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<span>Tunis</span>
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<span class="cat-tag tag-fact" style="display:inline-block;font-size:11px;font-weight:700;text-transform:uppercase;letter-spacing:0.8px;padding:3px 10px;border-radius:2px;margin-bottom:12px;">Fact-check</span>
<h1 class="font-serif" style="font-size:46px;line-height:1.1;margin:8px 0 16px;">
Is this viral video of flooding in Tunis authentic?
Our frame-by-frame verification
</h1>
<p style="font-size:20px;color:#4a4a4a;line-height:1.5;">
The 47-second clip topped 800,000 views on X and TikTok in two
days. Our Image–Caption Coherence and Edited Photo Detection
analyses reconstructed the origin of every shot.
</p>
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<div class="font-semibold">Maryem Ben Slimane</div>
<div class="text-sm text-gray-500">Lead — Caption Fidelity · Published April 27, 2026 at 9:42 AM</div>
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<img src="https://images.unsplash.com/photo-1547683905-f686c993aae5?auto=format&fit=crop&w=900&q=80" alt="Urban flooding" style="width:100%;height:auto;display:block;margin-bottom:20px;" />
<p class="text-sm text-gray-500 mb-8" style="font-style:italic;">
Screenshot of the viral video as it circulated on April 26 on X. Credit: "Tunisie en direct" account.
</p>
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<div class="sb-box why">
<span class="sb-label">Why it matters</span>
During extreme climate events, decontextualized videos amplify fear
and saturate emergency services. Verifying quickly and publishing
the chain of origin is the first line of defense.
</div>
<p style="font-size:17px;line-height:1.7;margin-bottom:18px;">
The video, first posted on Tuesday at 9:17 PM, shows submerged
streets presented as filmed "tonight in Tunis." Within 90 minutes,
the clip had been picked up by five pan-Arab accounts totaling 4.2
million followers. Our team began analysis at 10:04 PM.
</p>
<div class="sb-box big">
<span class="sb-label">The big picture</span>
Three key shots — out of the twelve in the video — come from a
separate flood event in Bab Bhar, in September 2018. Two new shots
were authenticated in Manouba this morning, around 6:12 AM.
</div>
<h2 class="font-serif" style="font-size:30px;margin:30px 0 14px;">What our modules found</h2>
<ul class="sb-bullets">
<li><strong>Image–Caption Coherence</strong> noted a 3,200 K luminance
shift between shots 4–7 and the rest: the classic signature of
nighttime archive footage re-injected into a daytime video.</li>
<li><strong>Edited Photo Detection</strong> isolated two added objects —
a road sign and a pharmacy sign — overlaid on 2018 frames.</li>
<li>The <strong>EXIF metadata</strong> was stripped on the viral
version, but the version posted 16 minutes earlier by another
account still carries a timestamp dated <strong>September 14, 2018</strong>.</li>
<li>By contrast, two shots (8 and 11) are <strong>authentic and unpublished</strong>:
they correspond to a local flood event that occurred this morning in Manouba.</li>
</ul>
<h2 class="font-serif" style="font-size:30px;margin:30px 0 14px;">How we established this</h2>
<p style="font-size:17px;line-height:1.7;margin-bottom:18px;">
The Verify verification process combines a reverse image search
(Yandex, TinEye, Google Lens) with our own visual analyses. For this
video, the first archived match was found in 4 minutes via TinEye
on frame 156. It pointed to a Mosaïque FM article published on
September 15, 2018.
</p>
<p style="font-size:17px;line-height:1.7;margin-bottom:18px;">
Once the source was identified, our analysts aligned each shot of
the viral video with the original archive, shot by shot. Shots 8
and 11 produced no match: they were then submitted to AI-Generated
Media Detection, which returned a confidence score &gt; 92% in
favor of authenticity.
</p>
<div class="sb-box next">
<span class="sb-label">What's next</span>
Our newsroom is opening an investigation into the Telegram channels
that first posted the video, and into the modus operandi — the same
archived shots were used last March for a false alert in Sfax.
Results expected on May 5.
</div>
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<h3>Want to verify suspicious content yourself?</h3>
<p>Upload an image, video or link — our five modules give you a score in less than 2 minutes.</p>
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<a href="verifier.html" class="btn-yellow">Verify this content</a>
</div>
<p style="font-size:17px;line-height:1.7;margin-bottom:18px;">
The stakes go beyond this one case. Over the past seven days,
Verify processed 421 user-flagged contents. 38% were marked as
manipulated, 17% as out of context. The rest — the majority —
is authentic: verification isn't just about debunking, it's also
about confirming.
</p>
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