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OWASP LLM Top 10 for working professionals
In this lesson
OWASP LLM Top 10 for working professionals
Classify each of the ten OWASP LLM 2025 risks (prompt injection, sensitive information disclosure, supply chain vulnerabilities, data and model poisoning, improper output handling, and excessive agency[^1][^2])…
You'll be able to
- Classify each of the ten OWASP LLM 2025 risks (prompt injection, sensitive information disclosure, supply chain vulnerabilities, data and model poisoning, improper output handling, and excessive agency[^1][^2]) according to their threat vectors and potential impact on production generative AI systems.
- Evaluate real-world LLM application architectures against the OWASP Top 10 for LLM Applications 2025 framework[^1], identifying which risks apply to specific deployment scenarios and justifying prioritization decisions based on organizational context.
- Apply OWASP-defined mitigations for prompt injection vulnerabilities[^2], sensitive information disclosure[^2], and supply chain risks[^2] to representative NVIDIA-aligned generative AI workflows, demonstrating how to implement controls at development, deployment, and management lifecycle stages[^1].
- Create a risk assessment matrix that maps OWASP LLM Top 10 categories to your organization's AI application inventory, documenting which vulnerabilities (such as data poisoning through manipulated training data[^2] or excessive agency in function-calling systems[^2]) require immediate remediation versus ongoing monitoring.