Migration Risk Management: Inventory, Prioritization, and Cutover

Monthly research note. Theme: Post-Quantum Cryptography & Migration.

TL;DR

Migration Risk Management: Inventory, Prioritization, and Cutover as an engineering constraint: write down assumptions, make invariants executable, and design operational recovery as part of correctness.

Key takeaways

• Hybrid composition must be explicit and transcript-bound to resist downgrade.
• PQC changes handshake costs; plan DoS defenses and budgets.
• Migration is mixed-version for years: compatibility and rollback are security features.
• Measure correctness signals, not only latency/throughput.
• Define safety properties before performance goals.

Why this matters

• Constant-time constraints are harder under large primitives.
• Hybrid designs fail if binding is ambiguous (mix-and-match, downgrade).
• Operationalization (monitoring, rollback) determines success more than crypto choice.
• Migration will be mixed-version for years; plan for it explicitly.

Key questions

• What does interoperability testing look like across vendors and stacks?
• What are the new DoS surfaces (bigger keys, more CPU, more bandwidth)?
• How do you handle failures: decryption failures, invalid ciphertexts, malformed keys?
• How do you bind hybrid secrets to prevent downgrade and mix-and-match attacks?
• Which parts must be constant-time, and how will you validate that?
• How do you rotate algorithms safely (crypto agility without chaos)?

Assumptions

• Side channels exist: timing and cache behavior leak information.
• Bandwidth is limited in some environments; larger handshakes matter.
• Active attacker can force retries, downgrades, and expensive handshakes.
• Deployments are mixed; old clients must interoperate or fail safely.

Non-goals

• Treating migration as a single flag flip.
• Assuming PQC is “drop-in” without changing operational processes.

Model & invariants

A KEM gives you shared secrets without discrete-log assumptions:

Binding is the whole game: make the transcript an input to the KDF.

Make costs explicit: measure CPU and bandwidth, then add protections.

Security properties

• Evidence: critical actions emit verifiable audit events.
• Integrity: invalid transitions are rejected (and detectable).
• Least authority: privileges are scoped by purpose and time.
• Downgrade resistance: negotiation can’t silently weaken security posture.

Failure modes

• Recovery paths that only work when nothing is broken.
• Resource exhaustion (CPU/bandwidth/storage) turning into correctness failures.
• Mixed-version behavior that violates assumptions silently.
• Observability gaps during incidents (missing evidence).

Design sketch

sequenceDiagram
  participant A as Initiator
  participant B as Responder
  A->>B: classical_keyshare + pqc_pk
  B-->>A: classical_keyshare + pqc_ct + sig
  A-->>B: sig
  Note over A,B: ss = HKDF(ss_classical || ss_pqc, transcript)

Implementation notes

Interop tests are the migration plan; everything else is a hypothesis.

// Hybrid binding sketch (pseudocode):
// ss = HKDF(ss_classical || ss_pqc, info=transcript_hash)
// Then derive traffic keys from ss.

Verification strategy

• DoS tests: measure CPU/bandwidth amplification and mitigation impact.
• Side-channel tests where tooling exists; constant-time audits.
• Interop matrices across vendors/versions and failure modes.
• Downgrade tests: active attacker manipulates negotiation.
• Chaos deploys: mixed versions + rollback during partial outages.

Operational notes

• Document supported algorithm sets and deprecation timelines.
• Roll out with canaries and explicit rollback triggers.
• Add telemetry for negotiation outcomes, failures, and client cohorts.
• Inventory long-lived secrets and migrate the highest-risk first.
• Cap handshake cost per peer/IP; use stateless cookies when needed.

What to monitor

• Retry/timeout rates by endpoint and client cohort.
• Authz failures and policy denials (unexpected spikes).
• Invariant violation rate (should be ~0).
• Error budget burn + tail latency under load.
• Rollback events and the conditions that triggered them.

Rollback plan

• Keep dual-write / dual-verify windows where appropriate.
• Use canaries and staged rollout; stop early when signals degrade.
• Preserve evidence (configs, artifacts, audit logs) to reconstruct what changed.
• Prefer backward-compatible changes; avoid “flag day” upgrades.
• Define an explicit rollback trigger (metrics + thresholds).

Evidence

• NIST Post-Quantum Cryptography Project (1) — Standardization process and algorithm selections.
  • Evidence: Treat PQ migration as a program (inventory, interop, rollback). Use NIST status to drive prioritization and timelines.
• Jepsen (2) — Fault injection and correctness testing for distributed systems.
  • Evidence: Turn faults into test cases; prioritize partition and clock-skew scenarios that violate user-visible guarantees.

Open questions

• Which clients will fail first, and what is the safe fallback behavior?
• What is the worst-case handshake cost under attack?
• How do you rotate algorithms without introducing configuration chaos?
• Where would a downgrade be visible today, and how would you detect it?

Checklist

• Failure modes enumerated with mitigations.
• Costs bounded (CPU/memory/bandwidth) under adversarial inputs.
• Rollback plan rehearsed and automated.
• Assumptions listed and reviewed.
• Telemetry captures correctness signals.
• Safety properties stated as invariants.

Further reading

• CRYSTALS-Kyber — KEM design and parameters commonly referenced in deployments.
• NIST Post-Quantum Cryptography Project — Standardization process and algorithm selections.
• RFC 5869: HKDF — Useful when discussing hybrid binding and context separation.
• CRYSTALS-Dilithium — Signature scheme design and deployment constraints.
• Site Reliability Engineering (Google) — Error budgets, incident response, and reliability as an engineering discipline.
• Jepsen — Fault injection and correctness testing for distributed systems.