The Biosecurity Handbook
Biological Security in the AI Era
Welcome to The Biosecurity Handbook
The same AI that accelerates drug discovery can accelerate the design of dangerous pathogens. Biology is getting easier to engineer, and governance has not caught up. Written for two communities that need each other’s expertise: biosecurity professionals who need AI context, and AI safety researchers who need biological grounding.
Three questions drive every chapter: How do emerging technologies change biological risk? What governance frameworks exist and where do they fail? What does credible preparedness and response require?
This resource is continuously updated as new research emerges.
A Note on Dual-Use Content
This handbook addresses biological security risks. Technical details that could enable misuse are cited from peer-reviewed literature but not expanded upon. The focus is frameworks, governance, and risk assessment, not operational protocols.
Recent Updates
- 8 Oct UK AISI reports chemistry and biology evaluation trends and safeguard limits Read in the handbook
- 7 Oct California AB 1864 makes the 2024 DNA synthesis screening framework binding Read in the handbook
- 30 Sep Stutz et al. report SynthIDBio protein watermarks in Nature Read in the handbook
- 29 Sep OpenAI reports GPT-6.1 Sol as High in biological and chemical capability Read in the handbook
- 28 Sep Klapsa et al.: London wastewater localized poliovirus circulation Read in the handbook
Start Here
Start with the risk frame, then read how AI changes biological risk. This path shows how the handbook separates biosecurity fundamentals from AI-enabled risk.
- Executive Summary: Key findings and recommendations
- What Is Biosecurity?: Core concepts and scope
- AI as a Biosecurity Risk Amplifier: How AI changes biological risk
Then continue to Policy Frameworks for AI-Bio Convergence for governance context.
For role-specific reading paths, see the Preface.
An AI assistant helping you should follow the Guidance for AI Agents.
Companion Handbooks
The Physician AI Handbook
Clinical AI across every ACGME-recognized medical specialty: FDA-cleared diagnostic tools, clinical decision support, AI-assisted documentation, LLMs in clinical practice, medical liability, privacy and HIPAA, workflow integration, and evaluation frameworks. Peer-reviewed evidence from JAMA, NEJM, Lancet, and specialty journals. For physicians, health system leaders, and anyone building or deploying clinical AI.
The Public Health AI Handbook
AI applications across population health: disease surveillance, epidemic forecasting, genomic pathogen analysis, outbreak detection, health department implementation, deployment failures, AI-assisted coding for epidemiological analysis, behavioral interventions, and health misinformation. For epidemiologists, public health practitioners, and health department leaders.
The Life Sciences AI Handbook
AI for biomedical discovery, molecular design, cellular systems, laboratory automation, and translational research. For researchers, biotechnology teams, computational biologists, physician-scientists, and students evaluating AI systems across molecules, cells, experiments, and therapeutic development.
Free to read and reuse under CC BY 4.0 · DOI 10.5281/zenodo.18252920 · How to cite
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