Bot Traffic Steady After Yandex Strikes, Despite Zelenskyy’s Claims

Ukrainian drone strikes on Yandex data centers prompted claims of cleaner social platforms, but trackers say bot activity is steady. Operators should not treat those claims as verified data.

What happened

Days after Ukrainian military drones took down several Russian data centers, President Volodymyr Zelenskyy claimed Monday that the operation had hurt Russia’s disinformation efforts. “It suddenly became a little easier to breathe on many social platforms,” Zelenskyy said. “There was less hate, less division, and fewer provocations.”

The strikes targeted data centers belonging to the Russian technology company Yandex. In the following days, social media users reported seeing less traffic on posts by MAGA-affiliated accounts and accounts tied to the far-right Alternative for Germany (AfD) party. Some users also said they noticed a steep drop in spam calls and messages.

Those observations are not supported by the available tracking data. The drone strikes appear to have affected Yandex’s web crawlers, not any disinformation or political operations.

Key facts

• Ukrainian drone strikes hit Russian data centers belonging to Yandex, and Zelenskyy said Monday that social platforms had “less hate, less division, and fewer provocations.”
• Social media users attributed lower traffic on MAGA-affiliated and AfD accounts to the strikes, with some reporting fewer spam calls and messages.
• The Verge reports the strikes appear to have affected Yandex’s web crawlers, not disinformation or political accounts.
• antibot4navalny, which tracks state-sponsored troll farms, reported bot traffic is steady as ever; on Monday, Kremlin-aligned accounts posted videos falsely claiming experts demand the EU lift sanctions on Russia.
• Danish analyst Valdemar Osted said interactions on MAGA and AfD accounts have actually increased since the strikes, and charts purporting to show a decline in bot activity appear to be AI-generated.

Our analysis

The gap between the official claim and the tracking data suggests a category error. Yandex web crawlers are infrastructure for indexing the web; bot farms and troll accounts are a separate coordinated activity. A strike on one system does not automatically mean the other is degraded. For content teams, that distinction matters because a false sense of platform health can change how they interpret engagement, moderation, and audience quality.

The fact that interactions on MAGA and AfD accounts reportedly increased after the strikes likely shows that coordinated activity can adapt or continue even when infrastructure is damaged. It also illustrates how quickly anecdotal evidence becomes a narrative: user complaints about spam calls and messages were folded into a political claim without supporting bot traffic data.

The AI-generated charts add another layer. If teams accept visual “proof” of a bot decline without source verification, they may make moderation or content decisions on fabricated data. The report from antibot4navalny offers a more reliable signal: bot traffic is steady, and Kremlin-aligned accounts were still posting coordinated false claims on the same day Zelenskyy declared the disinformation problem reduced.

What it means for operators

• Do not treat anecdotal drops in spam or engagement as evidence that bot activity has stopped. Check independent trackers such as antibot4navalny before adjusting community rules or content strategy.
• Treat charts and viral posts claiming a bot decline as unverified, especially when they support a political narrative. AI-generated charts can look credible while showing no real data.
• Monitor engagement quality and coordinated behavior rather than raw volume. If hostile or foreign-aligned activity persists, update blocklists, keyword filters, and report workflows promptly.
• Avoid amplifying claims about cleaner platforms or reduced disinformation until your team can verify the source. Internally correct the record so editors, moderators, and social managers don’t plan around a false assumption.