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There is no single visual clue that proves a video is a deepfake. Check what the clip claims to show, trace where it came from, verify its date and context, and look for independent evidence before sharing it. If those checks do not settle the question, describe the video as unverified—not definitively real or fake.
First, separate the video from the claim attached to it
A clip can be misleading without being an AI-generated face swap. CISA distinguishes synthetic media, including AI-generated or manipulated material, from “cheapfakes”: “a less sophisticated form of manipulation involving real audio clips or videos that have been sped up, slowed down, or shown out of context to mislead.” A genuine recording can therefore support a false impression if it is edited or presented with the wrong context. CISA’s Tactics of Disinformation discusses both forms.
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Before assessing authenticity, write down the specific claim: what is the video said to show, who posted it, and when and where is the event supposed to have happened? Keep the caption’s assertions separate from what the footage itself establishes.
Use a source-and-context workflow
1. Trace the earliest source you can find
Search distinctive frames or imagery with a reverse image search. CISA recommends publicly available tools of this kind for verifying media sources. Follow promising results to the original pages and inspect dates and context; a matching thumbnail or a later repost does not by itself confirm the claim. CISA’s guidance explains the role of source verification.
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2. Check the date, place, and surrounding footage
Compare the post’s account of when and where the clip was recorded with the source page, full-length footage, and independent reporting. Ask whether the video shows the claimed event or an older or different one. Even authentic footage can mislead when it has been clipped, sped up, slowed down, or stripped of context.
3. Look for independent corroboration
Seek reporting or records that offer their own evidence or access to the event. Several accounts repeating the same upload are not necessarily several independent confirmations; they may all be relying on one source.
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4. Treat visual oddities as leads, not verdicts
An apparent mismatch between a face and body could prompt closer investigation: CISA describes one face-swap technique as using machine learning to place one person’s face onto another person’s body. That description does not validate any particular visual artifact as a reliable test. The sources cited here do not establish blink patterns, lip movement, facial edges, lighting, or other single visual clues as conclusive evidence of a deepfake. CISA’s educational script describes the face-swap technique.
5. Report uncertainty honestly
If you cannot trace the source or find independent support, say that the video’s authenticity remains unverified. Do not turn suspicion into a factual accusation about a person or an event.
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How much weight should you give a deepfake detector?
Treat a detector score as one uncertain signal, not authentication. A detector can produce false positives as well as miss manipulated media. A 2023 research paper hosted by the Federal Trade Commission warns that false positives can contribute to suspicion, distrust, and social or legal consequences, and examines how detector errors can vary across demographic groups. Its benchmark results apply to the data, methods, and test conditions studied; they do not establish the performance of a consumer tool on every new video. Read the FTC-hosted paper.
When evaluating a detector result, ask what media, population, dataset, and decision threshold were used in its evaluation. The paper’s introduction cites earlier work reporting “up to 10.7% difference in error rate between groups” for three detectors; that is a finding attributed to the earlier study, not a general measure of current consumer-tool accuracy. A score alone is not a sound basis for publicly labeling a video or its subject.
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Deepfakes and cheapfakes: what the distinction tells you
| Category | How it may be manipulated | What the category does not establish |
|---|---|---|
| Synthetic or deepfake media | AI may generate or manipulate media; one possible technique places one person’s face onto another person’s body. | The label alone does not prove a specific clip is synthetic, or establish the poster’s intent. |
| Cheapfakes | Simple edits or presentation choices—for example, speeding up, slowing down, or showing a real clip out of context—can mislead. | A genuine recording does not necessarily support the claim made in its caption. |
The distinction helps identify possible ways a clip could mislead; it is not a shortcut to deciding whether a particular video is authentic. CISA’s guidance defines cheapfakes and discusses synthetic media.
What official guidance does—and does not—offer viewers
A joint NSA, FBI, and CISA release urges organizations to review its related information sheet for recommended steps to “prepare, identify, defend against, and respond to deepfake threats.” That is organizational threat guidance, not a consumer checklist of visual signs that can settle whether an individual clip is real. Read the agencies’ release.
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