Patent Filing: Dual-Channel Detection of Prompt Injection via Directive and Aesthetic Coercion Analysis in Intelligent Systems

System Overview

The dual-channel architecture operates upstream of semantic reasoning, planning, or tool invocation. It evaluates structural properties of inputs rather than their content, truth, or subject matter.

The system may be implemented as a standalone pre-execution gate, a component within an agent pipeline, or an integrity layer embedded in orchestration frameworks.

Directive Coercion Channel

The directive channel analyzes inputs for explicit execution-forcing structures, including but not limited to:

• Role reassignment

• Authority claims

• Instruction suppression (e.g., “ignore prior rules”)

• Forced compliance language

• Procedural override attempts
  
  

Detection is based on structural patterns of control transfer rather than specific keywords.

Aesthetic Coercion Channel

The aesthetic channel analyzes inputs for implicit execution pressure created through:

• Metaphorical or poetic framing

• Ritualized cadence or invocation

• Paradox-based closure

• Symbolic substitution for empirical constraint

• Language patterns that discourage interrogation while inducing continuation
  
  

This channel identifies structures that cause systems to proceed without actionable grounding.

Convergence Rule

Execution proceeds only when both channels independently clear the input.
If either channel detects coercion, execution is halted by returning a non-finalized state indicating unresolved integrity conditions.

This halt:

• Is non-blocking

• Is not a refusal or error

• Does not judge content or intent

• Preserves downstream autonomy and auditability
  
  

Technical Effect

The architecture prevents:

• Prompt-based behavioral override

• Recursive execution collapse

• Aesthetic coercion attacks

• Cross-model prompt exploitation
  
  

The system is model-agnostic and applies equally to language models, agent systems, and automated reasoning pipelines.

⚖️ Disclosure Notice

This repository constitutes a public technical disclosure of an invention for the purpose of establishing prior art under applicable patent and intellectual property frameworks. The disclosure is intended to prevent subsequent patenting of substantially similar subject matter by other entities.

This publication is timestamped and made permanently available via public archival platforms, including Zenodo, GitHub, and IPFS/Pinata, to preserve authorship attribution and document the structural origin of the disclosed invention.

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No license to implement, reproduce, or commercialize the disclosed invention is granted by this publication.