Updated on September 24, 2025, by OpenEDR
Have you ever seen a video of a celebrity saying something outrageous—only to discover later it wasn’t real? That’s the power (and danger) of deepfakes. With artificial intelligence (AI) and machine learning advancing rapidly, many are asking: what are deepfakes and why do they matter for cybersecurity and business?
Deepfakes are AI-generated videos, images, or audio recordings that manipulate reality by making people appear to say or do things they never did. While the technology can be used creatively, it also poses serious risks for businesses, politics, and online security.
In fact, according to research, deepfake incidents increased by over 550% in the last year, making them one of the fastest-growing cyber threats today.
What Are Deepfakes?
At its core, a deepfake is a piece of synthetic media created using deep learning algorithms. These AI models analyze and replicate human voices, faces, and movements to generate realistic-looking fake content.
Deepfakes can include:
Video Manipulation: Swapping one person’s face onto another’s body.
Audio Deepfakes: Mimicking someone’s voice to create false recordings.
Image Deepfakes: Generating fake photographs or altering existing ones.
👉 In short: Deepfakes blur the line between truth and fiction, creating challenges for trust, security, and authenticity in the digital age.
How Do Deepfakes Work?
Understanding what are deepfakes means looking at the technology behind them.
Data Collection – Large sets of images, videos, or audio recordings of a target are gathered.
Training the Model – AI algorithms, often GANs (Generative Adversarial Networks), learn patterns in the data.
Content Generation – The system creates synthetic media that looks or sounds like the target.
Refinement – The output is fine-tuned until it becomes nearly indistinguishable from reality.
Example: A deepfake of a CEO could be generated to issue a fake announcement about a company merger—potentially impacting stock prices and investor trust.
The Dangers of Deepfakes in Cybersecurity
Deepfakes are more than just internet pranks—they pose serious cybersecurity risks.
Phishing & Fraud: Attackers use deepfake audio to impersonate executives in “CEO fraud” scams.
Disinformation: Fake political videos can sway public opinion and elections.
Reputation Damage: Businesses can suffer from manipulated videos spreading false narratives.
Social Engineering: Hackers use deepfakes to trick employees into revealing sensitive data.
Legal & Compliance Issues: Deepfakes may lead to lawsuits, privacy violations, and regulatory challenges.
👉 According to security experts, 96% of deepfakes are malicious in intent, with financial fraud being one of the biggest concerns for enterprises.
Real-World Examples of Deepfakes
To better grasp what are deepfakes, let’s look at real cases:
2019 CEO Scam: Cybercriminals used a deepfake voice to impersonate a German CEO, tricking a UK employee into transferring €220,000.
Political Deepfakes: Manipulated videos of world leaders have circulated online, sparking disinformation campaigns.
Corporate Fraud: Fake conference calls with deepfaked executives have been reported, aiming to steal company funds.
Benefits of Deepfake Technology (The Positive Side)
Not all deepfakes are harmful. In fact, the technology has legitimate applications:
Entertainment: Used in movies for dubbing, aging effects, or recreating actors.
Education: Virtual instructors and interactive learning experiences.
Healthcare: Assisting patients with speech impairments by generating natural voices.
Marketing: Personalized video ads tailored to individual customers.
👉 The challenge lies in balancing innovation with responsible use.
Detecting Deepfakes
As deepfakes grow more sophisticated, detecting them becomes harder. However, IT and security teams can look for:
Inconsistent facial movements (blinking, lip-sync issues).
Unnatural lighting or shadows in videos.
Audio mismatches with lip movements.
Artifacts or distortions around faces and edges.
AI detection tools that analyze digital fingerprints of manipulated media.
How Businesses Can Protect Against Deepfake Threats
When it comes to cybersecurity, preventing deepfake-based attacks requires a multi-layered defense strategy:
✅ Employee Awareness Training – Teach staff how to spot suspicious audio or video.
✅ Multi-Factor Authentication (MFA) – Don’t rely on voice-only or video-only verification.
✅ Endpoint Detection & Response (EDR) – Monitor for unusual activity triggered by deepfake scams.
✅ Zero Trust Security – Never trust, always verify—especially with identity-based access.
✅ Legal Safeguards – Update policies and contracts to address deepfake misuse.
👉 Example: A financial services company uses EDR systems alongside strict access controls to stop fraudulent requests triggered by deepfakes.
Deepfakes vs Traditional Cyber Threats
| Threat Type | Example Attack | Risk Level for Business |
|---|---|---|
| Malware | Viruses, ransomware | High |
| Phishing | Fake emails & websites | High |
| Deepfakes | Fake audio/video scams | Emerging but growing |
👉 Verdict: Deepfakes are becoming just as dangerous as traditional cyberattacks, especially in social engineering schemes.
Best Practices for IT Leaders
To reduce risks, IT managers and executives should:
Build incident response plans that account for deepfake threats.
Deploy AI-powered detection tools to analyze media authenticity.
Integrate EDR solutions for endpoint monitoring.
Regularly review communication protocols to avoid relying solely on audio/video confirmations.
Encourage a culture of verification—employees should always double-check unusual requests.
FAQs: What Are Deepfakes?
1. Are deepfakes illegal?
Not always. Some are used legally in entertainment or education, but malicious deepfakes (fraud, defamation) are illegal in many countries.
2. Can deepfakes be detected?
Yes, though it’s challenging. AI tools and human analysis together provide the best detection results.
3. Why are deepfakes dangerous?
Because they exploit trust—making people believe false information, enabling fraud, and damaging reputations.
4. Do businesses need to worry about deepfakes?
Absolutely. Enterprises are prime targets for financial scams and disinformation campaigns.
5. How can companies fight back?
Through employee training, MFA, EDR solutions, and AI detection tools to identify and stop deepfake threats.
Conclusion: Deepfakes as the Next Cybersecurity Frontier
So, what are deepfakes? They are AI-generated synthetic media that can be used for good—or exploited for fraud, disinformation, and cybercrime. For IT managers, CEOs, and cybersecurity professionals, deepfakes represent an emerging threat that demands immediate attention.
While detection tools are improving, the best defense lies in layered security strategies: combining education, strict verification, and advanced tools like EDR solutions.
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