How Deepfake Attacks Are Redefining Security Risks

The New Face of Cyber Threats: How Deepfake Attacks and AI Scams Are Redefining Security Risks

As artificial intelligence continues to evolve, so do cybercriminals' tactics. One of the most alarming developments in recent years is the rise of deepfake attacks—highly convincing AI-generated media designed to impersonate real individuals. These attacks are now being leveraged to exploit businesses and individuals alike, causing significant financial, operational, and reputational damage.

But the threat doesn’t stop there. Last week, the FBI issued an update warning of how generative AI is being used to target smartphone users in unprecedented ways. The risks have grown exponentially, from phishing scams and fake customer support calls to deepfake audio and video impersonations.

Here’s a closer look at the FBI’s findings, real-world examples of deepfake attacks, and the proactive steps you can take to safeguard your organization.

FBI Update: Generative AI Targets Smartphone Users

In its latest public service announcement (PSA I-120324-PSA), the FBI detailed how cybercriminals are increasingly leveraging generative AI to enhance the believability of their scams. Key examples include:

• AI-generated photos and videos used to impersonate real people.
• Synthetic audio of loved ones in crisis situations, asking for urgent financial assistance.
• Deepfake video calls from “company executives” or law enforcement officials requesting sensitive information.
• Celebrity-endorsed AI-generated content promoting fraudulent activities.

The FBI advises users to adopt simple but effective protective measures, such as creating a "secret word" with family members to verify authenticity during emergencies and reporting suspicious activity immediately.

Siggi Stefnisson, CTO of cybersecurity firm Gen, warns:

“Deepfakes are becoming so sophisticated that even experts may struggle to distinguish real from fake. This could lead to everything from personal smear campaigns to widespread political misinformation.”

Inside a Deepfake Attack: A SaaS Security Perspective

In SaaS ecosystems, where identity verification and remote access play a critical role, deepfake attacks can bypass traditional security measures. Here’s how a typical deepfake attack unfolds:

1. Target Identification: Cybercriminals identify a high-value target, often an executive or IT administrator.
2. Data Collection: They gather publicly available media—conference speeches, social media posts, and interviews—to train their deepfake models.
3. Synthetic Media Creation: Using advanced AI tools, attackers replicate the target’s face, voice, and gestures.
4. Social Engineering: Posing as the target, they contact employees and create a sense of urgency, requesting sensitive actions such as wire transfers or credential sharing.
5. Exploitation: Employees comply, granting attackers unauthorized access to critical SaaS platforms, leading to data breaches or financial loss.

Real-World Cases:

• Wiz CEO Deepfake Attempt: Attackers mimicked Assaf Rappaport, CEO of Wiz, to extract credentials. The attempt failed due to subtle inconsistencies in the deepfake voice.
• $25 Million Deepfake Fraud: A finance employee authorized a massive transfer after a convincing deepfake video call with their CFO.

Why SaaS Security Is Especially Vulnerable

Deepfakes erode trust in identity verification methods, making traditional authentication tools insufficient. Organizations relying on SaaS platforms must rethink their security frameworks to address these emerging threats.

Building Resilience Against Deepfake Attacks

Combatting deepfake threats requires a proactive, identity-first security strategy. Here’s how Savvy’s advanced solutions mitigate risks:

1. Continuous MFA Monitoring: Identifies SaaS apps without MFA and enforces compliance to block unauthorized access.
2. Just-in-Time Security Guardrails: Provides contextual prompts during high-risk actions, empowering employees to recognize and resist deepfake-driven manipulation.
3. SSO Bypass Detection: Ensures all activity routes through secure Single Sign-On systems, preventing attackers from exploiting direct logins.
4. Dormant Account Detection: Automates offboarding of unused accounts to eliminate opportunities for impersonation.
5. Credential Hygiene Enforcement: Identifies weak or compromised credentials and strengthens them in real time.

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The Path Forward

As generative AI tools become more accessible, deepfake attacks will only increase in sophistication and scale. Organizations must prioritize identity-centric security measures to protect their SaaS environments, employees, and customers.

By combining continuous monitoring, adaptive security measures, and real-time guardrails, solutions like Savvy empower businesses to stay ahead of these evolving threats.