AI-driven impersonation attacks are swiftly becoming one of the most pressing security concerns for businesses globally. According to Gartner, social engineering attacks, including those leveraging AI, are projected to account for nearly 75% of security breaches by 2025. What’s more? The increasing accessibility of deepfake technology has amplified this threat, with Statista projecting that ”the market for deepfake technology alone could reach $1.5 billion by 2030.”
Particularly, popular consumer messaging platforms, like WhatsApp and iMessage, are vulnerable to deepfake campaigns. In a recent report by Safeguard Cyber, 42% of surveyed businesses reported new security incidents on WhatsApp alone in 2023.
These trends show the urgent need for organizations to further secure their business communication channels in response to these new AI-driven threats. As Dima Gutzeit, CEO of responsible business communications platform LeapXpert, warns, “AI-powered tools allow attackers to convincingly mimic real people, making it extremely challenging for employees to detect fraud.”
But, first, what makes AI-driven impersonation attacks so powerful and why do they succeed?
Why AI-Driven Impersonation Attacks Succeed
AI-driven impersonation attacks succeed because they exploit both human trust and vulnerabilities in device and communication channels, making it difficult to distinguish legitimate users from imposters. According to IBM Security, 95% of cybersecurity incidents are due to human error, highlighting how susceptible employees are to well-crafted impersonation attempts. Gutzeit explains that “Cyberattackers exploit the fact that most mobile theft victims do not use protective measures, which makes data breaches from stolen devices a significant concern. They leverage AI to automate impersonation attacks and generate convincing content at scale.”
The success of these attacks stems from:
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- Human Error and Trust: Employees can miss subtle irregularities, especially in high-stakes interactions or under time pressure.
- Channel Vulnerabilities and Device Theft: Network vulnerabilities, such as call and SMS interception, allow attackers to hijack communication channels, eavesdrop on calls, or read two-factor authentication codes. In addition, millions of smartphones are lost globally each year. In fact, a 2016 report by Kensington noted that over 70 million smartphones are lost annually in the U.S., with only 7% recovered. The report further noted that “nearly 45% of mobile theft victims do not use protective measures,” increasing the risk of data breaches.
- Scalability: AI allows for automation, enabling cybercriminals to scale impersonation attacks quickly and with minimal human intervention.
Combating AI-Driven Impersonation Attacks
From deepfakes to AI-powered phishing scams and more, malicious actors continue to evolve their tactics for attacking businesses and wreaking havoc. These attacks grow more sophisticated by the minute, especially with generative AI now helping threat actors to launch malicious campaigns at scale.
To meet this growing threat, several leading companies have developed innovative solutions that leverage AI and advanced technology to detect, prevent, and mitigate impersonation attacks in real-time. For example, Proofpoint’s Cloud App Security Broker (CASB) and TAP solution offers a multilayered approach that monitors cloud-based messaging platforms for anomalies and user behaviors that deviate from established patterns.
Then there’s LeapXpert’s recently launched Messaging Security Suite, which is designed to fortify messaging communications against security threats. The solution uses AI to identify and flag impersonation attempts over WhatsApp, WeChat, iMessage, SMS and LINE in real-time. As Gutzeit notes, it’s “a comprehensive suite of tools — including messaging impersonation detection, antivirus/antimalware and content disarm and reconstruction (CDR) — aimed at protecting business messaging from various threats at scale.”
There’s also BlackBerry’s CylancePROTECT, an AI-based threat detection tool that looks for trends and impersonation risks before they get to important endpoints by using machine learning. By analyzing behavioral data from user interactions, it detects subtle shifts in communication patterns that might suggest deepfake or impersonation attacks, providing early warning and proactive protection.
The Future of AI-Driven Impersonation Defense
As AI continues to advance, so too must the tools used to combat AI-driven impersonation. Gartner predicts that by 2026, 40% of organizations will integrate machine learning into their security strategies to counter increasingly sophisticated AI-based attacks. Statista also forecasts the cybersecurity market, driven by demand for AI-integrated solutions, will double by 2026 before reaching $134 billion by 2030.
Through anomaly detection and ongoing behavioral learning, we will see a shift towards AI-based security systems in the next few years that not only spot impersonation in real time but also help to predict attacks. This is why, according to a McAfee report, over 70% of enterprises plan to increase investment in AI-driven cybersecurity tools — reflecting the growing recognition of AI as both a threat and a tool in the security landscape.
The future of cybersecurity will most certainly include systems that use predictive AI models, proactive monitoring, and adaptive defenses tailored particularly to AI-fueled vulnerabilities. Companies that invest in sophisticated, AI-enhanced security solutions like LeapXpert’s Messaging Security Suite and other leading platforms may protect themselves from today’s AI-driven impersonation assaults while also preparing for tomorrow’s complicated issues.
“Businesses using messaging platforms like WhatsApp for external communications, must be vigilant against rising cyber threats and embrace AI-driven solutions to effectively counter evolving AI-based attacks,” says Gutzeit.
