Which two tools block inappropriate user-uploaded images?
You have an Azure subscription. You are building a social media app that will enable users to share images. You need to ensure that inappropriate content uploaded by the users is blocked. The solution must minimize development effort. What are two tools that you can use? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
Community Votes
83% of anonymous learners picked answer CD. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
The question tests which Azure services offer out-of-the-box image content moderation while minimizing development effort — the trap is choosing Custom Vision, which requires training your own model.
Azure AI Content Safety and Azure AI Vision both provide built-in image moderation, so either service blocks inappropriate user uploads without any custom model work. This page confirms C and D are the two valid answers on the AI-102 exam.
Many learners pick Azure AI Custom Vision (E) simply because it 'analyzes images', but it demands labelled training data and custom model building, which directly violates the minimize-development-effort requirement.
Community Discussion (8 comments)
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Expert Analysis
Why the Answer Is Correct
Azure AI Content Safety (C) is Microsoft's purpose-built moderation service: its image analysis APIs return severity scores for sexual, violence, hate and self-harm categories and can block harmful uploads through a simple REST call or SDK method. Azure AI Vision (D) exposes the same capability inside its Analyze Image feature, returning adult and racy flags plus gory content scores that a social media app can act on immediately. The question states that "Each correct answer presents a complete solution," so both tools independently satisfy the requirement rather than being combined. Neither requires training data, labelled datasets, or custom model deployment, which is exactly why they meet the "minimize development effort" constraint. Both are first-party Foundry Services/Foundry Tools offerings callable from the same subscription in the scenario.
Why the Other Options Are Wrong
Azure AI Document Intelligence (A) extracts text, key-value pairs and tables from forms and documents; it has no image moderation capability and would never inspect a user's photo for inappropriate content. Microsoft Defender for Cloud Apps (B) is a Cloud Access Security Broker used for shadow-IT discovery, session control and SaaS governance — it governs app usage, not the semantic content of uploaded images. Azure AI Custom Vision (E) can classify images, but you must upload and label your own training images and train a model, which adds weeks of development and maintenance effort and is the opposite of "minimize development effort." Custom Vision also lacks a prebuilt adult/racy classifier, so it cannot block inappropriate content without a bespoke dataset.
Community Comment Notes
Consensus in the thread is strongly behind C and D, with one learner stating the answers outright and another confirming them via a second source. The most useful reasoning comes from a voter who ties the requirement directly to the solution choice: "That means you should lean away from anything custom." Another commenter explains that Content Safety is "specifically designed to detect and filter out harmful or inappropriate content" across media types including images, which is why it counts as a complete solution on its own. Two learners linked Microsoft's adult-content detection documentation for Computer Vision, which is the Azure AI Vision (D) capability — reinforcing that D, not the Document Intelligence option, is the second tool. Note that one post labelled its pick as "A, D" while quoting that same Vision URL, which reads as a typo for D rather than a genuine vote for Document Intelligence.
Official Reference
Exam Strategy
When a question says "minimize development effort" or "each correct answer presents a complete solution," immediately discard any option that requires training a custom model. Then match the data type — images here — to services with prebuilt moderation or adult-content detection rather than general-purpose document or security tooling.
Frequently Asked Questions
Why is Azure AI Custom Vision wrong if it can classify images of user uploads?
Custom Vision requires you to label training images and train a model, which adds development effort. The question demands minimal development effort, and Custom Vision has no prebuilt adult-content classifier.
Can Azure AI Content Safety alone satisfy the requirement?
Yes. Content Safety analyzes images and returns harm category severity scores you can use to block uploads, making it a complete solution — as is Azure AI Vision's adult/racy detection.