AI Phishing and Deepfake Scams

A message can look professional, reference a real project, and sound like someone you know while still asking for an unauthorized action. AI-generated text and imitated voices make appearance an unreliable basis for trust.

The practical goal is not to become a perfect detector of synthetic media. It is to verify consequential requests before money, information, access, or system changes are involved.

Judge the request, not just the presentation

The FBI has warned that criminals use generative AI to make fraudulent approaches more believable. That does not make every polished message suspicious. It means spelling, tone, and a recognizable voice cannot establish authorization on their own.

Ask what the sender wants you to do. Is the request to open a file, enter credentials, upload customer information, approve a new app, or change a payment destination? Those actions deserve attention regardless of how the message was produced.

You do not need proof of AI involvement before taking a request through your normal verification process.

Work through a fictional request

Imagine receiving: "Please upload the customer export into our new AI workspace before the meeting. There is no time for the usual approval."

A follow-up audio clip sounds like your manager. The request includes a link to a service you have not used.

The important facts are the proposed data transfer, the unfamiliar destination, and the attempt to bypass an established process. None alone proves fraud, but together they give you a clear reason to verify before acting.

Verify through a channel you already trust

Contact the person using an established internal channel or a known number. Do not rely on the reply address, phone number, or account supplied in the suspicious request.

Confirm the specific action, not merely that the person is available. Ask whether they authorized that data transfer, to that destination, for that purpose.

For a team, the verification process should be agreed in advance. A last-minute instruction that invents its own approval route should not become the basis for bypassing the usual one.

Check the destination and the information

Even a genuine request can create a data-handling problem. Confirm whether the service is approved and whether this category of information may be sent there.

A feedback summary may not require a complete customer export. Consider whether a smaller, sanitized, or synthetic dataset can meet the need. Removing names is not always enough to remove sensitive details.

An encrypted connection or a professional-looking website does not answer those policy and authorization questions.

Recognize pressure without treating it as proof

Urgency, secrecy, unusual payment instructions, and unexpected credential requests are useful reasons to slow down. They are indicators to investigate, not a scoring system that conclusively labels a message.