Weaponized AI Attacks to Challenge Enterprise Cybersecurity by 2025: Are Organizations Ready?

By 2025, weaponized AI attacks targeting identities will pose a significant threat to enterprise cybersecurity. These attacks often go unnoticed and can be very costly to recover from.

Rogue attackers, cybercrime groups, and nation-state teams are increasingly using large language models (LLMs) as their tools of choice.

A recent survey revealed that 84% of IT and security leaders say AI-powered tactics make phishing and smishing attacks harder to identify and stop. As a result, 51% of security leaders now view AI-driven attacks as the most serious threat to their organizations.

Interestingly, while 77% of security leaders feel confident about their knowledge of AI security best practices, only 35% believe their organizations are ready to tackle the rise in weaponized AI attacks expected in 2025.

In the coming year, Chief Information Security Officers (CISOs) and their teams will face greater challenges. Adversarial AI-based attacks are already outpacing advanced security measures. 2025 is expected to be the year when AI becomes essential for real-time threat monitoring, reducing alert fatigue for security analysts, automating patch management, and improving the accuracy of deepfake detection.

Speaking of deepfakes, they currently lead all forms of adversarial AI attacks. In 2023, deepfakes cost global businesses $12.3 billion. This figure could soar to $40 billion by 2027, reflecting a 32% annual growth rate. Attackers are relentless in refining their techniques, using the latest AI tools for video and audio manipulation. Deepfake incidents are expected to rise by 50% to 60% in 2024, potentially reaching between 140,000 and 150,000 cases worldwide.

According to Deloitte, deepfake attackers primarily target the banking and financial services sectors. These industries are seen as soft targets for synthetic identity fraud, which is tough to detect. Last year, deepfakes were involved in nearly 20% of synthetic identity fraud cases. This type of fraud is among the hardest to identify and stop, and it's on track to defraud financial systems by nearly $5 billion this year alone.

As the threat of synthetic identity fraud grows, businesses are focusing on the onboarding process to verify customer identities and prevent fraud. Telesign CEO Christophe Van de Weyer recently stated, “Companies must protect their customers' identities, credentials, and personally identifiable information (PII), especially during registration.” The 2024 Telesign Trust Index highlights how generative AI has fueled phishing attacks, showing a 1265% increase in malicious phishing messages and a 967% rise in credential phishing within a year of ChatGPT’s launch.

Elia Zaitsev, CTO at CrowdStrike, pointed out that adversaries are getting faster. They are leveraging AI technology and automation, making modern attacks quicker and more sophisticated.

Generative AI has become a powerful tool for adversarial AI. Just weeks after OpenAI launched ChatGPT in November 2022, rogue attackers and cybercriminals began offering generative AI-based subscription attack services. One of the most notable is FraudGPT, which claimed to have 3,000 subscribers at one point.

Alarmingly, one in three organizations admits they lack a documented strategy to tackle generative AI and adversarial AI risks. CISOs and IT leaders are aware they are unprepared for AI-driven identity attacks. Ivanti’s recent 2024 State of Cybersecurity Report found that 74% of businesses are already feeling the impact of AI-powered threats. Furthermore, 89% of executives believe these threats are just beginning.

Research reveals a significant gap between how ready organizations are to defend against adversarial AI attacks and the real risk of facing one. 60% of security leaders say their organizations aren't equipped to handle AI-powered threats today. The four most common threats they faced this year include phishing, software vulnerabilities, ransomware attacks, and API-related vulnerabilities.

With tools like ChatGPT making many of these threats cheaper to produce, adversarial AI attacks are poised to skyrocket in 2025.

Attackers use a mix of generative AI, social engineering, and AI-based tools to create ransomware that’s tough to detect. They breach networks and move laterally to core systems, starting with Active Directory.

Once inside, attackers can lock identity access privileges and revoke admin rights after deploying malicious ransomware code throughout the network. They use generative AI-based code, phishing emails, and bots during the attack.

So, how can organizations defend themselves against these AI-driven threats? Here are some strategies:

• Clean up access privileges: Immediately revoke access for former employees, contractors, and temporary admin accounts. This reduces trust gaps that attackers exploit. Implement Multi-Factor Authentication (MFA) for all valid accounts to lower the risk of credential-based attacks.
• Enforce zero trust: Treat every endpoint as if it has already been breached. Segment your network to contain potential intrusions. This approach is essential as AI-driven attacks increase.
• Control machine identities: Machine identities, like bots and IoT devices, are growing faster than human identities. Implement AI-driven governance for these identities to prevent breaches.
• Strengthen IAM systems: If your company has an Identity and Access Management (IAM) system, enhance it across multicloud configurations. Many organizations rely on a single IAM for each platform, creating vulnerabilities.
• Real-time monitoring: Invest in AI-enhanced monitoring to detect anomalies and breaches in real-time. This helps you adjust policies immediately and supports zero trust principles.
• Make red teaming routine: Don’t just conduct red teaming when an attack occurs. It should be a regular part of your security strategy to identify weaknesses proactively.
• Stay updated: Keep a member of your DevSecOps team informed about the latest defensive frameworks. This knowledge can enhance your security posture.
• Reduce synthetic data risks: Integrate biometric modalities and passwordless authentication into your IAM systems. This can help secure systems against synthetic identity impersonation.

By 2025, adversarial AI techniques are expected to advance faster than many organizations can keep up with. The key isn’t necessarily spending more; it’s about enhancing and strengthening existing systems. Start with a Zero Trust framework and see how the NIST framework can be tailored to your business needs.

As we approach 2025, every security and IT team should treat endpoints as if they are already compromised. Focus on minimizing vulnerabilities at the identity level, which is a common entry point for AI-driven attacks. While these threats are on the rise, no amount of spending alone will solve the problem. Practical strategies that recognize the ease with which endpoints can be breached must be at the core of any cybersecurity plan.