Artificial intelligence (AI) is one of the hottest buzzwords across industries, seemingly connected to almost every aspect of technology. AI models are helping software and tech products take their services to the next level, enhancing speed, accuracy, and efficiency. But this leap forward also introduces a deceptive shadow: AI-powered cybercrime.
Companies may feel adequately protected against standard cyber threats, but many underestimate AI-powered cybercrime risks. This gap stems from a lack of understanding of the widespread prevalence of AI-powered cybercrime, how it works, and best practices for prevention.
Are you prepared to defend your business against the cyber threats lurking in some AI systems?
Read on to learn how AI is accelerating cyberattacks, real-world examples, and proactive security strategies to help your organization stand strong against the evolving world of cybercrime.
A Complete Guide to Cybersecurity
Download this eBook to learn how to protect your business with an effective cybersecurity program.
The rising threat of AI-powered cybercrime
AI is forever changing the landscape of cybercrime. The World Economic Forum’s latest Global Risks Report identifies adverse outcomes of AI technologies as one of the top 10 risks, alongside other technology risks like misinformation and disinformation, as well as cyber espionage and warfare.
This rising threat is due to the nature and ease of access to AI-powered cyberattacks. AI often utilizes automation to enhance speed and efficiency. For AI-driven cybercrime, automation lowers the barrier to entry for cybercriminals, making attacks more frequent and sophisticated—even if the attackers lack manual skills. Additionally, AI-driven cyber threats are constantly evolving, often faster than traditional security tools can detect.
The ability to quickly craft a cyber attack strategy and deploy it against organizations without proper defenses has led to an explosion of AI-powered cybercrime, including sophisticated phishing, deepfake, and malware attacks.
AI-powered cyberattacks: faster, smarter, and harder to detect
AI-powered cyberattacks are usually enhanced versions of standard cyberattacks that utilize artificial intelligence technology to enhance speed, sophistication, and evasion tactics. Examples include:
- AI-powered phishing
- Deepfake-based fraud
- Automated AI-driven malware
AI-powered phishing
Phishing is one of the most effective and common types of cyberattacks. It relies on tricking victims into clicking malicious links, sharing sensitive data, or downloading malware. Standard phishing emails and messages use predictive templates and poor grammar, which makes them easier to detect.
AI-powered phishing, however, creates a more sophisticated attack by addressing those shortcomings. AI can analyze vast amounts of online data (e.g., social media, company websites, and email patterns) to craft hyper-personalized messages that mimic real communications. Unlike traditional phishing, AI-generated messages are free from awkward phrasing, making them indistinguishable from legitimate communications. Plus, automated AI can generate thousands of unique, well-crafted phishing attempts at scale. These tactics can occur across email and real-time chat interactions.
Deepfake-based fraud
Deepfake technology uses AI to create hyper-realistic synthetic media that impersonate real individuals, including videos, images, and voice recordings. This capability has opened new doors for cybercriminals, specifically around business fraud and identity theft.
Hackers can utilize AI deepfake technology to create fake videos or voice recordings of key organization executives, tricking employees into transferring funds or sharing sensitive data. These deepfakes can even be generated in real-time, making live calls appear legitimate or used in tandem with phishing and ransomware campaigns to boost their credibility. Deepfake-based fraud is often used in urgent, high-stakes situations to encourage victims to act quickly, giving them little time to double-check the legitimacy of the content.
Automated AI-driven malware
Malware attacks traditionally are programmed with a fixed set of attack instructions. AI-driven malware takes this attack to the next level by using machine learning to evolve, adapt, and evade detection.
Whereas standard malware code is static, AI malware can alter its structure to bypass antivirus programs and security tools that rely on pattern recognition. The AI can even analyze a system’s defenses and adjust its attack strategy in real time—making it extremely difficult to detect and remove. Additionally, AI can scan networks, identify high-value targets, and prioritize attacks based on potential impact rather than just launching a blind attack.
A Complete Guide to Cybersecurity
Download this eBook to learn how to protect your business with an effective cybersecurity program.
Real-world cases of AI cybercrime in action
These examples of AI-powered cybercrime may seem far-fetched, but there are already examples across different industries. AI-driven cybercrime is having an active impact on businesses, including financial losses, reputational damage, and regulatory penalties. Some recent examples of AI-powered cybercrime include:
- Gmail users targeted via advanced AI-phishing campaign (2025): Attackers leveraged AI to craft compelling phishing emails targeting Gmail users. These emails utilized AI to generate content that closely mimicked legitimate communications, making them more persuasive and harder to detect.
- UK energy firm defrauded by Deepfake-based CEO impersonation (2019): The CEO of a UK-based energy firm was defrauded of €220,000 after scammers used AI-generated audio to mimic his boss’s voice, instructing him to transfer funds to a fraudulent account.
- AI-malware, SugarGh0st RAT, targets AI experts (2024): A cyberespionage campaign utilized the SugarGh0st Remote Access Trojan (RAT), an AI-enhanced malware, to target U.S. AI experts. The attackers employed AI to enhance the malware’s capabilities, enabling it to adapt and evade traditional security measures.
Alongside these examples is one small victory—when a Ferrari executive suspected messaging and a voice call from his CEO were utilizing deepfake technology, he asked the caller one question that completely derailed the scammer: “What book did I lend you recently?” The scammer immediately ended the call, a good reminder that even the smallest defense measure—security questions—can work against the biggest threats!
How to strengthen cyber defenses against AI threats
Unfortunately, one or two security questions are not always enough. Organizations must implement stronger cyber defenses to protect themselves against the growing threat landscape of AI-powered cyberattacks. With advancements in AI algorithms, generative AI, large language models, and other AI tools, companies must shift from reacting to breaches to proactively mitigating AI-powered threats.
Consider the following strategies that your organization can work on immediately implementing to help strengthen cyber defenses against AI threats.
Continuous attack surface monitoring
AI-powered cyber attacks focus on vulnerabilities in an organization’s external attack surface. These vulnerabilities can include misconfigured cloud storage, exposed security team credentials, or outdated software. Continuous attack surface monitoring helps organizations proactively detect and secure these weaknesses before attackers can exploit them.
While it may seem counterintuitive to use an AI cybersecurity tool to detect AI cyber threats, it’s a great way to utilize artificial intelligence's benefits. AI-driven scanning can identify publicly accessible assets and potential vulnerabilities across external attack vectors (including cloud environments, web applications, and network traffic) in real time, often faster and more accurately than manual scans. Unauthorized apps or cloud instances classified as Shadow IT can also inadvertently expose your organization. However, continuous attack surface monitoring identifies and alerts you of these gaps before attackers exploit them.
Consider the following steps to protect your organization using continuous attack surface monitoring:
- Deploy an attack surface management (ASM) tool that uses AI for continuous monitoring
- Regularly review your organization’s exposed assets, credentials, and misconfiguration flagged by ASM tools
- Automate alerts for new vulnerabilities to ensure immediate remediation
- Conduct penetration tests to assess security gaps from an attacker’s perspective
Advanced threat detection with AI
You often don’t hear the phrase “fight fire with fire” in cybersecurity circles, but when it comes to AI-powered cyberattacks, sometimes using your opponent’s tools can help strengthen yours. AI-powered threat detection does just that—using the power of AI to analyze behavioral patterns, detect anomalies, and respond in real time.
These enhanced tactics work perfectly against AI-enhanced cyberattacks, which are designed to evade traditional security systems by constantly changing tactics. AI-powered behavioral analytics identify any change from normal system activity to detect suspicious behavior, and machine learning algorithms can analyze attack data to predict and flag new AI-driven attack techniques. Additionally, AI-driven network monitoring can detect and isolate malicious activity faster than traditional rule-based detection methods.
Get started with AI-powered threat detection with the following:
- Invest in AI-powered security information and event management (SIEM) or extended detection and response (XDR) to detect threats in real-time
- Deploy endpoint detection and response (EDR) solutions that use AI to spot evolving malware tactics
- Continuously train AI detection models with attack pattern datasets to improve your threat identification
- Implement automated response systems to isolate any detected threats before they can spread immediately
Employee cyber awareness training
Even the most advanced cybersecurity defenses can be circumvented if employees fall victim to AI-driven phishing or deepfake scams. Cyber awareness training helps ensure that employees recognize these threats and take proactive measures to avoid them. This type of training is especially important as many employees are unaware of what AI-powered cyber threats are and how they work.
Focus your employee cyber awareness training around understanding AI-powered cyberattacks and how these new threats may affect your organization. Utilize hands-on projects, like evaluating AI-generated phishing emails and deepfake fraud attempts. This type of training data allows employees an up-close look into what a potential AI-powered cyber attack may look like in the future. Update your organization’s incident response plans to include AI-specific cyber incidents, which can help inform critical decision-making during a security incident.
Kickstart AI-focused employee cyber awareness training with these tips:
- Launch a phishing simulation program using AI-generated phishing attacks to train employees on potential threats.
- Conduct deepfake awareness training, showing employees typical deepfake user behaviors and how AI-generated social engineering attacks work.
- Establish a security verification process, requiring employees to confirm sensitive information requests through multiple communication channels.
- Reinforce password hygiene, multi-factor authentication (MFA), and other access control best practices.
Stronger identify verification controls
Deepfake technology allows cybercriminals to convincingly impersonate executives, employees, or vendors. Strengthening identity verification makes it harder for attackers to bypass authentication processes using AI-generated voices, images, or videos.
Take some time to review your organization’s existing identity verification controls and consider including additional controls specifically focused on preventing deepfake fraud. Multi-factor authentication (MFA) will prevent unauthorized access, even if security credentials are stolen through AI phishing. You can add an additional layer of identity verification through biometric authentication like fingerprint, facial recognition, or voice ID. Real-time liveliness detection is a new piece of technology that can ensure video or audio authentication isn’t faked using deepfake technology—a powerful way to prevent deepfake-specific cybersecurity threats.
Enhance identity verification controls at your organization by implementing the following:
- Require MFA for all user accounts, especially for financial transactions and access to sensitive data
- Use biometric authentication for executive approvals and high-risk transactions to prevent unauthorized access
- Implement real-time liveness detection to counter deepfake voice and video impersonation scams
- Adopt zero-trust access policies, limiting access to only verified users with just-in-time credentials
Third-party risk management
Like most cybersecurity incidents, many AI-driven cyberattacks infiltrate organizations through third-party vendors with weak security. Third-party risk management is your organization’s first step in protecting itself from third-party data breaches and other cybersecurity incidents—including those stemming from AI-powered cyberattacks.
Continuously assess the security posture of each vendor in your ecosystem to prevent malicious actors from accessing your organization. AI-powered risk assessment tools can help your organization quickly analyze third-party attack surfaces and identify any gaps that create security risks. Your organization can also require vendors to meet strict cybersecurity compliance standards, including AI-specific frameworks, before granting access to any sensitive data.
Consider the following steps to protect your organization using third-party risk management:
- Use a third-party risk management platform to automate vendor security assessments.
- Conduct regular risk assessments of high-risk vendors, particularly those with access to sensitive systems that pose a data security risk.
- Require vendors to implement MFA and secure access controls to prevent unauthorized entry.
- Establish a vendor breach response plan to mitigate the impact if a third party is compromised.
How UpGuard Breach Risk Helps Businesses Stay Ahead of AI Cybercrime
AI is revolutionizing cybercrime—making attacks faster, smarter, and harder to detect. We have already seen real-world examples of these attacks, illustrating how businesses suffer from underestimating AI threats. Companies must adopt updated cybersecurity strategies to protect their businesses and customers from AI-powered attacks.
UpGuard Breach Risk is our solution for proactively managing cybersecurity risks, integrating critical features in a user-friendly platform that enhances your organization’s security posture.
Breach Risk helps you understand the risks impacting your external security posture and ensures your assets are constantly monitored and protected. View your organization’s cybersecurity at a glance and communicate internally about risks, vulnerabilities, or current security incidents.
Learn more about Breach Risk and get started today at https://www.upguard.com/contact-sales.
