To understand the full scope of these attacks, let's break down the specific tactics cybercriminals are using to exploit deepfakes in real-world scenarios.

Voice cloning for vishing attacks

Attackers can now clone someone's voice and use it to impersonate your CEO, IT director, or a trusted vendor. In the first publicly known case of AI voice fraud, the CEO of a British energy company wired €220,000 (approximately $243,000) after receiving a phone call from what he thought was his superior at the group's German parent company. The deepfake was so convincing that the CEO even noted his boss's light German accent.

But it's not just business leaders being targeted. In July 2025, an unknown individual used an AI-synthesized voice to mimic US Secretary of State Marco Rubio. The impersonator was able to reach three foreign ministers and two US officials over Signal messaging until security teams discovered the deception.

Workday, the HR software giant, confirmed in August 2025 that hackers impersonated their own IT and HR officials to trick employees into resetting passwords, giving attackers access to sensitive customer data from a third-party platform.

So what makes these attacks so dangerous? They combine urgency with the trust of a familiar voice.

Video deepfakes for business email compromise (BEC)

Imagine joining a Zoom call with your CFO, only it's not your CFO at all, but a video deepfake. Attackers typically aim to persuade finance teams to initiate wire transfers or employees to give up their login credentials.

"Phishing isn't just about mass email blasts anymore. Attackers are leveraging breached data, open-source intelligence, and AI-generated deepfakes to craft highly personalized lures. We're seeing convincing deepfake audio used in wire fraud, generative AI powering phishing emails that evade detection, and attackers social engineering their way past identity verification."

—Prakash Ramamurthy Huntress Chief Product Officer

The good news? Even high-quality deepfakes still have tells, if you know where to look. Successful deepfake detection starts with recognizing these warning signs.

Visual inconsistencies

Look for unnatural facial movements, especially around the eyes and mouth. Deepfakes often struggle with realistic blinking patterns, lip synchronization, and natural facial expressions. Pay close attention to the boundary where the face meets the hair or background. Look for flickering or strange distortions in that area.

Audio irregularities

Even the most advanced voice clones have telltale signs. Listen for abnormal breathing patterns, unnatural voice modulation, or background noises that seem inconsistent with the supposed environment. AI can replicate the general tone, but it may miss nuances, like the way someone pronounces certain words, their specific accent, or the jargon they frequently use.

Context and behavioral cues

Trust your instincts. Does the request align with standard protocols? Is the urgency realistic? Scammers often create a sense of urgency to prevent you from overthinking. Verify unexpected requests through alternative communication channels, especially those involving financial transactions or sensitive information.

Technical artifacts

Examine the lighting. Deepfakes may not match environmental lighting conditions or contain shadows that fall in the wrong direction. Watch for sudden drops in quality or glitches that suggest AI processing.

Fighting deepfakes takes a combination of smart technology and alert employees:

Automated deepfake detection software

Deepfake detection software uses AI to fight AI—scanning videos and audio for the telltale signs of manipulation that the human eye and ear may not detect. The tools can scrutinize pixel-level irregularities, analyze compression artifacts, and identify AI-generated patterns invisible to the naked eye. Tools range from browser extensions to enterprise systems that scan incoming media.

Biometric analysis

Some advanced tools use biometric analysis to detect signs of manipulation, such as micro-expressions, pulse visible as slight color variations in the skin, and other natural physiological responses. These deepfake detection solutions can provide additional layers of verification for high-risk communications.

Verification protocols

Technology can only get you so far. Enforce multi-channel verification for sensitive requests. If you get a suspicious request during a video call, call the known, trusted number to confirm. Pre-establish verification systems, like code words, security questions, or other shared secrets that a deepfake attacker is unlikely to have. Also require multi-factor authentication (MFA) for key actions involving money or data.

Metadata analysis

Check the file's metadata for creation dates, editing history, and file source information. Sophisticated attackers may strip metadata, but its absence or anomalies can be a red flag in itself.

No matter how many threat detection tools you use, none of them will matter if employees lack the training and awareness to spot these threats.

Effective training programs don't simply explain what deepfakes are, but how they're used as part of a broader attack strategy, like multi-stage attacks. For instance, attackers might send a phishing email referencing a deepfake video call, or use a voice cloning attack that piggybacks on the data they gathered through social media reconnaissance.

Instill a company culture that doesn't punish employees for verifying suspicious activity. Make it part of your company culture for employees to ask questions about unusual requests, even if they seem to come from upper management. Encourage employees to double-check requests, even if they appear to be from the CEO.

Hold periodic red teaming exercises to help employees practice spotting fake emails and calls in realistic scenarios. These exercises help instill muscle memory around security protocols so employees are less likely to simply assume an unexpected communication is legitimate, even when it appears to be from a trusted colleague or superior.

The Huntress Managed SAT complements these efforts by keeping your employees alert to emerging threats. Paired with Huntress Managed Identity Threat Detection and Response (ITDR) solutions, your organization gains both the technical controls and the trained human layer needed to identify and respond to identity-based attacks.

Don't think of deepfake attacks as single, isolated attacks. Expect attackers to use deepfakes as part of larger, multi-stage campaigns designed to exploit your team's trust and circumvent existing controls. Combatting it requires a mix of detection strategies and a security-aware culture built to respond. As deepfake cybersecurity threats continue to evolve, staying ahead requires continuous adaptation.

Huntress Managed SAT keeps your employees focused on deepfakes and the social engineering attacks they enable. We keep your training up-to-date and relevant as new threats emerge so your employees can recognize the latest AI-powered scams.

Start a free trial of the Huntress platform to see how we help your teams recognize and respond to deepfake-enabled attacks before they cause harm.