Artificial Adaptive Control Language (AACL): State-Bound Ephemeral Grammars for Secure Web Actions

Web applications commonly rely on widely deployed defenses such as tokens, headers, and
server-side validation logic to mitigate request forgery, tampering, and replay. While effective
against many threats, these mechanisms primarily establish authenticity and coarse integrity
— validating who is acting and whether they are authorized — but do not formally enforce
the precise structural and semantic contract of individual stateful action instances. This paper
introduces AACL (Artificial Adaptive Control Language), a language-theoretic control framework
in which the server dynamically issues an ephemeral, intent-bound grammar for each sensitive
action instance. Unlike existing mechanisms, AACL defines and enforces the complete acceptable
form of a specific request instance — constraining structure, parameter relationships, state-
bound semantic values, and temporal validity within a single formal acceptance condition. Each
request is treated as a short-lived language instance and validated through formal recognition
grounded in a deterministic finite automaton (DFA) model before execution. In the prototype
realization, the DFA acceptance condition is implemented as key-set equality over intent-specific
alphabets a tractable and sufficient structural enforcement mechanism for JSON-based web
API payloads. Grammars are state-bound, derived from server-side snapshots at issuance time,
and invalidated after use or expiry, enforcing single-use semantics and preventing replay under
explicit threat-model assumptions. AACL is designed as a complementary enforcement layer
and does not replace authentication, authorization, or transport security rather, it adds
per-instance structural and semantic intent integrity at the language-recognition layer, addressing
a gap that existing mechanisms such as CSRF tokens, JWTs, nonces, and WAFs do not cover.
We formalize the AACL model, describe its integration into a web application architecture,
and present a prototype demonstrating how ephemeral grammars reduce replay and structural
mutation attacks. Empirical evaluation over 5000 requests confirms linear validation complexity
O(n) and modest latency overhead suitable for high-value, sensitive web operations.

Note: 

The prototype described in this paper was realized with AI-assisted tooling (Claude, Anthropic) for code generation and evaluation scripting, as disclosed in Section 11. The author's primary contributions are the conceptual framework, formal model, and security analysis. The prototype serves as a proof-of-concept demonstration of the theoretical acceptance condition rather than a production-ready implementation.

Specifically, the DFA acceptance condition is realized in the prototype as key-set equality — a tractable and sufficient enforcement mechanism for JSON-based API payloads, as stated in the abstract. Full DFA/NFA-based parsing for richer grammar expressiveness remains an avenue for future work (Section 10.1).

This work is a research preprint and has not undergone formal peer review. The formal model, security properties, and empirical measurements are presented to invite scrutiny, collaboration, and extension — particularly toward agentic AI security, MCP-layer enforcement, and Intent Lattice Architecture as outlined in Sections 8 and 10.