Enterprises are rapidly embracing Artificial Intelligence (AI) and Machine Learning (ML) tools, with transactions skyrocketing by almost 600% in less than a year, according to a recent report by Zscaler. The surge, from 521 million transactions in April 2023 to 3.1 billion monthly by January 2024, underscores a growing reliance on these technologies. However, heightened security concerns have led to a 577% increase in blocked AI/ML transactions, as organisations grapple with emerging cyber threats.
The report highlights the developing tactics of cyber attackers, who now exploit AI tools like Language Model-based Machine Learning (LLMs) to infiltrate organisations covertly. Adversarial AI, a form of AI designed to bypass traditional security measures, poses a particularly stealthy threat.
Concerns about data protection and privacy loom large as enterprises integrate AI/ML tools into their operations. Industries such as healthcare, finance, insurance, services, technology, and manufacturing are at risk, with manufacturing leading in AI traffic generation.
To mitigate risks, many Chief Information Security Officers (CISOs) opt to block a record number of AI/ML transactions, although this approach is seen as a short-term solution. The most commonly blocked AI tools include ChatGPT and OpenAI, while domains like Bing.com and Drift.com are among the most frequently blocked.
However, blocking transactions alone may not suffice in the face of evolving cyber threats. Leading cybersecurity vendors are exploring novel approaches to threat detection, leveraging telemetry data and AI capabilities to identify and respond to potential risks more effectively.
CISOs and security teams face a daunting task in defending against AI-driven attacks, necessitating a comprehensive cybersecurity strategy. Balancing productivity and security is crucial, as evidenced by recent incidents like vishing and smishing attacks targeting high-profile executives.
Attackers increasingly leverage AI in ransomware attacks, automating various stages of the attack chain for faster and more targeted strikes. Generative AI, in particular, enables attackers to identify vulnerabilities and exploit them with greater efficiency, posing significant challenges to enterprise security.
Taking into account these advancements, enterprises must prioritise risk management and enhance their cybersecurity posture to combat the dynamic AI threat landscape. Educating board members and implementing robust security measures are essential in safeguarding against AI-driven cyberattacks.
As institutions deal with the complexities of AI adoption, ensuring data privacy, protecting intellectual property, and mitigating the risks associated with AI tools become paramount. By staying vigilant and adopting proactive security measures, enterprises can better defend against the growing threat posed by these cyberattacks.
