azure-ai-contentsafety-java
Build content moderation apps with Azure AI
Moderate harmful content automatically in your applications. Azure AI Content Safety SDK for Java detects hate speech, violence, sexual content, and self-harm with configurable severity thresholds.
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Test it
Using "azure-ai-contentsafety-java". Analyze user comment for hate speech and violence
Expected outcome:
Hate: Severity 2 (low confidence), Violence: Severity 0 (not detected). Content passes moderation threshold.
Using "azure-ai-contentsafety-java". Check image for adult content
Expected outcome:
Sexual category detected at Severity 6. Recommendation: Block content per policy threshold of 4.
Using "azure-ai-contentsafety-java". Validate message against custom blocklist
Expected outcome:
Blocklist hit detected: Item ID abc123 matched term variant. Content blocked per haltOnBlocklistHit setting.
Security Audit
SafeStatic analyzer produced false positives due to misinterpreting Markdown documentation. All 33 external_commands findings are Java code examples in Markdown fences, not shell execution. Network findings are example URLs for configuration. Environment variable access is standard Azure SDK pattern. No actual security issues detected.
Risk Factors
🔑 Env variables (1)
🌐 Network access (2)
Quality Score
What You Can Build
Social Platform Moderation
Automatically screen user-generated posts and comments for harmful content before publication. Configure severity thresholds to match community guidelines.
Customer Support Filtering
Detect abusive messages in support tickets and chat systems. Route flagged content to human reviewers while allowing legitimate messages through.
Marketplace Content Review
Scan product listings, reviews, and images for policy violations. Maintain custom blocklists for brand-specific prohibited terms.
Try These Prompts
Analyze this text for harmful content using Azure AI Content Safety: [paste text]. Return severity scores for each category.
Analyze [text] for hate and violence categories only. Use 8 severity levels output. Stop if blocklist hit occurs.
Check the image at [URL] for harmful content. Report categories with severity >= 4. Format results as a moderation decision.
Create a blocklist named [name] with description [desc]. Add these terms: [terms]. Then analyze [text] against this blocklist with halt on hit enabled.
Best Practices
- Read Azure SDK documentation for authentication and client configuration before implementation
- Set severity thresholds based on your risk tolerance - severity 4+ is typical for strict moderation
- Allow 5 minutes for blocklist changes to propagate before testing new entries
- Cache analysis results for repeated content to reduce API calls and latency
Avoid
- Hardcoding credentials instead of using environment variables or DefaultAzureCredential
- Requesting all harm categories when only specific ones are needed - increases latency and cost
- Blocking severity 0 content - this creates false positives for borderline cases
- Synchronous API calls in high-throughput scenarios - use async patterns for batch processing
Frequently Asked Questions
What Azure subscription do I need for Content Safety?
How do I authenticate the SDK?
Can I customize harm detection thresholds?
How quickly do blocklist updates take effect?
Does the SDK support async operations?
What image formats are supported?
Developer Details
Author
sickn33License
MIT
Repository
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/azure-ai-contentsafety-javaRef
main
File structure
📄 SKILL.md