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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteThere is no single visual clue that can reliably prove a video is a deepfake. Check the clip’s original source, the claim and context attached to it, and independent evidence before deciding what it shows or sharing it. If those checks do not settle the question, describe the video as unverified—not as definitively real or fake.
Start with the claim, not the pixels
Separate what the video visibly contains from what its caption says. Write down who posted it, what it is claimed to show, and when and where the event allegedly happened. Those details give you specific facts to verify rather than leaving you to judge authenticity by appearance alone.
Also distinguish a deepfake from other misleading edits. The Cybersecurity and Infrastructure Security Agency (CISA) describes deepfakes as synthetic media created or manipulated with AI. A face swap is one possible technique: machine learning can place one person’s face onto another person’s body. But a video need not be AI-generated to mislead.
CISA calls relatively simple edits “cheapfakes,” defining them as “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 be presented deceptively through editing or a misleading caption. Read CISA’s guidance on tactics of disinformation.
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| Type | What may have been changed | What the category does not prove |
|---|---|---|
| Synthetic or deepfake media | AI may generate or manipulate media, including placing one person’s face onto another person’s body. | The label alone does not establish the clip’s intent, context, or truth. |
| Cheapfake | Simple editing or context removal, such as speeding up, slowing down, or presenting real footage out of context. | The clip may be misleading even though it is not an AI face swap. |
Trace where the video came from
- Search for distinctive frames. Use reverse image search on a clear frame or distinctive imagery from the clip. CISA recommends publicly available tools such as reverse image search to help verify media sources. See CISA’s source-verification guidance.
- Inspect the results and the pages behind them. Look for an earlier copy, an original publication, or reporting that identifies the footage. A matching thumbnail or a search result that repeats the caption is only a lead; it does not by itself verify the claim.
- Compare the earliest traceable version. Check whether its date, description, and surrounding footage match the claim now attached to the clip. An older copy can help establish provenance, but it may still be mislabeled or taken out of context.
Check the context and seek independent evidence
Compare the alleged date, place, people, and event with the full surrounding footage and independent reporting. Ask whether the clip shows what its caption says it shows, rather than assuming that finding the same video elsewhere confirms the caption.
Look for corroboration from sources with their own evidence or access to the event. Several accounts repeating the same upload may all trace back to one source; repetition is not the same as independent confirmation.
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Context checks matter even when the recording itself is genuine. A short excerpt, altered playback speed, or missing lead-in can change how a real event appears. Verify the event and the presentation of the clip separately.
Treat visual oddities as leads, not proof
A face that appears mismatched with the body may prompt you to investigate whether a face swap was used. It does not establish that the clip is fake, and an ordinary-looking video is not thereby proven genuine.
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The sources cited here do not validate blink patterns, lip movement, edges, lighting, or other individual visual artifacts as conclusive tests. Use anything that looks unusual as a reason to check provenance and context, not as a verdict.
Use detector results cautiously
A deepfake detector can offer another signal, but its score is not authentication. Detector results depend on the data, methods, and thresholds used, and a result on one clip does not settle the video’s history or context.
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A 2023 paper hosted by the Federal Trade Commission (FTC) discusses the consequences of false positives, including suspicion, distrust, and social or legal harm, and reports that detector errors can vary among demographic groups. Its benchmark findings apply to the tested data and methods; they do not establish how reliably any consumer service will classify a new video. Read the FTC-hosted 2023 paper.
When evaluating a detector result, check what population, dataset, media type, and threshold were tested. Do not publicly accuse a person or label a video as fake based only on a score. The available evidence does not establish a single best consumer detector or a universal real-world accuracy figure.
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Decide what you can responsibly say
- Source and context are supported: Describe what the evidence establishes, and avoid claiming more than it does.
- The source or context remains unclear: Say the video is unverified. Lack of confirmation is not proof that it is fake.
- You are considering sharing or accusing someone: Pause until independent evidence supports the specific claim. A visual impression or detector score alone is not a sound basis for a factual accusation.
For organizational rather than personal guidance, a joint NSA, FBI, and CISA release urges organizations to review its related information sheet for steps to “prepare, identify, defend against, and respond to deepfake threats.” That is threat-response guidance, not a consumer checklist for deciding whether a particular clip is authentic. Read the agencies’ advisory.
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