Update data_model.md#3012
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Add details to clarify scoring methodology
Removed the previous content and added a new structure for the data model documentation.
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Newest code from alexane-bougeardbebin-sekoia has been published to preview environment 🚀 Latest deployment was built on 2026-05-29 15:18:49 (51235c1f3ed6421866eab3bc5751e339d60a6be7). |
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| | **C3** | Fairly reliable source, possibly true. Use with caution; seek corroboration. | | ||
| | **F6** | Source reliability unknown, truth cannot be judged. Raw, unvalidated data. | | ||
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| In Sekoia's STIX objects, you can approximate this combined rating by cross-referencing the object's `confidence` field with the `confidence` field on the corresponding source `Identity` in `x_inthreat_sources_refs`. |
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I'm not sure that's how it works.
Generally speaking, an IOC would have two sources:
- Sekoia in B2
- Another in F5
I think it will have a high confidence level. I don't know how the score is calculated; you'll have to check with T&P.
In any case, you can keep it general and say: we calculate the confidence score by cross-referencing these sources. We get a score from 1 to 5—where 1 corresponds to A1 and 5 to F/E 5/6 (to be confirmed with T&P). On the platform, we shouldn’t have many IOCs with scores below 3
Removed the decision guide section for observables and indicators from the data model.
Replaced a reference to The MITRE Corporation with a reference to PhishTank in the data model.
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Add details to clarify scoring methodology