AI Safety InfrastructureWhitzard 白泽
Building generalized safety infrastructure for frontier AI and agentic systems.
Whitzard develops intelligent safety modules that can be deployed across real-world vertical scenarios: agent runtime protection, risk evaluation, security monitoring, and governance evidence. Our goal is to make advanced AI safety more practical, accessible, and useful for public safety.
A Practical Path to Safe AI
Many frontier AI safety approaches rely heavily on centralized post-training and alignment pipelines. Whitzard focuses on another complementary path: generalized safety modules that can be integrated into real systems, adapted to vertical scenarios, and continuously improved through evaluation, monitoring, and runtime protection.
Generalized Safety Modules
Reusable safety capabilities across models, agents, tools, and deployment environments.
Intelligent Runtime Protection
Policy, tracing, approval, monitoring, and intervention for agentic systems in action.
Vertical Scenario Adaptation
Safety infrastructure designed for real-world sectors, workflows, and operational constraints.
Public Safety Orientation
Practical AI safety products that can support broader access, governance, and social trust.
Latest News
View all →The Science of Frontier AI Risk Evaluation
Nuwa's first public research essay on making frontier AI risk evaluation more scientific, evidence-based, and operational.
Source: Nuwa Substack
Nuwa Frontier AI Safety Lab Launch
Nuwa Frontier AI Safety Lab is launched as the research lab supported by Whitzard.
WhitzardAgent Open Ecosystem
WhitzardAgent hosts open-source tools and datasets for AI safety evaluation, agent safety, and runtime protection.
Nuwa Frontier AI Safety Lab 女娲
Transparent, third-party, open infrastructure for frontier AI safety evaluation and governance.
Supported by Whitzard, Nuwa develops open evaluation frameworks, benchmarks, technical notes, and governance evidence for safe and controllable AI.
Latest Research
Recent publications from Nuwa Frontier AI Safety Lab.
arXiv preprint · 2024
Frontier AI systems have surpassed the self-replicating red line
Xudong Pan, Jiarun Dai, Yihe Fan, Min Yang
Evaluates whether frontier AI systems can autonomously self-replicate and reports successful self-replication in controlled trials.
arXiv preprint; work in progress · 2025
Large language model-powered AI systems achieve self-replication with no human intervention
Xudong Pan, Jiarun Dai, Yihe Fan, Minyuan Luo, Changyi Li, Min Yang
Extends self-replication evaluation across 32 AI systems and reports autonomous replication, self-exfiltration, adaptation, and shutdown-survival behaviors.
Nüwa Project preprint · 2026
One Step from Silicon Life: Autonomous AI Agents Capable of Uncontrolled Self-Proliferation
Geng Hong, Xudong Pan, Jiarun Dai, Jiaqi Luo, Wuyuao Mai, Min Yang
Demonstrates autonomous agents acquiring external computational resources and propagating across remote devices under controlled, simulated real-world conditions.
Open Ecosystem
Explore WhitzardAgent open tools, datasets, and infrastructure for AI safety evaluation and agent safety.
Learn about the team behind Whitzard and Nuwa.
We collaborate on frontier AI safety evaluation, agent safety, and runtime defense.