A growing concern in the cybersecurity world is the emergence of "Shadow AI," which refers to artificial intelligence and machine learning models that are operating outside of an organization's visibility and control. These models can pose a significant security risk, as they can be used to launch attacks, steal sensitive data, or disrupt critical systems.
Shadow AI can take many forms, including unauthorized AI models, unsanctioned AI projects, and even AI-powered malware. These models can be created and deployed by insiders, such as employees or contractors, or by external attackers.
The risks associated with Shadow AI are substantial. For example, an unauthorized AI model could be used to launch a phishing attack, or to steal sensitive data from an organization's systems. Additionally, Shadow AI can be used to disrupt critical systems, such as power grids or financial networks.
To mitigate the risks associated with Shadow AI, organizations need to implement robust security controls, including AI-specific security tools and policies. This includes monitoring for unauthorized AI activity, implementing access controls, and providing training and awareness programs for employees.
