Shifting Focus in the Fight Against Deepfakes: Why Contextual Analysis Matters

October is Security Awareness Training Month, and there’s no better time to sharpen our defenses against one of the most insidious threats out there: Deepfakes. With advancements in artificial intelligence, bad actors are using deepfakes to manipulate audio and video to impersonate trusted individuals in both professional and personal settings. The danger doesn’t stop at mimicking facial features or voice patterns—these deceptive tactics are being weaponized in social engineering, voice phishing, and business compromise scams.

In response, many organizations have emphasized teaching employees how to spot deepfakes by relying on visual or audio clues. But here’s the catch: deepfakes have become so sophisticated that visual markers like strange facial movements, odd lighting, or unusual voice tones are no longer reliable. Focusing solely on these physical traits is a risky approach.

Instead, we must shift our attention from “spotting” deepfakes visually to analyzing them contextually. By focusing on the content, intent, and context of the interaction, we can more effectively combat deepfakes, regardless of how flawless they appear visually or audibly.

Let’s explore a more effective approach using the STOP framework from Breacher.ai, which can help employees take a step back and evaluate interactions critically. This method prioritizes contextual clues over superficial markers, giving your team a much stronger defense against deepfakes.

The STOP Framework for Identifying Deepfakes

1. Source: Verify Source, Is it a Legitimate Ask or Authentic?

Evaluate where the message is coming from. Is the call, email, or video coming from a trusted channel, or is it an unexpected communication? Always verify the identity of the sender, especially if the request is urgent or unusual.

– Tip: Rather than trusting a familiar face or voice in a video, double-check contact details and cross-reference with known records before acting on any instructions.

2. Timing: Is there Urgency or Pressure to Act?

Ask whether the timing makes sense. Are you expecting a call from this person? Does the message align with any recent interactions? Fraudsters rely on urgency to pressure you into making quick decisions.

– Tip: If a message seems out of the blue or is asking for immediate action (especially involving money or sensitive data), take a pause and confirm directly with the person through a separate, verified communication channel.

3. Objective: What is being asked and Does it Contain Sensitive Information?

What is the goal of the interaction? Deepfakes are often used to manipulate people into sharing sensitive information or transferring funds. If the request seems unusual, even if it’s coming from someone you know, question the motives behind it.

– Tip: Ask yourself: “Why is this person asking for this information, and why now?” Requests for login credentials, financial transfers, or confidential data should always be treated with extra caution.

4. Place: Communication Channels That Deviate From the Norm.

Where is the interaction taking place? A sudden change in communication platform (such as switching from email to a private video call) should raise red flags. This can indicate an attempt to bypass normal security measures.

– Tip: If a colleague or partner suddenly wants to discuss sensitive business over a less secure platform, be suspicious and take steps to verify before proceeding.

The Importance of Contextual Analysis

Why should we prioritize contextual analysis over visual spotting? Quite simply, deepfakes are designed to deceive the eye. AI-generated video and audio are reaching levels where even experts struggle to differentiate real from fake based on visuals alone. Deepfake creators are well aware of traditional tell-tale signs, like unnatural blinking or lip-sync errors, and they’re constantly improving their techniques.

However, context remains much harder to manipulate. Fraudsters may be able to create a perfect likeness of a trusted colleague or CEO, but they can’t recreate the unique circumstances of your relationship or recent communications. By focusing on what’s being asked, when it’s being asked, and through which channel, employees can flag potentially fraudulent interactions even when they seem convincing on the surface.

Why Your Team Needs This Shift

Encouraging employees to stop relying on visual clues and start analyzing context will empower them to detect deepfakes based on the content of the message, not the appearance of the messenger. In today’s rapidly evolving threat landscape, this shift is crucial. Employees can no longer rely on gut instinct or basic visual tell-tale signs. They need a methodical, critical approach to evaluating every interaction.

Conclusion

As we observe Security Awareness Training Month, it’s time to evolve our defenses against deepfakes. The STOP framework provides a reliable method for identifying suspicious behavior by focusing on contextual clues rather than visual ones. Training your employees to apply these principles will help your organization stay one step ahead of even the most sophisticated AI-based attacks.