Side Channels in PQC Implementations: Where Theory Meets Cache

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

TL;DR

Side Channels in PQC Implementations: Where Theory Meets Cache as an engineering constraint: write down assumptions, make invariants executable, and design operational recovery as part of correctness.

Key takeaways

• Interop is the migration plan—test matrices are more important than whitepapers.
• Hybrid composition must be explicit and transcript-bound to resist downgrade.
• Migration is mixed-version for years: compatibility and rollback are security features.
• Make failure modes explicit and observable.
• Define safety properties before performance goals.

Why this matters

• PQC changes bandwidth and CPU costs; DoS surfaces move.
• Operationalization (monitoring, rollback) determines success more than crypto choice.
• Interop is the real risk: multiple stacks, vendors, and versions.
• Hybrid designs fail if binding is ambiguous (mix-and-match, downgrade).

Key questions

• What are the new DoS surfaces (bigger keys, more CPU, more bandwidth)?
• What does interoperability testing look like across vendors and stacks?
• How do you handle failures: decryption failures, invalid ciphertexts, malformed keys?
• Which secrets require long-term confidentiality (HNDL) and where are they today?
• What telemetry proves PQC is working (not just enabled)?
• Which parts must be constant-time, and how will you validate that?

Assumptions

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

Non-goals

• Relying on silent fallback to weaker modes during interop failures.
• Ignoring DoS implications of large primitives.

Model & invariants

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

Treat algorithm negotiation as adversarial: explicit downgrade resistance.

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

Security properties

• Least authority: privileges are scoped by purpose and time.
• Integrity: invalid transitions are rejected (and detectable).
• Authenticity: actions are bound to identity and purpose.
• Evidence: critical actions emit verifiable audit events.

Failure modes

• Config drift that weakens security posture over time.
• Observability gaps during incidents (missing evidence).
• Recovery paths that only work when nothing is broken.
• Timeout ambiguity causing double-apply or partial state transitions.

Design sketch

flowchart TD
  negotiate["Negotiate Algorithms"] --> bind["Bind Transcript"]
  bind --> kdf["KDF (hybrid)"]
  kdf --> keys["Traffic Keys"]
  keys --> monitor["Monitor + Rollback"]

Implementation notes

Explicit binding prevents downgrade and mix-and-match. Don’t leave it implicit.

// 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.
• Downgrade tests: active attacker manipulates negotiation.
• Chaos deploys: mixed versions + rollback during partial outages.
• Interop matrices across vendors/versions and failure modes.

Operational notes

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

What to monitor

• Retry/timeout rates by endpoint and client cohort.
• Authz failures and policy denials (unexpected spikes).
• Invariant violation rate (should be ~0).
• Admission-control / rate-limit rejections (by reason).
• Rollback events and the conditions that triggered them.

Rollback plan

• 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).
• Keep dual-write / dual-verify windows where appropriate.

Evidence

• RFC 5869: HKDF (1) — Useful when discussing hybrid binding and context separation.
  • Evidence: HKDF is the workhorse for domain separation; bind purpose/context to avoid cross-protocol key reuse.
• 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

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

Checklist

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

Further reading

• RFC 5869: HKDF — Useful when discussing hybrid binding and context separation.
• CRYSTALS-Kyber — KEM design and parameters commonly referenced in deployments.
• NIST Post-Quantum Cryptography Project — Standardization process and algorithm selections.
• CRYSTALS-Dilithium — Signature scheme design and deployment constraints.
• Jepsen — Fault injection and correctness testing for distributed systems.
• Learn TLA+ — Practical entry point for specification and model checking.