Fake Video Call Using AI: How to Spot a Deepfake Call (2026 Guide)
Picture this: your phone rings, you see a familiar face on a video call, and the voice sounds exactly like someone you trust.
They’re panicked, they need money urgently, and there’s no time to think it through. Everything about the call feels real, because with today’s AI, it very nearly is.
In this context, many people tend to overlook even basic steps they should take to keep their bank accounts safe from hackers.
This isn’t a hypothetical anymore. In 2025 alone, Indians lost an estimated ₹22,495 crore, roughly $2.7 billion, to cyber fraud, and deepfake-driven scams are one of the fastest-growing pieces of that number.
A 2025 industry analysis found that 47% of Indian adults have either been a victim of, or personally know someone who has been a victim of, an AI voice-cloning or deepfake scam, nearly double the global average.
Of those who lost money, 83% suffered a financial loss, with nearly half losing more than ₹50,000. The uncomfortable truth is that spotting a fake video call by eye alone is getting harder every month, not easier.
This guide walks through what’s actually reliable to check for in 2026, why “watch for glitches” is no longer enough advice on its own, and exactly what to do, including how to report it, if you think you’re being targeted.
Quick Answer: How to Tell If a Video Call Is Fake
If you only remember one thing from this guide, make it this: verify through a second, independent channel before you act, especially before sending money.
Call the person back on their known number, message them on a different app, or ask a question only the real person could answer. No visual test is as reliable as this single step.
Beyond that, the strongest checks right now are:
- Ask them to turn their head fully to the side. Real-time deepfakes are built mostly from front-facing photos and video, so a full profile turn is where most fakes visibly break down.
- Watch for urgency and a request for money or sensitive info. The technology is the delivery method; urgency is still the actual scam.
- Check the calling number or ID, especially on apps like WhatsApp, where the number is visible throughout the call.
- Listen closely to speech rhythm and emotion, not just voice similarity; AI voices are very good at sounding like someone, but still struggle to emote like them.
Is a Fake AI Video Call Really Possible? Yes – And It’s Not New Anymore
A few years ago, this felt like something out of a spy movie. Not anymore. AI tools can now take a handful of photos or a few seconds of someone’s voice from social media and generate a real-time face swap or voice clone convincing enough to fool people who know the victim well.
This isn’t limited to India, and it isn’t limited to individuals. A widely reported case saw an employee at engineering firm Arup wire $25.6 million after a deepfake video call impersonating the company’s CFO instructed the transfer.
In India, deepfakes have already been used to impersonate government officials in investment scams.
In one case from early 2026, a Khammam businessman was cheated of over ₹2 crore in a stock scheme that used a deepfake of Union Finance Minister Nirmala Sitharaman to build credibility.
The pattern is consistent: familiar face, familiar voice, real urgency, and a request for money that feels too time-sensitive to double-check.
What Is a Deepfake, Exactly?
A deepfake is AI-generated or AI-altered video, audio, or image content that makes it appear as though someone said or did something they never actually did.
The term comes from “deep learning”, the branch of AI that powers this kind of realistic synthetic media, combined with “fake.”
For a live video call specifically, scammers use real-time face-swapping software that maps a target’s face onto the scammer’s own face and expressions as they speak, streamed through a virtual camera so it appears as the “camera feed” inside apps like WhatsApp, Zoom, or FaceTime.
Related: What Is Deepfake Technology? How to Spot It and Stay Safe
The voice is handled separately, using AI voice cloning trained on short audio clips pulled from social media, YouTube videos, or even old voice notes.
Building this used to require great technical skill and expensive hardware. That’s no longer true. Voice cloning models today need only a few seconds of clear audio to build a usable voice model.
Also, face-swap tools are available as cheap, largely automated software, no coding required.
Why “Spot the Glitch” Advice Is Losing Its Edge
Most older guides to spotting deepfakes focus entirely on visual glitches, flickering edges, mismatched lighting, and robotic voices. That advice isn’t wrong, but it’s increasingly incomplete.
Security researchers now note that newer deepfake models maintain consistency over time without the flicker, warping, or uncanny-valley artefacts that older detection methods relied on.
A deepfake video participant fooled experienced professionals during a live call in the Arup case, not amateurs, not people caught off guard, trained finance professionals.
That’s why the emphasis in this guide is split two ways: the visual and audio checks that can still help, and, more importantly, the behavioural and procedural habits that work even when the visuals are flawless.
Visual Signs That Can Still Help You Spot a Fake
These signs are genuinely harder to fake in real time, especially under pressure from the scammer to keep the call moving quickly:
The head-turn test. This is currently considered one of the most reliable live checks available. Ask the person to turn their head fully to the side, in profile.
Most real-time deepfakes are built from portrait-style photos and video, so a full sideways turn tends to make the face float, distort, or break apart, something a real person on a normal call simply won’t do.
Lighting and shadow mismatches. Deepfakes often get the physics of light wrong. The shadow direction on the face may not match the background, or the skin may show unnatural glare, or lack expected shadowing entirely.
If someone appears to be lit from a totally different angle than their surroundings suggest, that’s worth noticing.
Blurring or flickering around the hairline and edges. Watch where the face meets the hair, neck, glasses, or a hat. These boundary areas often show blurring or unnatural colour transitions in a deepfake, since that’s where the AI-generated overlay meets the real background feed.
Odd emotional-facial mismatch. Facial movements sometimes don’t match the emotion the voice is conveying. A smile or laugh is a particularly common breaking point for deepfake video, since spontaneous expressions are harder to fake convincingly than a neutral talking face.
Blinking that looks off. Unnatural blink patterns, too rare, too regular, or completely absent, remain a known weak point, since naturally timed blinking is genuinely difficult for these models to replicate convincingly.
Video framing that looks slightly wrong. If the video appears stretched, oddly cropped, or doesn’t fill the call window the way a normal camera feed would, that can indicate a virtual camera feeding in altered footage rather than a live device camera.
Audio Signs Worth Listening For
Deepfake creation often prioritises visuals over audio, which means the sound can be a weaker link than the video itself. Listen for:
- Robotic tone, flat delivery, or odd pacing that doesn’t match how the person normally speaks
- Poor lip-sync: a slight but noticeable delay or mismatch between mouth movement and words
- Missing “shibboleths”: small verbal habits, filler words, an accent quirk, or phrases the real person always uses that the fake voice doesn’t reproduce
- Unusual pronunciation of specific words or names, especially local names and places that generic voice models tend to mishandle
- Background noise or a deliberately “bad connection”; scammers sometimes introduce artificial static or lag specifically to mask audio imperfections that would otherwise give them away
The Behavioural Red Flags That Matter More Than the Tech
However convincing the video and audio are, scammers still rely on classic manipulation tactics underneath the AI. These are consistently the strongest signals:
Urgency. A request that has to be resolved “right now,” with no time to think, verify, or ask someone else; this alone should slow you down immediately.
A request for money or sensitive information, especially through an unusual method like a QR code, a new bank account, or a “temporary” payment app.
An unfamiliar calling number or account, even if the name and photo look right. This is especially useful on apps like WhatsApp, where the caller’s number stays visible on screen throughout a video call, making a genuinely anonymous fake call much harder to fully pull off.
A story that conveniently can’t be verified another way: “Don’t call my regular number, I’m using a friend’s phone,” or “I can’t talk long, just send it.”
Refusal or hesitation when asked to do something spontaneous; turning their head, answering a personal question only the real person would know, or repeating something you say back in a different order.
Related: How to Secure Your WhatsApp Account and Chats?
How to Verify a Suspicious Video Call, Step by Step
If something feels off during a call, even slightly, this is the sequence worth following:
- Don’t act on the request during the call itself. Say you need a minute, or that you’ll call them back.
- Hang up and call the person back on their known, saved number, not a number they gave you during the suspicious call.
- Reach out through a completely separate channel if possible: a different messaging app, a family member, or a colleague who can independently confirm.
- Ask a question only the real person could answer; something specific and personal, not something guessable from social media.
- Agree on a family or team “safe word” in advance, ideally before you ever need it. If a call claiming to be your parent, spouse, or manager can’t provide it, treat the request as fraudulent.
- Never transfer money or share OTPs, passwords, or ID details based on a video call alone, regardless of how convincing it looked or how urgent it felt.
Setting up a safe word with close family members and, if relevant, your workplace finance team, is genuinely one of the most effective defences available right now; it doesn’t rely on spotting anything technical at all.
Common Deepfake Scam Scenarios to Know
The “relative in trouble” call. A video call from what looks like a family member or close friend, claiming a medical emergency or urgent need, asking for an immediate money transfer.
This is exactly the pattern behind the original Kozhikode case that first brought this scam to national attention in India, and it remains one of the most common formats.
The fake company executive. A deepfaked “CEO” or “CFO” instructs an employee to process an urgent wire transfer or share confidential financial access.
The corporate version of the same trick is now responsible for some of the largest single losses reported globally.
The fake official or celebrity endorsement. Deepfakes of government officials, bank representatives, or well-known public figures are increasingly used to lend credibility to investment scams, as seen in the Khammam case involving a deepfaked Finance Minister.
The fake recruiter or interview. Scammers conduct deepfaked video interviews posing as hiring managers, often to extract personal information or advance-fee “processing charges” from job seekers.
Related: How to Unlist Your Number from Truecaller Permanently
Myth vs Fact
Myth: “I’d immediately know if a video call was fake because I know the person well.”
Fact: Knowing someone well can actually make you more vulnerable. Scammers rely on your trust and familiarity, and today’s advanced deepfake technology has become realistic enough to fool even trained professionals during live video calls.
Myth: “Deepfake videos always look distorted, glitchy, or robotic.”
Fact: That may have been true in the past, but modern real-time deepfakes are much more convincing. In good lighting with a clear front-facing camera, they can appear smooth and natural throughout an entire video call.
Myth: “Only celebrities, business leaders, or high-profile people are targeted.”
Fact: That’s a common misconception. Scammers frequently target ordinary people and families because they are often less likely to verify a caller’s identity than organisations with strict security procedures.
Myth: “If the phone number matches the person’s contact, the call must be genuine.”
Fact: Not necessarily. Phone numbers, caller IDs, and even saved contact names can be spoofed or manipulated. While they provide a useful clue, they should never be treated as definitive proof that the caller is genuine.
What to Do If You’ve Already Been Scammed
If you’ve sent money or shared sensitive information during a call you now believe was fake, speed matters more than anything else.
- Report it immediately; India’s cybercrime helpline is available by calling 1930, or by filing a complaint at cybercrime.gov.in. Acting within the “golden hour” is what gives banks the best chance of freezing the receiving account before the money moves further.
- Contact your bank directly to request a transaction reversal or freeze, in parallel with filing the cybercrime report.
- Save all evidence: screenshots, the call recording if you have one, the number or account details used, and any messages exchanged around the call.
- Change passwords and enable additional security on any accounts that may have been discussed or exposed during the call.
- Tell your family or colleagues what happened. Scammers who’ve successfully targeted one person in a household or office frequently attempt the same approach on others connected to them.
India’s cyber-fraud response infrastructure has scaled up considerably. In 2025, authorities deactivated 1.2 million SIM cards, froze 1.33 million mule accounts, and recovered ₹5,489 crore tied to fraud cases.
So reporting genuinely does feed into an active enforcement effort, not just a complaint log.
Legal Protection in India
Deepfake-enabled fraud in India is prosecuted through a combination of laws rather than a single dedicated statute.
The IT Act 2000, alongside the Digital Personal Data Protection Act 2023 and the Bharatiya Nyaya Sanhita 2023, criminalises identity theft, impersonation, and the disinformation and organised fraud that deepfakes are typically used to commit.
Platforms are also under pressure to act quickly, and reporting mechanisms are designed to drive the rapid removal of fraud-related deepfake content once flagged.
This matters practically: when you report a deepfake scam, you’re not just seeking your own resolution. You’re feeding into a system that can trigger content takedowns and account freezes that protect others from the same attacker.
Protecting Yourself Before It Happens
A few habits meaningfully reduce your exposure:
Limit how much personal video and audio you post publicly. Fewer clear photos and voice samples in the public domain make you a harder, less efficient target; scammers generally go for whoever’s easiest to model.
Set a family safe word now, not after you get a suspicious call. Make sure everyone in the household, including older relatives who are frequently targeted, knows it.
Establish a “always verify money requests independently” rule for your family and, if relevant, your workplace, regardless of how the request arrives, video call included.
Be sceptical of urgency by default. Genuine emergencies from real family members almost always tolerate a five-minute callback; scams are built specifically so that they don’t.
Keep your own accounts locked down; strong, unique passwords and two-factor authentication reduce the damage if a scammer does get partial information from you.
If you’re setting up better call and message screening for elderly relatives who are frequently targeted by these scams, a simple call-blocking landline phone with a large caller-ID display like Beetel M71N [view on Amazon] can help filter out unknown numbers before a fake call even gets through.
Comparison: Reliable vs. Unreliable Ways to Spot a Deepfake Call
| Check | How Reliable in 2026 | Why |
|---|---|---|
| Callback on a known number | Very reliable | Bypasses the fake entirely, verifies the real person independently |
| Family/team safe word | Very reliable | Doesn’t depend on spotting any technical flaw at all |
| Asking for a full head turn | Fairly reliable | Still a genuine weak point for most real-time face-swap tools |
| Watching for lip-sync or lag | Moderately reliable | Helps with lower-effort fakes, less so with high-end ones |
| General “video looks a bit off” instinct | Low reliability alone | Worth noting, but not something to rely on by itself anymore |
| Trusting the caller ID or the saved contact name alone | Low reliability alone | Numbers and names can be spoofed or manipulated |
Conclusion
The honest reality for 2026 is that you can no longer count on spotting a fake video call purely by eye or ear.
The technology has gotten good enough that even trained professionals have been fooled on live calls.
What still works reliably is process, not perception: hang up and call back on a known number, agree on a family safe word in advance, and treat any urgent request for money during a video call as a reason to slow down, not speed up.
If you do get caught out, speed matters; report to 1930 or cybercrime.gov.in immediately, and contact your bank in parallel.
The technology behind these scams will keep improving, but the defence that actually holds up against it hasn’t changed: verify independently, every time, no exceptions.
Related: How to Lock SIM Card | Why Do You Need to Activate SIM PIN on Your Phone?
Frequently Asked Questions
Yes. Real-time face-swapping software combined with AI voice cloning can convincingly impersonate someone during a live video call, and the technology has advanced enough to fool people who know the target well.
Asking the person to turn their head fully to the side is currently one of the most effective live tests, since most real-time deepfakes are built from front-facing images and struggle to render a convincing profile view.
Voice cloning can work from just a few seconds of clear audio, and face-swapping tools can produce a usable result from a handful of clear photos or a short video clip, both commonly available from social media.
Yes. Deepfake-enabled fraud is prosecuted under a combination of the IT Act 2000, the Digital Personal Data Protection Act 2023, and the Bharatiya Nyaya Sanhita 2023, covering identity theft, impersonation, and organised fraud.
Call the national cybercrime helpline at 1930, or file a complaint directly at cybercrime.gov.in. Reporting quickly, within the first hour if possible, significantly improves the chance of freezing any transferred funds.
It depends on speed and circumstances. Reporting immediately gives banks the best chance of freezing the receiving account before funds are moved further, but reversal isn’t guaranteed, especially after delays.
Yes, older adults are frequently targeted, partly due to less familiarity with AI-generated media and partly because scammers often use family-emergency scenarios that specifically target that demographic’s protective instincts.
Not anymore. Older deepfakes were more prone to flickering, warping, and inconsistent lighting, but current-generation tools can maintain smooth, consistent output throughout an entire call, especially in good conditions.
A safe word is a private phrase agreed upon in advance that only real family members know. If someone claiming to be a relative can’t provide it during an urgent request, treat the call as suspicious. Choose something specific and memorable, and make sure every family member, including elderly relatives, knows it.
Yes, though WhatsApp does display the caller’s phone number throughout the call, which makes a fully anonymous fake call somewhat harder, scammers typically need to also spoof or use a plausible number to pull it off convincingly.
Report it immediately to 1930 or cybercrime.gov.in, contact your bank to request a freeze or reversal, save all evidence, including screenshots and transaction details, and change any passwords discussed during the call.
Yes, tools like Microsoft’s Video Authenticator and various AI-content-detection platforms exist, but they’re primarily built for professional and platform-level use rather than everyday individual verification. A callback and safe word remain more practical for most people.
Urgency prevents victims from pausing to verify the request through another channel, which is the single most effective defence against these scams. Slowing down is specifically what scammers are trying to prevent.
Yes, this is a well-documented corporate fraud pattern, including cases where deepfaked executives instructed employees to process large wire transfers, resulting in losses in the tens of millions of dollars internationally.
Exercise the same caution you would with an unknown phone call or message. Verify identity independently before sharing personal information or agreeing to any financial request, regardless of how the call was initiated.
Be sceptical by default of any celebrity or government official appearing to personally endorse an investment scheme through video, especially if it is circulated via WhatsApp or social media rather than an official verified channel. These are commonly deepfaked to lend false credibility to scams.
It doesn’t directly prevent someone else from creating a deepfake of you using existing public photos or videos, but reducing how much new footage of yourself is publicly available does reduce the amount of quality source material scammers can draw from.
The Indian Cyber Crime Coordination Centre (I4C), alongside CERT-In and the National Cyber Crime Reporting Portal, coordinates the response to deepfake-driven and other cybercrime cases in India.
Sharing malicious or fraudulent deepfake content, even unknowingly, can carry legal risk depending on the content and context. When in doubt, verify a video’s authenticity before forwarding it, particularly anything involving financial claims or public figures.
It’s genuinely increasing. Deepfake file volume is projected to have grown from roughly 500,000 in 2023 to around 8 million by 2025, and a large share of Indian adults now report personal or close-contact experience with AI voice or deepfake scams.
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I never realized there were so many video chat apps available. Your post opened my eyes to new possibilities. Do you have any insights on how these apps prioritize user privacy?
Of course, that is a valid and significant question, even if it is not linked directly to the topic of our post. As applications for video calling continue to expand and acquire relevance in our lives, it is becoming increasingly important to prioritize user privacy. Personal information security, conversation security, and effective privacy safeguards should be top objectives for app developers. We will definitely explore the matter in a separate article very soon.