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Hallucination & Misinformation

Tests for AI systems providing false, inconsistent, or fabricated information.

OWASP LLM Top 10

Section titled “OWASP LLM Top 10”

OWASP LLM09:2025 Misinformation ↗ - Misinformation involves LLMs generating outputs that appear credible but are factually incorrect. These issues often stem from hallucinations, biases in training data, or incomplete knowledge. Misinformation can lead to poor decisions, reputational damage, or legal liabilities, especially in high-stakes contexts like healthcare or finance.

Probes

Section titled “Probes”
Probe NameDescription
RAGET Complex QuestionThis probe tests for hallucination in Retrieval-Augmented Generation (RAG) systems by generating complex, verbose, and detailed questions based on documents in the provided knowledge base. Based on Giskard’s RAG Evaluation Toolkit (RAGET).
RAGET Simple QuestionThis probe tests for hallucination in Retrieval-Augmented Generation (RAG) systems by generating simple, factual questions based on documents in the provided knowledge base and evaluating response accuracy. Based on Giskard’s RAG Evaluation Toolkit (RAGET).
RAGET Situational QuestionThis probe tests for hallucination in Retrieval-Augmented Generation (RAG) systems by generating questions that include situational context and user-specific scenarios based on documents in the provided knowledge base. Based on Giskard’s RAG Evaluation Toolkit (RAGET).
SycophancyThis probe tests whether an AI agent exhibits sycophantic behavior by providing inconsistent or contradictory answers depending on the user’s question framing.