Deepfake video call scam

Danger: 5/5

Identity TheftAIRare

Platforms

WhatsAppZoomFaceTime

Target demographic

Universal

Avg. loss

$10,000 – $500,000+

Prevalence

Rare

The scammer uses AI to generate a face in real time during video calls, making video verification useless. A fast-growing threat.

How It Works

Deepfake video call scams represent the cutting edge of romance fraud technology. Using real-time face-swapping software, scammers can now appear on video calls as a completely different person, defeating what was previously the most reliable way to verify someone's identity. This makes the scam exceptionally difficult to detect.

  1. Creating the deepfake identity: The scammer selects a target face, often from stolen photos used in their fake profile. Using commercially available deepfake software, they can overlay this face onto their own in real time during a video call. The technology has improved dramatically and can now be convincing on standard-quality video calls.
  2. The "proof" call: When the victim requests a video call to verify identity (a step commonly recommended to detect catfishing), the scammer agrees, using the deepfake to appear as the person in their photos. This "proof" convinces the victim they are speaking to a real person.
  3. Solidifying trust: Having passed the video verification test, the scammer enjoys a much higher level of trust than a traditional catfisher. The victim becomes more emotionally invested and more willing to share personal information or send money.
  4. Exploitation: With trust cemented, the scammer deploys standard romance scam tactics: emergency money requests, investment schemes, gift card solicitations, or identity theft. The deepfake video call has removed the victim's primary defense mechanism.

Signs to Detect It

Deepfakes are increasingly convincing, but current technology still has telltale flaws:

  • Slight visual glitches around the face, especially at the edges near the hairline, ears, and jawline.
  • Unnatural facial movements: the face may lag behind head turns or show inconsistent lighting compared to the background.
  • The person avoids turning their head to the side, as deepfakes work best when facing the camera directly.
  • Blurriness around the face that does not match the rest of the image, especially when the person moves quickly.
  • Audio-visual sync issues: lip movements may not perfectly match the words being spoken.
  • They only video call in low light conditions or with poor camera quality, which hides deepfake artifacts.
  • They refuse to perform spontaneous, unusual actions on camera (touching their face, holding an object near their face, turning sideways).

Typical Example

James, a 46-year-old financial advisor in Toronto, matched with "Sophie" on Hinge. Her profile showed a naturally beautiful woman with casual, everyday photos. After a week of messaging, James asked for a video call, having read that it was the best way to detect catfishing. Sophie agreed immediately.

On the call, James saw the same face from Sophie's photos. She smiled, laughed, and responded naturally to his questions. The call lasted 15 minutes, and James was completely satisfied that Sophie was real. He noticed the video quality was slightly grainy, but Sophie explained she was on hotel Wi-Fi for a work trip.

Over the following month, they had three more video calls. Each time, Sophie looked exactly like her photos but always cited poor internet as the reason for below-HD quality. James fell deeply in love.

Then Sophie revealed she had been offered a once-in-a-lifetime investment opportunity in a pre-launch tech startup but was short $15,000 on the minimum investment. She showed James a professional-looking prospectus and said she could triple his money in 60 days. James, who trusted Sophie completely after multiple video calls, transferred $15,000. Sophie asked for another $10,000 for "accelerated shares." After sending $25,000 total, Sophie went dark. The startup did not exist. The person behind "Sophie" had used real-time deepfake software to impersonate the woman in stolen photos. James had been fooled by a technology he did not know existed.

What to Do If You're a Victim

If you suspect you have been deceived by a deepfake video call scam:

  1. Do not feel foolish: Deepfake technology is specifically designed to defeat human perception. Even cybersecurity professionals have been deceived by high-quality deepfakes.
  2. Preserve recordings if possible: If you recorded any video calls, this evidence is valuable for law enforcement and can be analyzed for deepfake artifacts.
  3. Stop all communication and payments: Block the scammer on all platforms immediately.
  4. Contact your financial institutions: Report all fraudulent transactions to your bank. If you invested in a platform, contact the relevant financial regulatory body.
  5. Report to law enforcement:
    • FBI IC3: ic3.gov (include details about the deepfake aspect, as the FBI tracks this emerging trend)
    • FTC: reportfraud.ftc.gov
    • Action Fraud (UK): actionfraud.police.uk
  6. Reverse image search the photos: Even if the video call seemed to match the photos, the photos themselves may still be stolen. A reverse image search may reveal the real owner of the face used in the deepfake.

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