Deepfake and AI Fraud: Operational Guide to Spot Fakes and Defend Yourself

Imagine receiving a phone call from your CEO. Perfect voice, urgent tone, request for an immediate wire transfer. Except it's not them. It's a deepfake audio generated by artificial intelligence. This is not science fiction: it's a real threat hitting businesses and individuals, growing exponentially. We at Meteora Web see it in the security projects we manage: AI fraud is the new favorite attack vector for cybercriminals. In this guide we will show you how to spot them and defend yourself, from awareness to operational tools.

How deepfakes work

A deepfake is audio, video, or text generated or manipulated by AI algorithms, especially Generative Adversarial Networks (GANs) or autoencoders. The AI learns from thousands of samples of a person (photos, videos, voice recordings) and creates new realistic sequences. Today the technology is so advanced that a well-made deepfake can fool even an experienced eye.

Types of deepfakes

• Video deepfakes: face swapping or lip-syncing to make a person say things they never said.
• Audio deepfakes: voice cloning used for fraudulent phone calls or fake voicemails.
• Image deepfakes: photos of non-existent people (already used for fake profiles) or manipulated images.
• Generated text: AI like ChatGPT can write personalized phishing emails, imitating a colleague's style.

Combining these vectors makes social engineering attacks extremely credible. Read more in our Social Engineering Pillar Guide.

How to recognize a deepfake

There is no foolproof method, but there are warning signs everyone can learn. The more senses you involve, the better.

Visual indicators

• Unnatural movements: irregular blinking, eyes not following natural motion, missing or misaligned micro-expressions.
• Lip-sync issues: audio and lip movements don't match perfectly.
• Digital artifacts: flickering around the face, blurry edges, unnatural reflections, inconsistent lighting.
• Missing details: jewelry, hair, background too smooth or generic.

Audio indicators

• Too-perfect voice: lack of natural pauses, breaths, monotone or abrupt variations.
• Artificial background noise: absence of ambient sounds or a constant unnatural buzz.
• Emotional inconsistency: the vocal emotion doesn't match the words.

Automated analysis tools

You can use specific software to unmask deepfakes. Some are free:

• InVID & WeVerify: browser extension to analyze videos, extract frames, and check metadata.
• Deepware Scanner: online tool that analyzes faces in videos.
• Microsoft Video Authenticator: analyzes frames and provides a confidence score.
• ExifTool: command-line tool to examine file metadata. Generators often leave traces in "Software" or "Creator" fields.

# Example: extract metadata from a video
exiftool -a -g1 video.mp4 | grep -E "Software|Creator|Producer|Model"

If you find names like "WaveNet", "Tacotron", "StyleGAN" or "DeepFaceLab", the content is most likely a deepfake.

Defending against AI fraud

Technology advances faster than defense, but you can reduce risk with a combined approach: organizational protocols, training, and technical tools.

Verification protocols

Establish clear rules for sensitive communications. Example:

1. Secret verification code: every person authorized to request transfers or sensitive data knows a secret word/phrase to ask when in doubt.
2. Dual channel: a request received via email or phone must always be confirmed through a different channel (e.g., SMS to a known number, call to another line).
3. False urgency: criminals create urgency. An urgent request is even more reason to verify.

Employee training

Organize hands-on sessions with real deepfake examples. Show your colleagues how to recognize visual and audio indicators. Explain that no one is immune, not even executives. Repeat training periodically.

Technical tools

• Multi-factor authentication (MFA) on all critical systems, email, and financial platforms.
• Digital signatures for official documents and communications.
• Watermarking corporate content (videos, training material) to make it harder to forge.
• Anti-phishing filters and anomaly detection in emails.

What to do if you suspect a deepfake

If you receive suspicious content, follow these steps:

1. Do not share the material – it could spread misinformation.
2. Document the contact (time, channel, who sent it).
3. Report internally to IT or the actual person involved (the real one, not the fake).
4. Contact authorities if it involves a financial fraud attempt. In many countries, report to the local cybercrime unit.
5. Update security protocols based on the incident.

In summary — what to do now

Don't wait for a deepfake to hit your company. Implement these actions right away:

1. Establish a secret verification code for all transfer or sensitive data requests.
2. Install the InVID/WeVerify extension on team browsers handling public communications.
3. Organize a bi-annual training with real deepfake examples.
4. Enable multi-factor authentication on corporate email and cloud services.
5. Follow the evolution of deepfake detection — read official resources like the CISA Deepfakes page.

We at Meteora Web are available to assess the security of your corporate communications. Defense starts with awareness — and today you have the tools to begin.