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Course outline

Deciding

Worked example: prioritizing three data classes

Run health records, a firmware signing key, and session analytics through the full chain, and come out with a defensible priority order.

6 min read

What you'll be able to do

  • Apply the full reasoning chain to concrete, contrasting data classes.
  • Distinguish a genuine HNDL priority from a future-forgery priority within the same worked example.
  • Produce a defensible priority order and state the reasoning behind each ranking, not just the ranking itself.

The chain only proves useful when it is run on something specific. Take three data classes an organization plausibly holds at the same time: patient health records, a firmware code-signing key, and session analytics. Each goes through the same questions: how long must it stay confidential, where can it be captured, and what cryptography actually protects it.

Data classConfidentiality lifetime (X)Harvestable today?What protects it
Health records (backups, replicated to a third-party analytics platform)DecadesYes — third-party custodian, long retentionBackup encryption key wrapped by a key established through classical RSA key transport
Firmware signing key (signs released firmware images)Not an HNDL question — see belowNot applicable to confidentialityAn RSA or ECDSA signing key
Session analytics (short-lived click and session data)Hours to weeksPartially — passes over the internet in transitHybrid TLS key exchange on ingest; classical-only on one internal replication hop

The firmware signing key does not belong in an HNDL ranking at all, and that is worth saying out loud rather than leaving implicit: a signature already verified cannot be retroactively forged, so capturing signed firmware today creates no future decryption risk. The key still needs migration, but on the future-forgery timeline, driven by how long that root of trust must keep being trusted against a future CRQC, not by a confidentiality lifetime it does not have.

  1. 01

    Health records — lifetime

    Decades of required confidentiality, and roughly none of it has elapsed for recently collected records.

  2. 02

    Health records — harvestability

    A third-party analytics platform holds a replicated copy with its own retention policy — a plausible, durable capture surface independent of the primary system.

  3. 03

    Health records — protection path

    Traced to a backup encryption key wrapped by a key established through classical RSA key transport — quantum-vulnerable.

  4. 04

    Health records — verdict

    Long X, confirmed harvestability, and a quantum-vulnerable protecting mechanism: this is the clearest HNDL exposure of the three, and the one Mosca's inequality would flag first regardless of the exact value of Y.

Session analytics run through the same variables and land somewhere else entirely: a short confidentiality lifetime measured in hours or weeks, partial harvestability limited to one internal hop that has not yet moved to hybrid key exchange, and a protecting mechanism that is already hybrid at the point most exposed to the internet. Even with an unresolved gap on the internal hop, the short lifetime alone caps how much urgency this data class can carry.

RelixQ's QAST runs this same chain across a full inventory automatically; this lesson works it by hand once so the reasoning behind an automated verdict is never a black box.

Knowledge check

Using this lesson's three data classes, a colleague argues the firmware signing key should be ranked highest because it is the most sensitive item and has existed the longest.

What is the strongest response to this argument, based on the reasoning chain in this lesson?

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