I-D Action: draft-das-protocols-enterprise-ai-00.txt

Internet-Draft draft-das-protocols-enterprise-ai-00.txt is now available.

   Title:   Architecting Resilience for Enterprise AI: Preventing Data Reconstruction, Exfiltration, and Unauthorized Consequence in Compromised AI Environments (DAS Protocols)
   Author:  Sangam Das
   Name:    draft-das-protocols-enterprise-ai-00.txt
   Pages:   36
   Dates:   2026-08-27

Abstract:

   A compromised enterprise AI server is no longer just a data-breach
   risk.  It can become a continuously updated reconstruction engine of
   the enterprise’s future — correlating customer records, engineering
   defects, financial systems, and internal communications into
   competitive intelligence and then externalizing that intelligence.
   Conventional security concentrates the powers of data access,
   semantic joining, and external effectuation inside the same workload.
   When that workload is compromised through prompt injection, model
   substitution, credential theft, or full server takeover, existing
   access-control, sandbox, TEE, DLP, and clean-room approaches do not
   structurally stop the escalation from computation to real-world
   consequence.

   This document presents the DAS Protocols enterprise-AI architecture,
   a focused embodiment of the broader execution-finality framework
   disclosed in PCT/IB2026/055615 (“THE DAS PROTOCOLS”).  It introduces
   Execution–Consequence Decoupling enforced by three pillars:
   Decomposition of Authority (Technical Non-Joinability) across
   independently controlled identity, content, relationship-mapping, and
   cryptographic vaults; Mandatory Mediation of every consequence-
   bearing Candidate Output; and Technical Non-Completability so that
   computation can finish without the ability to complete external
   consequence.

   Reconstruction is governed by a non-bearer Reconstruction
   Authorization Object bound to attested execution context, session,
   purpose, and Permitted Association Scope.  Candidate Outputs are
   sealed.  Live output-time re-verification and constitutive Protected
   Output Validation Receipt commitment are required before an output-
   specific Release Capability can be issued and exercised only at a
   designated Output Release Boundary.  Compromise of the AI computation
   plane therefore cannot automatically escalate into unrestricted
   enterprise-knowledge reconstruction or unauthorized external
   consequence.

   The document elaborates the full problem space, compares the
   architecture against representative conventional technologies,
   provides a detailed technical description, and supplies JSON Schema
   definitions for the core protected objects (Reconstruction
   Authorization Object, Protected Output Validation Receipt, and Output
   Release Capability).  Intellectual-property disclosures of related
   Indian provisional applications and PCT filings appear in the final
   appendix.

The IETF datatracker status page for this Internet-Draft is:
https://datatracker.ietf.org/doc/draft-das-protocols-enterprise-ai/

There is also an HTML version available at:
https://www.ietf.org/archive/id/draft-das-protocols-enterprise-ai-00.html

Internet-Drafts are also available by rsync at:
rsync.ietf.org::internet-drafts


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