Cybersecurity experts predict that by 2025, weaponized AI attacks targeting identities will be the most significant threat to enterprise cybersecurity. These attacks, often unseen and costly to recover from, are expected to be carried out using large language models (LLMs) by rogue attackers, cybercrime syndicates, and nation-state attack teams.
A recent survey revealed that 84% of IT and security leaders find AI-powered tradecraft increasingly complex to identify and stop when used in phishing and smishing attacks. As a result, 51% of security leaders consider AI-driven attacks as the most severe threat facing their organizations. Despite 77% of security leaders being confident in their knowledge of AI security best practices, only 35% believe their organizations are prepared to combat weaponized AI attacks expected to rise significantly in 2025.
In the upcoming year, CISOs and security teams will face challenges in identifying and stopping adversarial AI-based attacks, which are surpassing advanced AI-based security measures. AI technologies will play a crucial role in providing real-time threat monitoring, reducing alert fatigue for SOC analysts, automating patch management, and identifying deepfakes with enhanced accuracy and speed.
The surge in adversarial AI attacks, particularly deepfakes, is a growing concern for businesses. Deepfakes cost global businesses $12.3 billion in 2023 and are projected to reach $40 billion by 2027, with attackers continuously improving their techniques using AI applications and video editing tools. Deepfake incidents are expected to increase by 50 to 60% in 2024, with attackers targeting industries like banking and financial services.
To defend against AI-driven threats, organizations must prioritize cleaning up access privileges, enforcing zero trust on endpoints, controlling machine identities, strengthening IAM systems across multicloud configurations, implementing real-time infrastructure monitoring, incorporating red teaming and risk assessment, and adopting defensive frameworks tailored to their needs. Additionally, integrating biometric modalities and passwordless authentication techniques into identity access management systems can help reduce the risk of synthetic data-based attacks.
As adversarial AI techniques advance rapidly, organizations must acknowledge the potential for breaches and enhance existing security measures to withstand the increasing threat landscape. By incorporating AI technologies to improve monitoring, endpoint security, and patch management, businesses can strengthen their cybersecurity posture in preparation for the challenges posed by weaponized AI attacks in 2025.
