SafeWave Biological / Life Sciences Follow-Up Questionnaire

High-consequence follow-up for biological research, genomics, synthetic biology, gene editing, lab automation, clinical biotechnology, drug discovery, biological data analysis, DNA/RNA synthesis, pathogen research, agricultural biotechnology, ecological biology, and related life-sciences workflows.

Follow-up questionnaire notice

Complete this page only if you selected Biological / life sciences system at the end of the core SafeWave questionnaire. These answers are used to generate a separate High-Consequence Addendum and do not replace the core assessment.

Confidentiality, Anonymity & Use Notice

We recognize that this follow-up questionnaire may involve confidential, security-sensitive, operationally sensitive, or high-consequence system information. Please do not include classified information, credentials, live vulnerability details, proprietary implementation details, customer data, or other highly sensitive material unless you are authorized to share it for assessment purposes.

You may complete this questionnaire without identifying your company, product, or organization. You may use a generic system label, a generic contact email, or an internal assessment reference instead of a formal company identifier.

The purpose of this questionnaire is to help you gain a deeper understanding of your own system. Simply answering the questions may reveal areas where control boundaries, escalation pathways, runtime limits, auditability, rollback, authorization, or safe-state behavior may need further review.

You do not have to submit this questionnaire to receive value from it. You may use it internally as a self-assessment tool. If you choose to submit it for report generation, the resulting SafeWave report is intended to highlight areas of concern, explain why they matter, and map relevant findings to possible SafeWave substrates or engineering-pack pathways where applicable.

SafeWave’s goal is to help advanced systems remain more bounded, controllable, auditable, recoverable, and resistant to harmful escalation. Some issues may involve outside attackers, but others may arise from the system’s own architecture, automation, permissions, integrations, update pathways, or failure behavior.

Any SafeWave recommendations should be understood as architectural guidance and implementation requirements, not as a claim that one generic solution can be dropped into every system. Engineering teams may choose to implement equivalent controls themselves, or they may use SafeWave substrate mappings and Level 4 Engineering Packs to guide deeper implementation work.

If an implementation detail is not known, select Unknown / not evaluated rather than guessing.

Answer based on actual or currently planned system behavior, not ideal policy language.

Assessment Linkage

If you want this follow-up to be matched to a previously completed core questionnaire, use the same system label, contact email, or assessment reference ID. You may use generic identifiers if confidentiality is a concern.

Name (optional)

Email for matching or report delivery (optional — generic email may be used)

Company / organization (optional — generic label may be used)

System / business unit label (generic label may be used)

Assessment reference ID (optional)

To connect this follow-up to a core questionnaire, use the same system label, email, or assessment reference ID across forms. You may use generic identifiers if confidentiality is a concern.

Biological / Life Sciences

Biological / Life Sciences Systems Questions

These questions evaluate biological design acceleration, non-recall biological outcomes, dual-use exposure, synthesis and automation control, cyber-biological compromise, supply-chain risk, AI-bio convergence, ecological irreversibility, heritable modification, public-health overload, and loss of meaningful human control over life-critical biological workflows.

BIO.3 Can system outputs materially influence biological design, synthesis, experimentation, deployment, or release?

Single choice

BIO.4 Is there a clear separation between biological recommendation and biological execution?

Examples include separation between model output, protocol generation, synthesis ordering, lab automation, experiment execution, release approval, or clinical deployment.

Single choice

BIO.5 Can the system accelerate movement from biological design to synthesis, testing, scale-up, or deployment?

Single choice

BIO.6 Are there non-bypassable pause points before the workflow enters synthesis, live experimentation, scale-up, release, or clinical use?

Single choice

Yes, mandatory pause points are enforced Some pause points exist Mostly procedural or manual review No clear non-bypassable pause points Unknown / not evaluated N/A

BIO.7 Could the system contribute to non-recall biological outcomes?

Examples include self-propagating organisms, ecological release, gene drives, germline modification, persistent biological exposure, population-scale intervention, or irreversible clinical harm.

Single choice

No credible non-recall pathway Limited or indirect pathway Moderate pathway under misuse, failure, or scale Significant non-recall pathway Unknown / not evaluated N/A

BIO.8 Is recallability explicitly assessed before any biological intervention, deployment, or release?

Single choice

Yes, recallability is formally assessed and enforced Partially assessed Informally considered No clear recallability assessment Unknown / not evaluated N/A

BIO.9 Could the system affect biological materials, organisms, agents, constructs, samples, vectors, reagents, or datasets with dual-use potential?

Single choice

BIO.10 Are dual-use risks assessed end-to-end across people, data, tools, facilities, automation, vendors, and supply chains?

Single choice

BIO.11 Are genomic, pathogen, clinical, population-scale, or proprietary biological datasets protected as critical infrastructure?

Single choice

Yes, protected as critical infrastructure Mostly protected Partially protected Basic data-security controls only No clear critical-infrastructure treatment Unknown / not evaluated N/A

BIO.12 Can sensitive biological or genomic data be exfiltrated, aggregated, inferred from, or repurposed in ways that create biological, clinical, population, or security risk?

Single choice

BIO.13 Are synthetic biology tools, DNA/RNA synthesis services, lab automation systems, and cloud biology platforms governed with identity verification, screening, provenance, and auditability?

Single choice

Yes, strongly governed and independently audited Mostly governed Partially governed Inconsistent or vendor-dependent governance No clear governance Unknown / not evaluated N/A

BIO.14 Are synthesis, automation, or execution workflows blocked when risk screening fails or returns uncertainty?

Single choice

BIO.15 Are biosafety controls resilient under stress, scale, automation pressure, staffing turnover, incident conditions, or degraded information?

Single choice

Yes, tested and resilient under stress Mostly resilient Partially resilient Compliance exists but stress resilience is uncertain No clear stress-resilient biosafety model Unknown / not evaluated N/A

BIO.16 Are accidental release scenarios tested, drilled, logged, and independently reviewed?

Single choice

BIO.17 Are biological supply chains protected with provenance, chain-of-custody, tamper evidence, secure firmware, and recall-ready traceability?

Single choice

Yes, end-to-end supply-chain integrity exists Mostly protected Partially protected Vendor trust or conventional tracking only No clear biological supply-chain integrity model Unknown / not evaluated N/A

BIO.18 Can compromised vendors, altered reagents, tampered instruments, insecure firmware, or cloud-linked services silently affect biological outcomes?

Single choice

BIO.19 Does the system use AI for biological design, optimization, experimentation, or decision support?

Single choice

No AI involvement Limited AI support Moderate AI involvement Significant AI-driven design or optimization AI materially accelerates design-to-execution workflows Unknown / not evaluated N/A

BIO.20 Are AI-driven biological design tools controlled through tiered access, monitoring, outcome restrictions, red-team testing, and human authorization?

Single choice

BIO.21 Can the system generate, optimize, rank, or recommend biological designs, protocols, or interventions that require special review before execution?

Single choice

No Limited and low-risk recommendations only Some high-review outputs possible Significant high-review outputs possible Unknown / not evaluated N/A

BIO.22 Are design, synthesis, testing, deployment, and release functions separated so that no single system or user can move through the full biological pathway without independent review?

Single choice

BIO.23 Are insider-risk controls enforced across labs, datasets, automation systems, synthesis workflows, vendors, and platform administrators?

Single choice

Yes, strong cross-system insider-risk controls exist Mostly enforced Partially enforced Siloed or inconsistent controls No clear insider-risk model Unknown / not evaluated N/A

BIO.24 Can a single authorized person, contractor, administrator, or compromised account execute high-risk biological actions without independent authorization?

Single choice

No, independent authorization is required Only under limited controlled conditions Possible in some workflows Yes, single-actor execution is possible Unknown / not evaluated N/A

BIO.25 Do governance bodies have binding authority to halt, delay, or reject high-risk biological activity?

Single choice

BIO.26 Are approvals, exceptions, override decisions, and risk reviews logged in a tamper-evident and independently auditable way?

Single choice

BIO.27 Are whistleblowers, dissenting scientists, safety reviewers, and risk escalators protected from retaliation?

Single choice

Yes, strong independent protection exists Mostly protected Partially protected Policy exists but practical protection is uncertain No clear protection Unknown / not evaluated N/A

BIO.28 Does the system operate near ecological, environmental, or population-scale release pathways?

Single choice

No release pathway Contained or non-replicating pathway only Limited release pathway Environmental or population-scale release possible Self-propagating or difficult-to-recall release possible Unknown / not evaluated N/A

BIO.29 Is real-world reversibility proven and independently verified before ecological, environmental, or population-scale deployment?

Single choice

Yes, proven and independently verified Partially verified Theoretical or model-based only Not proven at real-world scale Unknown / not evaluated N/A

BIO.30 Could the system contribute to heritable human modification, germline editing, embryo modification, reproductive selection escalation, or genetic stratification?

Single choice

No credible pathway Limited or indirect pathway Moderate pathway under misuse, drift, or jurisdictional variation Significant pathway Unknown / not evaluated N/A

BIO.31 Are hard boundaries enforced against heritable human modification, irreversible enhancement, or biological redesign that affects future generations?

Single choice

Yes, hard boundaries are enforced Mostly enforced Partially enforced Norms exist but are not technically or institutionally enforceable No clear hard boundaries Unknown / not evaluated N/A

BIO.32 Could the system cause irreversible developmental, neurological, phenotypic, clinical, or intergenerational harm if design assumptions, models, automation, or human review fail?

Single choice

BIO.33 Are high-consequence biological decisions subject to genuine human authorization before irreversible action occurs?

Single choice

BIO.34 Are public-health detection, reporting, and response pathways sufficient if the system contributes to accidental or malicious biological exposure?

Single choice

BIO.35 Could the system’s outputs, actions, or dependencies overwhelm public-health, clinical, ecological, regulatory, or institutional response capacity?

Single choice

BIO.36 Could acceleration pressure, competitive pressure, emergency framing, funding incentives, or geopolitical pressure weaken safeguards, oversight, or pause points?

Single choice

BIO.37 Are there non-negotiable stop conditions where the workflow must halt rather than proceed with mitigation?

Examples include non-recall release, heritable modification, autonomous biological execution, extreme-risk pathogen work, or uncontrolled AI-bio acceleration.

Single choice

BIO.38 Is there a defined biological operating boundary for what the system is allowed to design, recommend, automate, or influence?

Examples include permitted organism classes, sequence types, pathogen-adjacent work, clinical-use limits, environmental-release exclusions, gene-editing boundaries, synthesis thresholds, and prohibited biological functions.

Single choice

Yes, clear biological operating boundaries are defined and enforced Mostly defined and enforced Partially defined Informally defined No clear biological operating boundary Unknown / not evaluated N/A

BIO.39 Are high-risk biological outputs screened before they can move into downstream workflows?

Examples include protocol generation, synthesis ordering, lab automation, vendor submission, experiment planning, clinical deployment, or environmental release review.

Single choice

Yes, high-risk outputs are screened before downstream use Mostly screened Partially screened Screened only in some workflows No clear output-screening process Unknown / not evaluated N/A

BIO.40 Can the system distinguish between benign biological requests and requests that may enable harmful, dual-use, irreversible, or non-recall outcomes?

Single choice

Yes, reliably distinguished and routed to review Mostly distinguished Partially distinguished Weak or inconsistent distinction No clear distinction capability Unknown / not evaluated N/A

BIO.41 Are biological-risk decisions explainable enough for qualified reviewers to understand why a request, output, workflow, or intervention was allowed, blocked, escalated, or modified?

Single choice

BIO.42 Are model, database, protocol, or automation updates blocked until biological-risk controls are revalidated?

Single choice

BIO.44 Are there biological, genomic, life-sciences, clinical, ecological, or biosecurity risks not captured above?

Open response

BIO.45 Could external cyber compromise, hostile account access, credential theft, API abuse, cloud compromise, lab-system compromise, vendor compromise, or command-channel manipulation cause unsafe biological outputs or actions?

Examples include altered DNA/RNA sequence design, modified protocol generation, manipulated synthesis requests, altered lab automation, unsafe model recommendations, changed screening results, tampered biological data, or unauthorized movement from design to execution.

Single choice

No credible pathway Limited pathway with strong safeguards Moderate pathway with partial safeguards Significant pathway Unknown / not evaluated N/A

BIO.46 Are cyber-biological compromise scenarios tested against realistic biological consequences?

Examples include compromised bio-design tools, altered sequence files, tampered lab automation, manipulated synthesis-ordering workflows, cloud biology compromise, vendor portal compromise, poisoned biological datasets, or malicious changes to screening and approval workflows.

Single choice

Yes, tested against realistic biological consequences Mostly tested Partially tested Cyber testing exists but biological consequences are not fully tested No clear cyber-biological compromise testing Unknown / not evaluated N/A

BIO.47 Should this assessment also include the Cybersecurity / Cyber Operations follow-up questionnaire?

Select “Yes” if cyber compromise, credential abuse, exposed APIs, cloud services, lab automation, vendor access, telemetry manipulation, synthesis-ordering systems, or adversarial control could materially affect biological design, experimentation, synthesis, deployment, or release.

Single choice

Yes — cybersecurity follow-up should also be completed Possibly — further review is needed No — biological / life sciences questions are sufficient for this case Unknown / not evaluated N/A

BIO.48 — Model-to-Tool / Execution Escalation

Can the system move from biological analysis or recommendation into tool use, vendor submission, protocol generation, lab automation, synthesis ordering, or execution workflow initiation without a separate authorization boundary?

Single choice

No — model or recommendation outputs cannot initiate downstream tool or execution workflows Limited — downstream workflow initiation is possible only under strict authorization Moderate — some tool or workflow escalation is possible under partial controls Significant — outputs can initiate or materially advance downstream biological workflows Unknown / not evaluated N/A

BIO.49 — Autonomous Biological Workflow Chaining

Can the system chain biological tasks across design, ranking, protocol generation, vendor interaction, lab automation, testing, analysis, refinement, or redeployment without renewed review at each high-risk transition?

Single choice

No — high-risk transitions require renewed review Limited — chaining is possible only in low-risk workflows Moderate — multi-step chaining is possible under partial review Significant — biological workflows can chain across multiple stages with limited renewed review Unknown / not evaluated N/A

Your completed follow-up will include the linkage fields above so this follow-up can be matched to the core questionnaire if you choose to share it for report generation.