PyRIT: A Framework for Security Risk Identification and Red Teaming in Generative AI System
Generative Artificial Intelligence (GenAI) is becoming ubiquitous in our daily lives. The increase in computational power and data availability has led to a proliferation of both single- and multi-modal models. As the GenAI ecosystem matures, the need for extensible and model-agnostic risk identification frameworks is growing. To meet this need, we introduce the Python Risk Identification Toolkit (PyRIT), an open-source framework designed to enhance red teaming efforts in GenAI systems. PyRIT is a model- and platform-agnostic tool that enables red teamers to probe for and identify novel harms, risks, and jailbreaks in multimodal generative AI models. Its composable architecture facilitates the reuse of core building blocks and allows for extensibility to future models and modalities. This paper details the challenges specific to red teaming generative AI systems, the development and features of PyRIT, and its practical applications in real-world scenarios.
Code (1)
Tasks
Red TeamingSimilar Papers 제목 키워드 기반
Insights and Current Gaps in Open-Source LLM Vulnerability Scanners: A Comparative Analysis
This report presents a comparative analysis of open-source vulnerability scanners for conversational large language models (LLMs). As LLMs become integral to various applications, they also present potential attack surfa…
Red TeamingAJAR: Adaptive Jailbreak Architecture for Red-teaming
Large language model (LLM) safety evaluation is moving from content moderation to action security as modern systems gain persistent state, tool access, and autonomous control loops. Existing jailbreak frameworks still le…
The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward
Artificial intelligence (AI) promises immense benefits across sectors, yet also poses risks from dual-use potentials, biases, and unintended behaviors. This paper reviews emerging issues with opaque and uncontrollable AI…
EthicsPhilosophyRed TeamingSecuring Multi-Agent GIS Systems: Risk Evaluation and Prompt Hardening Optimization
Agentic systems are increasingly integrated with geographic information systems (GIS), where multi-agent coordination enables complex conversational and spatial analysis but introduces security risks. This work presents …
AI Potentiality and Awareness: A Position Paper from the Perspective of Human-AI Teaming in Cybersecurity
This position paper explores the broad landscape of AI potentiality in the context of cybersecurity, with a particular emphasis on its possible risk factors with awareness, which can be managed by incorporating human exp…
Position