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How to Detect and Prevent Deepfake Attacks

Reading Time: 8 Minutes

Deepfake attacks are no longer just a social media curiosity. They have become a direct threat to businesses. Using AI-generated video and audio, criminals can now impersonate executives, employees, and customers convincingly enough to authorise payments, unlock accounts, or leak sensitive data. As the tools become cheaper and easier to use, the number of deepfake-enabled scams targeting organisations continues to climb. This guide explains how deepfake attacks work, how to spot them, and the effective controls that stop them before they cause damage.

What Is a Deepfake Attack?

A deepfake attack uses synthetic media to make a target believe they are dealing with a real, trusted person. Attackers typically gather publicly available clips such as interviews, webinars, voicemails, and social posts, then feed them into AI models that clone a voice or face. The more source material available, the more convincing the result. Because the fake carries the authority of a familiar person, victims comply without the usual suspicion, which is exactly what makes these attacks so effective.

How Deepfake Attacks Target Businesses

Deepfake fraud tends to fall into three patterns.

In CEO fraud and business email compromise, attackers clone an executive’s voice or appear on a video call to demand an urgent, confidential payment. Staff approves it believing the instruction is genuine. In deepfake phishing, a fake voice or video call pressures an employee into sharing passwords or one-time codes. In identity and biometric attacks, a synthetic face or voice is used to defeat facial recognition or voice authentication systems and gain access to accounts.

Companies have lost millions to a single well-timed fake call, and the reputational damage often outlasts the financial loss.

Signs of a Deepfake: What to Look For

Many deepfakes can still be caught by careful observation. Watch for unnatural or irregular blinking, facial expressions that seem stiff, and lighting or shadows that do not match the surroundings. Look for blurring, flickering, or ghosting around the mouth, jawline, and hairline, especially when the person moves quickly.

In audio, listen for a flat or robotic tone, odd pauses, or speech that is slightly out of sync with the lips. These tells are becoming subtler as the technology improves, so human judgement alone is no longer a reliable defence.

Deepfake Detection Tools

Because fakes keep getting better, pair human checks with dedicated detection tools. Microsoft Video Authenticator analyses frames for blending errors and gives a manipulation probability score. Deepware Scanner is a free option for quickly checking a suspicious video. Sensity, formerly known as Deeptrace, offers enterprise-grade monitoring that scans for deepfake threats across platforms.

No single tool is foolproof. Treat their scores as one signal alongside verification and staff awareness rather than a final verdict.

How to Prevent Deepfake Attacks

Preventing deepfake fraud takes layered controls, not a single fix.

Replace voice or face-only verification with liveness detection and multi-factor authentication, so a cloned voice or face cannot unlock access on its own. Require a second, independent channel such as a call-back to a known number to confirm any high-value payment or sensitive request. Train staff to pause and verify urgent instructions, even when they appear to come from a senior leader. Add AI-driven email and communication filtering to flag impersonated or manipulated messages, and rehearse a clear response plan so employees know exactly who to contact when something feels wrong.

Staying Ahead of Deepfake Threats

Deepfake attacks succeed by exploiting trust and urgency, not just technology. The organisations that resist them combine the right tools with strong verification habits and a workforce trained to question anything that pressures them to act fast. Building those defences before an incident is far cheaper than recovering from successful fraud. Paramount helps businesses assess their exposure and put these protections in place.

Protect your business from deepfake fraud and talk to Paramount’s cybersecurity team today.

Frequently Asked Questions

A deepfake attack uses AI-generated video, audio, or images to impersonate a real person and commit fraud, theft, or manipulation. For the basics of the technology itself, see our glossary entry on what a deepfake is.

Require second-channel verification for every payment request, enforce multi-factor authentication, and train staff to pause on urgent voice or video demands. No single voice or face should ever be enough to authorise a transfer on its own.

No. Detection tools are improving but none is fully reliable, and deepfakes are getting harder to spot. Treat tool scores as one signal and combine them with human verification and strict payment controls.

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