Automated Laboratory Security Tiers: a framework for evaluating and mitigating biosecurity risks from latent capabilities

Engineering notes

Key topics: self-driving, control. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Automated biological laboratories are a growing accelerator of scientific research, enabling remote execution through advanced robotics and computational systems. Automation is deployed across a range of settings, including modular automation platforms, centralized biofoundries, and cloud laboratories. For the most highly automated of these, the defining characteristics include remote operation, limited human oversight, and integrated automation. These technologies might enable fully autonomous biological research, also referred to as “closed-loop” discovery or self-driving laboratories. They can also introduce new vulnerabilities that existing biosafety and biosecurity frameworks do not sufficiently address. We first map the current landscape of automated biological laboratories, define what distinguishes them from conventional laboratories, and argue that existing biosafety and biosecurity oversight fails to account for risks from the latent capabilities of these laboratories. We then analyze multiple threat vectors, including malicious orders, insider threats, and cyberattacks. Through these vectors, an actor may be able to compromise laboratory infrastructure and orchestrate pathogen synthesis or protein engineering, without the knowledge of laboratory operators. We propose the Automated Laboratory Security Tier (AST) framework to categorize facilities into three tiers based on the biosecurity risks they could pose if fully compromised. We use “fully compromised” to mean an attacker can control protocol execution and relevant information technology and operational technology (IT/OT) controls sufficiently to bypass all oversight and safeguards. We outline methods to improve customer verification, order screening, cybersecurity measures, insider threat protections, and independent security assessments. Although limited information regarding automated laboratory capabilities is publicly available, we argue that most current automated laboratories do not possess latent capacity for serious harms. These risks appear low for most current facilities, but laboratories outside the scope of our review may possess greater latent capability, and capabilities may advance faster than anticipated. Our analysis draws on expert interviews with automated laboratory operators and biosecurity experts. We recommend that researchers and industry stakeholders engage with standard-setting bodies to establish security standards for automated biological laboratories. With ongoing monitoring of capability levels and adoption of proportionate safeguards, these laboratories can be safely operated.

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