Case Study 18-1: The Zelensky Deepfake Surrender Video (March 2022)

Overview

On March 16, 2022, three weeks into Russia's full-scale invasion of Ukraine, a video appeared on social media platforms and Ukrainian television channels showing a figure appearing to be Ukrainian President Volodymyr Zelensky. In the video, he stands against a background and delivers a short message — approximately 60 seconds — that appeared to order Ukrainian soldiers to lay down their arms and surrender to Russian forces. The video was posted to a hacked Ukrainian news website and subsequently shared across Russian Telegram channels and other social media platforms.

Within hours, the video had been identified by deepfake researchers, platform moderators, and Ukrainian officials as synthetic. Zelensky himself posted a video from his presidential office complex — geotagged to demonstrate he was still in Kyiv — debunking the video. Meta removed the video from Facebook and Instagram. YouTube removed it from their platforms. The incident was over quickly by the standards of disinformation events.

Yet it was not without consequence. It required a response from a sitting head of state in the middle of an active war. It demonstrated — for the first time in an active military conflict — that deepfake technology could be weaponized as a disinformation tool in information warfare. And it raised questions that remain important: what would happen when the technology improved? How will future conflict deepfakes be handled?

This case study examines the technical characteristics of the video, the information dynamics of its spread and debunking, the geopolitical context, and the lessons it offers for understanding synthetic media in conflict environments.

Technical Analysis of the Video

What Made It Detectable

Researchers at various institutions — including the Digital Forensic Research Lab (DFRLab) at the Atlantic Council — analyzed the video and identified several specific technical anomalies that marked it as synthetic:

Proportional inconsistencies: The most immediately obvious artifact was that Zelensky's head appeared disproportionately large relative to his body and the background behind him. This is a characteristic artifact of the face-swapping approach used: the face-swap process typically handles the face region well but struggles with the neck, shoulders, and background integration, creating jarring proportional inconsistencies.

Flat and robotic audio: The voice in the video sounded flat and mechanical — lacking the natural prosodic variation and emotional emphasis characteristic of human speech. The audio was likely generated by a text-to-speech system rather than being a voice clone of Zelensky's actual voice. Trained listeners immediately identified it as synthetic, and even casual listeners found it unnatural.

Lighting and texture inconsistencies: The facial lighting in the video appeared inconsistent with the apparent lighting of the background — the face was lit differently than it would be in a genuine video. This inconsistency is a common artifact when a generated face is applied to a different background.

Limited motion: The figure in the video exhibited limited and somewhat mechanical movement — a common characteristic of talking head generation systems that animate a static face image rather than tracking a genuinely moving subject.

Background inconsistency: The background used in the synthetic video appeared to be a different setting than Zelensky's typical media appearances, and the integration between the foreground figure and background was imperfect.

What This Tells Us About the Technology Used

Based on the artifact profile, researchers assessed that the video was produced using a "talking head" generation system — likely a system like DeepFaceLab or a similar tool — rather than the more sophisticated real-time face-swap systems. The producers appear to have taken a static or limited-motion image of Zelensky and animated it to speak the surrender text, with text-to-speech audio overlay.

This assessment is consistent with the crude quality: the video used technology that was widely available at the time and that required no specialized expertise or significant computing resources. It was not a state-level production using advanced synthetic media capabilities.

Contrast with capabilities: Even at the time of the video, more sophisticated deepfake tools could have produced significantly better results. The crude quality suggests either haste (a quickly produced propaganda asset for rapid deployment), limited technical capability on the part of the producers, or a deliberate choice to produce something "good enough" for the intended audience and distribution channel.

Information Dynamics: Spread and Debunking

The Spread

The video was initially posted to the website of Ukrainian news channel "Ukraine 24," which had been hacked to host the content. This was a deliberate choice: the authentic-seeming source gave the video initial credibility before the hacking was identified. From Ukraine 24, the video spread to:

  • Russian Telegram channels, where it was shared by pro-Russian accounts with commentary presenting it as genuine.
  • Russian social media platforms.
  • International social media platforms including Facebook, Twitter, and Reddit, where it was shared both by those who believed it and those who were fact-checking or debunking it.

A crucial element of the spread: the video also appeared briefly on the air of the real Ukraine 24 television channel — another indication that the website hacking may have been accompanied by other infrastructure compromises. This brief on-air appearance gave the deepfake an additional layer of apparent credibility.

Platform Response

The speed of platform response was notably effective in this case:

Meta: Facebook's automated systems flagged the video, and human reviewers removed it relatively quickly. Meta cited its deepfake policy — which prohibits videos edited by AI in ways that are misleading — as the basis for removal.

YouTube: Google/YouTube removed the video under its existing deepfake and disinformation policies.

Twitter/X (at the time under pre-Musk leadership): The video was labeled as manipulated media using Twitter's existing synthetic media labels.

The effective platform response was aided by several factors: the video's crude quality made automated detection more feasible; the fact that it depicted a major world leader with substantial platform monitoring gave it heightened review priority; and the geopolitical context (active armed conflict) meant platform trust and safety teams were already monitoring for exactly this type of content.

Zelensky's Response

Zelensky's own response was rapid and effective. He posted a real-time video from the government quarter of Kyiv — a location that could be geolocated — in which he stated, in Ukrainian, that he had not posted any surrender video and that Ukrainian forces would continue to fight. He also appeared in a press conference the same day.

The effectiveness of Zelensky's response depended on several factors: - His established public presence: audiences familiar with Zelensky's genuine video appearances had references for comparison. - The geolocatable context: the genuine response video provided verifiable location information. - The coordination with platform removals: the combination of platform action and direct debunking accelerated the debunking process.

Geopolitical Context

Russia's Information Warfare Strategy

Russia's 2022 invasion of Ukraine was accompanied by a sophisticated information warfare campaign that preceded the military invasion. The Russian information operation included: spreading disinformation about Ukrainian government officials (claiming they had fled, were incapacitated, or were planning to surrender); amplifying internal Ukrainian disagreement; and attempting to demoralize Ukrainian civilian and military populations.

The Zelensky surrender deepfake was consistent with this strategic objective: undermining confidence in Ukrainian leadership, creating confusion about the government's actual position, and potentially providing a pretext for Russian military claims that Ukraine had signaled willingness to negotiate.

The target audience question: The video's intended audience is important for assessing its potential impact. If intended primarily for Russian domestic consumption — to reinforce the narrative that Ukraine was losing and its leadership was collapsing — then its crude quality was less important. Russian domestic audiences consuming Russian state media might not have compared it critically to genuine Zelensky appearances. If intended for Ukrainian or international audiences, the crude quality substantially undermined its effectiveness.

The Coup Attempt Parallel

The Zelensky deepfake shares a structural feature with the Gabon Bongo controversy discussed in Section 18.5: in both cases, a video showing a leader behaving in a way inconsistent with expectations (Zelensky surrendering, Bongo alive and apparently healthy) was contested as potentially synthetic. The political consequences of the contest were real regardless of the video's actual authenticity.

In Zelensky's case, the video was fake and the debunking was rapid. In Bongo's case, the video was likely authentic and the deepfake allegation was itself a form of disinformation. Both cases illustrate how the deepfake context — the knowledge that synthetic media is possible — creates new political dynamics around video evidence.

The "Why Now" Question: Why Deploy a Crude Deepfake?

A question that analysts have discussed is why the perpetrators deployed a video of this quality when more sophisticated tools were available. Several hypotheses:

Speed over quality: In an active military conflict, speed may be more valuable than quality. A crude deepfake deployed rapidly might serve its propaganda function before the quality becomes the focus of attention.

Target audience considerations: For audiences consuming content on low-bandwidth platforms, or Russian domestic audiences not expected to compare critically, the video's quality may have been considered adequate.

Testing and probing: The deployment may have been intended partly as a test of Ukrainian platform defenses and response capacity — learning how quickly the video would be detected and removed.

The "good enough" principle in disinformation: Research on disinformation operations has consistently found that production values are often lower than one might expect given the resources of the operators. The goal is often not to convince every viewer but to confuse, distract, and create enough uncertainty to serve the propaganda objective.

Lessons for Future Conflict Deepfakes

Lesson 1: The Technology Will Improve

The crude quality that made the March 2022 video quickly detectable will not be characteristic of future conflict deepfakes. The rate of improvement in synthetic media quality, combined with declining production costs, means that state and non-state actors with modest resources will soon be able to produce deepfakes substantially more convincing than the 2022 Zelensky video.

The window in which easy detection is available based on artifact quality is closing. Future conflict deepfakes may not be identifiable through casual viewing.

Lesson 2: Rapid Response Depends on Established Infrastructure

The rapid and effective response to the Zelensky deepfake depended on infrastructure that will not always be in place: - Platform trust and safety teams monitoring for specific content - Deepfake researchers with established presence on relevant social media platforms - A credible subject (Zelensky) with the platform, resources, and security to post an immediate authentic video response - Geopolitical context that made this specific video a high-priority monitoring target

Conflicts in regions with less developed platform monitoring, less media-savvy leadership, or more restricted internet environments may face very different conditions.

Lesson 3: The Liar's Dividend Works in Both Directions

The Zelensky case illustrates a bidirectional version of the Liar's Dividend. The fake surrender video was debunked (clear benefit). But the Bongo parallel suggests an equally concerning scenario: what if a genuine video of a leader saying something compromising is dismissed as a deepfake? The existence of the deepfake technology creates plausible deniability for both synthetic and authentic content.

Russian state media has claimed that various authentic videos of Russian military atrocities — in Bucha and elsewhere — were staged or fabricated. While these specific claims have been comprehensively refuted through independent investigation (satellite imagery, forensic analysis, witness testimony), the pattern of claiming that authentic evidence is fabricated is well-established. Deepfake technology provides an additional layer of technical-sounding plausibility to these denials.

Lesson 4: Pre-Bunking and Media Literacy Matter

Ukraine's relatively effective response to the deepfake — both at the platform level and in public communication — reflects a broader Ukrainian investment in media literacy and disinformation response that predated the 2022 invasion. Ukrainian journalists, NGOs, and government communicators had developed significant capacity for rapid fact-checking and disinformation response during years of hybrid information warfare with Russia.

This suggests that media literacy and pre-bunking investment (preparing audiences for synthetic media disinformation before it occurs) have practical value in reducing the impact of conflict deepfakes.

The Zelensky deepfake revealed a significant gap: there are no established international norms, treaties, or law-of-war provisions that clearly address the use of deepfakes in armed conflict. The laws of armed conflict prohibit "perfidy" — deception that betrays the enemy's reliance on legal protections — but it is unclear how this provision applies to synthetic media. The question of state responsibility for synthetic media disinformation in conflict remains legally unsettled.

Discussion Questions

  1. The Zelensky surrender deepfake was debunked quickly and effectively. Does this suggest that the current threat from political deepfakes is overstated, or does it reveal the special conditions required for effective debunking that will not always be present?

  2. The video's crude quality is described as a factor in its rapid identification. As technology improves, who bears primary responsibility for maintaining detection capacity — platforms, governments, academic researchers, or individual media consumers?

  3. Russian information warfare strategy is described as including the use of deepfakes as part of a broader disinformation campaign. How should democratic countries respond to state-sponsored synthetic media disinformation? What legal and diplomatic tools are available?

  4. Ukraine's effective response to the deepfake is attributed partly to media literacy investments that predated the invasion. What investments in media literacy infrastructure should democratic societies make as a form of preparedness for synthetic media disinformation?

  5. The laws of armed conflict regulate many forms of deception and propaganda in wartime. Should deepfakes in armed conflict be regulated under existing international humanitarian law, under new treaty provisions, or primarily through other mechanisms? What are the practical challenges of any of these approaches?

  6. Consider the argument that the existence of the Zelensky deepfake — even though debunked — was itself a propaganda victory for Russia because it required Zelensky to respond to it, consuming attention and resources and generating international media coverage of the deepfake story. Is this assessment accurate? What does it imply about the effectiveness threshold for disinformation operations?