For decades, people have been told to “trust their eyes.” But in the age of generative AI, that advice is no longer enough. Enter deepfakes, the highly realistic videos, images or audio recordings created or manipulated with artificial intelligence. Yes, we are actually living in the future now. Such content is making it increasingly difficult to tell the difference between what is real and what is fabricated. A politician may appear to say something they never said. A celebrity may seem to promote a fake investment scheme. A family member’s voice may appear in an urgent call asking for money. A company executive may seem to authorize a financial transfer. And the list goes on.
However, I think it's important to understand that the technology behind deepfakes is not always malicious, but it has received a notorious reputation of being misused. It can actually be used in harmless or constructive ways, for instance in entertainment, satire, accessibility, education and creative production. But cybercriminals have quickly turned it into a powerful tool for fraud, manipulation and social engineering, and we'll dive more into that.
What Are Deepfakes?
In simple terms, deepfakes are synthetic or altered media generated with AI. They can replace a person’s face, clone a voice, imitate speech patterns, change expressions or generate entirely fictional scenes that appear authentic. Modern deepfakes can be extremely convincing because they combine several AI capabilities at once: facial mapping, voice cloning, lip-syncing, natural language generation and video editing. The result can look and sound believable enough to bypass human judgment, especially when viewed quickly on a phone, shared in a group chat or attached to an urgent request.
This is the real danger: deepfakes do not need to be perfect. They only need to be convincing enough, for long enough, to make someone click, share, pay, vote, panic or trust the wrong person.
And by being convincing, they spread rapidly, both manually and with the help of algorithms.
Why Do Deepfakes Exist?
Deepfakes exist because generative AI has made it easier, faster and cheaper to create realistic synthetic content. In legitimate contexts, like mentioned earlier, this technology can support film production, digital avatars, language dubbing, parody, education and accessibility tools. However, the same capabilities are now attractive to scammers. A fake video of a trusted public figure can make a fraudulent investment appear legitimate. A cloned voice can make a phone scam feel personal. A manipulated video can damage reputations, spread misinformation or create false urgency during political, financial or social events. Deloitte has warned that generative AI could drive fraud losses in the U.S. to $40 billion by 2027, up from $12.3 billion in 2023. Bitdefender’s own consumer research also shows why this matters: AI scams, including deepfakes, are now a leading concern for internet users, while social media has overtaken email as the top channel for successful scams. AI is changing the rules of the game here as well.
How Deepfakes Manipulate People
Deepfakes work because they exploit human trust. People are naturally more likely to believe something when it appears to come from a familiar face, a recognizable voice or a respected authority figure. Cybercriminals take advantage of this by impersonating people users already trust: celebrities, executives, politicians, influencers, journalists, customer support agents, friends or family members. This is the most insidious tactic employed by bad actors. Most deepfake scams rely on a few psychological triggers, and there are a few notable examples here. The first and perhaps most common one is the example of authority. A fake CEO, government official, doctor, police officer or public figure tells the victim to act. Then there's of course the urgency trigger, where the victim is told there is no time to verify the request. Next, they are exploiting fear.
Here, the message suggests danger, legal trouble, financial loss or a family emergency. Another trigger is greed. Deepfakes also press sensitive buttons by promoting a fake investment, a giveaway, crypto scheme or “exclusive” opportunity to earn quick revenue (btw, there's no such thing, so let's get this straight once and for all). There's no "easy money", there's always a catch and "too good to be true" is of course a cliche, but for good reason.
Social proof is yet another way of sneaking deception in. A familiar person appears to endorse a product, platform or idea. But in reality, that person never did that.
This is why deepfakes are so effective. They don’t just fake content, they fake trust.
Who Is Most Vulnerable?
The truth is, no group is immune to deepfakes. Anyone who uses social media, messaging apps, video platforms or online financial services can be targeted. And when someone thinks "it won't happen to me", or "I can't fall for these silly tricks" this is exactly the type of ignorance that makes them so lucrative, and because people are caught off guard and not really paying attention to this.
However, some users can be more exposed or more vulnerable depending on the scam type.
As explained previously, Bitdefender’s research found that social media is now the leading channel for successful scams, with users aged 25–34 more than twice as likely as those 55+ to be scammed through social media. This makes highly connected social media users especially exposed to deepfake ads, fake endorsements and impersonation campaigns.
Older adults may face a different kind of risk in the form of emotionally manipulative scams involving family emergencies, cloned voices or trusted public figures. A recent Bitdefender survey found that nearly half of respondents aged 55+ worry about AI scams, including deepfakes.
The most vulnerable category, therefore, is not defined only by age. It is anyone placed in a high-pressure moment where trust, fear and urgency override verification. In practice, that often includes social media users, online shoppers, investors, employees handling money or data, and families receiving alarming messages from seemingly familiar voices or faces. And now we move to the dangerous part where things become concerning.
Why Deepfakes Are Dangerous
We can argue that deepfakes are dangerous because they attack the trusted foundations of digital life. There are often mixed with real content, in a newsfeed or series of videos and this allows them to camouflage themselves even better, especially if we are talking about platforms that users consider trustworthy. Deepfakes can be used for a variety of purposes, and there's always a motivation behind them.
They can be used to steal money through fake investment ads, romance scams or emergency requests. They can be used to harvest login credentials by impersonating trusted brands or support teams. A common objective is to spread political misinformation or manipulate public opinion in times of unrest, or during ellections or important global events. To attract unsuspecting followers for a specific party, candidate, side or ideology. To damage reputations through fabricated videos or false statements, or to commit business fraud by impersonating executives or colleagues.
And of course, to pressure people into sharing personal, financial or sensitive information, which can later be used for fraudulent purposes.
In one widely reported case cited by Deloitte, a finance worker in Hong Kong transferred $25 million after joining a video call where fraudsters used deepfake technology to impersonate company executives. So, if you still think deepfakes are inoffensive, think again. For everyday internet users, the risk is becoming more personal. The circumstances and context matter a lot. A deepfake may arrive as a video in a social feed, a link in a message, an ad featuring a celebrity, or a file forwarded by someone they trust. By the time the victim realizes something is wrong, the money may be gone, the account may be compromised, the reputation may be irreversibly damaged, or the false content may have already spread.
How to Spot a Deepfake
Here's where common sense and situational awareness come into play. Deepfakes are becoming harder to detect with the nake d eye, but internet users can still reduce their risk by slowing down and looking for warning signs. Be cautious if a video or audio clip includes:
- Unnatural facial movements, blinking or expressions
- Poor lip-syncing or speech that does not match mouth movement
- Strange lighting, shadows or skin texture
- Robotic, flat or slightly distorted voice patterns
- Background glitches or visual warping
- Unusual phrasing that does not match how the person normally speaks
- A request for money, credentials, personal data or urgent action
- A celebrity or public figure promoting an investment, giveaway or “secret” opportunity
- A video shared without a credible original source
However, visual clues are no longer enough. Why? Because high-quality deepfakes can look very convincing, especially on small screens or compressed social media videos. That is why detection must combine user awareness with trusted technology.
With this concept in mind, Bitdefender has introduced RealCheck, a standalone deepfake detection solution designed to help consumers evaluate whether video content has been manipulated and whether it carries malicious intent, such as financial fraud, credential theft or defamation. RealCheck is available for Android and iOS and allows users to submit a video link or upload a file for analysis. Instead of offering a simplistic verdict, it provides a structured report assessing manipulation likelihood, deceptive intent and transcript-level indicators.
How Bitdefender RealCheck Helps. Do You Need It?
Well, RealCheck was created for this new reality, one where consumers need more than instinct to decide whether a video can be trusted. And this new reality is not going away, as AI technology evolves rapidly, deepfakes will get even better. Or worse, for that matter.
As explained earlier, RealCheck allows users to submit a video link or upload a file for analysis. The good part is that it works across local uploads, web-hosted videos and major social platforms including X, YouTube, Instagram, Facebook and TikTok. It can also help identify public figures, celebrities, business executives and politicians who are being impersonated or misused in active deepfake campaigns.
I think what makes RealCheck especially useful is its layered approach. It does not simply label a video as fake or real. It evaluates the likelihood that the video or audio was manipulated, it investigates whether the content shows signs of deceptive or malicious intent, it has transcript-level indicators that may reveal suspicious claims, pressure tactics or scam language, and researches specific segments where manipulation may have occurred. This matters because yet again, not every synthetic video is harmful. Some are clearly satire, parody or entertainment. Yes, the irony here is that deepfakes can also be used for fun. The app helps users understand both authenticity and intent, so they can make safer decisions before they trust, share or act.
Another feature I like about this app is that RealCheck reports are also shareable, allowing people to warn friends and family even if they don't have an account. That can be especially valuable when a suspicious video spreads through a family group chat, social feed or community group. I can relate to this because I started to find more and more deepfake content being shared by relatives and friends, and this was also one of the reasons I decided to write this article.
Perhaps the best defense against deepfakes is a combination of skepticism, verification and security tools. Users should also avoid clicking suspicious links, downloading unknown files, sending money based on video or voice instructions, or trusting investment advice from celebrity videos on social media. If a family member, colleague or executive appears to make an urgent request, verify it through a separate channel, for example, by calling a known phone number rather than replying to the message.
Of course, strong cybersecurity habits still matter. As the safety rulebook says, use unique passwords, enable multi-factor authentication, protect devices with a trusted security solution, keep apps and operating systems updated, and be careful about what personal content you share online. The more public voice, video and image data scammers can access, the easier it may be to impersonate someone. And this is a fact. This is how scammers can target with such precision. They use the publicly available information shared by their targets directly or indirectly online, to craft and personalize their attacks. Once again, think twice before oversharing online.
Trust, But Verify
I think we can conclude that deepfakes are not just a technology problem. They are a trust problem. They exploit the way people make decisions online, and that is quickly, emotionally and often on mobile devices. They turn familiar faces into fraud tools and trusted voices into attack vectors. As AI-generated scams become more convincing, I think consumers need a new habit. To pause before believing, verify before acting, and use trusted tools before sharing. Deepfakes have become one of the strongest tools of deception out there. In a digital world where seeing is no longer believing, verification is protection.
I think this new RealCheck app gives users a practical way to do exactly that. By analyzing manipulation likelihood, deceptive intent and transcript-level clues, it helps people separate fact from fabrication before a scam becomes a loss, or before they share manipulative content to others. As deepfakes proliferate across social media at an unprecedented pace, tools that can help separate truth from fiction are finally emerging, and this is a good thing, because harmful deepfakes will continue to exist, and this is a real-world problem which can no longer be ignored.
Did you ever doubt a video you saw online, or have you ever been tricked by a deepfake?
Share your experiences in the comments below and make sure to get the RealCheck app at the links above.
It's definitely worth it.
