Practical guides for checking video sources, examining manipulation signals, and interpreting AI-related evidence without treating any single clue as proof.
Begin with the closest task, then follow related methods when one check is not enough.
An AI news video can look credible before it is credible. A synthetic anchor can read a real headline. Real disaster footage can be mixed with generated scenes. A genuine interview can receive cloned audio. A completely fictional event can be packaged with a logo, ticker, location tag, and “breaking news” banner that makes it […]
A deepfake app is software that uses AI to create or alter media so that a person can appear to have a different face, voice, expression, or performance. Some apps are built for entertainment and creative effects. Others can produce realistic impersonation content that is difficult to judge from a quick look at a phone […]
A voice clone scam succeeds when a familiar voice makes you act before you verify. The caller may sound like your child, manager, bank representative, government official, or someone you recognize from online videos. The audio may be AI-generated, but the fraud usually depends on something much older: urgency, authority, fear, secrecy, and a request […]
AI lip sync used to look like a cheap movie dub. Today it can look surprisingly convincing, especially in short clips on social media where you do not have time to study every frame. That is why AI lip sync is now a common ingredient in misinformation, scam ads, fake celebrity endorsements, and manipulated “apology” […]
A face swap video changes who appears to be performing an action without necessarily changing the performance itself. The body may be real. The camera may be real. The room, timing, gestures, and even the original voice may all be real. What changes is the identity viewers attach to that performance. That is what makes […]
Synthetic media is digital content whose image, sound, video, text, or other meaningful elements are generated or materially altered by automated systems, especially generative AI. It includes fully generated scenes, cloned voices, AI avatars, face swaps, synthetic narration, AI-edited footage, and multimodal content that mixes captured and generated material. But “synthetic” does not mean “false,” […]
Video provenance is the history of a video, not a verdict about whether it looks real. It asks where the footage came from, what happened to it between capture and the copy in front of you, and whether the story attached to that copy still matches the original context. This matters because a perfectly authentic […]
C2PA metadata is provenance information that can be cryptographically bound to digital media so people and software can inspect where an asset came from, how it was created, and what changes were declared along the way. It is used by the C2PA standard behind Content Credentials, and it applies to more than AI-generated media. A […]
Content Credentials are a way to inspect the recorded provenance of digital media. When a compatible photo, video, audio file, or document carries them, you may be able to see who or what signed the media, which tools were involved, what creation or editing actions were recorded, and whether the credential still validates against the […]
