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Published on 2026-07-25

How can you actually tell if a video is a deepfake?


A famous fake was caught by a bent neck and total silence elsewhere. Both clues fade fast with better software, but one of them never will.

Three weeks into the full-scale invasion of Ukraine, in March 2022, a video hit Ukrainian TV screens and social feeds within minutes of each other. President Volodymyr Zelenskyy, standing at a podium, told his soldiers to lay down their weapons and surrender. Except he never said any of it.

Hackers had slipped the fake clip onto the scrolling news ticker of a Ukrainian broadcaster and pushed it out on social platforms at the same time. Fact checkers at Lead Stories had it debunked within a day: Zelenskyy's neck, in a side by side comparison with real footage, was grossly out of proportion with his head, a seam left by software that had stitched a fabricated face onto old footage of his body. Meanwhile nobody, not Ukrainian officials, not Russian state media, not even Vladimir Putin, said a word about any surrender. The real Zelenskyy spent that day meeting European leaders and addressing the US Congress, then recorded a new video calling the fake 'a provocation'.

None of this required exotic tools. It required checking what else was happening that day: in-person meetings with three European leaders, a session with the International Criminal Court's prosecutor, a speech to Congress by video link. A man cannot be surrendering his army and doing all of that at once. The fake fell apart the moment someone looked away from the screen and asked what everyone else was reporting.

What still gives a fake away

Video deepfakes are built by training software on hundreds of images of a real face, then mapping that face onto someone else's performance. The stitching leaves marks, at least for now. Blinking is one of them: a 2018 study by researchers at the University at Albany found that resting adults blink around 17 times a minute, more while talking, less while reading, and that early deepfake models simply had not learned that rhythm, because the training photos scraped from the internet mostly show people with their eyes open. A face that barely blinks, or blinks with a strange, clockwork regularity, is worth a second look. Those researchers built a detector that combined two kinds of neural network and caught the irregular pattern with 99 percent accuracy in their tests, against 79 percent for a simpler method that just measured how open the eyes were frame by frame.

Except the list keeps changing

Here is the catch. The very year that blinking study came out, newer generators had already learned to fake blinking convincingly. Every detection trick built on a visible flaw has a shelf life, because whatever gets published as a giveaway becomes, within months, a bug the next model fixes. Chasing today's list of tells is a bit like memorising last season's lock picks: useful until the locks change, and they always do. A checklist that worked last year against last year's tools tells you nothing about the tool released last week.

The one thing that does not expire

What actually cracked the Zelenskyy case was not the neck, even though it helped. It was the silence everywhere else. No credible outlet, in any country, reported that Ukraine had surrendered. Not one. A claim that dramatic, if genuine, does not stay confined to a single hacked video feed: it shows up in wire reports, official statements, even enemy propaganda gloating about it. When it shows up nowhere except the clip itself, that absence tells you more than any frame of the video does.

A face can be faked in an afternoon. A day of independent, boring confirmation from other sources is much harder to fake.

So look at the neck, the blink, the lips, by all means. Those checks are free, and sometimes they catch a clumsy fake outright. Just do not stake your judgment on them alone, because the tools update constantly. Reporting from three continents on the same Tuesday does not.

Topics : deepfakes video verification

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