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AgentDojo

AgentDojo is a dynamic environment designed to evaluate prompt injection attacks and defenses for LLM agents. Developed by researchers from ETH Zurich and Invariant Labs, it provides tools for benchmarking and creating new attack and defense models, aiding in the study of AI vulnerabilities.

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AgentDojo is a sophisticated platform developed to assess prompt injection attacks and defenses specifically for large language model (LLM) agents. Created by a team of researchers from ETH Zurich and Invariant Labs, AgentDojo serves as a critical tool for understanding and mitigating vulnerabilities in AI systems. The platform has gained recognition for its contributions to AI safety, having won a SafeBench first prize alongside Cybench and BackdoorLLM.

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The primary function of AgentDojo is to provide a controlled environment where users can run benchmarks to test the resilience of AI models against prompt injection attacks. Users can install the package and execute benchmarks using scripts, with detailed documentation available to guide them through the process. This makes it an invaluable resource for researchers and developers looking to enhance the security of AI systems.

AgentDojo also allows users to create new defense mechanisms and models, offering comprehensive documentation on how to develop custom pipelines. This flexibility ensures that users can tailor their defenses to specific needs, making the platform adaptable to various research and development scenarios.

The platform's impact is further highlighted by its use in demonstrating the vulnerabilities of AI models like Claude 3.5 Sonnet to prompt injections. This capability underscores the importance of AgentDojo in the ongoing efforts to secure AI technologies. However, users should note that the API is still under development, which may lead to changes in the future.

Overall, AgentDojo is targeted at AI researchers, developers, and security experts who are focused on improving the robustness of AI systems against malicious attacks. Its comprehensive features and adaptability make it a vital tool in the field of AI security research.

  • CategoryAI Cybersecurity Tools
  • Pricing ModelFree
  • DeploymentCloud
  • PlatformsWeb

  • Evaluate prompt injection attacks

  • Develop new defense models

  • Run benchmarks with scripts

  • Comprehensive documentation

  • Create custom pipelines

  • Demonstrate AI vulnerabilities

  • API under development

  • SafeBench prize winner

  1. Install: download and set up the package

  2. Run benchmark: execute scripts to test models

  3. Develop: create new defense models

  4. Document: refer to detailed guides for setup

  • AI security research
  • Defense model development
  • Benchmarking AI systems
  • Custom pipeline creation
  • AI vulnerability demonstration

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