Resources
AI Safety Knowledge Base
Free downloadable guides, frameworks, and research to help you understand and implement AI safety testing.
BlackIndian AI
The Observability Edge
AI Observability for Healthcare, Insurance & Enterprise
The Observability Edge
Your complete guide to monitoring, measuring, and understanding AI systems in production. Written for healthcare, insurance, and enterprise teams who need to detect model drift, catch hallucinations, and build audit-ready observability frameworks.
Covers real-time monitoring, drift detection, compliance dashboards, and the observability stack used by enterprise AI teams.
Guides
Complete Guide to Prompt Injection Testing
Master the fundamentals of prompt injection vulnerabilities. Learn testing techniques, attack vectors, and mitigation strategies to protect AI systems from malicious input manipulation.
Download PDFLLM Jailbreak Testing Methodology
Step-by-step methodology for testing AI systems against jailbreak attempts. Covers filter evasion, role-playing exploits, and systematic approaches to uncover safety bypasses.
Download PDFAI Safety Testing Career Roadmap
Your path from QA engineer to AI safety specialist. Covers essential skills, certifications, industry demand, and salary expectations ($150K-$300K) in this emerging field.
Download PDFFrameworks
7-Category Vulnerability Framework
Our comprehensive framework for categorizing AI vulnerabilities: Prompt Injection, Data Leakage, Hallucination, Bias, Jailbreaks, Privacy Violations, and Compliance Gaps.
Download PDFCompliance Testing Checklist
Pre-launch compliance checklist covering GDPR, HIPAA, EU AI Act, SOC 2, and industry-specific requirements. Ensure your AI deployment meets regulatory standards.
Download PDFResearch
State of AI Safety Testing 2024
Annual report on AI vulnerability trends, real-world incident analysis, emerging attack vectors, and testing best practices. Data-driven insights for enterprise AI deployments.
Download PDF