, behavioral follow-ups, and post-interview validation dramatically reduces risk. Use tools like Hyproctor to surface evidence, but let trained humans make the final call.