no_std Crypto in Rust: Determinism, Side Channels, and Constraints

Monthly research note. Theme: Quantum-Resilient Systems Engineering.

TL;DR

no_std Crypto in Rust: Determinism, Side Channels, and Constraints as an engineering constraint: write down assumptions, make invariants executable, and design operational recovery as part of correctness.

Key takeaways

• Inventory long-lived secrets first; you can’t migrate what you can’t locate.
• Measure cost shifts (CPU/bandwidth) and adapt DoS defenses accordingly.
• Define success metrics beyond “enabled”: cohorts, failures, and evidence.
• Measure correctness signals, not only latency/throughput.
• Bind security decisions to evidence (audit, invariants, telemetry).

Why this matters

• Long-lived devices and PKI lifecycles are the hard constraint.
• Cost changes drive new DoS surfaces; defenses must evolve.
• Quantum risk is uneven: some secrets must last decades, others do not.
• Hybrid protocols fail if binding is unclear or downgrade is possible.

Key questions

• What does rotation look like at fleet scale (devices, certs, tunnels, identities)?
• How do you validate resilience (DoS, side channels, rollback, compromise)?
• How do you stop downgrade under active adversaries?
• How do you manage mixed deployments across regions and vendors?
• Which protocols need hybrid now, and which can wait without regret?
• How do you define success metrics for PQ readiness beyond “enabled”?

Assumptions

• Key and certificate lifecycles outlive application versions.
• Operational teams need safe playbooks; crypto changes are not one-off.
• Adversaries record traffic today (HNDL) and attack later.
• Rollouts happen under partial adoption; compatibility matters.

Non-goals

• Relying on ‘automatic’ negotiation without downgrade resistance.
• Switching algorithms without inventorying where secrets are used.

Model & invariants

Risk is a function of exposure and lifetime:

Make downgrade resistance explicit and test it like a security feature.

Inventory first. You can’t migrate what you can’t locate.

Security properties

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

Failure modes

• Config drift that weakens security posture over time.
• Mixed-version behavior that violates assumptions silently.
• Timeout ambiguity causing double-apply or partial state transitions.
• Recovery paths that only work when nothing is broken.

Design sketch

flowchart LR
  threat["Threat Model (quantum + classical)"] --> design["Protocol Design"]
  design --> impl["Implementation (no_std where needed)"]
  impl --> verify["Verification (tests + formal)"]
  verify --> ops["Operationalization (rotation + monitoring)"]
  ops --> threat

Implementation notes

Operationalize early: rollback and monitoring are part of the design.

// PQ migration note: "enabled" is not "safe" unless binding and downgrade resistance are explicit.

Verification strategy

• Performance profiling under load to quantify DoS risk.
• Downgrade simulations with active attackers.
• Side-channel audits for constrained implementations.
• Rotation drills: certificates, tunnels, device identities.
• Interop tests across stacks and versions.

Operational notes

• Define compatibility windows and communicate them to stakeholders.
• Maintain an inventory of long-lived secrets and their lifetimes.
• Practice emergency deprecation (turn off broken algorithms quickly).
• Add telemetry for algorithm negotiation and failure modes.
• Roll out hybrid with canaries and explicit rollback triggers.

What to monitor

• Retry/timeout rates by endpoint and client cohort.
• Error budget burn + tail latency under load.
• Invariant violation rate (should be ~0).
• Admission-control / rate-limit rejections (by reason).
• Rollback events and the conditions that triggered them.

Rollback plan

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

Evidence

• RFC 8446: TLS 1.3 (1) — A useful reference for handshake structure and downgrade resistance patterns.
  • Evidence: Handshake transcript binding and downgrade resistance patterns; monitor negotiation paths and failure reasons.
• Learn TLA+ (2) — Practical entry point for specification and model checking.
  • Evidence: Model the smallest thing that can break; use model checking to validate invariants before optimizing.

Open questions

• How do you prevent configuration drift from re-enabling weak modes?
• Which protocol surfaces are most exposed to HNDL risk in your environment?
• What is your plan for third-party dependencies that can’t migrate quickly?
• What is your minimal ‘safe mode’ when PQ paths fail?

Checklist

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

Further reading

• RFC 8446: TLS 1.3 — A useful reference for handshake structure and downgrade resistance patterns.
• NIST Post-Quantum Cryptography Project — The standardization baseline for PQC readiness programs.
• Let's Encrypt Incident Reports — Operational lessons relevant to rotation and recovery at scale.
• Designing Data-Intensive Applications (Kleppmann) — The systems-engineering baseline for correctness, replication, and failure.
• Jepsen — Fault injection and correctness testing for distributed systems.
• Learn TLA+ — Practical entry point for specification and model checking.