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KnowBe4: Deepfake Detection & Defense Training for Organizations

KnowBe4
04/29/2026
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TL;DR

  • 62% of organizations experienced deepfake attacks in the last 12 months, with attackers now using consumer-grade tools ($0-20/month) to create nation-state-quality synthetic media targeting social engineering and biometric verification systems.
  • Current deepfake detection tools show significant limitations with "coin toss accuracy" for pre-recorded content, though multi-layered detection during live video calls (voice prints, frame rates, liveness detection) offers more promise for specific use cases like remote hiring.
  • KnowBe4's new platform feature allows administrators to create custom deepfake training videos using company executives in 20-30 minutes, helping inoculate employees by demonstrating how easily convincing synthetic media can be generated.
  • Real-world attack vectors include ringless voicemail campaigns with voice cloning, FBI-documented government official impersonations, and systematic harvesting of YouTube videos for unauthorized deepfake creation and political manipulation.
  • Organizations must adopt verification frameworks that emphasize confirming requests through separate communication channels rather than relying solely on detection technology, as persistent attackers can bypass most automated detection systems.
  • The "folk grade" accessibility of deepfake tools means anyone with internet access can now create weaponizable synthetic media, requiring fundamental shifts in how organizations approach identity verification and trust in digital communications.

The Deepfake Threat Landscape in 2026

Perry Carpenter, KnowBe4's Chief Human Risk Management Strategist, delivers a comprehensive examination of how deepfake technology has reached a critical tipping point in 2025-2026. Recent Gartner research reveals that 62% of organizations experienced deepfake attacks within the last 12 months, with attacks targeting both social engineering scenarios and automated verification systems like voice biometrics. The presentation emphasizes that deepfake creation tools have reached "folk grade" accessibility—anyone with an internet connection and $0-20 per month can now create nation-state-quality synthetic media. This democratization of sophisticated attack technology means organizations can no longer rely solely on detection tools, which Carpenter demonstrates can be bypassed with persistence. The session explores real-world attack vectors including ringless voicemail campaigns, CEO impersonations, and political disinformation, while providing practical frameworks for building organizational resilience against synthetic media threats.

Detection Limitations and Multi-Layered Defense

The presentation provides critical insights into the current state of deepfake detection technology, revealing significant limitations that security teams must understand. Carpenter demonstrates through personal testing that most detection platforms exhibit "coin toss accuracy" when analyzing pre-recorded video, audio, or images—attackers with sufficient persistence can bypass these tools. However, detection shows promise in specific scenarios: live video calls where multiple verification layers can be applied simultaneously, including voice print analysis, frame rate monitoring, vascular liveness detection, and artifact identification. This multi-layered approach makes it significantly harder for attackers to maintain convincing synthetic identities during prolonged interactions. The session emphasizes that organizations should implement detection as one component of a broader defense strategy, particularly for high-risk scenarios like remote hiring interviews and executive communications, rather than relying on it as a silver bullet solution.

KnowBe4's Deepfake Training Platform

Chris Littlefield, Principal Product Manager at KnowBe4, demonstrates the company's new deepfake creation capability within their security awareness platform. The tool allows administrators to upload a 1-2 minute video of a company executive or leader, then automatically generate convincing deepfake videos using pre-built social engineering scenarios. The two-step process uses ElevenLabs for voice cloning (approximately 3 minutes) and relipsync technology for video generation (20-30 minutes), requiring only basic video upload and scenario selection from the admin. The platform currently supports four languages (US English, UK English, European Spanish, Latin American Spanish) with expansion planned. Five pre-built scenarios cover common attack vectors including urgent requests, personal connections, and CEO impersonations. The feature is designed to help organizations inoculate employees against deepfake attacks by demonstrating how easily convincing synthetic media can be created using familiar faces from their own leadership team, reinforcing the critical importance of verification through separate communication channels.

Practical Attack Vectors and Real-World Examples

The session explores multiple real-world deepfake attack scenarios currently targeting organizations. Ringless voicemail technology combined with voice cloning enables attackers to deliver convincing messages directly to voicemail inboxes without triggering phone rings, achieving significantly higher engagement rates than traditional phishing. The FBI has documented ongoing campaigns impersonating US government officials dating back to 2023, often using multi-stage attacks that begin with text or email directing targets to "secure" channels like Signal or WhatsApp. YouTube content creators face systematic harvesting of their videos for unauthorized deepfake creation, with political commentators finding themselves saying things they never said. Carpenter demonstrates the ease of creating convincing deepfakes using readily available tools: Google Gemini's image generation, HeyGen's Avatar 4 for image-to-video animation, and various relipsync platforms. The presentation includes live demonstrations showing how a single image can be transformed into a speaking video, and how existing video can be manipulated to change words while maintaining lip sync—all using consumer-grade tools accessible to anyone.

Chapters

0:00 - Introduction and Session Overview
2:04 - Defining Deepfakes and Synthetic Media
5:03 - Current Threat Landscape Statistics
6:41 - Detection Technology Limitations
11:18 - Folk Grade Accessibility of Tools
35:59 - Ringless Voicemail Attack Vector
37:38 - FBI Government Impersonation Cases
39:10 - Live Deepfake Creation Demonstrations
42:38 - YouTube Video Manipulation Examples
55:30 - KnowBe4 Platform Demo Introduction
56:01 - Admin Deepfake Creation Workflow
59:42 - Why Organizations Need This Feature

Key Quotes

4:48 "Deep is just the neural networks, the AI-ness of it all. And fake is the fact that you are generating a false version of reality."
11:36 "We're at the point right now where everything that I look at and everything that I'm going to show to you today is at this folk grade level. And by folk grade, I mean it is accessible to anybody with an Internet connection and zero to $20 per month."
11:48 "You can now create deep fakes that are weaponizable at the level of a nation state actor. Now, of course, nation states always have a little bit better, a little bit more robust technology. But right now we have all of us, anybody attending this session has tools that they can use at their fingertips that would have made a nation state salivate a few years ago."
12:19 "The real problem of humanity is that we have paleolithic emotions, medieval institutions and godlike technology."
5:45 "Nearly two thirds, 62 percent of organizations have experienced a deepfake attack within the last 12 months, according to a new Gartner survey."
7:10 "Every single deepfake detection platform that I've tested right now, I've been able to bypass either intentionally or accidentally."
37:27 "The ability to create emotion in a voice has gotten to where it's just as good as a human using a microphone. And you may not believe me, but I'll tell you it's true."
60:19 "It is already, technology is quite good. It's only going to get better and more difficult to tell reality versus deepfake."

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