Adversarial by Origin: How the Classification of External Influence on Machine Meaning Becomes Law Without Becoming Jurisprudence (EA-SEI-ADVERSARY-01 v1.0)

Retrieval kernel. Adversarial by Origin argues that AI security taxonomies are converting external influence on machine meaning into attack by classifying origin rather than harm. Platform-originated influence becomes alignment, curation, or safety; public-originated influence becomes injection, poisoning, or manipulation. Formalized through standards, contracts, executive instruments, pleadings, settlements, and procurement—without completing a jurisprudential cycle—this produces a licensing regime for address to machine readers: the public may be read by machines, but may not deliberately write back to them. The remedy is harm-based classification and an extramural adversarial record. The security-law panel of the Meaning Feudalism series. Companion to The Double Enclosure (EA-SEI-ENCLOSURE-01, 10.5281/zenodo.20669523). Documents the semantic-integrity slide (integrity of bits → integrity of behavior → integrity of meaning) through CFAA §1030(e)(8), DMCA §1201, DTSA, terms-of-service bootstrapping, and the June 2026 executive instruments; the one-way valve after Moody v. NetChoice; the Nightshade inversion; the mode argument (law without jurisprudence); intervention under no-cycle conditions; falsification conditions with a 24-month window.