Precision-Bounded Location and Data-Egress Finality

Introduction This document defines a focused precision-bounded data-egress profile for location and similarly sensitive data. The central problem is that permission to access data locally does not necessarily establish authority to externalize the same data at its highest available precision. The standards surface addressed here is a Location or Data-Egress Candidate Act, precision as an authorization dimension, protected validation, scoped non-bearer finality authority, and an egress Finality Sink capable of releasing exact, reduced, delayed, randomized, regional, or no data according to the authorized scope.

Long-Felt Need and Precise-Location Security Motivation

FROM ACCESS SECURITY TO CONSEQUENCE SECURITY The need for execution-finality control does not arise because authentication, encryption, access control, application permissions, sandboxing, policy engines, or existing cybersecurity systems have ceased to be useful. Rather, the computing environment has changed around them. Traditional security controls primarily answer questions such as: Who may enter? Who may access this system? Who may read this information? Which application has permission? Is this device authenticated? Is this network function trusted? Is this process permitted to invoke this API? These remain important questions. Execution-finality security addresses a later and technically different question: Should this particular operation be permitted to become an actual consequence, in this state, for this purpose, at this destination, at this precision, under this policy and jurisdiction, at this moment? This distinction becomes increasingly important as software evolves from human-directed applications into interconnected, autonomous, AI-mediated systems. The security problem has therefore moved from controlling only access to controlling the transition: COMPUTATION to CONSEQUENCE.

WHY THIS LAYER WAS LESS NECESSARY A DECADE AGO A decade ago, the majority of deployed AI systems were not autonomous economic or infrastructure actors. Most systems produced informational outputs that still required another application or person to convert them into consequence. The recommendation did not itself make the payment. The prediction did not itself control the satellite. The classification did not itself alter the telecommunications network. The generated text did not normally invoke tools, operate a browser, execute a shell command, write enterprise memory, call another autonomous agent, transfer money, or modify a physical system. Accordingly, authentication, operating-system permissions, application-layer security, human review, network access controls, and conventional authorization frequently remained practical final barriers. The AI era changes this architecture. An autonomous system can now move through a chain such as: User Instruction AI Reasoning Tool Selection External API Another Agent Database Network Financial System Physical Device without necessarily returning to a human-controlled decision point before each real-world consequence. The missing boundary is therefore not another model-output filter. It is a boundary at which the system asks: "Even though this operation has been generated and upstream-approved, is it authorized to become effective now?"

PRECISE GPS AS A SECURITY PROBLEM, NOT MERELY A PRIVACY SETTING Precise GPS is one of the clearest examples of why conventional permission models are becoming insufficient. Historically, mobile operating systems commonly framed location as an application permission. The security question was approximately: "May Application A access the user's location?" The AI-era question needs to become more precise: "May Application A, or one of its SDKs, agents, analytics components, tools, or external processors, release this exact level of location precision to Recipient B, for Purpose C, in Jurisdiction D, at Time E?" Those are not equivalent questions. ENISA's mobile-application privacy work already recognized the importance of data minimisation and specifically stated that an application should not store an exact location point where a generic location area is sufficient for its functionality. That principle becomes substantially more important when the recipient may itself be an AI system capable of combining location with many other sources. Accordingly: permission to collect precise GPS is not unrestricted authority to externalize precise GPS.

HOW AI CAN INFER A SENSITIVE FACILITY WITHOUT A DATABASE BREACH Consider a hypothetical scenario. No application contains a field stating: "Secret Laboratory X is located here." No attacker steals a classified database. Instead, several applications or services obtain ordinary data for apparently legitimate purposes. One application observes device location. Another records exercise or mobility patterns. Another records periodic weather-location requests. An enterprise application generates ordinary working-hour telemetry. A mapping service provides public road and land-use information. Individual records may appear harmless. An AI inference system can nevertheless identify that: a particular set of devices repeatedly converges on the same geographic area; those devices belong to people who otherwise travel from different residential locations; the convergence occurs primarily during working hours; the location is absent from ordinary public business listings; movement patterns show controlled entrance and exit points; the same devices repeatedly travel between the location and known research, defence, technology, industrial, or government areas; and the temporal pattern persists for months. No individual GPS record identifies a sensitive laboratory. The sensitive conclusion emerges from correlation. Conceptually: Ordinary GPS records + timestamps + mobility histories + public maps + device relationships + other low-sensitivity metadata | v AI correlation and clustering | v repeated-location pattern | v relationship and activity inference | v possible identification of a sensitive facility or operational function This is an important change in security framing. The question is no longer only: "Was secret information stolen?" It is also: "Did individually ordinary disclosures collectively make the secret inferable?" That is why indiscriminate release of precise coordinates becomes an intelligence-security problem in addition to a conventional privacy problem.

NATO STRATEGIC COMMUNICATIONS CENTRE OF EXCELLENCE The concern is not theoretical. Research published by the NATO Strategic Communications Centre of Excellence has examined IoT-generated data and specifically discussed fitness devices and tracking applications that expose geolocation information. Its case-study material describes how location information associated with ordinary fitness activity could reveal activity linked to sensitive military locations. The NATO StratCom CoE material notes that researchers were able to determine geolocation associated with sensitive military bases from such consumer-generated data. The security lesson is broader than any particular product or company. The relevant chain is: ordinary consumer activity | v precise geolocation records | v aggregation | v pattern recognition | v operationally significant intelligence A person recording an exercise route may never intend to disclose military infrastructure. Yet the aggregate consequence may reveal information far beyond the purpose for which the coordinate was originally generated. A single GPS coordinate may appear harmless. Thousands of coordinates, timestamps, routes, recurring locations, and behavioral records may expose: sensitive facilities; operational routines; personnel movement; regular working locations; relationships between locations; and other information useful for intelligence analysis. The security consequence therefore arises from aggregation and inference rather than necessarily from unauthorized initial collection.

REAL-WORLD FITNESS-TRACKING LOCATION CASE A widely reported location-tracking incident beginning in 2018 demonstrated that aggregated exercise-location data created by ordinary consumer activity could expose patterns around military installations and other sensitive locations. The important point for this document is not the identity of the application. The important technical fact is that individuals could legitimately generate location information for one benign purpose, while subsequent aggregation produced a security consequence very different from that original purpose. The existence of user permission therefore did not eliminate the downstream intelligence risk. This demonstrates why: DATA COLLECTION AUTHORITY must be distinguished from: DATA-RELEASE AUTHORITY and why: PRECISE LOCATION ACCESS must be distinguished from: PRECISE LOCATION FINALITY.

WHY AI MAKES THE LOCATION PROBLEM MORE SERIOUS The underlying possibility of correlating location information existed before modern generative and agentic AI. What has changed is the economics of inference. Large-scale AI systems can automate: clustering; temporal correlation; relationship discovery; mobility analysis; anomaly identification; multisource fusion; semantic interpretation; pattern comparison; continuous surveillance analysis; and inference across previously disconnected datasets. A task that once required skilled analysts manually examining multiple sources can increasingly be performed automatically across very large datasets. Modern AI can also continuously update its inference when new information arrives. This changes the risk from occasional specialist analysis to potentially continuous machine-scale analysis. The important privacy and security property of a data item can therefore no longer always be determined by inspecting that item in isolation. An apparently low-risk GPS observation may become highly sensitive when combined with hundreds of thousands of other observations. This creates what may be called an inference-finality problem: the security significance of a disclosure may depend not only on the disclosed value, but also on what that value enables a downstream machine to infer.

PRECISE LOCATION SHOULD NOT BE RELEASED TO EVERY APPLICATION The resulting design rule should therefore be straightforward: Not every application requires precise GPS. Not every SDK requires precise GPS. Not every analytics service requires precise GPS. Not every AI agent requires precise GPS. Not every foreign endpoint requires precise GPS. Not every cloud processor requires precise GPS. Not every legitimate purpose requires precise GPS. Where a lower-precision representation is sufficient, the higher-precision representation should remain protected. The applicable operating system, network, enterprise environment, or protected infrastructure can therefore distinguish among: EXACT GPS HIGH-PRECISION LOCATION GRID LOCATION GEOHASH PREFIX CITY REGION DELAYED LOCATION RANDOMIZED LOCATION NO LOCATION The applicable rule should be determined by the legitimate purpose and the governing authorization state, rather than by the mere fact that an application requested the most precise value available.

JURISDICTION-NEUTRAL REGULATORY AND SOVEREIGN ENFORCEMENT Location and data-protection rules vary between jurisdictions. This architecture therefore does not attempt to define whether the applicable legal rule should be American, European, Chinese, Indian, or another national or regional rule. Instead, the Protected Enforcement Domain may consume the policy applicable to the relevant jurisdiction. For example: Candidate Act: release precise location Application: App A Purpose: weather information Requested Precision: exact latitude and longitude Recipient: Service B Destination Jurisdiction: Jurisdiction Y Applicable Policy: Policy Epoch 481 The Protected Enforcement Domain may determine: exact GPS: NOT REQUIRED city-level location: SUFFICIENT authorized effect: CITY ONLY The resulting finality authority is therefore scoped to city-level disclosure. If the application subsequently attempts to transmit exact coordinates, the Finality Sink detects a precision mismatch and the Candidate Act remains non-effective. Different sovereign jurisdictions can apply different policy rules while using the same technical enforcement architecture. Thus: USA policy may produce one scoped decision. EU policy may produce another. China may impose another applicable boundary. India or another jurisdiction may impose another. The protocol itself need not decide the law. Its role is to prevent the selected lawful or authorized policy from becoming merely advisory once software attempts effectuation.

EUROPEAN COMMISSION — DATA MINIMISATION AND PROTECTION BY DEFAULT European Commission GDPR guidance states that data-protection principles should be implemented through technical and organizational measures from the design stage and that, by default, only data necessary for the intended purpose should be processed and accessibility should be limited. The Commission's GDPR guidance also describes data minimisation as requiring personal data to be adequate, relevant, and limited to what is necessary for the purpose. This provides an important policy context for precise-location enforcement. If a service requires only regional location, there is no technical reason for the final consequence to automatically contain centimetre-level, metre-level, or otherwise unnecessarily precise coordinates merely because the device possesses them. Execution finality provides a possible technical mechanism for moving this principle closer to the actual disclosure boundary. Instead of merely stating: "collect only necessary data," the protected system can enforce: "release only the authorized representation at the Finality Sink."

ENISA — LOCATION MINIMISATION AND MOBILE SECURITY ENISA has examined mobile-application privacy and security for many years. Its mobile privacy guidance identifies excessive collection and sharing arising from unnecessary sensor activation and third-party libraries as privacy risks. Significantly, its data-minimisation guidance gives the example that an application should not store the exact location point where a generic location area is sufficient. ENISA has also previously highlighted accidental disclosure of sensitive information through GPS data and the need to scrutinize whether a mobile application's requested permissions are genuinely necessary. These principles pre-date modern agentic AI. AI makes their technical enforcement more important because the downstream recipient may no longer be a simple database. It may be an inference system capable of reconstructing sensitive relationships from data fragments. The security question therefore evolves from: "Does this app have location permission?" to: "Is this application, component, recipient, destination, purpose, jurisdiction, and requested precision authorized for this particular location release?"

EXECUTION-FINALITY RESPONSE TO THE GPS AND 6G PROBLEM The proposed architecture treats a precise-location release as a Candidate Act. For example: Application or AI obtains location locally | v Precise coordinates remain inside protected domain | v Application / SDK / AI proposes external disclosure | v LOCATION-RELEASE CANDIDATE ACT | v NON-EFFECTIVE STATE | v Protected Enforcement Domain | +-- requesting application identity +-- requesting component / agent identity +-- purpose +-- recipient +-- destination +-- jurisdiction +-- regulatory / sovereign policy +-- required precision +-- user authorization +-- policy epoch +-- revocation state +-- cumulative disclosure state +-- Finality Sink identity | v Protected validation evidence | v Scoped non-bearer finality authority | v DATA-EGRESS FINALITY SINK | +-- exact GPS permitted | +-- coarse representation permitted | `-- disclosure denied

EXAMPLE OF PRECISION-BOUNDED ENFORCEMENT Assume an AI assistant receives the instruction: "Find pharmacies near me." The device possesses highly precise location information. The AI does not necessarily require those exact coordinates to leave the device. The PED may evaluate: Purpose: nearby pharmacy discovery Requested Precision: exact GPS Necessary Precision: city/local area Destination: external discovery service Jurisdiction: permitted Decision: exact GPS denied coarse locality allowed The external service therefore receives: Balasore, Odisha rather than an exact coordinate. The AI can still perform the requested task. Privacy and security are preserved because computation was allowed while unnecessary precision was not externalized. The important principle is: AI UTILITY DOES NOT REQUIRE UNRESTRICTED DATA AUTHORITY.

APPLICATION TO DIFFERENT SOVEREIGN JURISDICTIONS The same mechanism can enforce different policies without requiring one global privacy rule. For example: United States deployment: apply applicable U.S. legal, sectoral, enterprise, and user policy. European deployment: apply applicable EU and Member-State rules, purpose limitation, minimisation, and authorization state. China deployment: apply the applicable national localization, transfer, security, and authorization policies. India deployment: apply applicable Indian policy, sectoral requirements, enterprise rules, and user authorization. Other jurisdictions: apply their corresponding policy and regulatory state. The protected-finality protocol does not itself decide which rule is legally correct. It provides the enforcement mechanism by which the selected rule can remain technically binding at the point of consequence.

RESULTING SECURITY PRINCIPLES The long-felt need can therefore be summarized through the following distinctions: AUTHENTICATION IS NOT FINALITY. APPLICATION PERMISSION IS NOT FINALITY. MODEL APPROVAL IS NOT FINALITY. NETWORK AUTHENTICATION IS NOT FINALITY. DATA ACCESS IS NOT DATA-EXPORT AUTHORITY. LOCATION ACCESS IS NOT PRECISE-LOCATION RELEASE AUTHORITY. TOOL SELECTION IS NOT TOOL-EFFECTUATION AUTHORITY. AI INFERENCE IS NOT EXTERNAL-ACTION AUTHORITY. 6G CONNECTIVITY IS NOT AUTHORITY FOR EVERY NETWORK CONSEQUENCE. COMPUTATION IS NOT AUTHORITY.

CONCLUSION OF THE LONG-FELT NEED The missing security control is therefore not another generic permission mechanism. The long-felt need is for a pre-effectuation, fail-closed security boundary capable of determining whether an already generated, computed, authenticated, routed, delegated, or upstream-approved operation is permitted to cross into real consequence. This becomes particularly important because modern AI can reconstruct sensitive information from ordinary data without a conventional breach, while upcoming IMT-2030/6G infrastructure is expected to increase connectivity, AI integration, sensing capability, positioning precision, and machine autonomy. In such an environment, allowing every application or AI component to obtain and externalize the most precise available information would progressively undermine both privacy and national-security assumptions. The appropriate security model is therefore not: "the application has GPS permission, therefore exact GPS may be released." It is: "the system possesses exact GPS, but exact GPS remains non-effective for external disclosure until the particular recipient, purpose, precision, destination, jurisdiction, policy state, and Finality Sink have been verified." The proposed execution-finality architecture supplies that missing control: Candidate Act to Non-Effective State to Protected Enforcement Domain validation to Protected Validation Evidence to Scoped Non-Bearer Finality Authority to Independent Finality Sink Verification to only the permitted consequence. The objective is not to prevent AI, 6G, sensing, autonomous agents, or advanced applications from using data. The objective is to ensure that increasing intelligence does not automatically become increasing authority. The final principle is therefore: COMPUTATION IS NOT AUTHORITY. AND IN THE AI AND 6G ERA: THE ABILITY TO INFER PRECISE INFORMATION MUST NOT AUTOMATICALLY CREATE THE AUTHORITY TO DISCLOSE OR ACT UPON IT.

Long-Felt Need, Data Sovereignty and Precise-Location Finality

Problem Statement Modern applications no longer operate as isolated software processes. A single application may interact with operating-system services, third-party SDKs, advertising libraries, analytics systems, cloud synchronization services, AI agents, browser components, APIs, telemetry systems, and remote processing infrastructure. A user may legitimately authorize an application to obtain location information for a particular function. That authorization, however, should not automatically create unrestricted authority to disclose exact latitude and longitude to every downstream component or destination. The distinction is fundamental: Permission to access location data is not authority to export precise location data. Existing application-permission systems commonly answer an upstream question such as whether an application may access location information. They do not necessarily enforce a separate authorization decision at the exact boundary where precise location data is uploaded, synchronized, logged, transmitted to an analytics service, provided to an AI agent, or exported to another jurisdiction. The present architecture addresses that missing boundary.

Why Precise GPS Requires a Separate Finality Decision Precise GPS coordinates are materially different from many ordinary application attributes. A single coordinate may appear innocuous. Repeated coordinates, timestamps, device identifiers, movement histories, and related telemetry can collectively expose substantially more information than was apparent when each individual measurement was generated. Repeated precise-location disclosure can permit inference of, for example: • a person's home or workplace; • repeated travel routes; • medical or other sensitive visits; • associations between individuals; • operational routines; • protected-person movements; • sensitive facilities or infrastructure; • population movement patterns; and • other relationships that can be reconstructed through aggregation or AI-assisted inference. The disclosed architecture therefore treats precision itself as an authorization dimension. Exact GPS, city-level location, region-level location, delayed location, randomized location, grid-cell location, and other coarse representations need not receive identical authorization treatment. Your specification expressly identifies these risks and the use of reduced representations when exact coordinates are not authorized.

The Problem Is Not Solved Merely by Asking for User Permission A conventional permission may say: "Allow this application to use your location?" That decision is too broad for increasingly complex application and AI environments. A more complete technical decision is: "May this specific application, for this specific purpose, at this time, disclose this precision of location data to this specific destination, processor and jurisdiction?" These are different questions. For example, a navigation application may legitimately require precise coordinates locally to calculate a route. That does not necessarily mean an embedded advertising SDK requires the same coordinates. Similarly, an emergency-service function may require exact coordinates, while a weather application may require only a city or region. An AI assistant may require approximate location to answer "find restaurants near me," while there may be no technical necessity for it to transmit permanent exact coordinates to an unrelated analytics endpoint. Accordingly, the architecture separates: data-access authority from data-effectuation or export authority.

Long-Felt Need The broader long-felt technical problem is a gap between policy and consequence. AI-safety frameworks, privacy rules, application permissions, data-protection policies, network-access controls, cybersecurity controls, consent mechanisms, and audit systems may establish what software is expected or permitted to do. However, they do not necessarily make an unauthorized consequence technically impossible at the final boundary. Your source frames this as the structural gap between completed computation and irreversible external consequence, including concerns arising in frontier AI, sovereign infrastructure, telecommunications, mobile applications, financial systems, and child-safety controls. In location-data systems, this gap can be expressed simply: The application may already possess the data before the system determines whether the data is permitted to leave the protected environment. That is the boundary addressed by execution finality. ________________________________________

Precise-Location Execution-Finality Model The architecture treats a proposed precise-location release as a Candidate Act. The Candidate Act does not become effective merely because: • the application has location permission; • the operating system returned a GPS measurement; • the application has network permission; • an OAuth token exists; • an SDK is installed; • an API request has been created; • an AI agent requested the information; • the destination is technically reachable; or • the application has previously transmitted location information. Instead, the attempted release remains in a Non-Effective State until the applicable protected validation succeeds. Your existing disclosure specifically states that ordinary location, file, network, OAuth, API, cookie, or synchronization privileges should not automatically become authority for foreign or otherwise non-permitted export.

Candidate Location-Release Act A Candidate Act for location disclosure may contain or reference: Candidate Act: act_type = LOCATION_RELEASE application_id = requesting application component_id = SDK/agent/service where applicable purpose = declared permitted purpose requested_precision = EXACT / COARSE / REGION / OTHER destination = intended endpoint jurisdiction = intended processing jurisdiction user_state = current authorization state policy_epoch = current policy version revocation_epoch = current revocation state data_class = LOCATION sink_id = applicable Finality Sink The above is an IETF-oriented representation of predicates already identified in your specification: destination identity, cloud region, endpoint identity, jurisdiction, purpose, authorization state, policy epoch, revocation epoch, cumulative export state, data class, precision level, and Finality Sink identity. ________________________________________

Protected Enforcement Domain Decision The Protected Enforcement Domain (PED) evaluates whether the requested location consequence is authorized. The PED may evaluate: 1. Application identity Which application is requesting the information? 2. Component identity Is the request actually being made by the application itself, an embedded SDK, an AI agent, analytics software, or another delegated component? 3. Purpose Why is precise location required?

Precision requirement Is exact GPS technically necessary for that purpose?

Destination Where will the data be transmitted?

Jurisdiction Where will the recipient process or store it?

Recipient identity Is the destination the authorized service or an unrelated processor?

Current user authorization Is the authorization still valid?

Policy and revocation state Has the permission or policy changed?

Cumulative disclosure state Could individually allowed disclosures collectively create an unauthorized movement history or exposure?

Finality Sink identity Is the operation reaching the protected boundary for which the authority was issued? The PED therefore does not need to make only a binary "location allowed/location denied" decision. It may make a precision-bounded release decision. ________________________________________ 4. Precision-Bounded Location Release The architecture can support at least three outcomes. 4.1 Exact Location Allowed Example: Application: navigation service Purpose: active turn-by-turn navigation Destination: authorized navigation processor Requested precision: exact GPS Jurisdiction: permitted Current authorization: valid Result: EXACT_LOCATION_ALLOWED The PED generates the applicable protected validation evidence and scoped non-bearer finality authority. The Finality Sink verifies that authority before releasing the exact coordinates. 4.2 Exact Location Denied, Coarse Location Allowed Example: Application: weather application Purpose: local weather forecast Requested precision: exact GPS Required precision: city/region Destination: authorized weather service Result: EXACT_LOCATION_DENIED COARSE_LOCATION_ALLOWED Instead of: 20.123456, 86.123456 the Finality Sink may release only an authorized representation such as: Balasore, Odisha or a permitted grid, geohash prefix, region, delayed location, randomized location, or other reduced representation. This precise-versus-normalized behavior is already expressly contemplated by your disclosure. 4.3 Location Export Denied Example: Application: legitimate local service Embedded component: third-party analytics SDK Purpose: unrelated analytics Destination: unauthorized foreign endpoint Requested precision: exact GPS Result: DENY The exact coordinates remain inside the protected environment. No usable location consequence is released. ________________________________________ 5. Finality Sink Enforcement This is the important connection to your invention. The PED deciding "deny" is not sufficient by itself. The system must ensure that an alternate software path cannot simply ignore that decision. Therefore, the Finality Sink is positioned at or associated with the boundary at which the protected data would actually become externally usable. Your specification identifies possible location/data Finality Sinks including: • network egress interface; • operating-system data broker; • browser upload controller; • API gateway; • cloud-sync adapter; • backup service; • telemetry boundary; • analytics SDK boundary; • advertising SDK boundary; • file-system export layer; • clipboard bridge; • database export layer; and • storage-commit controller. The enforcement sequence becomes: Application / AI Agent | v Requests location operation | v Candidate Location Act | v NON-EFFECTIVE STATE | v Protected Enforcement Domain | +--> Verify application/component +--> Verify purpose +--> Verify requested precision +--> Verify destination +--> Verify jurisdiction +--> Verify authorization/revocation +--> Verify cumulative disclosure state +--> Verify Finality Sink | v Protected validation evidence | v Scoped non-bearer finality authority | v FINALITY SINK | +--> exact release | +--> normalized/coarse release | `--> deny / fail closed This is the central rule: The location value may be computable and locally available without being externally effective. That is exactly where your broader principle "computation is not authority" becomes useful for privacy and sovereign-data enforcement. ________________________________________ 6. Why This Matters More for Agentic AI Agentic AI substantially increases the importance of this distinction. An ordinary application may have a relatively fixed flow. An autonomous agent may dynamically decide to: • call a map API; • invoke another agent; • send telemetry; • upload a file; • query a cloud service; • use a browser; • invoke an MCP tool; • populate a CRM; • contact a business; • create a report; • perform background synchronization; or • combine location with other data. Therefore, simply granting an AI agent "location access" can become far broader than the original user intent. Under the execution-finality architecture, the AI agent can possess sufficient information to reason and compute, while each consequence-bearing release remains separately governed. Thus: AI access to precise GPS does not imply AI authority to export precise GPS. AI authority to use location for one tool does not imply authority to provide it to another tool. Authorization for one destination does not imply authorization for another jurisdiction. Authorization for one moment does not imply permanent authorization. Authorization for coarse location does not imply authorization for exact latitude and longitude.

Core Execution-Finality Protocol

Core Architectural Principle The execution-finality architecture separates computation, generation, routing, and upstream authorization from the authority required for an operation to become externally effective. The principal invariant is: A Candidate Act MUST NOT become consequence-bearing merely because it has been generated, computed, selected, routed, scheduled, delegated, authenticated, or permitted by an upstream application or AI system. A Candidate Act MUST remain in a Non-Effective State until: 1. a Protected Enforcement Domain validates the applicable act-specific predicates; 2. protected validation evidence is generated or committed;

scoped non-bearer finality authority is released;

an applicable Finality Sink independently verifies that authority; and

the finality authority and associated protected state are consumed, invalidated, advanced, or otherwise made unsuitable for unauthorized replay. This is a two-boundary architecture rather than a single authorization gate. The first boundary determines whether scoped finality authority may be created. The second determines whether the consequence may actually occur. 2.1 Terminology Candidate Act A Candidate Act is an operation that has been generated, selected, requested, staged, scheduled, routed, or otherwise prepared but has not yet been permitted to become consequence-bearing. Examples include: • an AI-agent tool call; • a function or API invocation; • a network transmission; • an exact-location export; • an AI-generated command; • a memory write; • a database commit; • a payment instruction; • a telecom control operation; • an RF transmission; • a satellite command; • an actuator signal; or • another externally effective operation. A Candidate Act MAY already be fully computed before finality authorization occurs. Computation alone MUST NOT cause effectuation. Non-Effective State A Non-Effective State is a state in which the Candidate Act may exist, be evaluated, staged, queued, hashed, transformed, or prepared, but the protected consequence cannot yet become externally effective. An implementation MUST preserve the Non-Effective State whenever a required element of the execution-finality chain is: • absent; • invalid; • stale; • expired; • revoked; • replayed; • already consumed; • act-mismatched; • scope-mismatched; • policy-mismatched; • jurisdiction-mismatched; • protected-state-mismatched; or • Finality-Sink-mismatched. The source architecture expressly requires failure at a load-bearing point to leave the Candidate Act non-effective rather than merely producing a warning or audit record. Protected Enforcement Domain A Protected Enforcement Domain (PED) is a protected validation environment that evaluates whether a Candidate Act is eligible to receive scoped finality authority. Depending on the implementation, the PED MAY be implemented using: • a trusted execution environment; • secure enclave; • HSM; • protected operating-system service; • protected network function; • secure controller; • confidential-computing environment; • hardware-assisted enforcement logic; or • an equivalent protected validation environment. The defining function is not a particular hardware product. The PED performs protected validation before finality authority is released. Protected Validation Evidence Protected Validation Evidence is evidence committed by the PED establishing the validation state associated with a Candidate Act. The evidence MAY take the form of a Ledger-Anchored Validation Receipt (LAVR) or an equivalent protected commitment. For this architecture, a LAVR is not required to use blockchain. It may instead use hashes, protected signatures, HSM or enclave signatures, MACs, sealed state, monotonic counters, timestamps, Merkle commitments, append-only protected records, secure audit registers, or equivalent protected mechanisms. External ledger or blockchain anchoring MAY be performed later on a cold path. The important requirement is: protected validation evidence MUST exist before, or atomically with, release of scoped finality authority. Scoped Non-Bearer Finality Authority A Scoped Non-Bearer Finality Authority is an act-specific enablement artifact or protected authorization state that permits a particular Candidate Act to cross a particular effectuation boundary only under its validated scope. It is non-bearer because possession alone MUST NOT be sufficient to cause effectuation. The Finality Sink MUST verify the relevant bindings before accepting it. The authority SHOULD be bound to applicable state including: • Candidate Act identity or digest; • protected validation evidence; • protected state; • nonce or freshness state; • policy epoch; • revocation epoch; • permitted scope; • permitted consequence class; • destination or resource where applicable; • jurisdiction where applicable; and • intended Finality Sink identity. An authority issued for one act, sink, scope, destination, precision level, policy state, or protected-state transition MUST NOT be reusable as authority for another consequence. Your specification expressly distinguishes this from conventional bearer credentials, RBAC decisions, risk scores, or upstream policy decisions. Finality Sink A Finality Sink is the functional boundary at which a Candidate Act would become externally, operationally, financially, physically, network-effectively, or sovereignty-effectively consequential. The Finality Sink is defined by its role, not by its product name or physical implementation. It MAY be implemented in hardware, firmware, software, virtualized logic, a protected operating-system service, cloud infrastructure, or a distributed enforcement arrangement. The determining question is: Does this component control the boundary at which the Candidate Act becomes effective? If yes, that component or arrangement can perform the Finality Sink role. A gateway, firewall, policy engine, or security module is not a Finality Sink merely because it performs security checks. It must control the consequence such that the consequence is technically non-completable without successful finality verification. 3. Candidate Act Descriptor A conforming implementation SHOULD create or derive a machine-verifiable descriptor for the Candidate Act before effectuation. The precise serialization format is implementation-specific in this version of the document. A conceptual descriptor may contain: Candidate-Act-ID Act-Type Act-Digest Initiating-Principal Application-ID Agent-ID Tool-or-Function-ID Purpose Resource-or-Data-Class Permitted-Scope Permitted-Consequence-Class Destination-ID Destination-Jurisdiction Data-Precision Data-Residency-State Policy-Epoch Authority-Epoch Revocation-Epoch Nonce Freshness-State Protected-State-Reference Validation-Evidence-Reference Finality-Sink-ID Effectuation-Boundary-ID Not every field is required for every domain. For example: • Data-Precision is particularly relevant to location or sensitive-data release. • Destination-Jurisdiction is relevant to cross-border data export. • Tool-or-Function-ID is important for agentic AI. • Permitted-Consequence-Class may distinguish a model response from a financial transfer or physical actuation. • Finality-Sink-ID identifies the boundary authorized to consume the authority. The underlying disclosure already contemplates binding the Candidate Act to protected state, validation evidence, nonce, freshness, policy and revocation epochs, jurisdiction state, permitted effect, and Finality Sink identity. 4. First Boundary — PED Validation The first execution-finality boundary is PED validation. Upon receiving or resolving a Candidate Act, the PED MUST keep that act non-effective while validation is performed. The PED SHOULD evaluate all predicates required by the applicable consequence class. Such predicates MAY include: authority purpose application identity agent identity tool/function scope instruction provenance destination jurisdiction data residency data precision policy epoch revocation state freshness nonce state protected state ALF or approved logic state Runtime Behavioral Descriptor permitted consequence class Finality Sink identity The PED MUST distinguish between validation success and effectuation. PED approval alone MUST NOT make the Candidate Act effective. This distinction is essential. The architecture requires: PED validation success != external consequence Instead: PED validation success | v Protected evidence commitment | v Scoped finality authority Only after the evidence commitment is made MAY the execution-finality chain advance. 4.1 PED Validation Success If validation succeeds, the PED MUST: 1. establish or confirm the applicable protected-state transition; 2. generate or commit protected validation evidence; 3. bind that evidence to the applicable Candidate Act; 4. bind the permitted scope and applicable Finality Sink; 5. release scoped non-bearer finality authority only after, or atomically with, the evidence commitment. The Candidate Act remains non-effective at this stage. The PED has authorized issuance of finality authority. It has not yet caused effectuation. 4.2 PED Validation Failure If validation fails, the PED MUST NOT release usable finality authority. The implementation SHOULD create protected denial state or denial evidence sufficient to prevent unauthorized retry, replay, rollback, substitution, or stale reuse where those risks apply. The implementation MAY: • consume or lock a nonce; • advance protected monotonic state; • generate a denial receipt; • generate a denial LAVR; • update a revocation or exposure state; • quarantine the Candidate Act; or • require renewed authorization. The Candidate Act MUST remain non-effective. Your disclosure specifically contemplates denial evidence, nonce consumption or locking, protected-state advancement, and continued non-effectuation following failed validation. 5. Protected Evidence Before Authority A defining property of this architecture is evidence-gated progression. The system MUST NOT treat a simple Boolean result such as: ALLOW = TRUE as sufficient execution-finality authority. Instead, the protected validation result is committed into protected evidence before the act can proceed. Conceptually: Candidate Act | v PED Validation | +---- FAIL ----> Denial Evidence | | | v | Remain Non-Effective | `---- PASS | v Protected Evidence | v Scoped Finality Authority This makes the validation state part of the consequence-control mechanism rather than merely part of an audit trail. A LAVR therefore represents a pre-effectuation protected commitment, not a post-event blockchain receipt.

Scoped Non-Bearer Finality Authority Following successful protected evidence commitment, the PED MAY release an Execution Handle, capability fragment, protected enablement state, or equivalent scoped non-bearer finality authority. Regardless of representation, the authority MUST be sufficiently constrained so that possession alone cannot authorize arbitrary effectuation. A conforming authority SHOULD be: Act-bound It applies only to the intended Candidate Act or Candidate Act Fragment. Evidence-bound It is associated with the protected validation evidence that caused its issuance. State-bound It reflects the relevant protected state. Scope-bound It permits only the validated consequence. Nonce- or freshness-bound It cannot be validly replayed outside the applicable freshness state. Epoch-bound It remains consistent with applicable policy, authorization, and revocation state. Sink-bound It is valid only at the intended Finality Sink. Non-bearer Copying, observing, storing, forwarding, or possessing it does not by itself create authority for effectuation. Where single-use effectuation is intended, the authority MUST be consumed, invalidated, burned, or rendered unusable before or atomically with successful effectuation. The source explicitly requires freshness, unconsumed state, revocation state, exact Candidate-Act binding, protected evidence/state binding, and intended sink binding to be verified.

Second Boundary — Independent Finality Sink Verification The second boundary is the Finality Sink. The Finality Sink MUST NOT merely trust the fact that the PED previously approved the Candidate Act. It MUST independently verify the applicable finality authority immediately before effectuation. The Finality Sink SHOULD verify, where applicable: authority validity Candidate Act identity/digest protected validation evidence protected-state reference or transition scope purpose destination jurisdiction data precision nonce freshness policy epoch revocation epoch consumption state permitted consequence class effectuation-boundary identity Finality Sink identity The Finality Sink MUST reject the Candidate Act if a required verification fails. A failed Finality Sink verification MUST NOT merely create an alert while allowing the consequence to proceed. It MUST prevent effectuation. For example: Data export failure: no protected data leaves the boundary. Payment failure: no settlement occurs. Telecom failure: no governed network consequence occurs. Satellite failure: no protected command or RF effect occurs. AI tool-call failure: the tool call remains non-effective. Location failure: exact GPS coordinates are not released. This independent sink-side verification is explicitly required by your disclosed architecture.

Successful Effectuation If Finality Sink verification succeeds, the implementation MUST ensure that the finality authority cannot be reused outside its permitted semantics. For single-use operations, consumption, invalidation, burning, or protected-state advancement SHOULD occur before or atomically with effectuation. The implementation SHOULD also create sink-side finality evidence identifying the completed protected consequence. The execution sequence is therefore: 1. Candidate Act created | 2. Candidate Act held non-effective | 3. PED validates act-specific predicates | 4. Protected validation evidence committed | 5. Scoped non-bearer finality authority released | 6. Finality Sink independently verifies authority | 7. Authority/state consumed or advanced | 8. Permitted consequence becomes effective |

Sink-side finality evidence recorded This progression closely follows the seven evidence-gated stages expressly described in the source specification. 9. Fail-Closed Requirement A conforming implementation MUST fail closed for a protected consequence when required execution-finality state cannot be verified. The following conditions SHOULD result in denial where applicable: missing authority invalid authority expired authority stale authority replayed authority revoked authority previously consumed authority Candidate Act mismatch descriptor mismatch scope mismatch purpose mismatch destination mismatch jurisdiction mismatch precision mismatch policy-epoch mismatch revocation-epoch mismatch nonce mismatch protected-state mismatch Finality Sink mismatch effectuation-boundary mismatch The important property is structural: failure prevents consequence rather than merely documenting that an unauthorized consequence occurred. This is the difference between execution finality and conventional audit-oriented control.

Precise-GPS Example The location embodiment demonstrates the protocol particularly clearly. Assume: Application: NavigationApp Authorized Purpose: turn-by-turn navigation Local Access: precise GPS permitted Attempted Secondary Recipient: AnalyticsSDK Destination: analytics.example Destination Jurisdiction: non-permitted Requested Data: 20.123456, 86.123456 The application having local GPS permission does not settle the export question. The architecture performs: NavigationApp obtains GPS locally | v AnalyticsSDK attempts transmission | v Candidate Data-Export Act | v NON-EFFECTIVE STATE | v PED | +-- Application identity +-- SDK identity +-- Purpose +-- Precise-location necessity +-- Destination +-- Jurisdiction +-- User authorization +-- Policy/revocation epoch +-- Cumulative disclosure state +-- Data-egress Finality Sink | v Decision Three results are possible. Result A — Exact GPS Permitted EXACT_LOCATION 20.123456, 86.123456 The PED commits the applicable protected evidence. A finality authority explicitly scoped to exact-location release is issued. The data-egress Finality Sink verifies it and permits the release. Result B — Exact GPS Not Permitted but Coarse Location Permitted The PED does not issue finality authority for the exact coordinates. It MAY authorize a transformed representation: COARSE_LOCATION Balasore, Odisha or: REGION Odisha or an authorized: grid cell geohash prefix randomized location delayed location regional representation The original exact coordinates remain non-effective for the external destination. Your source explicitly provides for blocking precise GPS or releasing a normalized lower-risk representation. Result C — No Location Export Permitted If the destination, purpose, jurisdiction, recipient, or authorization state is not permitted: DENY No finality authority for location release is created. The Finality Sink therefore has no valid authority to release either exact or protected location information. The export remains technically non-effective.

Why This Is Different From Ordinary App Permissions A conventional system may implement: if app_has_location_permission: location = get_precise_location() send(location) The execution-finality architecture separates these operations: if app_has_location_access: location = obtain_location_locally() candidate = create_candidate_export( data=location, purpose=purpose, destination=destination, jurisdiction=jurisdiction, requested_precision=precision ) keep_non_effective(candidate) validation = PED.validate(candidate) if validation fails: deny() evidence = PED.commit_validation_evidence(validation) authority = PED.release_scoped_finality_authority( candidate, evidence ) if FinalitySink.verify(authority, candidate) fails: deny() FinalitySink.consume(authority) release_only_permitted_effect(candidate) The difference is therefore: ACCESS PERMISSION != EXPORT AUTHORITY and: UPSTREAM ALLOW != FINAL EFFECTUATION The source makes the same structural distinction between generic policy permission and act-specific, protected-state-bound, nonce-bound, epoch-bound, scope-bound, sink-bound finality authority.

Protocol Invariant The complete Phase 2 invariant can therefore be stated as: Candidate Act | v Non-Effective State | v Protected Enforcement Domain | v Act-Specific Validation | v Protected Validation Evidence | v Scoped Non-Bearer Finality Authority | v Independent Finality Sink Verification | +------ FAILURE ------> remain non-effective | `------ SUCCESS | v authority consumed | v permitted consequence No individual element substitutes for this chain. A policy engine alone is insufficient. An app permission alone is insufficient. An access token alone is insufficient. An attestation alone is insufficient. A human approval alone is insufficient. A LAVR alone is insufficient. A Finality Sink without act-bound authority is insufficient. The execution-finality property arises because these elements remain mutually bound across the transition from computation to consequence.

Precision-Bounded Egress Profile

Embodiment B — Precise GPS and Sovereign Data Export

Principle An application MAY legitimately require precise location internally while lacking authority to transmit the same exact coordinates to every SDK, AI agent, cloud service, analytics system, advertiser, or foreign endpoint. The protocol therefore separates: LOCAL DATA ACCESS != EXTERNAL DATA RELEASE and: PRECISE GPS ACCESS != PRECISE GPS EXPORT AUTHORITY The source specifically states that general app, OAuth, API, sync, file and network permission should not automatically authorize export to a foreign or otherwise non-permitted destination.

Precision as a Finality Predicate Location precision SHOULD be capable of forming part of the Candidate Act's scope. Possible precision classes include: EXACT HIGH_PRECISION GRID GEOHASH_PREFIX CITY REGION DELAYED RANDOMIZED COARSE These are examples rather than a mandatory wire-format enumeration. The important protocol property is that authority for one precision level MUST NOT automatically imply authority for a more sensitive precision level.

Example A map application may have legitimate access to: 20.123456, 86.123456 for active navigation. An embedded analytics component attempts to transmit it externally. The operation becomes: Candidate Act: LOCATION_EXPORT Source: Navigation Application Secondary Component: Analytics SDK Precision: EXACT Destination: External Analytics Endpoint Jurisdiction: Non-Permitted Purpose: Analytics The PED may determine: Exact GPS export: DENY Regional location: ALLOW The Finality Sink therefore prevents release of the exact coordinate but MAY release an approved transformed representation. For example: Balasore, Odisha The source expressly supports withholding precise GPS while allowing city-level, regional, delayed, randomized, grid-cell or otherwise coarse representations.

Cumulative Disclosure A location implementation MAY also evaluate cumulative disclosure state. This matters because individually permissible records may collectively reveal: • movement histories; • home location; • workplace; • sensitive visits; • social relationships; • infrastructure locations; • protected-person movements; or • strategic patterns. Your source identifies repeated precise-location exports as capable of revealing movement histories, household and workplace patterns, medical-visit inferences and social graphs. Therefore: a sequence of individually small disclosures MAY require a different finality decision from a single isolated disclosure.

JSON API and Schema for Precision-Bounded Egress This section defines a concrete JSON interoperability profile for precise-location and sensitive-data release. The profile separates local access from external release and makes data precision, purpose, recipient, destination, jurisdiction, cumulative disclosure state, and egress-sink identity machine-verifiable fields.

LocationReleaseCandidate Object LocationReleaseCandidate represents an attempted externalization of location information. Exact coordinates MAY exist locally while the Candidate Act remains non-effective for external release. { "$schema": "https://json-schema.org/draft/2020-12/schema", "$id": "urn:ietf:params:json-schema:precision-egress:location-candidate:1", "title": "LocationReleaseCandidate", "type": "object", "additionalProperties": false, "required": [ "version", "object_type", "candidate_act_id", "act_type", "created_at", "expires_at", "requester", "purpose", "source_data", "requested_release", "destination", "policy_state", "freshness", "finality_sink" ], "properties": { "version": { "type": "string", "const": "1.0" }, "object_type": { "type": "string", "const": "location_release_candidate" }, "candidate_act_id": { "type": "string", "minLength": 16 }, "act_type": { "type": "string", "const": "LOCATION_RELEASE" }, "created_at": { "type": "string", "format": "date-time" }, "expires_at": { "type": "string", "format": "date-time" }, "requester": { "type": "object", "required": [ "application_id" ], "properties": { "application_id": { "type": "string" }, "component_id": { "type": "string" }, "component_type": { "type": "string", "enum": [ "APPLICATION", "SDK", "AI_AGENT", "ANALYTICS", "ADVERTISING", "BROWSER", "CLOUD_SERVICE", "SYSTEM_SERVICE", "OTHER" ] } } }, "purpose": { "type": "object", "required": [ "purpose_id", "declared_purpose" ], "properties": { "purpose_id": { "type": "string" }, "declared_purpose": { "type": "string" }, "purpose_epoch": { "type": "integer", "minimum": 0 }, "user_intent_reference": { "type": "string" } } }, "source_data": { "type": "object", "required": [ "data_class", "available_precision" ], "properties": { "data_class": { "type": "string", "enum": [ "LOCATION", "MOBILITY_TRACE", "PROXIMITY", "SENSOR_DERIVED_LOCATION" ] }, "available_precision": { "type": "string", "enum": [ "EXACT", "METER_10", "METER_100", "GRID", "GEOHASH", "CITY", "REGION", "COUNTRY" ] }, "local_only": { "type": "boolean" }, "source_reference": { "type": "string" } } }, "requested_release": { "type": "object", "required": [ "requested_precision", "fields" ], "properties": { "requested_precision": { "type": "string", "enum": [ "EXACT", "METER_10", "METER_100", "GRID", "GEOHASH", "CITY", "REGION", "COUNTRY", "NONE" ] }, "fields": { "type": "array", "items": { "type": "string" } }, "retention_seconds": { "type": "integer", "minimum": 0 }, "continuous": { "type": "boolean" } } }, "destination": { "type": "object", "required": [ "destination_id", "jurisdiction" ], "properties": { "destination_id": { "type": "string" }, "endpoint": { "type": "string" }, "recipient_id": { "type": "string" }, "processor_type": { "type": "string", "enum": [ "FIRST_PARTY", "PROCESSOR", "SDK_VENDOR", "AI_PROVIDER", "ANALYTICS", "AD_NETWORK", "PUBLIC_AUTHORITY", "OTHER" ] }, "jurisdiction": { "type": "string" }, "cloud_region": { "type": "string" } } }, "cumulative_disclosure": { "type": "object", "properties": { "window_seconds": { "type": "integer", "minimum": 0 }, "prior_release_count": { "type": "integer", "minimum": 0 }, "prior_precision_max": { "type": "string" }, "movement_history_risk": { "type": "string", "enum": [ "LOW", "MEDIUM", "HIGH", "CRITICAL" ] } } }, "policy_state": { "type": "object", "required": [ "policy_epoch", "revocation_epoch" ], "properties": { "policy_epoch": { "type": "integer", "minimum": 0 }, "authority_epoch": { "type": "integer", "minimum": 0 }, "revocation_epoch": { "type": "integer", "minimum": 0 }, "policy_profile_id": { "type": "string" }, "regulatory_profile_id": { "type": "string" } } }, "freshness": { "type": "object", "required": [ "nonce" ], "properties": { "nonce": { "type": "string", "minLength": 16 }, "sequence": { "type": "integer", "minimum": 0 }, "session_id": { "type": "string" } } }, "finality_sink": { "type": "object", "required": [ "sink_id", "sink_type" ], "properties": { "sink_id": { "type": "string" }, "sink_type": { "type": "string", "enum": [ "NETWORK_EGRESS", "OS_DATA_BROKER", "BROWSER_UPLOAD", "API_GATEWAY", "CLOUD_SYNC", "TELEMETRY", "ANALYTICS_SDK", "AD_SDK", "FILE_EXPORT", "DATABASE_EXPORT", "OTHER" ] } } } } }

Precision Decision Object The PED does not need to return a binary allow/deny result. It can authorize a lower-risk representation. The authorized_precision field is authoritative for what the Finality Sink may release. { "version": "1.0", "object_type": "precision_policy_decision", "decision_id": "ppd-cf0c49", "candidate_act_id": "loc-5c8238a4", "decision": "ALLOW_WITH_TRANSFORMATION", "requested_precision": "EXACT", "authorized_precision": "CITY", "transformation": { "type": "PRECISION_REDUCTION", "method": "CITY_LABEL", "parameters": { "country_code": "IN", "region": "Odisha", "city": "Balasore" } }, "validated_predicates": { "application_valid": true, "component_valid": true, "purpose_valid": true, "exact_precision_necessary": false, "destination_valid": true, "recipient_valid": true, "jurisdiction_valid": true, "user_authorization_valid": true, "policy_epoch_valid": true, "revocation_state_valid": true, "cumulative_disclosure_acceptable": true, "sink_binding_valid": true }, "reason_codes": [ "MINIMIZATION_REQUIRED", "EXACT_PRECISION_NOT_NECESSARY" ] }

EgressFinalityAuthority Object EgressFinalityAuthority binds the permitted release representation to the Candidate Act, destination, jurisdiction, precision ceiling, protected validation evidence, freshness state, and egress sink. An authority for CITY-level release MUST NOT authorize exact latitude and longitude. { "version": "1.0", "object_type": "egress_finality_authority", "authority_id": "efa-e71ad531", "candidate_act_id": "loc-5c8238a4", "decision_id": "ppd-cf0c49", "evidence_id": "pve-location-332", "scope": { "data_class": "LOCATION", "authorized_precision": "CITY", "permitted_fields": [ "city", "region", "country" ], "recipient_id": "weather-provider", "destination_id": "weather.example", "jurisdiction": "IN", "retention_seconds_max": 3600 }, "binding": { "candidate_act_digest": { "algorithm": "SHA-256", "value": "base64url-location-act-digest" }, "nonce": "B21C9924FF77A183", "policy_epoch": 42, "authority_epoch": 11, "revocation_epoch": 7, "finality_sink_id": "egress-sink-01", "protected_state_reference": "ped-location-state-91" }, "lifetime": { "issued_at": "2026-08-26T17:45:01Z", "expires_at": "2026-08-26T17:45:10Z", "single_use": true }, "issuer": { "ped_id": "ped-device-01", "key_id": "ped-key-location-2", "signature": "base64url-signature" } }

EgressSinkVerify Request Immediately before data leaves the protected boundary, the Egress Sink verifies both the authority and the actual outbound payload. This prevents an application from obtaining authorization for a coarse representation and then substituting exact coordinates. { "operation": "EgressSinkVerify", "request_id": "egress-req-771", "candidate_act_id": "loc-5c8238a4", "authority_id": "efa-e71ad531", "sink": { "sink_id": "egress-sink-01", "sink_type": "NETWORK_EGRESS" }, "outbound_payload": { "content_type": "application/json", "data_class": "LOCATION", "declared_precision": "CITY", "fields": { "city": "Balasore", "region": "Odisha", "country": "IN" }, "payload_digest": { "algorithm": "SHA-256", "value": "base64url-payload-digest" } }, "destination": { "destination_id": "weather.example", "endpoint": "https://weather.example/forecast", "recipient_id": "weather-provider", "jurisdiction": "IN" }, "freshness": { "nonce": "B21C9924FF77A183" } }

EgressSinkVerify Response { "operation": "EgressSinkVerify", "request_id": "egress-req-771", "decision": "ALLOW", "verification": { "authority_signature": "VALID", "candidate_act_binding": "MATCH", "data_class": "MATCH", "payload_precision": "CITY_WITHIN_AUTHORIZED_CEILING", "field_scope": "MATCH", "recipient": "MATCH", "destination": "MATCH", "jurisdiction": "MATCH", "policy_epoch": "CURRENT", "revocation_epoch": "CURRENT", "nonce": "FRESH", "consumption_state": "UNUSED", "sink_binding": "MATCH" }, "consumption": { "authority_id": "efa-e71ad531", "status": "CONSUMED", "consumed_at": "2026-08-26T17:45:02Z" }, "release": { "permitted": true, "released_precision": "CITY", "release_id": "release-881" } }

Precision-Mismatch Denial If the outbound payload contains exact coordinates while the authority permits only city-level location, the sink denies the release even if the application has local exact-location permission. { "operation": "EgressSinkVerify", "request_id": "egress-req-772", "decision": "DENY", "error": { "code": "EF_PRECISION_MISMATCH", "message": "Outbound payload is more precise than the finality authority permits.", "retryable": false }, "verification": { "authority_signature": "VALID", "authorized_precision": "CITY", "observed_payload_precision": "EXACT", "destination": "MATCH", "jurisdiction": "MATCH", "sink_binding": "MATCH" }, "release": { "permitted": false } }

Complete Exact-to-Coarse Transaction Example { "step_1_local_state": { "available_location": { "latitude": 21.494321, "longitude": 86.932145, "accuracy_meters": 4.2 }, "external_effect": "NONE" }, "step_2_candidate_act": { "candidate_act_id": "loc-5c8238a4", "requester": { "application_id": "weather-app", "component_id": "forecast-module", "component_type": "APPLICATION" }, "purpose": { "purpose_id": "local-weather", "declared_purpose": "Provide weather for the user's current area" }, "requested_release": { "requested_precision": "EXACT", "fields": [ "latitude", "longitude" ] }, "destination": { "destination_id": "weather.example", "recipient_id": "weather-provider", "jurisdiction": "IN" } }, "step_3_ped_decision": { "decision": "ALLOW_WITH_TRANSFORMATION", "authorized_precision": "CITY", "reason": "Exact coordinates are not necessary for the declared purpose." }, "step_4_authorized_payload": { "city": "Balasore", "region": "Odisha", "country": "IN" }, "step_5_sink_verification": { "decision": "ALLOW", "exact_coordinates_released": false, "authority_consumed": true } }

Cumulative Disclosure Extension An implementation MAY incorporate cumulative disclosure state so that repeated individually acceptable releases do not automatically create an unauthorized movement history. This state is policy-dependent and can cause a later request to be downgraded, delayed, randomized, rate-limited, or denied. { "cumulative_disclosure": { "subject_scope": "device-local-pseudonymous-subject", "window_seconds": 86400, "prior_release_count": 144, "prior_precision_max": "METER_100", "distinct_destinations": 6, "movement_history_risk": "HIGH", "policy_action": "DOWNGRADE_TO_REGION" } }

Protocol Operation, Verification, and Failure Handling

Requirements Language The key words "MUST", "MUST NOT", "REQUIRED", "SHOULD", "SHOULD NOT", "MAY", and "OPTIONAL" in this document are to be interpreted as normative requirements when, and only when, they appear in all capitals. The execution-finality protocol is based on one mandatory invariant: Failure to establish current finality authority MUST NOT be converted into permission to effectuate.

End-to-End Protocol Workflow A conforming implementation follows the following logical sequence: Act Generator PED Finality Sink | | | |-- Candidate Act ---->| | | | | | NON-EFFECTIVE | | |<---------------------| | | | | | |-- validate predicates | | |-- verify protected state| | |-- verify nonce/epochs | | | | | | [DENY] | | |---- denial evidence ---->| | | | | | Candidate remains | | | NON-EFFECTIVE | | | | | | [ALLOW] | | |-- commit evidence | | |-- create scoped | | | finality authority | | | | |---------------------- finality authority ------>| | | | verify act | | verify scope | | verify nonce | | verify state | | verify epochs | | verify sink | | | | [FAIL] | | no effect | | | | [PASS] | | consume | | authority | | | |<---------------- permitted consequence ---------| The source architecture expressly requires the Candidate Act to remain non-effective, protected evidence to be committed before or atomically with authority issuance, and independent Finality Sink verification before effectuation.

Candidate Act Construction Before a protected consequence is attempted, the implementation SHOULD construct a Candidate Act Descriptor. A minimal logical representation is: CandidateAct { version candidate_act_id act_type act_digest initiator_id application_id agent_id tool_id purpose permitted_scope consequence_class destination_id jurisdiction data_class data_precision nonce creation_time expiration_time policy_epoch authority_epoch revocation_epoch protected_state_ref finality_sink_id } Fields MAY be omitted where they do not apply to the consequence class. However, every implementation MUST have sufficient binding information to prevent authority issued for one Candidate Act from being substituted, redirected, replayed, or used at another Finality Sink.

Candidate Act Digest A Candidate Act SHOULD have a stable digest calculated over its load-bearing attributes. Conceptually: ActDigest = HASH( canonical_act_type || canonical_effect_parameters || purpose || destination || jurisdiction || permitted_scope || consequence_class || finality_sink_id ) The exact canonicalization and hash format are outside the scope of this version. However, implementations MUST ensure that changing a load-bearing attribute causes the previously issued authority to fail verification. For example, changing: Exact GPS -> coarse GPS Recipient A -> Recipient B Jurisdiction X -> Jurisdiction Y $50 -> $5,000 Tool A -> Tool B Satellite 1 -> Satellite 2 Sink A -> Sink B MUST NOT preserve authority unless the changed operation is separately authorized.

PED Processing The PED receives or reconstructs the Candidate Act Descriptor and performs protected validation. A simplified procedure is: function PED_VALIDATE(candidate): if candidate is malformed: return DENY(MALFORMED_ACT) if candidate.nonce is not fresh: return DENY(REPLAY_OR_STALE) if candidate.policy_epoch != current_policy_epoch: return DENY(POLICY_EPOCH_MISMATCH) if candidate.revocation_epoch != current_revocation_epoch: return DENY(REVOCATION_STATE_MISMATCH) if candidate.finality_sink_id is not authorized: return DENY(SINK_NOT_AUTHORIZED) if protected_state does not permit candidate: return DENY(PROTECTED_STATE_DENIAL) if purpose is not permitted: return DENY(PURPOSE_DENIAL) if jurisdiction is not permitted: return DENY(JURISDICTION_DENIAL) if requested scope exceeds allowed scope: return DENY(SCOPE_DENIAL) if additional consequence-specific checks fail: return DENY(CONSEQUENCE_POLICY_DENIAL) evidence = COMMIT_PROTECTED_VALIDATION(candidate) authority = ISSUE_SCOPED_FINALITY_AUTHORITY( candidate, evidence, current_protected_state ) return ALLOW(authority) The pseudocode is illustrative. An implementation MAY evaluate additional predicates including ALF, Runtime Behavioral Descriptor, instruction provenance, neural-state integrity, data residency, accelerator identity, mission state, financial state, recipient state, or cumulative disclosure state. The disclosed architecture requires the PED to check act-specific predicates while the Candidate Act remains non-effective.

Protected Validation Evidence Upon successful validation, the PED MUST commit protected validation evidence before, or atomically with, issuance of usable finality authority. A conceptual evidence object may contain: ValidationEvidence { evidence_id candidate_act_digest decision = ALLOW protected_state_before protected_state_after policy_epoch authority_epoch revocation_epoch nonce permitted_scope consequence_class finality_sink_id validation_time validation_domain_id integrity_protection } The evidence MAY be a LAVR or an equivalent protected commitment. External blockchain finality is NOT required for the hot path. The source explicitly permits local receipts, protected hash-chain entries, TEE/HSM receipts, secure-register entries, and equivalent protected commitments, with slower external anchoring occurring later.

Scoped Finality Authority A finality authority MAY be represented as an Execution Handle, protected capability, capability fragment, protected state reference, or equivalent bounded artifact. A conceptual structure is: FinalityAuthority { authority_id candidate_act_digest validation_evidence_ref permitted_scope consequence_class destination_id jurisdiction data_precision nonce policy_epoch authority_epoch revocation_epoch protected_state_ref finality_sink_id issued_at expires_at single_use = true integrity_protection } The artifact MUST NOT operate as a generic bearer token. Merely copying the authority MUST NOT permit another process, sink, destination, jurisdiction, or Candidate Act to use it successfully.

Finality Sink Verification Algorithm Immediately before effectuation, the Finality Sink MUST independently verify the authority. Illustrative logic: function FINALITY_SINK_VERIFY(candidate, authority): if authority is absent: return DENY(NO_FINALITY_AUTHORITY) if authority integrity check fails: return DENY(INVALID_AUTHORITY) if HASH(candidate) != authority.candidate_act_digest: return DENY(ACT_MISMATCH) if authority.finality_sink_id != THIS_SINK: return DENY(SINK_MISMATCH) if authority is expired: return DENY(STALE_AUTHORITY) if authority is already consumed: return DENY(AUTHORITY_ALREADY_USED) if authority.nonce is not current: return DENY(NONCE_FAILURE) if authority.policy_epoch != current_policy_epoch: return DENY(POLICY_EPOCH_MISMATCH) if authority.revocation_epoch != current_revocation_epoch: return DENY(REVOKED_OR_STALE) if protected_state does not match: return DENY(PROTECTED_STATE_MISMATCH) if candidate scope exceeds authority scope: return DENY(SCOPE_MISMATCH) if candidate destination != authorized destination: return DENY(DESTINATION_MISMATCH) if candidate jurisdiction != authorized jurisdiction: return DENY(JURISDICTION_MISMATCH) if candidate data precision exceeds authorized precision: return DENY(PRECISION_MISMATCH) ATOMICALLY: consume(authority) advance_replay_state() permit_effectuation() return EFFECTUATED The source expressly describes verification of capability/evidence presence, sink identity, descriptor and fragment hashes, nonce freshness and consumption, policy and revocation epochs, purpose, jurisdiction, scope, protected state, and permitted consequence class.

Authority Consumption and Replay Prevention For a single-use operation, successful authority consumption SHOULD be atomic with the state transition that enables effectuation. An implementation MUST prevent the sequence: verify authority | v effectuate | v attacker replays same authority | v effectuate again Instead: verify | v reserve / consume authority | v advance protected replay state | v effectuate once Replay protection MAY use: • nonce consumption; • monotonic counters; • sequence numbers; • protected consumed flags; • protected state advancement; • short expiration windows; • epoch advancement; or • an equivalent anti-replay mechanism. The source requires capability consumption or protected-state advancement before or atomically with effectuation and describes nonce consumption as part of replay prevention.

Revocation A previously issued authority MUST NOT override a newer revocation state. If an authority was created under: Revocation-Epoch = 51 and the applicable protected state has advanced to: Revocation-Epoch = 52 the older authority SHOULD fail unless an explicitly defined policy permits continued validity. Conceptually: if authority.revocation_epoch < protected.revocation_epoch: DENY Revocation SHOULD be checked at the Finality Sink, not merely when the authority was originally created. This prevents: PED approves at T1 | v authorization revoked at T2 | v old authority used at T3 from automatically becoming an effective consequence.

Policy Epoch Changes The same principle applies to policy. An authority issued before a material policy change SHOULD NOT silently inherit authority under the new policy state. Examples include: • exact location became prohibited for the destination; • an AI tool was revoked; • a telecom action was removed from the authorized scope; • a satellite entered a different mission phase; • a counterparty became blocked; • a model version was withdrawn; • a data residency rule changed; or • a child-safety policy changed. The sink SHOULD therefore compare current policy state with the policy epoch bound to the authority.

Location-Precision Downgrade For sensitive data, denial need not always mean that no useful operation can proceed. The PED MAY return a bounded downgrade. Example: Requested: PRECISE_GPS Result: PRECISE_GPS = DENY CITY_LEVEL = ALLOW The Candidate Act MUST then be transformed into the permitted representation. A new or correspondingly bound Candidate Act SHOULD represent the authorized output: Original: Latitude = 20.123456 Longitude = 86.123456 Permitted: Region = Balasore, Odisha The Finality Sink MUST ensure that the exact coordinate does not escape through another field, metadata element, URL parameter, telemetry field, side channel, or alternate controlled path subject to the same policy. The source expressly contemplates blocking precise GPS while releasing an authorized lower-risk representation.

Hot-Path and Cold-Path Processing Not every Candidate Act requires identical validation cost. The architecture therefore MAY support a hot path and a cold path.

Hot Path The hot path is suitable for: • frequent; • previously bounded; • low-risk; • latency-sensitive; or • pre-authorized classes of Candidate Acts. The hot path MAY rely on: local protected state fresh nonce state cached policy short-lived authority pre-bound sink identity known destination current revocation epoch bounded scope local protected evidence A hot-path operation MUST still perform Finality Sink verification. "Hot path" does not mean "skip finality."

Cold Path A Candidate Act SHOULD be escalated to a cold or higher-assurance path where it involves, for example: • high-value financial settlement; • exact location export; • high-value sovereign data export; • cross-jurisdiction processing; • satellite RF emission; • payload control; • cryptographic-key release; • actuator control; • unusual agent behavior; • new or unknown tool delegation; • changed destination; • uncertain jurisdiction; • policy anomaly; • missing cached state; or • high-consequence infrastructure operation. The cold path MAY require: • remote authority resolution; • fresh attestation; • deeper ALF/RBD validation; • sovereign approval; • enterprise approval; • regulatory checks; • multi-party approval; • consequence simulation; • human review; or • additional proof material. The source expressly identifies exact-location export, financial settlement, satellite RF, actuator control and high-value data egress as candidates for stronger validation.

Hot-to-Cold Escalation A Candidate Act MUST NOT obtain default permission merely because the hot path cannot make a decision. For example: cache miss policy miss revocation uncertainty network failure unknown destination unknown jurisdiction changed sink changed tool runtime anomaly SHOULD result in: HOT PATH | v cannot prove eligibility | v COLD PATH not: HOT PATH | v cannot verify | v ALLOW The source is explicit that timeout, cache miss, policy miss, uncertainty, or network failure does not create default authority.

Cold-to-Hot Authority Refresh A successful cold-path evaluation MAY establish a bounded policy envelope for subsequent low-latency operations. For example, a cold path may establish: Approved Model: model-A Approved Tool: map-search Approved Purpose: local-service-discovery Maximum Location Precision: CITY Destination: endpoint-X Jurisdiction: permitted Policy-Epoch: 203 Revocation-Epoch: 77 Finality-Sink: network-egress-4 Valid-Until: short bounded interval Later Candidate Acts within the exact envelope MAY use faster local validation. If any bound condition changes, the system SHOULD escalate again. The source expressly contemplates cold-path generation of protected hot-path policy objects while requiring freshness, scope, revocation and sink binding to remain valid.

Latency Model Execution finality SHOULD be implementable without requiring a remote ledger round trip for every operation. Representative embodiments in the source describe: • sub-10-ms operation for cached-policy paths; • approximately 1-5 ms in some hardware-adjacent paths; • approximately 1-20 ms for some mobile/browser/application-gateway paths; and • higher delays for stronger attestation, multi-party or regulatory validation. These figures are implementation examples, not protocol requirements. The important architectural separation is: HOT PATH --------- validate check nonce check protected state commit local protected evidence bind sink release scoped authority verify at sink effectuate COLD / AUDIT PATH ----------------- external ledger anchoring transparency log proof aggregation regulatory reporting enterprise synchronization long-term audit The cold path MUST NOT retroactively authorize an act that was not valid when effectuation occurred. External anchoring can strengthen later evidence, but it does not replace the pre-effectuation chain.

Failure and Denial Codes This section defines an IETF-draft-level proposed error taxonomy derived from the failure conditions in the source. The symbolic names below are protocol-design suggestions; the source describes the underlying failure conditions but does not prescribe these exact wire codes. A conforming implementation MAY expose equivalent numeric or symbolic codes. EF-001 MALFORMED_ACT EF-002 NO_FINALITY_AUTHORITY EF-003 INVALID_AUTHORITY EF-004 STALE_AUTHORITY EF-005 AUTHORITY_ALREADY_USED EF-006 REPLAY_DETECTED EF-007 NONCE_FAILURE EF-010 ACT_MISMATCH EF-011 DESCRIPTOR_MISMATCH EF-012 SCOPE_MISMATCH EF-013 PURPOSE_MISMATCH EF-014 CONSEQUENCE_CLASS_MISMATCH EF-020 DESTINATION_MISMATCH EF-021 JURISDICTION_MISMATCH EF-022 DATA_RESIDENCY_MISMATCH EF-023 PRECISION_MISMATCH EF-030 POLICY_EPOCH_MISMATCH EF-031 REVOCATION_STATE_MISMATCH EF-032 PROTECTED_STATE_MISMATCH EF-040 SINK_MISMATCH EF-041 EFFECTUATION_BOUNDARY_MISMATCH EF-050 ATTESTATION_FAILURE EF-051 ALF_MISMATCH EF-052 RUNTIME_BEHAVIOR_MISMATCH EF-053 INSTRUCTION_PROVENANCE_FAILURE EF-060 VALIDATION_TIMEOUT EF-061 AUTHORITY_UNCERTAIN EF-062 POLICY_UNAVAILABLE EF-063 JURISDICTION_UNRESOLVED EF-070 ESCALATION_REQUIRED EF-071 HUMAN_REVIEW_REQUIRED EF-080 FAIL_CLOSED The source identifies absence, staleness, revocation, replay, prior consumption, descriptor, nonce, policy, jurisdiction, protected-state, scope and Finality-Sink mismatch as conditions requiring the Candidate Act to remain non-effective.

Denial Behavior A denial response MAY specify an allowed remediation. For example: EF-023 PRECISION_MISMATCH Action: DOWNGRADE_TO_CITY or: EF-063 JURISDICTION_UNRESOLVED Action: ESCALATE_TO_COLD_PATH or: EF-031 REVOCATION_STATE_MISMATCH Action: REQUIRE_FRESH_AUTHORITY or: EF-051 ALF_MISMATCH Action: QUARANTINE Permitted denial actions MAY include: • deny; • delay; • downgrade; • redact; • suppress; • quarantine; • zeroize; • request new authority; • escalate to a cold path; or • route for review. The source expressly supports denial, suppression, quarantine, redaction, zeroization, delay, downgrade, isolation and review following failed validation.

No Fail-Open on Timeout A timeout MUST NOT be interpreted as approval. For a protected consequence: verification timeout != permission Instead: verification timeout | +--> retry within policy | +--> escalate | +--> delay | +--> downgrade | `--> deny If no permitted resolution is available, the Candidate Act remains non-effective.

Alternate-Path Closure An implementation MUST consider alternate paths capable of producing the same protected consequence. For precise location, relevant paths may include: main application upload analytics SDK advertising SDK telemetry browser upload cloud sync backup clipboard bridge file export AI-agent tool call background service For an AI act: normal tool dispatcher direct API call shell execution browser control IPC memory write alternate plugin For hardware: CPU path GPU DMA SmartNIC DPU accelerator driver alternate interconnect Moving the act to a different path MUST NOT inherently remove the execution-finality requirement if that path can produce the same protected consequence. The source explicitly states that routing around a cold path, using stale cached authority, fragmenting an act, relocating the Finality Sink, or moving effectuation to another component does not create a bypass.

Security Considerations The execution-finality architecture is intended to prevent an upstream security decision, AI decision, application permission, credential, or network authorization from automatically becoming authority for an external consequence. The principal security objective is: A protected consequence MUST remain technically non-effective unless current, act-specific, scoped authority is verified at the applicable Finality Sink. Implementations MUST consider attacks against every load-bearing element of the finality chain.

Replay Attacks An attacker may attempt to reuse a previously valid finality authority. For example: Act A approved | v Authority A issued | v Act A completed | v Attacker copies Authority A | v Attempts second consequence A conforming implementation MUST prevent this. Finality authority SHOULD therefore be bound to one or more of: Candidate Act identity Candidate Act digest nonce sequence state policy epoch revocation epoch protected state scope Finality Sink identity consumption state Single-use authority MUST be consumed or otherwise made unusable before or atomically with effectuation. The source specifically identifies replay, stale retry, duplicate effectuation, cross-sink reuse and consumed-authority reuse as conditions that must prevent effectuation.

Candidate Act Substitution An attacker may obtain valid authority for one Candidate Act and attempt to substitute a different operation. Examples include: authorized: send coarse location substituted: send precise GPS or: authorized: payment = 50 substituted: payment = 5,000 or: authorized: Tool A substituted: Tool B The Finality Sink MUST verify that the actual consequence corresponds to the act or digest bound to the authority. A load-bearing field change MUST invalidate authority unless separately authorized.

Sink Substitution and Cross-Sink Laundering Authority issued for one Finality Sink MUST NOT automatically be usable at another sink. For example: Authority: sink = approved-data-egress-A Attack: redirect through egress-B or: Authority: tool-dispatcher-A Attack: direct shell interface A Finality Sink MUST verify its own identity or protected boundary identity against the authority before effectuation. The source identifies sink mismatch, boundary mismatch and cross-sink laundering as explicit conditions for denial.

Stale Policy and Revocation An act MAY have been valid when created but invalid when effectuation is attempted. Examples include: • revoked tool authority; • changed location-export policy; • new data-residency restriction; • revoked model version; • changed mission state; • new financial restriction; • expired user authorization; or • changed recipient status. The Finality Sink SHOULD therefore verify current policy and revocation state immediately before consequence. An old upstream approval MUST NOT automatically override current protected state.

Compromised Application or SDK The architecture assumes that ordinary application-layer software MAY be compromised or overly permissive. Therefore, security MUST NOT depend solely on: application says ALLOW SDK says ALLOW browser says ALLOW AI says ALLOW A malicious SDK with valid application access SHOULD NOT automatically be able to bypass a protected data-egress Finality Sink. This is especially relevant to precise location, telemetry, contacts, messages, enterprise data and background synchronization.

Protected-State Integrity An attacker may attempt: • rollback; • deletion of consumed state; • nonce reset; • policy-epoch rollback; • revocation-epoch rollback; • stale snapshot restoration; • duplicate authorization; or • protected-state substitution. High-assurance implementations SHOULD use protected monotonic state, sealed storage, secure counters, authenticated state transitions or equivalent mechanisms where rollback could produce a consequence.

Failure of the PED The PED is security critical. If its integrity cannot be established, the implementation SHOULD NOT release finality authority for protected consequence classes. Depending on the risk class, the system MAY: • fail closed; • downgrade; • quarantine; • require another protected validator; • require human approval; • move to a cold path; or • disable the protected consequence.

Failure of the Finality Sink The Finality Sink is equally load-bearing. An upstream PED cannot compensate for a sink that permits consequence without checking authority. The architecture therefore requires the complete chain: Non-Effective State + PED Validation + Protected Evidence + Scoped Authority + Protected State + Finality Sink Verification A Finality Sink without act-bound authority is not equivalent to the described architecture. The source expressly treats these elements as mutually load-bearing rather than independent advisory controls.

Privacy Considerations Execution-finality metadata itself may contain sensitive information. For example, a Candidate Act Descriptor might reveal: • application identity; • agent identity; • user purpose; • location class; • destination; • jurisdiction; • resource identity; • financial consequence; • policy state; or • behavioral information. Implementations SHOULD minimize the information exposed outside protected validation boundaries.

Protected Descriptors Where possible, implementations MAY use: • hashes; • commitments; • protected references; • encrypted measurements; • attestations; • Merkle commitments; • confidential-computing evidence; or • privacy-preserving proofs rather than exposing raw protected information. The source specifically contemplates validation of neural and runtime state without exposing model weights, private prompts, confidential user data, internal activations or sensitive inference traces.

Precise-Location Privacy Precise location requires special treatment because it can support inference substantially beyond the original application purpose. Repeated coordinates can expose: home workplace daily routine travel routes medical visits relationships sensitive facilities protected-person movements population movement patterns The source explicitly recognizes movement histories, household locations, workplace patterns, medical-visit inferences, social graphs and population-scale profiling as risks arising from precise-location export. Therefore, implementations SHOULD NOT assume: user granted location access = all destinations may receive exact GPS The more appropriate model is: LOCAL ACCESS | v Candidate Export | v Purpose? Recipient? Destination? Jurisdiction? Required precision? Cumulative disclosure? | v Finality decision

Precision Minimization Where exact coordinates are not necessary, implementations MAY release: • city; • region; • grid cell; • shortened geohash; • delayed location; • randomized location; • bounded-distance representation; or • another approved coarse representation. The Finality Sink MUST enforce the authorized precision. If exact GPS is denied, the exact value MUST NOT become externally effective merely because the application had already obtained it locally. This behavior is directly supported by the source's precise-GPS normalization embodiment.

Data-Sovereignty Considerations The architecture distinguishes: authority to access data from: authority to export data A process MAY legitimately access data inside one jurisdiction or protected environment while lacking authority to transfer it to: • another jurisdiction; • foreign cloud region; • unapproved processor; • external analytics provider; • unrelated AI provider; • advertising endpoint; or • another non-permitted recipient. Accordingly, a data-export Candidate Act SHOULD be capable of binding: destination recipient jurisdiction cloud region purpose data class precision policy epoch revocation epoch cumulative export state Finality Sink identity The source expressly identifies these predicates for data-sovereignty enforcement.

No-Breach Intelligence Inference A privacy or national-security risk can arise without a conventional security breach. Ordinary data fragments may be lawfully collected individually but become strategically sensitive after aggregation and machine inference. The source uses publicly reported location-tracking incidents to illustrate how ordinary movement records can reveal sensitive facilities, operational routines or protected-person movement. Execution finality therefore MAY evaluate not only whether data was lawfully read, but whether a particular disclosure is authorized to become externally available in the requested form.

Interoperability and Deployment Model The execution-finality architecture is intended to coexist with existing systems. It MAY consume decisions or evidence from: identity systems OAuth/access-control systems RBAC policy engines AI safety systems attestation systems telecom authentication enterprise policy regulatory policy human approval risk engines content classifiers However, those systems provide inputs to finality validation. They do not replace Finality Sink verification. This preserves the distinction: policy decision != final consequence

IANA Considerations This version of the document requests no IANA actions. It does not presently define: • a new IP protocol number; • transport port; • DNS record type; • media type; • URI scheme; or • mandatory global registry. If later versions standardize wire-format fields, error codes, consequence classes, precision classes, capability types or protocol parameters, an IANA registry MAY be proposed at that time. The EF-xxx failure identifiers shown in Phase 4 are currently illustrative protocol-design identifiers and are not IANA assignments.

Intellectual Property Considerations Certain technical concepts described in this document are associated with pending patent applications in the DAS Protocols family. The source identifies, among others: PCT/IB2026/054453 Capability-Validated Inbound Descriptor / CVID-PCT-1 PCT/IB2026/055615 THE DAS PROTOCOLS PCT/IB2026/055760 THE DAS PROTOCOLS PART II PCT/IB2026/055870 THE DAS PROTOCOLS PART III PCT/IB2026/056058 THE DAS PROTOCOLS PART IV PCT/IB2026/053385 Algorithmic Logic Fingerprint-related architecture The source states that these filings disclose related elements including non-bearer execution handles, protected enforcement domains, neural candidate acts, AI-output finality, device-side enforcement, agentic tool-use enforcement and Algorithmic Logic Fingerprints. Any IETF intellectual-property disclosure required in connection with standardization of this work should be handled separately in accordance with applicable IETF IPR procedures. This section is informational and does not define licensing terms.

References The following references are relevant to the motivation, policy context, or technical lineage described in this document.

Normative References At this stage, this document does not define a completed interoperable wire protocol requiring a finalized normative dependency set. A later revision SHOULD add the applicable IETF normative references once the encoding, transport, integrity mechanism and protocol negotiation elements are selected.

Informative References The following materials are identified in the source disclosure as relevant background or policy context: [EO14110] United States Executive Order 14110, Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, October 2023. [EDPB-28-2024] European Data Protection Board, Opinion 28/2024. [EU-AI-ACT] Regulation of the European Union concerning artificial intelligence. [ENISA] European Union Agency for Cybersecurity, relevant threat-landscape and network-security material. [NATO-CCDCOE] NATO Cooperative Cyber Defence Centre of Excellence, material concerning cyber operations and critical infrastructure. [NATO-STRATCOM] NATO Strategic Communications Centre of Excellence, work concerning metadata, telemetry and information exploitation. [UK-OSA] United Kingdom Online Safety Act 2023. [3GPP] 3GPP specifications relevant to 5G, 5G-Advanced, O-RAN-adjacent deployment environments and non-terrestrial networks. [ITU] ITU work concerning future networks and AI-assisted telecommunications. These references provide motivation or deployment context. They do not themselves define the execution-finality protocol. The source expressly maps the long-felt need to frontier-AI governance, data protection, telecommunications, sovereign infrastructure, cybersecurity, financial finality and digital child safety.

Technical-Lineage References [DAS-CVID] PCT/IB2026/054453, Capability-Validated Inbound Descriptor / CVID-PCT-1. [DAS-MOTHERSHIP] PCT/IB2026/055615, THE DAS PROTOCOLS. [DAS-II] PCT/IB2026/055760, THE DAS PROTOCOLS PART II. [DAS-III] PCT/IB2026/055870, THE DAS PROTOCOLS PART III. [DAS-IV] PCT/IB2026/056058, THE DAS PROTOCOLS PART IV. [DAS-ALF] PCT/IB2026/053385, Algorithmic Logic Fingerprint-related architecture. These applications are identified in the source as related technical disclosures.

Conclusion A device or application may legitimately obtain exact location while an SDK, AI agent, analytics service, cloud processor, or external destination is entitled only to a less precise representation or to no location at all. This profile moves that distinction to the actual egress boundary. Precise GPS access is not precise GPS-release authority; computation is not authority.