The COMPEL Glossary Graph visualizes relationships between framework terminology, showing how concepts interconnect across domains, stages, and pillars. Term nodes cluster by pillar affiliation while cross-references reveal semantic dependencies — for example, how risk appetite connects to control effectiveness, model governance, and assurance requirements. This network representation helps practitioners navigate the framework vocabulary and understand that COMPEL terminology forms a coherent conceptual system rather than isolated definitions.
COMPEL Glossary / ai-incident-for-llms
AI incident (for LLMs)
A subtype of the NIST AI RMF MANAGE 1.4 incident concept specific to LLM systems: confident-but-wrong answer, safety bypass, prompt injection success, sensitive data leakage, or policy-violating tool-call execution.
What this means in practice
Classification drives response severity and regulator-notification thresholds.
Synonyms
LLM incident , generative AI incident
See also
- Model and prompt registry — A versioned inventory of models, system prompts, retrieval sources, and guardrails deployed in production.
- Serious incident (Art. 3(49)) — Under Regulation (EU) 2024/1689, an incident or malfunction of an AI system that directly or indirectly leads to the death of a person or serious harm to a person's health, to a serious and irreversible disruption of critical infrastructure, to infringement of fundamental-rights obligations, or to serious harm to property or the environment..
- Post-market monitoring (Art. 72) — Under Regulation (EU) 2024/1689, the ongoing, documented collection, analysis, and corrective-action process that providers of high-risk AI systems must operate after the system is placed on the market.