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Consider the next email in your inbox or incoming phone call. It could be the boss assigning you a task. Or perhaps someone with legitimate credentials is requesting information. And next thing you know, you’ve fallen victim to a financial scam.
Cybersecurity faces a new frontier: Synthetic identity fraud and AI-driven phishing. These threats impersonate trusted individuals. They utilize generative AI to create convincing fakes and bypass traditional defenses.
It’s time to expose these digital doppelgangers!
What is Synthetic Identity Fraud?
Synthetic identity fraud is not traditional identity theft. Attackers don’t steal a single person’s identity. Instead, they fabricate new ones.
Building Identities with Real and Fake Data
Synthetic identity fraud is like building Frankenstein. It uses stolen or made-up elements (in this case, personal information, not body parts) and combines them to create a persona.
Fraudsters take real Social Security Numbers (SSNs) and addresses, sprinkle in some fake names with background information, and voilà — a fake identity that seems legitimate.
Why Synthetic Identities Are Hard to Detect
Synthetic identities are patient. Once cybercriminals create a believable persona, they nurture and develop it over time. They’ll, for instance:
- Open bank accounts and credit lines, and build financial histories
- Pay bills (but only in small amounts)
- Establish an online footprint (email address, social accounts, etc.)
- Apply to jobs
It’s the diligence and patience that make these more complex. Blatantly stolen identities are relatively easy to detect. One red flag, like suddenly appearing across the country or a personal data mismatch, and the jig is up.
With synthetic identities, however, those mismatches never appear. Victims remain unaware because attackers fabricate the persona from the ground up. It’s so challenging to find, in fact, that fraud losses from this attack hit $35 billion in 2023.
What starts as a fabricated digital persona can quickly escalate when paired with AI; these identities evolve into tools for convincing impersonation and social engineering.
Deepfakes and AI-Driven Social Engineering
Artificial intelligence (AI) threats take these nuances a step further. After creating a convincing profile, AI delivers convincing impersonation attacks via deepfake social engineering, making them dangerously persuasive.
Voice Cloning for Business Email Compromise (BEC)
Imagine this: You get an urgent call from your boss. At least you assume it is your boss because the voice sounds identical. They instruct you to send $100,000 to a specific account to make a late payment to a vendor. In reality, a cybercriminal is behind the voice.
In the past, attackers would craft legitimate-looking emails appearing to be from a trusted sender (email spoofing). Of course, email security tools have improved in spotting the scams.
Fast-forward to today, and attackers scrape voice samples from social media to clone accents and speech patterns. These voice and video impersonation attacks are common in AI-driven phishing campaigns. In 2024, over 105,000 deepfake attacks were reported, resulting in $200 million loss in just Q1.
Video Deepfakes in Remote Work Environments
Video deepfakes take social engineering a step further. With so much adoption of Zoom and other video conferencing tools, every conversation has to be legit, right?
Sadly, no. Deepfake technology can animate a still image (using AI) to make it appear as if someone is speaking live. You might think you’re talking to a work colleague when, in reality, it’s a sophisticated cybercriminal.
Like voice cloning, they’ll use this attack to authorize fraudulent transactions or extract sensitive information.
These aren’t just hypotheticals. Organizations across industries are already experiencing high-profile attacks that show the financial and operational damage of synthetic identities and deepfakes.
Real-World Examples of Synthetic Identity and Deepfake Attacks
The theoretical is now reality. Synthetic identities resulted in over $3.3 billion in lending exposure to individuals who aren’t even real. These false profiles and deepfakes can truly hit victims hard. Here are some high-profile cases:
High-Dollar Financial Fraud Cases
Financial institutions, large and small, have fallen victim to fraud by synthetic identities. Some notable cases include:
- New York Bank scam: Dozens of conspirators used synthetic identities to steal nearly $1 million from multiple New York banks and illegally take COVID relief funds.
- 2017 Georgia bank fraud: An Atlanta, Georgia resident used stolen SSNs to create synthetic identities. He defrauded banks out of $2 million in credit and loans.
- Decade-long Ontario scheme: In 2024, 12 individuals in Ontario, Canada, created over 680 synthetic identities to open fake accounts and credit lines. This scheme resulted in over $4 million in confirmed losses.
Deepfake Impersonation in Corporate Environments
Your everyday employees have also fallen victim. In one wild case in Hong Kong, a finance employee thought he was on a video conference with the CFO and a few other colleagues.
It turns out that every person on that call was a deepfake. They ultimately persuaded him to transfer nearly $25.6 million to fraudulent accounts. What’s crazier is that the team of fraudsters all stole citizen identity cards for data to create synthetic identities. There were 90 loan applications and 54 bank account registrations before the attack.
Another case targeted the CEO of the world’s largest advertising group. Though unsuccessful, scammers created a fake WhatsApp account pretending to be the CEO. They then set up a Microsoft
Teams meeting with the employee and used YouTube video footage to create a voice clone of the executive. The goal: Convince the victims to set up a new business to solicit money and personal information.
With incidents like these already costing millions, the question becomes not if but how organizations can verify identities and detect AI-powered fraud before damage occurs.
Detection and Verification Methods
No one seems safe anymore. The best practice for phishing emails used to be call-and-confirm. But with voice cloning and deepfakes, that doesn’t seem as foolproof.
Proactiveness and layered defenses are the best bet against the AI revolution and sophisticated attackers.
Multi-Layered Identity Verification
Relying on a single data point is obsolete. Companies must layer their controls with mechanisms that cybercriminals can’t deepfake.
Biometric authentication, such as fingerprinting, facial recognition, and eye scans, is nearly impossible to break. Each individual carries unique data, so scammers cannot replicate it.
Users also have unique behavioral patterns. After all, we are creatures of habit. Some log in at specific time windows, only use certain apps or devices, and exhibit online patterns (such as keystrokes, navigation, etc.). Set baselines for “normal” and continuously monitor to spot anomalies that could indicate a threat.
Deepfake Detection Technologies
Fortunately, the security industry became aware of deepfake technology early. Specialized tools can now analyze digital media for signs of manipulation.
Unnatural eye blinking? Probably fake. Inconsistent lighting or weird audio glitches? Another tell-tale. For audio-specific deep fakes, algorithms can also detect the synthetic lack of breath sounds or unnatural cadence.
Human-in-the-Loop Verification Workflows
Consider the human advantage. While people are the biggest liability to security, we can also set controls that technology cannot.
Implement protocols like mandatory callbacks to a verified number for payment approvals. Or dual-authorization requirements, where multiple users must review and approve requests. And if it’s unusual or invoking urgency and secrecy, manually review with your own eyes.
These verification methods are most effective when integrated into a comprehensive security strategy. CyberMaxx’s MDR approach offers unique value in that role.
CyberMaxx’s Role in Protecting Against Emerging Threats
CyberMaxx integrates defense against these nuanced threats directly into our Managed Detection and Response (MDR) service. Rather than wait, we constantly hunt, looking for signs of fabrication.
Integrating Threat Intelligence for Social Engineering
Attackers use new tactics, techniques, and procedures every day. Our intelligence feeds stay agile to anticipate and counter those moves.
Our team continuously monitors the evolving methods of synthetic identity fraud and emerging deepfake tools. Using data from dark web and criminal forums, threat research reports, and Open-Source Intelligence (OSINT) threads, our defenses stay one step ahead.
Proactive Response to Identity and Deepfake Threats
Is there a potential indicator of an impersonation or social engineering attack? No matter how subtle, our team is on the scene.
We’ll correlate identity verification failures, network anomalies, and suspicious communication patterns to uncover coordinated campaigns. With our fast, guided response, our team quickly identifies and removes cyber threats before they can trick employees.
Value for CyberMaxx Clients
Real-time, integrated defense sets CyberMaxx apart. You don’t have time to evaluate countless data sources and determine whether a request is legit or fake.
We integrate deepfake and synthetic identity detection into the core of our MDR service. A single, unified view of threats across endpoints, identities, and cloud environments that prevents threat actors from hiding.
The lesson is clear: threats are advancing fast, but with the right partner, organizations can stay a step ahead.
Staying Ahead of Synthetic Identity Fraud and AI-Powered Threats
Deepfake fraud cases are on the rise. From 2022 to 2023, there was a 1,740% surge in cases across North America. This surge isn’t an emerging threat; it’s already here.
But CyberMaxx is here to defend your trust layer against AI-powered impersonation. With advanced detection and proactive response, you can combat social engineering tactics and stay resilient in the deepfake era.