AI security resource center
Is shadow AI putting your organization at risk? Are your current defenses AI-ready? Get answers, expert strategies, and actionable insights to secure your cloud environment. Let's dive in.
According to the Wiz Research team, managed AI services like Amazon SageMaker, Azure AI, and GCP Vertex AI are present in over 70% of cloud environments, showing rapid adoption of AI advancements by organizations
Shadow AI is the unauthorized use or implementation of AI that is not controlled by, or visible to, an organization's IT department. Datasets for AI, AI models, and AI products are being released every day for anyone to use- no deep expertise required. This is especially true for generative AI Increasingly, people are adopting GenAI in the form of personal assistants, and many have come to rely on the variety of tailored experiences and optimized processes offered by AI.
AI researchers often share massive amounts of external and internal data to construct their AI models, which poses significant security risks. Security teams must establish clear guidelines for sharing AI datasets externally. The Wiz research team discovered 38TB of data was accidentally exposed by Microsoft AI researchers. Using a dedicated storage account for public AI datasets could've limited exposure.
AI is heavily based on open-source datasets, models, and pipeline tools with limited security controls. Vulnerabilities exploited in the supply chain can not only compromise the AI system but also extend to other production components. Attacks may involve model subversion or injecting adversarial data into compromised datasets.
The types of AI risk that apply to your organization depend on the AI that you employ and deploy. Understanding the security controls to set up around AI requires you to first have a good overview of the security risks that come with GenAI.
AI Security Posture Management provides visibility into AI pipelines and their security posture so organizations can effectively remove AI risks. It embeds security within your AI models, training data, and AI services, ensuring accelerated—but safe—adoption of AI technologies. AI-SPM solutions should enable you to protect your AI models.
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