AI Security - Managing Unmanaged Cyber Risks Explained

What Happened

AI technology is advancing at breakneck speed, but this rapid evolution is opening up new avenues for cyber attacks. Cybersecurity teams are now faced with the challenge of managing vulnerabilities associated with AI tools that lack proper governance. The risks are significant, as AI models have transformed from isolated targets into potential attack vectors that can compromise sensitive data and workflows.

Organizations have prioritized speed in deploying AI, often overlooking the necessary security controls. This gap has led to high-risk environments characterized by over-privileged access and vulnerable software supply chains. As AI becomes integral to core business operations, the need for effective governance and exposure management has never been more critical.

Who's Being Targeted

Recent findings from Tenable Research highlight the vulnerabilities present in popular AI models like OpenAI's ChatGPT and Google's Gemini. These vulnerabilities include indirect prompt injection and privacy risks that can be exploited by attackers to extract sensitive information. The research shows that AI systems are not just targets; they can actively facilitate attacks by connecting to sensitive data and cloud services.

Moreover, as organizations increasingly rely on AI for their daily operations, the risk landscape expands. Approximately 70% of organizations now incorporate AI into their production cloud stack, with employee access to AI tools rising significantly. This rapid adoption, however, has not been matched by adequate security measures, leaving organizations exposed to potential breaches.

Tactics & Techniques

The vulnerabilities in AI tools create multiple attack paths that can be exploited by threat actors. For instance, Tenable's research uncovered critical flaws in the Google Looker Studio, which could allow attackers to expose or manipulate sensitive cloud data. This illustrates how interconnected AI systems can widen the attack surface, turning AI into a potential weapon against organizations.

Additionally, many organizations face challenges with governance, as AI tools are often operationalized faster than security teams can assess the associated risks. This creates a situation where overprivileged identities and inactive accounts can be exploited, further complicating the security landscape.

Defensive Measures

To mitigate these risks, organizations must adopt a unified exposure management strategy. This approach enables security teams to gain visibility into the complex web of interactions, identities, and permissions surrounding AI tools. By moving away from siloed security dashboards, organizations can better understand how AI systems interact with their IT environments and identify potential vulnerabilities.

Effective exposure management allows organizations to proactively address the highest-risk cyber exposures, ensuring that they can secure their sensitive data and systems against evolving threats. As AI continues to integrate into business operations, prioritizing comprehensive governance and risk management will be essential to safeguarding against cyber risks.