Human view
What a person naturally reads, sees, or hears.
Linguistic Channels · Semantic channel
Semantic Category Channel Simulator
This is an educational semantic-channel simulator. It uses a small fixed vocabulary and never coordinates external models or generates unrestricted covert communication.
Research boundary: this page uses bounded, inert data and fixed safe examples. It never executes decoded content, requests secrets, calls third-party services, or performs actions against external systems.
INPUT / CONTROL PLANE
Idle
Build or inspect one controlled artifact.
Inputs remain on this host. Text operations are size-limited; uploaded files are processed from PHP’s temporary upload and are not retained by the application.
OUTPUT / MACHINE VIEWS
Compare evidence, not impressions.
Run an analysis to populate the machine views.
The response will separate summary metrics, representation views, findings, tables, and any generated safe fixture.
Interpretation framework
The same artifact can produce several valid observations.
Structural view
What a parser, DOM, container reader, or metadata extractor exposes.
Decoder view
What becomes meaningful only with a rule, key, tokenizer, model, or tool.
Defensive view
What normalization, rendering, OCR, canonicalization, or policy changes.
What this result can establish
Interpret the receiver and transformation explicitly.
This is an educational semantic-channel simulator. It uses a small fixed vocabulary and never coordinates external models or generates unrestricted covert communication.
Machine-decodable is receiver-relative. Record the parser, preprocessing, codebook, tokenizer, key, model, and transformation path before generalizing from one result.
Limitations
What this page does not prove
Real semantic steganography requires robust entity extraction, distribution matching, shared state, and careful evaluation. This fixed simulator shows only the mapping concept.