What Is a Deepfake? (Definition)

A deepfake is an artificial intelligence tool that can replace a person’s face, voice, or both with someone else’s. Unlike basic photo editing or filters, deepfakes use advanced machine learning to analyse thousands of images or audio samples, learning how a person moves, speaks, and expresses emotion. The process, called deep learning, involves two AI systems working in opposition: one generates the fake, and the other attempts to detect flaws. This back-and-forth repeats millions of times until the result is almost impossible to distinguish from the real thing.

How Deepfakes Actually Work

Understanding the mechanics helps with detection. Here’s what happens behind the scenes:

• Data Collection: Scammers gather photos, videos, or audio of their target from social media, company websites, or public appearances
• Training: AI analyses this data, learning facial movements, speech patterns, and mannerisms
• Generation: The system creates new content, mapping the learned patterns onto different words or actions
• Refinement: Multiple passes improve quality, removing obvious tells like flickering or mismatched lighting
• Deployment: The finished deepfake gets deployed through video calls, voice messages, or recorded content

The Evolution of Deepfake Technology

Deepfake technology has developed at an insane pace, moving from niche research projects in the 1990s to one of the most accessible deception tools available today. What began with academic work on neural networks and facial mapping has evolved into a mainstream capability, with apps, websites, and AI tools that anyone can use to create realistic fakes in minutes.

Here’s a brief timeline of how it started:

• 1997: First academic papers on facial re-enactment appear
• 2014: Generative Adversarial Networks (GANs) make realistic face generation possible
• 2017: “Deepfake” term coined as the technology goes mainstream
• 2019: First documented voice-clone fraud costs UK energy firm €220,000
• 2020: Free deepfake apps flood mobile app stores
• 2023: Real-time voice cloning becomes commercially available
• 2024: Arup loses $25 million to deepfake video conference scam
• 2025: McAfee reports 3 seconds of audio creates 85% accurate voice clone

Current State of Deepfake Technology

In 2025, creating a convincing deepfake no longer requires technical expertise or expensive equipment. Free smartphone apps can face-swap in real-time. Online services offer voice cloning for £20. One platform I tested (for research purposes) created a believable video clone from just 12 photos and a 30-second voice sample.

The numbers tell the story:

• Creation time: 5-20 minutes for a basic deepfake
• Cost: Free to £50 for consumer-grade fakes
• Required input: As little as one photo or 3 seconds of audio
• Detection difficulty: 40% of people can’t identify a well-made deepfake
• Availability: Over 100+ apps and websites offer deepfake creation

Why This Matters: We’ve reached the democratisation of deception. When anyone with a smartphone can create a convincing fake of anyone else, traditional trust systems collapse. The technology that once required Hollywood budgets now sits in the pocket of every potential scammer.

Types of Deepfake Scams: The Modern Fraud Playbook

Deepfake scams tend to follow the same playbook. Over time, criminals have refined these tricks to target our fears, emotions, and relationships. I’ve seen five main types keep coming up, each with its own way of breaking down your guard. Knowing them doesn’t just make you more aware, it’ll equip you with the knowledge you need to shut things down before they get too far.

Family Emergency Scams

These prey on our protective instincts and willingness to help loved ones in crisis. The basic pattern involves a distressed call from a family member needing immediate financial help. What makes the deepfake version particularly cruel is the use of actual voice patterns and speech habits that bypass our natural scepticism.

The most sophisticated versions I’ve investigated include background noises (sirens, hospital sounds) and emotional voice modulation that makes the fake caller sound genuinely distressed. As we saw with Arup’s $25 million loss, even experienced professionals can be fooled when the technology is combined with psychological pressure.

Corporate and Business Fraud

Business deepfake scams have evolved beyond simple CEO impersonation. Today’s attacks involve entire fake meetings, complete with multiple participants and realistic interaction. The Arup case represents the current pinnacle of this threat – a finance employee transferred $25.6 million after a video call where everyone except him was a deepfake, including colleagues he recognized.

Common corporate attack vectors include:

• Fake video conferences for urgent wire transfers
• Voice-cloned calls from “vendors” changing payment details
• Deepfaked ‘executives’ authorising unusual transactions
• AI-generated “training videos” that are actually phishing attempts

Romance and Relationship Scams

The darkest use of deepfakes often targets human loneliness. Romance scammers now use AI-generated videos to ‘prove’ their identity, creating elaborate fake relationships that can last months. The Brad Pitt scam that cost a French woman €830,000 shows how sophisticated these operations have become, using AI-generated photos and messages to maintain the illusion.

These scams typically escalate through predictable stages, now enhanced with deepfake ‘proof’ at each step:

• Initial contact through dating sites or social media
• Quick emotional escalation with AI-crafted messages
• Video “dates” using real-time deepfake technology
• Manufactured crisis requiring financial help
• Disappearance once money is sent

Political Manipulation

Political deepfakes aim for maximum disruption with minimal investment. The New Hampshire Biden robocalls during the 2024 primary demonstrated how cheaply democracy can be attacked – the fake audio cost just $1 to create but reached thousands of voters with disinformation.

Current political deepfake tactics include:

• Fake speeches or statements released before elections
• Manipulated debate footage shared on social media
• Voice clones spreading disinformation through robocalls
• Fabricated “leaked” private conversations

Sextortion and Intimate Image Abuse

Perhaps the most personally destructive deepfake scams involve manufactured intimate content. Victims receive messages claiming to have compromising videos that do not actually exist, or they discover deepfaked intimate images of themselves circulating online. These fakes can be created from as little as a single public photo, and in many cases, no real intimate material ever existed.

Because sextortion plays on fear, shame, and urgency, it can push victims into making snap decisions that only make things worse. Our full guide to sextortion and how to prevent it explains how these scams typically unfold, the psychological tactics used to pressure victims, and the exact steps you can take to protect yourself or support someone who has been targeted.

Traditional Scams vs. Deepfake-Enhanced Versions

Every classic scam has now been weaponised with deepfake technology. Understanding the evolution helps recognise new threats. Traditional scams relied on text, basic impersonation, and social engineering. Today’s deepfake versions add visual and audio “proof” that overwhelms our defences. When you see and hear your loved one asking for help, your analytical mind often shuts down.

Deepfake Examples – Real Cases with Dates

These verified cases prove that deepfakes aren’t targeting just the naive or careless – they’re successfully deceiving professionals, loving families, and entire communities. From multinational corporations with sophisticated security protocols to individuals seeking companionship, from voters participating in democracy to established businesses, no one is immune. With FBI IC3 reporting record cybercrime losses of $16.6 billion in 2024 and Sumsub detecting a 4x increase in deepfakes year-over-year, the tactics used against these victims are the same ones that could target you tomorrow, which is why studying these examples carefully matters.

• February 2024 – Arup Hong Kong $25 Million Loss: Multinational engineering firm Arup confirmed a finance employee transferred $25.6 million (200 million Hong Kong dollars) after a video conference where every participant except him was a deepfake, including the company’s CFO. The sophisticated scam involved multiple deepfaked colleagues in a single meeting.
• January 2024 – Brad Pitt Romance Scam €830,000: A 53-year-old French woman lost €830,000 to scammers posing as Brad Pitt using AI-generated images and messages. NBC News reports the victim believed she was in a relationship with the actor for over a year. The scammers used deepfaked photos showing “Pitt” in a hospital to solicit money for fake cancer treatment.
• January 2024 – New Hampshire Biden Deepfake Robocalls: Thousands of New Hampshire voters received deepfaked robocalls imitating President Biden telling Democrats not to vote in the primary. The voice clone was created for just $1 and reached thousands of voters. Political consultant Steve Kramer was charged and Lingo Telecom paid $1 million in FCC fines.
• March 2019 – CEO Voice Clone €220,000 Theft: The Wall Street Journal reported criminals used AI to mimic a chief executive’s voice and tricked a UK energy firm into transferring €220,000 to a Hungarian supplier. This was one of the first documented cases of AI voice cloning used in fraud.
• Ongoing – 77% of Businesses Unprepared: Business.com research finds only 23% of companies have deepfake response plans despite iProov reporting a 704% increase in deepfake fraud attempts year-over-year.

Why This Matters: These aren’t isolated incidents – they’re part of a growing pattern. The Arup case shows that even multinational corporations with sophisticated security can fall victim. The Brad Pitt scam demonstrates how deepfakes exploit emotional vulnerability. The Biden robocalls prove that democratic processes themselves are at risk. With Sumsub reporting a 245% year-over-year increase in deepfakes globally and Deloitte predicting AI-enabled fraud could reach $40 billion in the US by 2027, every case teaches us that traditional verification methods no longer work.

Platform-Specific Deepfake Risks

Different communication platforms make deepfake attacks easier in different ways. The warning signs you look for on a live video call are not the same as the ones to watch out for in a voice note or a social media post. Knowing how deepfakes may differ on each platform can help you to tailor your defences (and others).

Video Conferencing (Zoom, Teams, Google Meet)

Real-time deepfakes now work seamlessly with standard video conferencing. Warning signs often include:

• Sudden ‘connection issues’ when asking unexpected questions
• Unusual lighting that seems to follow the person’s face
• Delayed reactions to visual cues or gestures
• Background inconsistencies with known locations

Social Media (Facebook, Instagram, LinkedIn)

Deepfakes on social platforms often appear in a number of ways:

• Fake live streams soliciting donations
• Manipulated video testimonials
• False emergency announcements
• Investment scam presentations

Messaging Apps (WhatsApp, Telegram, Signal)

Voice note deepfakes are particularly dangerous here because of the following:

• Lower audio quality masks imperfections
• Emotional context overrides suspicion
• Messages feel more personal and urgent
• End-to-end encryption prevents platform-level detection

Signs a Deepfake Is Being Used on a Video Call

In 2025, video calls are now one of the most popular tools for AI-powered deepfake scammers. The technology is improving fast, but even the best fakes still show subtle signs if you know where to look. On any call that feels unusual, urgent, or high-stakes, stay alert for visual, audio, and behavioural cues that could reveal you are not speaking to the real person. Here are some things to look out for:

• Lighting inconsistencies: Face lighting doesn’t match the room or changes unnaturally
• Facial boundaries: Blurring or flickering where the face meets the hair or neck
• Mouth synchronisation: Lips don’t perfectly match the words, especially with ‘B’, ‘P’, and ‘M’ sounds
• Eye movement: Unnatural blinking patterns or eyes that don’t properly track movement
• Emotional mismatches: Facial expressions don’t align with the conversation’s emotional tone
• Technical glitches: Brief flashes of the original face or sudden pixelation during movement
• Background issues: Shadows fall incorrectly or background elements seem disconnected
• Audio delays: Voice slightly out of sync with lip movements, especially during rapid speech
• Behavioural anomalies: Person avoids specific movements or keeps unusually still
• Connection excuses: Frequent claims of “bad connection” when asked to perform verification actions

Detection Techniques That Actually Work

After analysing hundreds of deepfake attempts, I’ve realised that most tips online are completely outdated. Forget looking for obvious glitches – modern deepfakes have evolved past those. Instead, focus on behavioural patterns and verification techniques that AI can’t yet replicate.

Technical Indicators

Current deepfake technology struggles with certain visual elements:

• Temporal flickering: Watch for subtle flickering around facial boundaries during the 15-30 second mark of videos
• Asymmetric features: Cover half the face with your hand – deepfakes often show different expressions on each side
• Reflection inconsistencies: Glasses, eyes, and shiny surfaces may show impossible reflections
• Hair behaviour: Individual strands don’t move naturally, especially around the face
• Skin texture: Too smooth or waxy appearance, particularly visible on 4K displays

Voice Detection Strategies

Voice clones have tells that become apparent when you know what to listen for:

• Emotional flatness: AI struggles with subtle emotional variations mid-sentence
• Breathing patterns: Unnatural or absent breathing sounds between phrases
• Micro-pauses: Slightly robotic spacing between certain word combinations
• Background silence: Too-perfect silence when the person isn’t speaking
• Pitch consistency: Natural voices vary pitch more than AI versions

The Power of Active Verification

The most effective detection method? Make the suspected deepfake do something unexpected:

• Ask them to touch their ear while speaking – coordinates facial movement with speech
• Request they show something specific in their immediate environment
• Have them write something on paper and show it on camera
• Ask about shared memories with specific sensory details
• Request they call from a different device simultaneously

Behavioural Red Flags

Beyond technology, deepfake scammers exhibit predictable behaviours:

• Urgency without precedent: Sudden emergency with immediate action required
• Privacy insistence: “Don’t tell anyone else about this call”
• Verification avoidance: Excuses when asked to verify identity
• Emotional manipulation: Heavy use of fear, guilt, or excitement
• Channel switching: Pushing to move from video to audio only

Technical Detection Tools

Deloitte’s 2025 Tech Trends highlights several AI-powered detection tools now available to businesses. However, Business.com’s research shows only 29% of companies have implemented any deepfake detection technology, despite 77% expressing concern about the threat. Free tools like Microsoft’s Video Authenticator or Reality Defender can help, but they’re not infallible – determined attackers often stay one step ahead of automated detection.

Trust Your Instincts

This is the part most people skip over, and it is the one that matters most. If you get that gut-deep ‘something is off’ feeling, pay attention to it. Every person I have spoken to who has been hit by a deepfake scam says the same thing: ‘I knew something felt wrong at the start, but I told myself not to be paranoid.’ That hesitation cost them. It is not paranoia, it is awareness. Humans have spent thousands of years becoming very good at spotting tiny cues that do not match what our brain expects. AI is improving, but it is still not perfect, and your instincts are one of the last lines of defence we have. So if you’re talking to ‘your boss’, ‘your child’, or ‘a friend’, and something does not sit right, slow down, ask questions, and verify.

Prevention Strategies: Building Your Defence System

You don’t need a corporate security budget to protect yourself from deepfakes. Most of the best defences cost nothing but a little time and a willingness to plan ahead. Here’s my top tips:

Protection for Families

Every family needs a deepfake defence plan. Here’s the system I recommend:

1. Establish Safe Words

• Create a secret family code or password that everyone will remember. Choose phrases that:
  • Reference shared memories only your family would know
  • Include sensory details (smells, sounds, textures)
  • Change monthly or after any suspicious contact
  • Stay offline and unwritten

2. Verification Protocols

• Agree on steps you’ll follow before sending money or sensitive information:
  • Always use video calls for money discussions
  • Call back on a known number before taking action
  • Implement a 24-hour cooling-off period for large requests
  • Have one trusted family member as the ‘verification contact’

3. Information Security

• Limit what scammers can learn about your family:
  • Review your social media privacy settings at least quarterly
  • Avoid posting long voice recordings or detailed personal videos
  • Never share travel plans publicly

Workplace Security Protocols

Even if you run a small team or family business, set simple, clear rules so no one makes a snap decision under pressure.

Financial Controls

• Use multi-person authorisation for transfers over £5,000
• Always confirm payment changes with a call to a pre-verified number
• Set a short delay on unusual or large payment requests
• Run regular training sessions on how small businesses get scammed online and how to stop it

Communication Verification

• Use unique phrases for authentic communications
• Verify sensitive requests through a separate contact method
• Do quick ‘fire drills’ to keep detection skills sharp
• Have a clear process for escalating anything suspicious

Technology Safeguards

• Put a cybersecurity policy in writing so everyone’s on the same page
• Use security suites with AI threat detection
• Enable short waiting periods on payment systems
• Install deepfake detection software where possible

Personal Digital Hygiene

Small habits add up to big protection. Here are a few easy wins:

Voice Sample Protection

• Keep voicemail greetings short (under 10 seconds)
• Don’t post long, clear readings of text on public platforms
• Use voice distortion for non-essential recordings
• Update your voicemail greeting regularly

Visual Data Management

• Watermark personal photos before sharing
• Avoid posting high-resolution, front-facing images
• Use privacy settings on video platforms
• Delete old, unused social media content

Communication Security

• Use secure email services for sensitive discussions
• Enable two-factor authentication on all key accounts
• Verify unexpected messages via a different contact method
• Keep your password manager updated with strong, unique passwords

Where Deepfakes Are Created and Sold

Understanding the deepfake ecosystem helps recognise threats. The creation and distribution networks operate in plain sight, making the technology dangerously accessible.

Consumer Creation Platforms

• Mobile apps offering ‘face swap’ entertainment (often repurposed for fraud)
• Web services providing ‘AI avatars’ for business use
• Open-source tools on GitHub requiring minimal technical knowledge
• ‘Voice cloning’ services marketed for content creation

Underground Marketplaces

• Dark web forums selling custom deepfake services
• Telegram channels offering ‘revenge’ videos
• Discord servers teaching deepfake creation
• Freelance platforms with sellers offering “video editing”

Distribution Networks

• Fake social media profiles spreading manipulated content
• Compromised YouTube channels hosting deepfake tutorials
• Messaging app groups sharing creation techniques
• Cloud storage links distributing deepfake software

The FBI’s Internet Crime Complaint Center reports that most deepfake scams originate from just a handful of creation services, but tracking and shutting them down proves nearly impossible due to jurisdictional challenges.

Legal Consequences of Creating Deepfakes

While most of this guide focuses on protecting yourself from deepfakes, it’s equally important to understand the severe legal ramifications of creating them. Whether you’re tempted to create a ‘harmless’ deepfake or want to understand your rights as a victim, knowing the legal landscape is crucial. Law enforcement and courts are rapidly adapting to this threat, with new legislation and precedents emerging monthly. What might seem like a prank or quick profit scheme can result in years of imprisonment and financial ruin.

Disclaimer: This information is for educational purposes only and does not constitute legal advice. Consult a qualified solicitor for specific legal guidance.

Criminal Charges

Creating malicious deepfakes can result in prosecution under various laws:

• Fraud: Using deepfakes for financial gain – up to 10 years imprisonment (UK Fraud Act 2006)
• Harassment: Creating intimate deepfakes – up to 6 months imprisonment (pending UK Online Safety Bill)
• Identity Theft: Impersonating others – varies by jurisdiction
• Election Interference: Political deepfakes – severe federal charges in most democracies

Civil Liabilities

• Defamation lawsuits for reputational damage
• Privacy violation claims
• Emotional distress damages
• Lost earnings compensation

Current Legal Landscape

• UK: Online Safety Bill includes specific deepfake provisions
• EU: AI Act requires deepfake labelling and disclosure
• US: State-by-state legislation, federal bills in progress
• Global: Interpol developing international deepfake protocols

The legal framework continues evolving, but prosecutors increasingly pursue deepfake creators using existing fraud, harassment, and identity theft laws. The US National Institute of Standards and Technology maintains updated guidance on deepfake legislation.

What to Do If You Suspect or Fall Victim to a Deepfake Scam

Despite our best efforts, sophisticated deepfake scams sometimes succeed. How you respond in the first 24 hours often determines whether you recover your losses and prevent further damage.

Immediate Response Checklist

If you suspect you’ve encountered a deepfake scam:

• Stop All Communication – End the call, close the chat, don’t respond
• Document Everything – Screenshot, record, save all evidence
• Verify Independently – Contact the real person through known channels
• Secure Your Accounts – Change passwords, enable 2FA immediately
• Alert Your Network – Warn others who might be targeted

If You’ve Been Scammed

First Hour Actions:

• Contact your bank’s fraud department immediately
• File a report with Action Fraud (UK) or IC3 (US)
• Change all passwords for financial accounts
• Alert your employer if work systems were compromised
• Contact the platform where the scam occurred

First 24 Hours:

• Gather all documentation for law enforcement
• Notify credit monitoring services
• Review all recent transactions
• Seek support from Identity Theft Resource Center
• Consider legal consultation for large losses

Reporting Procedures

Proper reporting helps authorities track patterns and potentially recover funds. The FBI emphasises that reporting all incidents, regardless of loss amount, helps build cases against organised deepfake crime rings. Many victims don’t report due to embarrassment, but this silence enables continued scams.

Report deepfake incidents to:

• Law Enforcement: Local police and national cybercrime units
• Financial Institutions: Banks, credit card companies, payment platforms
• Platform Providers: Social media sites, video conferencing services
• Regulatory Bodies: CISA, telecommunications regulators
• Support Organisations: Victim support services, elder abuse hotlines

Emotional and Financial Recovery

Deepfake scam victims often experience profound betrayal because they believed they were helping loved ones. Recovery involves both practical and emotional components:

Financial Recovery Steps:

• Work with banks on chargeback procedures
• File insurance claims if covered
• Document all losses for tax purposes
• Monitor credit reports for secondary fraud
• Consider civil litigation for large losses

Emotional Support Resources:

• Victim support services offer free counselling
• Online support groups for scam victims
• Family therapy to rebuild trust
• Educational resources to prevent re-victimisation

Technology Evolution Timeline

Understanding where deepfake technology is headed helps us prepare defences before new threats emerge. Based on current research trajectories, patent filings, and insider knowledge from AI labs, this timeline maps out the likely evolution of both deepfake creation and detection technologies. While some predictions may seem like science fiction, remember that today’s reality would have seemed equally impossible just five years ago. Use this forecast to plan your personal and organisational security strategies for the coming years.

Based on current development trajectories and insider knowledge from AI researchers, here’s what we think is coming:

2025-2026: The Accessibility Era

• Real-time deepfakes standard on smartphones
• Voice cloning from under 1 second of audio
• AI avatars indistinguishable from humans in most contexts
• Automated deepfake-as-a-service platforms proliferate

2027-2028: The Detection Arms Race

• Quantum-computing assisted deepfake creation
• Biometric verification becomes standard
• Blockchain authentication for critical communications
• AI vs AI detection warfare intensifies

2029-2030: The New Normal

• Deepfakes integrated into everyday communication
• Legal frameworks finally catch up
• Trust networks replace individual verification
• Physical presence becomes premium verification

Emerging Deepfake Threats

While we’re still grappling with today’s deepfake threats, researchers are already seeing prototypes of next-generation attacks that will make current scams look primitive. These emerging technologies combine deepfakes with other AI capabilities to create unprecedented deception tools. Understanding these future threats isn’t meant to frighten – it’s to ensure we start building defences now, before these capabilities become mainstream. The following threats are currently in development in various AI labs and criminal forums worldwide.

Security researchers are already seeing early versions of these next-generation threats:

• Emotional AI: Deepfakes that read and respond to your emotional state
• Memory Mining: AI that constructs false shared memories from social media
• Behavioural Cloning: Not just voice and face, but complete personality replication
• Temporal Attacks: Deepfakes of future events to manipulate decisions
• Synthetic Relationships: Long-term AI personas that develop trust over months

Staying One Step Ahead of Deepfake Scammers

Despite these sobering predictions, I remain optimistic. Every previous technological threat – from email phishing to phone scams – seemed insurmountable at first. Yet we adapted, developed defences, and learned to navigate safely. The same will happen with deepfakes.

The key is staying informed and prepared. The criminals using deepfakes rely on our ignorance and isolation. By understanding the technology, maintaining strong verification habits, and supporting each other, we can maintain human trust in an age of artificial deception.

Deepfake Scam Predictions for 2025-2030

1. Biometric Verification Becomes Standard: Just as two-factor authentication is now routine, multi-biometric verification will be required for any significant transaction or communication by 2027.
2. Insurance Against Deepfake Fraud: By 2026, major insurers will offer specific deepfake fraud coverage, similar to current identity theft protection.
3. AI Detection Integrated Everywhere: MIT’s latest research suggests that by 2028, deepfake detection will be built into all major communication platforms, running automatically in the background.
4. Legal Precedents Reshape Liability: The first major corporate lawsuit holding a company liable for inadequate deepfake protections will occur by 2026, fundamentally changing corporate security requirements.
5. Physical Verification Renaissance: In-person meetings and physical documentation will experience a resurgence as the gold standard for critical decisions, reversing the digital-everything trend of the 2020s.

The next five years represent a critical window. The choices we make now about detection, prevention, and response will determine whether deepfakes remain a manageable threat or fundamentally undermine digital communication. Based on everything I’ve seen, I believe we’ll rise to the challenge – but only if we start taking it seriously today.

Final Thoughts: Protecting Yourself in a World of AI Fakes

Deepfake technology will continue to improve, but staying safe doesn’t have to be complicated. You now know how these scams work and the simple steps that make them far less effective. You now know what a deepfake is, how AI voice and video scams operate, and the steps that make them far less effective.

Family safe words, workplace verification processes, and taking a moment to confirm details are practical habits that help protect you from deepfake and voice-clone scams. They’re simple adjustments to how we communicate, not drastic changes. Share this knowledge with others who might be at risk. The more people who understand how to spot a deepfake, the harder it becomes for scammers to succeed.

We’ve adapted to other online threats before, from phishing to identity theft. Deepfakes are the next challenge but with the right habits, they can be managed just as effectively.
For more information on deepfake threats and prevention strategies, explore our guides on AI-powered phishing, spotting catfish scams, and protecting yourself from romance fraud.https://www.business.com/security/deepfake-readiness-in-corporate-america/