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docs(blog): state the durable-enforcement rollout as opt-out
The note said workspace files refuse an unknown classification and the other surfaces are being brought up to that bar, which described the effect but not the mechanism, and left the impression that strictness is something surfaces gradually earn. It is the other way round. Omitting a surface enforces, so an unreviewed call site refuses by default; naming one is how a surface opts into reporting while enforcement is rolled out. Three sentences, and the design point leads. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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apps/sim/content/blog/secret-provenance/index.mdx

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**Durable storage.** Files, table cells, knowledge base documents and agent memory all outlive the run that produced them. If provenance stopped at the end of an execution, a secret written in one run and read back in another would launder itself through storage. So durable writes carry an encrypted provenance record and a version marker alongside the content. An empty marker means the row predates the system and is treated as legacy; a set marker means the record has to match. Content whose provenance cannot be established is marked `unknown`, which is deliberately a different state from clean rather than a synonym for it.
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Not every surface enforces that state at the same strictness yet. Workspace files refuse an unknown classification outright; the others are being brought up to the same bar one at a time, behind configuration, because switching refusal on everywhere at once would reject a large volume of rows written before any of this existed.
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Enforcing that is a rollout, and it is deliberately opt-*out*. A caller that names no surface refuses an `unknown` classification outright, which is what anything unreviewed gets by default. The surfaces that do name one — agent memory, table rows, knowledge documents — currently record the gap instead of failing the run, while enforcement is switched on one surface at a time.
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**Tool results.** A result crossing back into the model goes through the same machinery, against the JSON-normalized value rather than the raw string, so a secret that arrives as a number, a boolean, or a nested field is handled rather than only the top-level strings.
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