Google Cloud has announced AI Protection, a complete solution to protect chance to, and threats within, the use of relational AI.
Google Cloud’s AI Protection is designed to” to support groups fully manage AI risk”. It has three main capabilities: learn AI inventory, safe AI assets, and control threats with detect, investigate, and answer capabilities.
AI Protection integrates with Google’s Security Command Center (SCC ) to provide groups with a consolidated view of their IT tone and manage AI threats in the context of other sky challenges.
Discovering AI products. The aged CISO adage of ‘ you may secure what you cannot notice’ is writ large in the AI period. But, writes Archana Ramamoorthy Senior Director, product management at Google Cloud Security in a on AI Protection,” Our capabilities help you quickly learn and catalog AI assets, including the use of models, applications, and data — and their relationships”.
Coupled with this, Google Cloud’s Sensitive Data Protection then extends its automatic identification to Vertex AI data. Vertex is Google Cloud’s gen-AI development program that includes more than 150 basis types including Gemini 1.5 Pro and Gemini 1.5 Flash.
When you know what you have and where it is, the integration with SCC comes in – online red teaming can be invoked to recognize’ dangerous combinations’ and possible attack paths, and to provide remediation recommendations.
Securing AI goods. AI Protection’s Model Armor is a key component in securing the LLMs and their use. It detects and prevents rapid treatment and hack attempts. It inspects inspires and sanitizes them before passing to the LLM. It inspects messages and sanitizes them before passing to the customer. It uses RBAC to control access and permissions, it filters for indecent or taunting information and malignant URLs, and it provides data loss prevention through Google Cloud’s Sensitive Data Protection preventing the leakage of both IP and PII.
Managing AI threats. AI Protection calls upon the combined intelligence and research available from both Google and Mandiant. ” Detectors in Security Command Center can be used to uncover initial access attempts, privilege escalation, and persistence attempts for AI workloads”, writes Ramamoorthy.
Overall, AI protection offers a suite of capabilities to defend against the new risks directly associated with the growing use of AI models. But in many senses, it is more than just a new product – it’s an expansion of the Google Cloud AI security platform, and its integration with other Google Cloud offerings provides a wider solution to AI security issues. Integration with SCC ensures that AI security can be viewed in the context of all network threats, and doesn’t become a separate siloed requirement.
Integration with Sensitive Data protection can help with regulatory compliance. This can be enhanced by Google Cloud’s Assured Workloads which can control the geographic region in which data at rest is located — essential for heavily regulated industries and European regulations. Integration with protects data at rest and in transit, and” can help ensure data remains protected throughout the entire processing pipeline, reducing the risk of unauthorized access, even by privileged users or malicious actors within the system”, writes Ramamoorthy.
So, while AI Protection is a major new AI security product, it is best viewed as a key component in an umbrella AI protection. This is important. A Darktrace survey ( ) of 1, 500 security professionals working with AI, released on March 4, 2025, notes, “CISOs have expressed a preference for broader platforms over point products (89 % )”
AI Protection on Google Cloud provides a broad AI security platform. ” Piecemeal solutions can leave and have left critical vulnerabilities exposed, rendering organizations susceptible to threats like adversarial attacks or data poisoning, and added to the overwhelm experienced by security teams”, adds Grace Trinidad, research director, IDC. ” Google Cloud simplifies and thus improves the experience of securing AI for customers”.
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