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Technical mechanisms and engineering interventions that directly modify how an AI system processes inputs, generates outputs, or operates, including changes to models, training procedures, runtime behaviors, and supporting hardware.
Reasoning
Term "Defenses" too vague to identify focal activity or determine L1 category without description.
Defenses > Inference Time Defense
1.2 Non-ModelDefenses > Training Time Defense
1.1 ModelInference Time Defense > Preprocess
The input is preprocessed to detect or guard against harmful content before the generation process.
1.2.1 Guardrails & FilteringInference Time Defense > Intraprocess
Utilizes safer decoding or generation strategies to ensure the outputs are secure and adhere to safety guidelines
1.2 Non-ModelInference Time Defense > Postprocess
The output is postprocessed to enhance safety.
1.2.1 Guardrails & FilteringPreprocess > PPL
(Alon and Kamfonas, 2023)
1.2.3 Monitoring & DetectionAISafetyLab: A Comprehensive Framework for AI Safety Evaluation and Improvement
Zhang, Zhexin; Lei, Leqi; Yang, Junxiao; Huang, Xijie; Lu, Yida; Cui, Shiyao; Chen, Renmiao; Zhang, Qinglin; Wang, Xinyuan; Wang, Hao; Li, Hao; Lei, Xianqi; Pan, Chengwei; Sha, Lei; Wang, Hongning; Huang, Minlie (2025)
As AI models are increasingly deployed across diverse real-world scenarios, ensuring their safety remains a critical yet underexplored challenge. While substantial efforts have been made to evaluate and enhance AI safety, the lack of a standardized framework and comprehensive toolkit poses significant obstacles to systematic research and practical adoption. To bridge this gap, we introduce AISafetyLab, a unified framework and toolkit that integrates representative attack, defense, and evaluation methodologies for AI safety. AISafetyLab features an intuitive interface that enables developers to seamlessly apply various techniques while maintaining a well-structured and extensible codebase for future advancements. Additionally, we conduct empirical studies on Vicuna, analyzing different attack and defense strategies to provide valuable insights into their comparative effectiveness. To facilitate ongoing research and development in AI safety, AISafetyLab is publicly available at https://github.com/thu-coai/AISafetyLab, and we are committed to its continuous maintenance and improvement.
Other (general)
General mitigation not specific to a single lifecycle stage
Other
Actor type not captured by the standard categories
Other
Risk management function not captured by the standard AIRM categories
Other
