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Giskard

Open-source testing framework for scanning LLMs and machine learning models for hallucinations, prompt injections, and biases.

Technical Architecture & Overview

Giskard is an open-source Python library for automated red teaming, vulnerability scanning, and behavioral testing of LLM agents and RAG pipelines. It identifies prompt injection vulnerabilities, hallucination issues, and harmful output risks through automated test generation.

Targeted Technical Use Cases

Automated vulnerability scanning and behavioral testing of LLM agents and RAG pipelines before deployment.

Evaluation & Trade-offs

Core Strengths

  • +Automated test generation for prompt injection, hallucination, and harmful output detection.
  • +Specialized for testing RAG pipelines and agentic LLM workflows.
  • +Used in the DeepLearning.AI red-teaming LLM applications course.

Trade-Offs & Limitations

  • -Requires Python scripting to integrate with custom LLM application code.
  • -Test coverage depends on the quality of provided application interfaces.

Defensive Security Application

Pre-deployment vulnerability assessment of LLM agents and RAG systems against prompt injection and hallucination risks.

Frequently Asked Questions

What is Giskard?

Giskard is an open-source Python library for automated red teaming, vulnerability scanning, and behavioral testing of LLM agents and RAG pipelines. It identifies prompt injection vulnerabilities, hallucination issues, and harmful output risks through automated test generation.

What is Giskard used for?

Automated vulnerability scanning and behavioral testing of LLM agents and RAG pipelines before deployment.

What are the strengths of Giskard?
  • +Automated test generation for prompt injection, hallucination, and harmful output detection.
  • +Specialized for testing RAG pipelines and agentic LLM workflows.
  • +Used in the DeepLearning.AI red-teaming LLM applications course.
What are the limitations of Giskard?
  • +Requires Python scripting to integrate with custom LLM application code.
  • +Test coverage depends on the quality of provided application interfaces.
How is Giskard used defensively?

Pre-deployment vulnerability assessment of LLM agents and RAG systems against prompt injection and hallucination risks.