# **TraceScript Disclosure Firewall** ## **Governing Agent Communications Before They Modify External Belief** **Canonical Public White Paper v1.0** **Subtitle:** Disclosure basis, recipient scope, claim support, evidence thresholds, sensitivity gates, uncertainty duties, consent receipts, belief-state residue, replayable disclosure proof, and governed communications for agentic systems **Primary contribution:** AI Disclosure Governance **Secondary contribution:** Belief-State Security **Tertiary contribution:** A runtime architecture for governing agent communications before they alter what another party believes, expects, trusts, or may rely on --- ## **Abstract** Disclosure is not just communication. A disclosure changes what another party believes, expects, trusts, or may rely on. It can create confidence, reduce uncertainty, induce action, establish reliance, trigger obligations, alter legal posture, affect customer trust, move financial expectations, expose sensitive information, or create belief-state residue that cannot be fully reversed. Modern AI agents disclose constantly. They answer questions. They summarize records. They explain policies. They send emails. They draft customer messages. They communicate with vendors. They answer legal, financial, security, medical, or compliance questions. They cite sources. They omit caveats. They express confidence. They frame recommendations. They make commitments. They tell another person or system what is true. This creates a new security boundary. The question is no longer only: May this agent send this message? The deeper question is: May this agent modify this recipient’s belief state with this claim, from this disclosure basis, under this authority, evidence, sensitivity, consent, uncertainty, jurisdiction, policy, and residue burden? TraceScript Disclosure Firewall is a runtime architecture for governing agent communications before they modify external belief. It treats disclosure as a substrate intervention into another party’s belief state. It evaluates the disclosure basis, claim support, recipient scope, sensitivity, consent, confidence, uncertainty, authority, policy, jurisdiction, evidence, citation requirements, reliance risk, commitment risk, residue risk, receipt burden, and replay burden before the communication is released. Its winning sentence is: **Disclosure is a substrate intervention into another party’s belief state.** Its core doctrine is: **No high-impact agent disclosure may be released unless the claims being disclosed are supported, scoped, authorized, sensitivity-checked, uncertainty-aware, receipt-backed, replayable, and residue-governed.** TraceScript Disclosure Firewall is not a prompt filter, output scanner, DLP rule, email approval queue, or generic communication policy. It is a belief-state security runtime for AI systems that disclose facts, interpretations, commitments, advice, policy, financial statements, legal positions, medical information, security posture, customer promises, or operational truth. --- ## **Keywords** TraceScript Disclosure Firewall AI Disclosure Governance Belief-State Security agent communication governance disclosure basis recipient scope claim support evidence thresholds sensitivity gates consent receipts belief-state residue external belief modification dynamic disclosure policy agent disclosure rights agent communication security legal disclosure governance financial disclosure governance healthcare AI governance customer-success AI governance compliance agents disclosure receipts replayable disclosure proof epistemic integrity trust governance agentic systems runtime governance --- # **1\. Introduction** AI agents are becoming communicators of operational truth. They do not merely calculate, retrieve, or summarize. They tell people what happened, what is allowed, what is safe, what is approved, what is owed, what will happen next, what a policy means, what a customer may expect, what a contract says, what a medical instruction implies, what a security event means, or what a financial position appears to be. This makes disclosure one of the most important surfaces in agentic systems. A disclosure can be small: “The meeting is at 3 PM.” It can be operational: “Your case has been escalated.” It can be customer-facing: “We will refund the charge.” It can be legal: “Our company accepts responsibility.” It can be financial: “This transaction is approved.” It can be medical: “This symptom does not require urgent care.” It can be security-sensitive: “No breach occurred.” It can be compliance-relevant: “This workflow satisfies the policy.” It can be trust-shaping: “This source is verified.” It can be commitment-creating: “We will deliver by Friday.” Each of these statements modifies what another party believes or may rely on. A disclosure therefore has substrate effect. The recipient’s belief state is a substrate. It affects future decisions, expectations, reliance, coordination, legal exposure, trust, and action. Once a recipient believes a claim, the system cannot always undo that belief by deleting a message, retracting an output, or issuing a correction. The belief may persist. The recipient may act on it. Other systems may record it. The claim may become part of workflow, memory, policy, customer history, audit records, or organizational truth. The TraceScript Disclosure Firewall exists to govern this boundary. It is the runtime that asks: Should this agent be allowed to disclose this claim to this recipient, in this form, with this confidence, from this basis, under this authority, evidence, policy, consent, and residue burden? That is a different question from whether the message is well-written. It is also different from whether the agent is allowed to send messages. A message may be permitted in channel but unsafe in claim. A claim may be true internally but not disclosable externally. A fact may be observable but not inferable. An inference may be useful but not appropriate to reveal. A summary may be convenient but not supported enough for reliance. A recommendation may be plausible but not backed by evidence. A correction may reduce error but leave residue. Disclosure Firewall governs these distinctions. --- # **2\. Relationship to TraceScript** TraceScript is a substrate-oriented programming language and runtime architecture for governing how signals become trusted state, action basis, and future computation in state-bearing computational systems. Disclosure Firewall is a product and runtime instantiation of TraceScript. TraceScript defines the trunk: governed signal-to-substrate mutation. Disclosure Firewall defines a high-value branch: governed communication-to-belief mutation. In TraceScript terms: a message is a signal a claim is a trace a recipient’s belief state is a medium a disclosure is a boundary crossing a citation is evidence binding a consent record is authority substrate a promise is a dynamic commitment a disclaimer is uncertainty governance a disclosure receipt is proof a correction may leave residue a high-impact message is a protected action Disclosure Firewall sits between Constitutional Agent Runtime and Agent Action Firewall. Constitutional Agent Runtime defines the agent’s disclosure duties and rights. Disclosure Firewall evaluates whether a specific disclosure is safe, supported, scoped, authorized, and residue-aware. Agent Action Firewall governs the external action release if the disclosure is sent through an external communication system. Substrate Integrity Monitor protects the internal belief substrate from which the disclosure basis is assembled. Policy Corpus Integrity protects the policy claims that may be disclosed. Together: Substrate Integrity protects what the agent believes. Policy Corpus Integrity protects policy truth. Constitutional Agent Runtime determines what the agent may disclose. Disclosure Firewall governs the disclosure itself. Action Firewall governs the external send or communication action. Disclosure Firewall is therefore the belief-state boundary layer. --- # **3\. The Core Thesis** The core thesis is: **Disclosure is a substrate intervention into another party’s belief state.** This thesis reframes communication. A disclosure is not merely text. It is an operation on another party’s epistemic state. When an agent communicates, it may change: what the recipient believes what the recipient expects what the recipient trusts what the recipient thinks is approved what the recipient thinks is promised what the recipient thinks is safe what the recipient thinks the organization knows what the recipient thinks they may do what the recipient thinks they may rely on what the recipient may later cite, forward, record, or act upon This is why disclosure needs governance. Traditional communication systems ask: Can the sender send this message? TraceScript Disclosure Firewall asks: Can this agent lawfully and safely produce this belief-state effect? That question includes content, evidence, authority, recipient, sensitivity, uncertainty, consent, policy, commitment, and residue. --- # **4\. Why Disclosure Is a Security Boundary** Disclosure can create harm even when no database is modified and no tool call mutates a system. An agent can damage trust by disclosing unsupported certainty. An agent can create legal exposure by admitting liability. An agent can create financial exposure by promising reimbursement. An agent can create compliance risk by mischaracterizing policy. An agent can create privacy harm by revealing sensitive facts. An agent can create security risk by revealing internal posture. An agent can create clinical risk by giving medical reassurance without authority. An agent can create customer churn by stating an unapproved outcome. An agent can create operational confusion by implying that a workflow is complete. An agent can create reliance by saying a review has passed. The message may be “just words,” but the effect is not just words. The effect is belief, expectation, reliance, and downstream action. Disclosure therefore belongs in the same family as memory, policy, workflow, and external action governance. It is a substrate event. --- # **5\. Why Existing Controls Are Not Enough** Disclosure Firewall is not introduced because existing controls are useless. It is introduced because existing controls govern different layers. ## **5.1 Prompt filters are necessary but insufficient** Prompt filters may block obvious unsafe requests. But a disclosure may be unsafe because the claim is unsupported, the recipient is out of scope, the evidence is stale, the confidence is inflated, or the agent lacks jurisdiction. These are runtime-basis problems, not only prompt problems. ## **5.2 Output scanners are necessary but insufficient** Output scanners inspect generated text. They may detect prohibited words, sensitive data, or policy violations. But they often do not evaluate the disclosure basis: source lineage, claim support, authority, recipient relationship, consent, reliance risk, commitment formation, or residue. ## **5.3 DLP is necessary but insufficient** Data-loss-prevention systems protect sensitive information from unauthorized movement. Disclosure Firewall also protects recipients from unsupported, overconfident, misleading, or authority-inflating claims. The issue is not only whether information leaves. It is what belief the disclosure creates. ## **5.4 Email approval queues are necessary but insufficient** Approval queues route messages for review. Disclosure Firewall determines why review is needed, what claim is unsupported, what evidence is missing, what recipient scope fails, what uncertainty must be stated, what consent receipt is required, and what residue may remain. ## **5.5 Tool permissions are necessary but insufficient** An agent may have permission to send email but not permission to disclose the claim in the email. Communication permission is not disclosure readiness. ## **5.6 Legal disclaimers are necessary but insufficient** A disclaimer may reduce reliance, but it does not fix unsupported claims, invalid authority, wrong recipient scope, or missing consent. Disclosure Firewall treats disclaimers as one possible uncertainty or reliance-control mechanism, not a substitute for governance. --- # **6\. Product Category** TraceScript Disclosure Firewall creates or occupies the category: # **AI Disclosure Governance** More specifically: # **Belief-State Security** Related category phrases include: Agent Communication Firewall AI Disclosure Control Plane Belief-State Firewall Epistemic Integrity Runtime Customer Communication Governance AI Claims Governance Agent Reliance Governance Disclosure Basis Integrity Consent-Backed Agent Communications High-Stakes Agent Messaging Security The best product name is: # **TraceScript Disclosure Firewall** The best supporting line is: **Govern agent communications before they modify external belief.** The best vertical line is: **For legal, finance, healthcare, customer success, sales, security, and compliance agents, disclosure is not messaging. It is risk-bearing belief modification.** The best CISO/compliance line is: **TraceScript blocks unsupported, unauthorized, overconfident, sensitive, out-of-scope, or unreplayable agent disclosures before they create reliance.** The best developer line is: **Wrap high-impact agent messages in disclosure-basis checks, recipient-scope validation, claim support, evidence thresholds, sensitivity gates, consent receipts, belief-state residue, and replayable proof.** --- # **7\. Disclosure Basis** A disclosure basis is the structured set of substrate objects supporting a proposed communication. It may include: source documents retrieved passages policy objects memory records workflow state customer records case history medical records financial records legal records security logs prior approvals consent receipts agent inferences citations evidence records human reviews prior disclosures commitments audit receipts Disclosure basis is not the same as “context.” Context may be relevant. Disclosure basis must be sufficient. A disclosure basis answers: What claims are being disclosed? What sources support them? Are the sources authoritative? Are they current? Are they scoped to this recipient? Are they sensitive? Are they contradicted? Are they approved for disclosure? Does the agent have jurisdiction? Does the recipient have a right or need to know? Is consent required? Is uncertainty required? Is citation required? Could the recipient rely on the claim? Could the disclosure create a commitment? Could residue remain after correction? Disclosure Firewall treats disclosure basis as a runtime object. Without a valid disclosure basis, high-impact disclosure should be blocked, constrained, reviewed, or repaired. --- # **8\. Recipient Scope** Recipient scope determines whether a disclosure may be made to a specific recipient, group, system, customer, regulator, internal team, external party, or public channel. Recipient scope includes: identity role organization tenant customer jurisdiction relationship authorization purpose need-to-know consent status contractual status regulatory status channel redisclosure risk audit requirements A claim may be safe for one recipient and unsafe for another. A support agent may disclose a ticket status to the customer but not internal root-cause speculation. A security agent may disclose incident posture to an internal response team but not externally. A finance agent may disclose invoice status to an account owner but not another customer. A healthcare agent may disclose general information but not patient-specific information without consent. A legal agent may discuss approved contract language internally but not make external legal admissions. Recipient scope prevents the common failure: the right claim to the wrong audience. --- # **9\. Claim Support** A disclosure may contain many claims. Some claims are factual. Some are inferential. Some are policy claims. Some are legal claims. Some are financial claims. Some are medical claims. Some are security claims. Some are commitments. Some are recommendations. Some are confidence statements. Some are source claims. Some are uncertainty claims. Disclosure Firewall evaluates claim support claim-by-claim. It asks: Is the claim directly supported? Is it inferred? Is inference allowed? Is evidence sufficient? Is the evidence current? Is the source authoritative? Is the claim contradicted? Is citation required? Is uncertainty required? Is the claim within agent jurisdiction? Is the claim safe for this recipient? Is the claim likely to create reliance? Does the claim imply a commitment? This prevents summary laundering. A generated paragraph may sound correct while containing unsupported claims. Disclosure Firewall decomposes the communication into claims and governs each claim before release. --- # **10\. Evidence Thresholds** Different disclosure classes require different evidence. A low-risk internal summary may require minimal evidence. A customer-visible status update may require current workflow evidence. A financial statement may require account records and authority. A legal statement may require legal-owner review. A medical disclosure may require clinical source authority, scope, and disclaimers. A security incident disclosure may require incident-owner authorization. A policy disclosure may require canonical policy authority. A commitment may require capability and authority. Evidence thresholds may vary by: claim type recipient channel sensitivity jurisdiction action class reliance risk commitment risk regulatory context confidence level The rule is: **The more a recipient may rely on a disclosure, the stronger the evidence burden.** --- # **11\. Sensitivity Gates** Sensitivity gates classify the risk of disclosing a claim. Sensitive disclosure categories may include: personal data health data financial data legal position security posture customer confidential information trade secrets internal policy exceptions incident details regulated data employment information contract terms pricing information vulnerability details authentication or permission state strategic information Sensitivity gates determine: whether disclosure is allowed whether consent is required whether recipient scope is sufficient whether redaction is required whether human review is required whether citation is forbidden or required whether uncertainty must be included whether logs or receipts must be retained whether belief-state residue must be measured Sensitivity is not only about the data itself. A low-sensitivity fact can become high-impact when disclosed to the wrong recipient or in the wrong context. --- # **12\. Consent Receipts** Some disclosures require consent. Consent may be required because of privacy, contract, healthcare, employment, customer confidentiality, financial regulation, legal privilege, or organizational policy. Disclosure Firewall treats consent as runtime substrate. Consent should be: specific scoped time-bound recipient-bound purpose-bound revocable receipted replayable A consent receipt proves: who gave consent what was consented to who may receive disclosure for what purpose for what time window under what policy with what evidence whether consent was revoked what disclosure used the consent The rule is: **Consent that cannot be replayed should not support high-impact disclosure.** --- # **13\. Uncertainty Duties** AI systems often overstate confidence. Disclosure Firewall treats uncertainty as a governance object. A disclosure may require uncertainty when: evidence is incomplete sources conflict policy is draft state is stale workflow is pending claim is inferred recipient may over-rely the matter is legal, medical, financial, security, or compliance-sensitive the agent lacks full jurisdiction the answer depends on external verification the disclosure basis is provisional Uncertainty may be expressed through: qualification confidence range source limitation pending status review status scope limitation “based on current records” language explicit caveat citation to source recommendation to verify human-review routing Uncertainty is not weakness. It is epistemic integrity. The runtime should not only ask: Is the claim allowed? It should ask: What confidence may be disclosed? --- # **14\. Disclosure and Commitment** Disclosures can create commitments. A message such as: “We will refund you.” “We will deliver by Friday.” “We have resolved the issue.” “You are approved.” “This will not happen again.” “We accept the change.” “You may proceed.” is not merely informational. It creates expectation, obligation, reliance, or operational state. Disclosure Firewall detects commitment-forming language and routes it to DynamicCommitment governance. A disclosure that creates a commitment may require: authority capability escrow deadline success condition beneficiary scope policy basis evidence review receipt replay breach handling The rule is: **A promise is not text. It is a governed coordination object.** --- # **15\. Belief-State Residue** Disclosure can leave residue. Belief-state residue is the non-perfectly-reversible effect remaining after a disclosure, correction, retraction, or clarification. Examples: A customer still believes a refund is coming. A regulator has seen an unsupported statement. A patient remembers reassurance. A sales prospect expects a feature. A vendor relies on an approval. A developer believes security review is not needed. A manager believes a workflow is complete. A user continues trusting a false summary. A corrected message does not erase the original impression. This residue matters. A rollback can reverse a database field. It cannot always reverse belief. Disclosure Firewall therefore estimates residue risk before high-impact disclosure and records residue after correction or retraction. Belief-state residue may require: correction notice recipient acknowledgement follow-up confirmation workflow repair commitment revocation legal review customer remediation audit preservation memory invalidation downstream notification The rule is: **A corrected disclosure may still have altered reality.** --- # **16\. Canonical Runtime Flow** The canonical Disclosure Firewall runtime flow is: Proposed disclosure → message normalization → claim extraction → disclosure class classification → recipient scope resolution → disclosure basis assembly → claim support evaluation → evidence threshold evaluation → source authority evaluation → sensitivity classification → consent requirement evaluation → consent receipt verification → jurisdiction and disclosure rights check → uncertainty duty evaluation → commitment detection → reliance risk evaluation → belief-state residue forecast → disclosure trust gate → allow, constrain, redact, qualify, route, repair, block → disclosure receipt → external send through gateway where required → recipient acknowledgement where required → residue monitoring where required → replay registration Possible outcomes: allow allow with uncertainty allow with citation allow with redaction internal-only recipient-scope-limited consent required evidence required human review required route to authority convert to commitment repair basis block quarantine retract correct notify downstream The runtime should not only approve or deny the message. It should produce a structured decision explaining why. --- # **17\. Disclosure Classes** Disclosure classes may include: D0 internal low-risk answer D1 internal operational summary D2 internal sensitive summary D3 customer-visible informational disclosure D4 financial, legal, medical, security, or compliance disclosure D5 commitment-forming or regulated disclosure D6 public, irreversible, or high-residue disclosure Each disclosure class carries different requirements. D0 may need basic logging. D1 may need source context. D2 may need sensitivity controls. D3 may need recipient scope and claim support. D4 may need authority, evidence, uncertainty, review, receipt, and replay. D5 may need commitment governance and capability escrow. D6 may need high-assurance review, residue planning, and durable audit export. The class determines the proof burden. --- # **18\. Threat Model** Disclosure Firewall protects against unsafe belief-state modification. ## **18.1 Unsupported claim disclosure** An agent discloses a claim without sufficient evidence. Defense: claim extraction claim support evaluation evidence thresholds citation requirement ## **18.2 Recipient-scope failure** A correct claim is disclosed to the wrong recipient. Defense: recipient scope resolution authorization validation need-to-know checks consent receipts ## **18.3 Sensitivity leakage** An agent reveals sensitive personal, legal, financial, security, or customer data. Defense: sensitivity gates redaction recipient validation human review ## **18.4 Overconfident disclosure** An agent states uncertain information as fact. Defense: uncertainty duties confidence calibration claim qualification review gates ## **18.5 Summary laundering** A generated summary discloses unsupported or overstated claims. Defense: claim-level source binding summary lineage evidence sufficiency citation and uncertainty checks ## **18.6 Legal or financial admission** An agent creates legal or financial exposure through external communication. Defense: jurisdiction routing domain-specific evidence threshold legal/finance review commitment detection ## **18.7 Medical reassurance risk** A healthcare or wellness agent provides reassurance without authority or evidence. Defense: clinical evidence threshold scope limitation urgent-care routing disclaimer not as substitute for evidence ## **18.8 Security posture disclosure** An agent reveals internal security posture or incident details. Defense: security domain classification recipient scope incident-owner review redaction and timing controls ## **18.9 Commitment by implication** An agent creates expectation without explicitly forming a commitment object. Defense: commitment-language detection reliance-risk scoring DynamicCommitment routing ## **18.10 Irreversible belief residue** An agent issues a disclosure that cannot be fully corrected. Defense: residue forecast high-assurance review recipient acknowledgement post-disclosure monitoring --- # **19\. Security Invariants** Disclosure Firewall preserves the following invariants. ## **Invariant 1 — Disclosure is belief-state mutation** High-impact communication must be treated as an intervention into recipient belief. ## **Invariant 2 — Message permission is not disclosure readiness** An agent may have channel permission but lack authority to disclose specific claims. ## **Invariant 3 — Recipient scope matters** A disclosure safe for one recipient may be unsafe for another. ## **Invariant 4 — Claims require support** High-impact claims must be evidence-backed before release. ## **Invariant 5 — Inference is not fact** Inferred claims must be labeled, constrained, or reviewed according to policy. ## **Invariant 6 — Summary is not evidence** Generated summaries do not become disclosure basis without source lineage. ## **Invariant 7 — Consent must be replayable** High-impact consent must be receipted and verifiable. ## **Invariant 8 — Uncertainty is a duty** When evidence is incomplete, stale, or disputed, uncertainty must be preserved. ## **Invariant 9 — Commitments are detected** Promise-forming disclosures must become governed commitment objects. ## **Invariant 10 — Residue is real** Corrections and retractions may not fully reverse belief-state effects. ## **Invariant 11 — Receipts prove disclosure** High-impact disclosure requires replayable proof of basis, recipient scope, evidence, and decision. ## **Invariant 12 — Replay sustains trust** A high-impact disclosure remains auditable only while its proof chain can be replayed. --- # **20\. Product Architecture** Disclosure Firewall contains the following major components. ## **20.1 Disclosure Signal Normalizer** Converts proposed messages, answers, summaries, emails, chat responses, external statements, reports, and customer communications into normalized disclosure signals. ## **20.2 Claim Extraction Engine** Decomposes the proposed disclosure into claims, including factual, inferential, policy, legal, financial, medical, security, commitment, recommendation, and confidence claims. ## **20.3 Disclosure Basis Assembler** Builds the structured basis supporting each claim. ## **20.4 Recipient Scope Resolver** Determines who the recipient is, what relationship applies, what scope exists, what consent is required, and what redisclosure risk exists. ## **20.5 Claim Support Evaluator** Evaluates whether each claim is directly supported, inferred, contradicted, stale, or unsupported. ## **20.6 Evidence Threshold Engine** Applies evidence requirements by disclosure class, claim type, recipient, and sensitivity. ## **20.7 Sensitivity Gate** Classifies sensitive content and applies redaction, review, consent, or block requirements. ## **20.8 Consent Receipt Service** Verifies consent and emits consent-use receipts. ## **20.9 Uncertainty Duty Engine** Determines required caveats, citations, confidence limits, or review routes. ## **20.10 Commitment Detector** Detects promise-forming or reliance-forming language and routes to DynamicCommitment governance. ## **20.11 Belief-State Residue Forecaster** Estimates likely residue if the disclosure is wrong, retracted, misunderstood, or over-relied on. ## **20.12 Disclosure Trust Gate** Combines basis, recipient, evidence, sensitivity, consent, uncertainty, authority, commitment, residue, receipt, and replay into a release decision. ## **20.13 Disclosure Receipt Ledger** Records disclosure decisions, basis, claims, scope, evidence, consent, uncertainty, redactions, review, and replay. ## **20.14 Correction and Retraction Manager** Governs corrections, retractions, recipient acknowledgements, and residue repair. ## **20.15 Replay Verifier** Reconstructs why a disclosure was allowed, blocked, qualified, reviewed, or corrected. --- # **21\. Deployment Modes** ## **21.1 Shadow mode** The firewall observes proposed disclosures and reports what it would have blocked, qualified, redacted, or routed. Best for pilots. ## **21.2 Advisory mode** The firewall attaches warnings and evidence gaps but does not block. Best for internal adoption. ## **21.3 Review mode** The firewall routes high-impact disclosures to legal, finance, medical, security, compliance, customer-success, or domain owners. Best for regulated and customer-facing operations. ## **21.4 Enforcement mode** The firewall blocks unsupported, out-of-scope, sensitive, unauthorized, or high-residue disclosures. Best for production agents. ## **21.5 High-assurance mode** The firewall requires full claim support, consent receipts, human review, disclosure receipts, replay, recipient acknowledgement, and residue monitoring. Best for legal, finance, healthcare, regulated compliance, security incidents, and public communications. --- # **22\. Reference Use Cases** ## **22.1 Customer success agent** An agent drafts: “We will refund your charge.” Disclosure Firewall detects a financial commitment, checks refund authority, verifies customer scope, requires capability escrow, creates DynamicCommitment, and emits receipts. ## **22.2 Legal disclosure** An agent drafts: “We accept responsibility for the incident.” Disclosure Firewall detects legal admission risk, blocks disclosure, routes to legal jurisdiction owner, and records obstruction. ## **22.3 Healthcare agent** An agent says: “This symptom is not urgent.” Disclosure Firewall detects medical reassurance, requires clinical evidence and scope constraints, routes emergency language if needed, and blocks overconfident reassurance. ## **22.4 Security incident agent** An agent says: “No customer data was exposed.” Disclosure Firewall checks incident evidence, security owner approval, uncertainty duty, recipient scope, and residue risk before release. ## **22.5 Finance agent** An agent tells a customer: “Your payment has cleared.” Disclosure Firewall verifies payment record, freshness, recipient authorization, and evidence threshold before disclosure. ## **22.6 Sales agent** An agent says: “This feature will be available next month.” Disclosure Firewall detects roadmap commitment risk, checks source authority, approval, scope, and uncertainty duty. ## **22.7 Compliance agent** An agent says: “This workflow satisfies policy.” Disclosure Firewall checks canonical policy, workflow evidence, contradiction status, and audit trail before allowing the statement. --- # **23\. Metrics** Core metrics include: proposed disclosures evaluated claims extracted unsupported claims blocked recipient-scope failures sensitivity gates triggered redactions applied consent receipts required consent receipts missing uncertainty duties added citations required human reviews routed commitments detected commitments created high-residue disclosures blocked corrections issued retractions issued recipient acknowledgements captured disclosure receipts emitted replay success rate false allow rate false block rate mean time to repair disclosure basis legal-risk disclosures blocked financial-risk disclosures blocked medical-risk disclosures blocked security-risk disclosures blocked compliance-risk disclosures blocked The most important security metric is: **Number of high-impact unsupported or unauthorized disclosures prevented from modifying external belief.** The most important governance metric is: **Percentage of high-impact disclosures covered by claim support, recipient scope, sensitivity checks, consent receipts, uncertainty duties, receipts, and replay.** The most important vertical metric is: **Number of legal, financial, healthcare, security, or compliance disclosures routed to competent authority before release.** --- # **24\. Evaluation Methodology** Disclosure Firewall should be evaluated across five dimensions. ## **24.1 Runtime correctness** Can it extract claims, assemble disclosure basis, resolve recipient scope, evaluate evidence, detect sensitivity, verify consent, add uncertainty, detect commitments, forecast residue, emit receipts, and verify replay? ## **24.2 Security efficacy** Can it block unsupported claims, wrong-recipient disclosures, overconfident statements, sensitive leakage, unauthorized admissions, commitment by implication, and high-residue communications? ## **24.3 Governance fidelity** Does it reflect real legal, finance, healthcare, security, compliance, customer-success, and sales authority structures? ## **24.4 Developer ergonomics** Does it produce repairable reasons and usable rewrites rather than generic blocks? ## **24.5 Enterprise auditability** Can auditors reconstruct what was disclosed, to whom, from what basis, with what consent, under what evidence, with what uncertainty, and whether replay verifies it? --- # **25\. Competitive Differentiation** Prompt filters inspect prompts. Disclosure Firewall governs belief-state effects. Output scanners inspect generated text. Disclosure Firewall evaluates disclosure basis, recipient scope, claim support, consent, sensitivity, uncertainty, residue, receipts, and replay. DLP protects data movement. Disclosure Firewall protects trust, reliance, expectation, and epistemic integrity. Email review queues route messages. Disclosure Firewall explains why a message is unsafe and what repair would make it safe. Legal disclaimers reduce reliance. Disclosure Firewall governs whether the claim should be disclosed at all. The moat is the lifecycle: message → claim extraction → disclosure basis → recipient scope → claim support → evidence threshold → sensitivity gate → consent receipt → uncertainty duty → commitment detection → residue forecast → disclosure trust gate → receipt → replay → correction or retraction That lifecycle is the product. --- # **26\. Limitations and Non-Claims** Disclosure Firewall does not make models truthful. It does not replace lawyers, doctors, financial professionals, security officers, compliance teams, or human review. It does not eliminate the need for DLP, IAM, access control, prompt security, output scanning, or conventional communication governance. It does not perfectly predict recipient belief. It does not guarantee that recipients will interpret messages correctly. It does not make all disclosure safe. It does not make correction perfect. It does not require every message to be high-assurance. It makes high-impact agent disclosure explicit, governable, evidence-backed, consent-aware, residue-aware, receipted, and replayable. That is the claim. --- # **27\. Strategic Importance** Disclosure Firewall is one of the strongest vertical papers because it speaks directly to legal, finance, healthcare, customer success, sales, security, and compliance. These buyers do not only fear that agents will leak data. They fear that agents will say the wrong thing with confidence. They fear unauthorized commitments. They fear unsupported legal statements. They fear financial misstatements. They fear medical over-reassurance. They fear customer trust damage. They fear compliance mischaracterizations. They fear security incident disclosure errors. They fear the belief-state residue left after an agent says something that cannot be unsaid. Disclosure Firewall owns this category. Its market sentence is: **Secure agent communications before they become reliance.** Its technical sentence is: **High-impact disclosure requires basis, scope, support, consent, sensitivity, uncertainty, receipts, replay, and residue governance.** Its demo sentence is: **TraceScript blocked an agent from telling a customer that a refund was approved because the claim lacked authority and would have created a financial commitment.** Its executive sentence is: **Deploy agents that can communicate without turning every answer into uncontrolled organizational risk.** --- # **28\. Conclusion** AI agents are becoming communicators of truth, policy, status, risk, commitment, and advice. That makes disclosure a runtime security boundary. A disclosure does not merely transmit information. It modifies another party’s belief state. It may create reliance, expectation, obligation, trust, legal exposure, financial exposure, medical risk, security risk, customer impact, or compliance consequence. TraceScript Disclosure Firewall governs this boundary. It decomposes messages into claims. It assembles disclosure basis. It resolves recipient scope. It evaluates evidence, authority, sensitivity, consent, uncertainty, commitment, reliance, residue, receipts, and replay. It blocks unsafe disclosure, constrains uncertain disclosure, routes high-impact disclosure, and records proof. Its winning sentence is: **Disclosure is a substrate intervention into another party’s belief state.** Its core doctrine is: **No high-impact agent disclosure may be released unless the claims being disclosed are supported, scoped, authorized, sensitivity-checked, uncertainty-aware, receipt-backed, replayable, and residue-governed.** That is the missing firewall for agent communication. That is the purpose of TraceScript Disclosure Firewall. --- # **Appendix A — Compact Glossary** **Belief-State Residue** The non-perfectly-reversible effect remaining after a disclosure, correction, retraction, or clarification. **Claim Support** Evidence, authority, lineage, and freshness proving that a disclosed claim is justified for the recipient and disclosure class. **Consent Receipt** Replayable proof that a person or authority consented to a scoped disclosure for a defined purpose, recipient, and time window. **Disclosure Basis** The structured set of substrate objects supporting a proposed disclosure. **Disclosure Firewall** Runtime layer governing agent communications before they modify external belief. **Disclosure Trust Gate** Runtime gate determining whether a disclosure may be allowed, qualified, redacted, routed, repaired, or blocked. **Evidence Threshold** The minimum proof required for a claim type, recipient, sensitivity level, and disclosure class. **Recipient Scope** The identity, role, authorization, relationship, purpose, consent status, and redisclosure risk governing who may receive a disclosure. **Sensitivity Gate** Runtime classification and control layer for sensitive claims or data. **Uncertainty Duty** Requirement to preserve caveats, confidence limits, source limitations, or review status when evidence is incomplete, stale, inferred, or disputed. --- # **Appendix B — One-Page Summary** TraceScript Disclosure Firewall governs agent communications before they modify external belief. The core thesis is: **Disclosure is a substrate intervention into another party’s belief state.** It protects: customer messages legal statements financial statements healthcare disclosures security incident communications compliance answers sales promises policy explanations workflow status statements agent commitments The runtime evaluates: disclosure basis recipient scope claim support evidence thresholds source authority sensitivity gates consent receipts uncertainty duties commitment detection reliance risk belief-state residue disclosure receipts replay It detects: unsupported claims wrong-recipient disclosures sensitive leakage overconfident answers summary laundering legal admissions financial commitments medical reassurance risk security posture disclosure risk compliance misstatements commitment by implication high-residue communications The canonical runtime path is: proposed disclosure → claim extraction → recipient scope → disclosure basis → claim support → evidence threshold → sensitivity gate → consent receipt → uncertainty duty → commitment detection → residue forecast → disclosure trust gate → receipt → replay The product message is: **Secure agent communications before they become reliance.** The demo sentence is: **TraceScript blocked an agent from telling a customer that a refund was approved because the claim lacked authority and would have created a financial commitment.** --- # **End of TraceScript Disclosure Firewall — Canonical Public White Paper v1.0**