# XVI. SECURITY ## 16.1 Digital Trust Doctrine ### 16.1.1 Security by design. Security under the Distributed Digital Public Goods Framework shall be treated as an architectural condition of digital public-good trust, not as an afterthought, optional enhancement, or post-release control. Every DDPGF object shall be designed, classified, reviewed, released, supported, corrected, and archived with security proportional to its object class, access class, sensitivity, intended use, dependency profile, jurisdictional context, public-safe status, and lifecycle state. Security by design shall apply to software objects, data objects, model objects, AI-agent objects, API objects, dashboard objects, Studio workflows, digital twins, simulations, repositories, learning objects, Reports, Marketplace listings, Registry records, Grid inputs, TRL notes, National Portfolio objects, Nexus Universe objects, secure rooms, data rooms, compute-to-data workflows, and lawful handoff packages. Security by design shall require early identification of security assumptions, attack surfaces, dependencies, secrets, privileged roles, access pathways, repository risks, data exposure risks, model exposure risks, AI workflow risks, API abuse risks, cyber-physical risks, infrastructure risks, cross-border risks, and downstream misuse risks. Security shall be recorded as evidence, not asserted as reputation. A digital public-good object that has not been security-classified shall not be treated as security-reviewed, safe for release, ready for open distribution, ready for Marketplace listing, ready for handoff context, or ready for deployment by any downstream actor. ### 16.1.2 Privacy by design. Privacy under DDPGF shall be designed into object identity, data intake, metadata creation, user records, learner records, contributor records, access controls, Marketplace analytics, Registry records, Studio workflows, Campaign participation, Academy pathways, model workflows, dashboards, Reports, public-safe summaries, data rooms, secure rooms, compute-to-data workflows, and handoff packages. Privacy by design shall require data minimization, purpose limitation, consent and permission records where applicable, sensitive data controls, youth protections, health data protections, community data protections, Indigenous protocol-sensitive data controls where applicable, role-based access, retention rules, deletion pathways, sealing pathways, archive rules, and correction pathways. Privacy by design shall also require that data subjects, learners, contributors, communities, workers, public authority participants, and other affected persons are not converted into uncontrolled data sources, training data, Marketplace analytics, ranking inputs, public display objects, or downstream handoff assets without proper authority and recorded permissions. Privacy status shall remain contextual and correctionable. A privacy label, data-use label, or access class shall not be treated as a legal compliance determination unless separately issued by competent legal authority. ### 16.1.3 Resilience by design. Resilience under DDPGF shall be designed into digital-public-good architecture so that objects, repositories, registries, data rooms, secure rooms, learning systems, dashboards, APIs, Studio workflows, Reports, Marketplace listings, National Portfolio records, and handoff packages can withstand disruption, degradation, cyber incident, dependency failure, access interruption, repository outage, infrastructure failure, censorship risk, disaster impact, connectivity limitation, maintenance failure, or institutional discontinuity. Resilience by design shall include redundancy, decentralization, federated storage, offline fallback, low-bandwidth access, degraded-mode operations, backup, restore testing, disaster recovery, continuity records, archive mirrors, and sovereign continuity where appropriate. Resilience by design shall not imply that DDPGF provides guaranteed uptime, emergency command, official continuity infrastructure, public authority redundancy, regulated critical infrastructure service, or service-level warranty. Resilience features shall be recorded as capability features and limitations, not as operational guarantees. ### 16.1.4 Zero-trust principles. DDPGF shall apply zero-trust principles to sensitive workflows, controlled repositories, secure rooms, data rooms, compute-to-data environments, Studio workflows, APIs, model workflows, AI-agent workflows, Marketplace administration, Registry administration, National Portfolio records, public authority learning rooms, capital-reader rooms, insurance-reader rooms, donor-reader rooms, and handoff-recipient-only packages. No user, device, system, model, workflow, repository, partner, provider, sponsor, public authority participant, contributor, maintainer, or downstream recipient shall be trusted by default merely because of affiliation, prior participation, institutional status, location, role title, sponsor status, provider status, or historical access. Zero-trust implementation shall include identity verification, authentication, authorization, least privilege, session controls, device or environment controls where appropriate, logging, monitoring, access recertification, anomaly review, export controls, role separation, and revocation. Zero-trust principles shall be used to reduce risk, not to create surveillance overreach, social scoring, unnecessary data collection, or unrestricted monitoring of learners, contributors, workers, communities, or participants. ### 16.1.5 Least privilege. DDPGF shall apply least privilege across all systems, rooms, workflows, repositories, and object classes. Users, maintainers, reviewers, contributors, stewards, providers, sponsors, public authority learning participants, capital readers, insurers, donors, learners, Academy users, Campaign participants, Foundry contributors, Studio users, Registry stewards, Marketplace stewards, and handoff recipients shall receive only the minimum access required for the recorded purpose, recorded object, recorded workflow, recorded time period, and recorded role. Least privilege shall apply to data access, model access, repository write access, administrative rights, API access, dashboard access, Studio tool permissions, AI-agent tool permissions, secure-room access, data-room access, export rights, publication rights, Registry update rights, Marketplace listing rights, and handoff package access. Privilege shall be revocable, reviewable, logged where appropriate, and correctable. Role status shall never be used to bypass security, privacy, public-safe, safeguard, or boundary controls. ### 16.1.6 Public-safe security disclosure. Security disclosure under DDPGF shall be public-safe by default. Vulnerability reports, exploit-adjacent information, security configurations, cyber-sensitive diagrams, access logs, credential records, incident records, red-team records, infrastructure-sensitive information, OT/IoT/IIoT records, AI security issues, prompt-injection details, model leakage risks, secure-room findings, and critical dependency risks shall be disclosed only in a manner that reduces harm, protects affected systems, preserves privacy, avoids enabling misuse, and supports correction. Public-safe security disclosure may include controlled disclosure, coordinated vulnerability disclosure, delayed publication, aggregate reporting, restricted technical detail, secure-room review, affected-party notice, repository notices, public-safe summaries, Registry status updates, Marketplace delisting, Report correction, Studio shutdown, Grid or TRL downgrade, handoff recall, and archive action. Public-safe disclosure shall not be treated as official public warning, cybersecurity certification, public authority notice, operational instruction, or security guarantee. ### 16.1.7 Correctionability as trust. Trust under DDPGF shall be preserved through correctionability. Security, privacy, cyber, resilience, public-safe, data-use, AI-use, repository, dependency, support, access, disclosure, Marketplace, Registry, Studio, Grid, TRL, Reports, and handoff records shall be correctable where errors, vulnerabilities, misstatements, unsafe disclosures, outdated dependencies, privacy risks, security failures, access errors, boundary overclaims, or incidents are identified. Correctionability shall include issue intake, severity classification, containment, claims freeze, data freeze, technical freeze, access suspension, output review, public-safe notice, Registry update, Marketplace delisting, Report correction, repository notice, Studio shutdown, Grid or TRL downgrade, handoff recall, archive, and reinstatement where appropriate. A DDPGF object that cannot be corrected, withdrawn, recalled, superseded, archived, or marked non-continuing shall not be treated as trustworthy. Correctionability shall be part of digital safety, not merely institutional reputation management. ### 16.1.8 No security certification by implication. No security review, privacy review, cyber review, vulnerability disclosure, threat model, SBOM record, dependency scan, secret scan, access-control record, secure-room workflow, data-room workflow, compute-to-data workflow, resilience test, backup record, recovery test, Registry status, Marketplace listing, Grid input, TRL note, Report publication, Studio demonstration, Nexus Universe presentation, or handoff context shall constitute security certification, privacy certification, compliance certification, cyber certification, safety certification, public authority approval, procurement readiness, financeability, insurability, deployment authorization, service-level warranty, or execution authority by implication. Security under DDPGF shall be evidence-bearing, bounded, lifecycle-based, and correctionable. Certification, where required, must be separately issued by a competent certifying authority or lawful actor outside default DDPGF status and recorded only as external provenance within scope. ## 16.2 Security Controls ### 16.2.1 Identity and access management. DDPGF shall require identity and access management appropriate to each object class, environment, role, and risk level. Identity and access management shall include account creation, identity verification where appropriate, role assignment, authentication, authorization, access scoping, time-limited access, purpose-based access, access review, access recertification, suspension, revocation, and auditability. The identity model shall support contributors, maintainers, reviewers, stewards, learners, public authority learning participants, providers, sponsors, capital readers, insurers, donors, communities, National Nodes, Competence Cells, Working Groups, secure-room users, data-room users, Studio users, and lawful handoff recipients without collapsing their roles. Identity and access records shall not create authority beyond recorded scope. Identity verification shall not create endorsement, credential status, employment status, procurement qualification, public authority approval, or execution authority. ### 16.2.2 Multi-factor authentication where appropriate. Multi-factor authentication shall be required where risk, sensitivity, privilege, or system function justifies it, including administrative accounts, repository maintainer accounts, secure-room access, data-room access, compute-to-data access, Registry administration, Marketplace administration, Studio administration, public authority learning rooms involving sensitive materials, capital-reader rooms, insurance-reader rooms, handoff-recipient-only packages, API administration, model repository administration, and access to restricted or protected objects. Multi-factor authentication shall be implemented proportionally and inclusively, accounting for accessibility, low-bandwidth environments, device limitations, national contexts, and recovery pathways. MFA shall improve security without excluding legitimate users or creating unnecessary data collection. ### 16.2.3 Least privilege. Least privilege shall be enforced technically and procedurally. Access shall be limited by object, role, room, workflow, repository, data class, AI-use class, export permission, administrative permission, review permission, publication permission, and handoff permission. Privileged access shall be time-limited where appropriate, reviewed periodically, and removed when no longer required. Least privilege shall apply especially to secrets, keys, credentials, restricted datasets, protected knowledge, AI-agent tools, deployment-like environments, write access, Registry status changes, Marketplace listing changes, publication approvals, public-safe release, and handoff packages. Privilege escalation shall be logged and justified. ### 16.2.4 Secrets management. DDPGF shall require secrets management for credentials, API keys, tokens, certificates, private keys, service accounts, database credentials, repository secrets, cloud secrets, model access keys, encryption keys, secure-room credentials, and handoff-package access credentials. Secrets shall not be stored in public repositories, Reports, notebooks, dashboards, learning objects, screenshots, logs, issue threads, public-safe summaries, Marketplace listings, Registry records, or uncontrolled files. Secrets management shall include secret minimization, rotation where appropriate, access controls, encryption where appropriate, secret scanning, incident response, revocation, and archive or deletion rules. Secret exposure shall trigger incident response, technical freeze where necessary, access review, correction, and public-safe disclosure where appropriate. ### 16.2.5 Secure repositories. DDPGF repositories shall be governed according to object class and sensitivity. Secure repositories shall apply access controls, branch protections where appropriate, maintainer roles, contributor rules, dependency controls, secret scanning, security disclosure channels, issue triage, release controls, license records, support records, vulnerability records, correction pathways, archive rules, and public-safe documentation. Repository visibility shall be open, controlled, restricted, secure, metadata-only, or archived according to object classification. Repository existence shall not imply that materials are safe, supported, certified, approved, deployable, procurement-ready, or executable. Public repositories shall not contain restricted data, protected knowledge, credential secrets, unsafe cyber instructions, sensitive infrastructure details, or materials not cleared for public release. ### 16.2.6 Dependency scanning. DDPGF shall require dependency scanning where software, notebooks, APIs, dashboards, models, infrastructure-as-code, Studio workflows, or reproducibility packages rely on third-party packages, libraries, services, containers, models, data sources, APIs, or infrastructure. Dependency scanning shall identify known vulnerabilities, license conflicts, deprecated packages, unsupported components, supply-chain risks, malicious packages, transitive dependencies, and update needs. Dependency scan results shall be recorded as bounded security evidence. A completed dependency scan shall not mean that an object is vulnerability-free, secure-certified, production-approved, procurement-ready, deployable, or safe for all use. ### 16.2.7 SBOM records. Software Bill of Materials records shall be maintained where appropriate for software objects, public-good technical baselines, APIs, services, dashboards, infrastructure-as-code, notebooks, reproducibility packages, Studio components, and handoff-relevant software packages. SBOM records shall identify components, versions, dependencies, licenses, known vulnerabilities where applicable, maintainer status, update status, and correction pathways. An SBOM record shall support transparency, security review, correction, dependency provenance, and handoff context. It shall not create security certification, warranty, supplier approval, procurement qualification, or deployment authorization. ### 16.2.8 Vulnerability disclosure. DDPGF shall maintain vulnerability disclosure pathways for software objects, APIs, infrastructure templates, repositories, dashboards, Studio workflows, model workflows, AI-agent workflows, controlled runtime environments, and other cyber-relevant objects. Disclosure pathways shall define reporting channels, confidentiality expectations, triage procedures, severity classification, affected-object identification, embargo or coordinated disclosure where appropriate, correction procedures, public-safe summaries, Registry updates, Marketplace actions, and archive rules. Vulnerability disclosure shall be handled to reduce harm and protect affected users. Disclosure shall not be treated as official public warning, security certification, exploit instruction, operational command, or admission of unrestricted liability by default. ### 16.2.9 Threat modeling. Threat modeling shall be applied to higher-risk digital public-good objects, including public-facing APIs, data rooms, secure rooms, compute-to-data workflows, AI-agent workflows, model repositories, dashboards, digital twins, Studio workflows, National Portfolio systems, Marketplace systems, Registry systems, Campaign platforms, Academy platforms, and handoff packages. Threat modeling shall consider assets, adversaries, misuse cases, attack paths, dependencies, privilege boundaries, data flows, trust assumptions, public-safe risks, protected knowledge risks, AI misuse risks, cyber-physical risks, and recovery paths. Threat models shall be recorded and updated as objects evolve. Threat modeling shall not constitute security certification, compliance determination, public authority approval, or production authorization. ### 16.2.10 Incident response. DDPGF shall maintain incident response procedures for security incidents, cyber incidents, privacy incidents, data incidents, AI incidents, repository incidents, dependency incidents, secret exposure, vulnerability exposure, access misuse, public-safe failures, protected knowledge exposure, unsafe publication, Marketplace overclaim, Registry error, Studio misuse, room breach, compute-to-data misuse, handoff package misuse, or boundary overclaim. Incident response shall include detection, reporting, triage, containment, claims freeze, data freeze, technical freeze, access suspension, severity classification, affected-object mapping, correction, notice, Registry update, Marketplace action, repository action, Report correction, Studio shutdown, Grid or TRL update, handoff recall, archive, and lessons learned. Incident response shall preserve legal, privacy, safeguard, public-safe, and security constraints. Public communications shall be public-safe and boundary-disciplined. ### 16.2.11 Backup and recovery. DDPGF shall maintain backup and recovery practices appropriate to repositories, Registry records, Marketplace metadata, Reports, public-safe summaries, learning objects, data objects, model cards, system cards, benchmark cards, software packages, documentation, Studio workflows, secure-room records, data-room records, audit logs, correction records, archive records, and handoff packages. Backup and recovery shall consider redundancy, restore testing, encryption where appropriate, access controls, retention, jurisdiction, data sovereignty, protected knowledge, and deletion obligations. Backup availability shall not create service-level warranty, operational continuity guarantee, public authority continuity, or execution authority. Backup systems shall remain subject to access class, data-use restrictions, and sensitivity controls. ### 16.2.12 Resilience testing. DDPGF may conduct resilience testing for repositories, APIs, dashboards, Studio workflows, Marketplace systems, Registry systems, data rooms, secure rooms, compute-to-data environments, backup systems, low-bandwidth access modes, offline materials, archive mirrors, and continuity pathways. Resilience testing may include restore tests, failover tests, degraded-mode tests, access recovery tests, repository integrity checks, dependency-failure exercises, tabletop exercises, and public-safe incident simulations. Resilience testing shall be recorded as bounded evidence only. It shall not create service guarantee, disaster recovery certification, public authority approval, deployment authorization, procurement readiness, financeability, or insurability. ## 16.3 Privacy Controls ### 16.3.1 Data minimization. DDPGF shall collect, store, process, display, publish, export, and archive only the minimum personal, sensitive, community, institutional, technical, or operational data required for a recorded purpose. Data minimization shall apply to learner records, contributor records, Marketplace analytics, Registry records, Campaign participation, Academy records, WILPs, iCRS records, support requests, access logs, secure-room records, data-room records, public authority learning participation, capital-reader participation, insurance-reader participation, donor-reader participation, and handoff records. Data minimization shall also apply to public-safe release. Objects shall not disclose unnecessary personal data, sensitive locations, protected knowledge, credential details, access logs, user behavior, or participant identities where aggregate, masked, pseudonymous, metadata-only, or controlled alternatives are sufficient. ### 16.3.2 Purpose limitation. DDPGF shall require that data be used only for recorded purposes compatible with the relevant object class, data-use label, AI-use label, access class, consent or permission record, public-safe status, and jurisdictional context. Data collected for learning shall not automatically be used for employment, ranking, AI training, marketing, public display, public authority profiling, finance analysis, insurance analysis, procurement analysis, or handoff without appropriate review and recorded authority. Purpose changes shall require review, notice where appropriate, updated records, and correction pathways. Unauthorized purpose expansion shall be treated as a privacy and boundary incident. ### 16.3.3 Consent and permission. DDPGF shall record consent, permission, authorization, license, or rights basis where required for personal data, learner data, contributor data, community data, protected knowledge, Indigenous protocol-sensitive data where applicable, health data, youth data, images, recordings, interviews, field data, survey data, work product, credential display, portfolio display, AI-use, data sharing, publication, or handoff. Consent and permission records shall be specific, understandable, revocable where applicable, and linked to object records. Consent shall not be assumed from attendance, participation, contribution, download, public interest, Campaign support, public authority learning, Marketplace use, or community engagement. Participation without recorded consent shall not become consent by implication. ### 16.3.4 Data subject rights where applicable. Where applicable law or governance rules provide data subject rights, DDPGF shall support access, correction, deletion, portability, objection, restriction, withdrawal, appeal, or explanation pathways. These pathways may apply to learners, contributors, workers, Campaign participants, Marketplace users, Registry participants, public authority learning participants, community participants, youth participants, and other affected persons. Data subject rights shall be implemented in a manner consistent with record integrity, legal retention, archive obligations, security, protected knowledge controls, and public-safe reporting. Where deletion is not possible because of lawful retention, archive, audit, or institutional memory requirements, sealing, restriction, or annotation may be used where appropriate. ### 16.3.5 Sensitive data controls. Sensitive data controls shall apply to data that could create harm, discrimination, exploitation, legal risk, safety risk, reputational harm, community harm, Indigenous protocol breach, public authority sensitivity, cyber risk, infrastructure risk, health risk, youth risk, or protected knowledge exposure. Sensitive data shall be classified, minimized, access-controlled, purpose-limited, logged where appropriate, reviewed before output, and archived or deleted according to rules. Sensitive data shall not be placed in open repositories, open Reports, public Marketplace listings, public dashboards, public learning objects, AI training datasets, public-safe summaries, or handoff packages without appropriate transformation, permission, and review. ### 16.3.6 Youth data controls. Youth data shall receive heightened protection. DDPGF shall apply age-appropriate data minimization, guardian or institutional permission where required, youth-safe learning design, restricted portfolio display, restricted Marketplace display, restricted public recognition, careful iCRS display, anti-exploitation controls, WILP protections, Campaign safeguards, and limits on AI profiling, ranking, behavioral analytics, or public exposure. Youth participation shall not create unrestricted public display, employment status, procurement status, public authority status, AI training permission, or handoff eligibility by implication. Youth data incidents shall receive heightened incident response. ### 16.3.7 Health data controls. Health data shall be treated as sensitive and shall be handled only under recorded purpose, permissions, access class, data-use label, public-safe status, and jurisdictional constraints. Health data controls shall apply to public health resilience materials, climate-health risk data, One Health data, WFEH-B health components, community health inputs, field data, learning records with health disclosures, and protected health-related knowledge. Health data shall not be used to make medical decisions, public health orders, insurance decisions, employment decisions, procurement decisions, public authority decisions, or automated determinations by default. Health-related DDPGF outputs shall not constitute medical advice, public health decision, clinical validation, or regulatory approval. ### 16.3.8 Community data controls. Community data controls shall protect community-sensitive, place-based, Indigenous protocol-sensitive where applicable, public-interest, humanitarian, cultural, ecological, geospatial, vulnerability, resilience, local-risk, and protected knowledge data. Community data shall be handled through non-extractive engagement, public-safe transformation, consent boundary records, protected knowledge controls, sensitive location controls, and community-facing correction where appropriate. Community data shall not be converted into open data, AI training data, operational intelligence, procurement input, finance signal, insurance signal, or handoff material without appropriate authority and safeguards. Community participation shall not equal consent. ### 16.3.9 Cross-border controls. Cross-border controls shall apply where data, repositories, models, workflows, rooms, users, servers, public authority records, protected knowledge, community data, health data, youth data, cyber-sensitive records, infrastructure-sensitive records, or handoff packages cross jurisdictional boundaries. Controls shall consider data sovereignty, localization, transfer restrictions, access restrictions, repository location, cloud region, secure enclave location, public authority sensitivity, contractual restrictions, and applicable law. Cross-border availability shall not create cross-border permission. A user’s ability to access an object from another jurisdiction shall not imply lawful transfer, reuse, publication, AI training permission, handoff permission, or deployment authorization. ### 16.3.10 Deletion, sealing, and archive. DDPGF shall distinguish deletion, sealing, and archive. **Deletion** shall remove data or records where lawful and appropriate. **Sealing** shall restrict access to records that must be retained but should no longer be visible or usable in ordinary workflows. **Archive** shall preserve records for institutional memory, citation, correction, audit, or historical purposes subject to access controls and sensitivity rules. Deletion, sealing, and archive decisions shall account for legal retention, privacy rights, correction records, public-safe needs, protected knowledge, security risks, repository integrity, downstream dependencies, handoff recalls, and institutional memory. Archived or sealed records shall not create current authority or current use rights. ## 16.4 Cyber-Sensitive Objects ### 16.4.1 Vulnerability reports. Vulnerability reports shall be treated as cyber-sensitive objects unless classified otherwise. They shall identify affected object, affected version, severity, reporter, steward, reproduction conditions where safe, impact, mitigation, correction path, disclosure status, public-safe summary status, Registry update, Marketplace action, repository notice, and archive rule. Technical detail shall be limited according to harm risk and coordinated disclosure needs. A vulnerability report shall not be public warning, exploit instruction, security certification, legal determination, or deployment prohibition by default. It shall trigger review, correction, and public-safe communication where appropriate. ### 16.4.2 Exploit-adjacent information. Exploit-adjacent information means information that could enable misuse, unauthorized access, cyberattack, evasion, privilege escalation, data exfiltration, model abuse, prompt injection, infrastructure compromise, OT/IoT compromise, or exploitation of vulnerable systems. Such information shall be restricted, transformed, delayed, summarized, or withheld as appropriate. Exploit-adjacent information shall not be published openly merely because it is technically interesting, academically useful, or relevant to a Report. Public-safe security disclosure shall control. ### 16.4.3 Critical infrastructure diagrams. Critical infrastructure diagrams, network maps, system architecture diagrams, facility diagrams, telecom diagrams, OT/IoT/IIoT diagrams, edge-node maps, sensor maps, digital twin diagrams, geospatial infrastructure layers, and dependency maps shall be classified for sensitivity before release. They may require masking, aggregation, abstraction, controlled access, secure-room review, or metadata-only description. Publication of infrastructure diagrams shall not create operational authority, public authority decision, procurement status, security approval, or deployment authorization. Sensitive diagrams shall not expose exploitable details. ### 16.4.4 OT / IoT / IIoT records. Operational technology, Internet of Things, and Industrial Internet of Things records shall be treated as potentially cyber-physical and safety-sensitive. Such records may include device inventories, firmware notes, network relationships, sensor locations, control dependencies, vulnerability notes, configuration records, digital twin links, and incident histories. They shall be access-controlled, public-safe reviewed, and protected against misuse. OT, IoT, and IIoT records shall not be used as operational instructions, command pathways, or deployment authorizations under DDPGF default posture. ### 16.4.5 Access logs. Access logs shall be protected as sensitive operational and privacy-relevant records. They may include user access, room entry, file access, repository access, API calls, query execution, model execution, export attempts, permission changes, and administrative actions. Access logs shall support audit, security, incident response, correction, and accountability. Access logs shall not be published openly, used for unauthorized surveillance, used for social scoring, used for employment decisions, used for learner ranking, or used for public authority profiling by default. ### 16.4.6 Credential records. Credential records, including passwords, tokens, API keys, certificates, private keys, service accounts, identity records, verification records, digital badges, learner credentials, micro-credentials, access credentials, and secure-room credentials, shall be protected according to sensitivity. Technical credentials shall be secret-managed. Learning and identity credentials shall be privacy-managed. Credential records shall not be exposed through repositories, reports, dashboards, logs, public Marketplace listings, or public Registry records except as approved public display records with privacy controls and boundary notices. ### 16.4.7 Security configurations. Security configurations, including firewall rules, access policies, network configurations, cloud configurations, IAM policies, encryption settings, secure enclave settings, container settings, repository permissions, CI/CD settings, logging settings, and monitoring settings, shall be controlled where disclosure could increase risk. Public documentation may describe security posture at a high level without exposing exploitable detail. Security configuration review shall not create security certification, provider validation, deployment approval, or service guarantee. ### 16.4.8 Incident records. Incident records shall document security, privacy, data, AI, cyber, protected knowledge, public-safe, repository, Marketplace, Registry, Studio, room, compute-to-data, handoff, or boundary incidents. Incident records shall include classification, timeline, affected objects, containment, correction, notifications, public-safe communications, Registry updates, Marketplace actions, repository actions, handoff recalls, lessons learned, and archive status. Incident records may be controlled or public-safe summarized. They shall not be suppressed where correction requires visibility, but sensitive details shall be protected. ### 16.4.9 Red-team records. Red-team records shall document adversarial testing, abuse testing, AI safety testing, model probing, cyber testing, prompt-injection testing, data leakage testing, API abuse testing, dashboard misuse testing, Studio misuse testing, or public-safe stress testing. Red-team records shall be controlled where methods or findings could enable misuse. Red-team records shall support correction and readiness review. They shall not be treated as security certification, AI safety certification, public authority approval, or deployment authorization. ### 16.4.10 Public-safe cyber summaries. Public-safe cyber summaries shall translate sensitive cyber findings into safe, non-exploit-enabling, actionable, and boundary-disciplined public or semi-public communication. Such summaries may identify that an issue existed, what object class was affected, what status changed, what users should do, what has been corrected, and what remains limited, without exposing unsafe technical details. Public-safe cyber summaries shall not be public warnings by default, shall not instruct exploitation, and shall not overstate security assurance. ## 16.5 Digital Resilience ### 16.5.1 Redundancy. DDPGF shall support redundancy where appropriate for repositories, Registry records, Marketplace metadata, Reports, data packages, public-safe summaries, learning objects, software releases, documentation, critical schemas, ontologies, APIs, dashboards, Studio workflows, and archive records. Redundancy may include replicated storage, backup repositories, mirrored metadata, replicated documentation, and multiple access pathways. Redundancy shall improve continuity but shall not create service guarantee, critical infrastructure status, public authority continuity, or operational warranty. ### 16.5.2 Decentralization. DDPGF shall support decentralized patterns where they improve resilience, national ownership, local access, repository independence, public-good continuity, anti-capture discipline, and disaster resilience. Decentralization may include National Nodes, regional repositories, mirrored packages, federated metadata, local learning objects, local public-safe summaries, and distributed contributor models. Decentralization shall not mean uncontrolled fragmentation, semantic drift, authority collapse, ungoverned forks, or bypass of Registry status truth. Decentralized objects shall remain versioned, recorded, correctable, and boundary-disciplined. ### 16.5.3 Federated storage. Federated storage may be used to preserve digital public-good objects across global, regional, national, institutional, controlled, secure, public, and archive repositories. Federated storage shall support data sovereignty, localization, access control, resilience, continuity, public-safe release, and lawful handoff context. Metadata federation may allow discoverability without exposing restricted objects. Federated storage shall not create unrestricted access, cross-border transfer permission, public authority approval, data rights, or deployment authorization. ### 16.5.4 Offline fallback. DDPGF shall support offline fallback for appropriate learning objects, public-safe guides, reports, documentation, data dictionaries, schemas, checklists, public-safe summaries, and operationally non-command materials where connectivity is limited or disrupted. Offline fallback shall be designed to preserve version labels, correction notices, expiration notices, boundary notices, and update pathways. Offline materials shall not be treated as current if superseded, withdrawn, recalled, or archived. Offline access shall not authorize execution, emergency command, public warning, procurement, finance, or deployment. ### 16.5.5 Low-bandwidth access. DDPGF shall support low-bandwidth access to appropriate objects through lightweight formats, compressed files, text-first versions, static pages, low-resolution public-safe imagery, offline packages, plain-language summaries, and accessible formats. Low-bandwidth design shall support inclusion, rural access, disaster-affected contexts, mobile-first access, and national localization. Low-bandwidth access shall not remove security, privacy, public-safe, license, correction, or boundary requirements. ### 16.5.6 Degraded-mode operations. DDPGF shall support degraded-mode operation for appropriate systems and workflows so that users can still access essential public-safe knowledge, documentation, learning materials, Registry status snapshots, correction notices, and archive references during partial outages. Degraded mode may reduce features, disable downloads, suspend write access, restrict AI use, pause Marketplace updates, or freeze handoff routing. Degraded-mode operation shall not authorize operational command, public authority action, emergency response, deployment, procurement, finance, insurance, or execution. ### 16.5.7 Disaster recovery. DDPGF shall maintain disaster recovery plans for key digital public-good infrastructure, including repositories, Registry, Marketplace, Reports, learning systems, Studio environments, secure rooms, data rooms, compute-to-data records, object metadata, correction records, and archives. Disaster recovery plans shall identify recovery priorities, backup locations, restoration procedures, access controls, communication pathways, testing cadence, and archive protection. Disaster recovery planning shall support institutional continuity but shall not create guaranteed uptime or regulated critical infrastructure service by default. ### 16.5.8 Continuity records. Continuity records shall document resilience arrangements, backup status, restore tests, repository mirrors, archive mirrors, degraded-mode plans, support dependencies, critical maintainer dependencies, security dependencies, data sovereignty dependencies, and recovery gaps. Continuity records shall be reviewed and corrected as infrastructure changes. Continuity records shall not create service-level warranty, financeability, insurability, procurement readiness, or public authority approval. ### 16.5.9 Archive mirrors. Archive mirrors may preserve public-safe, open, controlled, or metadata-only copies of objects across repositories or jurisdictions where appropriate. Archive mirrors shall preserve version, citation, license, access class, sensitivity class, boundary notices, correction records, withdrawal records, recall records, and successor links. Archive mirrors shall not revive withdrawn, recalled, deprecated, or non-continuing objects for current use. Mirrored access remains subject to status truth. ### 16.5.10 Sovereign continuity. Sovereign continuity shall support the ability of national, regional, and local Nexus contexts to preserve access to nationally relevant digital public-good objects, learning objects, public-safe reports, data dictionaries, schemas, National Portfolio records, DRI summaries, Observatory records, and handoff context within appropriate jurisdictional and data sovereignty constraints. Sovereign continuity may require national repositories, localized records, national language materials, sovereign compute, secure enclaves, controlled access, and national archive rules. Sovereign continuity shall not imply public authority ownership, national endorsement, public authority approval, procurement status, data transfer permission, deployment authority, or execution authority by default. ## 16.6 Security and Privacy Boundary Rules ### 16.6.1 Security review is not certification. A security review, threat model, dependency scan, secret scan, SBOM record, vulnerability review, repository review, cyber review, secure-room review, access review, resilience test, or incident response record shall not constitute cybersecurity certification, safety certification, compliance certification, public authority approval, procurement readiness, financeability, insurability, deployment authorization, or warranty. ### 16.6.2 Secure-room access is not safety approval. Access to a Secure Room, Cyber Review Room, AI Review Room, Data Room, Clean Room, Protected Knowledge Room, or compute-to-data environment shall not imply that the object reviewed is safe, certified, approved, deployable, procurement-ready, financeable, insurable, public-authority-approved, or execution-ready. Room access permits controlled review only within recorded scope. ### 16.6.3 Privacy label is not legal compliance determination. A privacy label, data-use label, AI-use label, sensitivity class, access class, public-safe status, data-room status, or compute-to-data status shall not constitute legal compliance determination, regulatory approval, consent determination, cross-border transfer approval, public authority approval, or unrestricted permission to process, publish, reuse, train, transfer, or hand off data. ### 16.6.4 Vulnerability disclosure is not public warning. A vulnerability disclosure, public-safe cyber summary, incident notice, repository notice, Registry status update, Marketplace delisting, Report correction, or handoff recall shall not be treated as official public warning, emergency alert, regulatory notice, public authority command, or operational instruction unless separately issued by a competent public authority or responsible operator. ### 16.6.5 Cyber artefact is not operational instruction. A cyber artefact, vulnerability report, red-team record, threat model, security configuration, OT/IoT/IIoT record, access log, incident record, public-safe cyber summary, or technical note shall not be used as operational instruction, exploitation guidance, emergency command, infrastructure command, deployment authorization, procurement recommendation, or public authority decision by default. ### 16.6.6 Resilience feature is not service guarantee. A resilience feature, backup, mirror, offline fallback, low-bandwidth mode, degraded-mode capability, continuity plan, disaster recovery plan, sovereign continuity feature, archive mirror, or restore test shall not create uptime warranty, service-level agreement, operational guarantee, public authority continuity guarantee, regulated critical infrastructure status, procurement readiness, financeability, insurability, deployment authorization, or execution authority. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.therisk.global/organization/operations/frameworks/distributed-digital-public-goods-framework-ddpgf/xvi.-security.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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