Backup/Restore as a Protocol: RPO/RTO with Adversaries

Monthly research note. Theme: DevSecOps & Resilience Engineering.

TL;DR

A focused memo on Backup/Restore as a Protocol: RPO/RTO with Adversaries: define the model, state the properties, then design the system so those properties remain true under failure and adversaries.

Key takeaways

• Provenance is a cryptographic statement; ship evidence with artifacts.
• Treat CI/CD as attacker-controlled until proven otherwise; minimize secrets and privileges.
• Short-lived credentials (OIDC) beat long-lived tokens in pipelines.
• Write assumptions down; treat them as interfaces.
• Measure correctness signals, not only latency/throughput.

Why this matters

• Rollouts are where incidents happen; safe rollback is a security feature.
• Supply-chain attacks target your CI/CD because it has keys and reach.
• Runtime security needs evidence pipelines, not just dashboards.
• Secrets in CI turn “one compromised job” into “full compromise.”

Key questions

• How do you prevent “break glass” from becoming the standard path?
• Which signals prove correctness (not just availability) in production?
• How do you rehearse incident response as code (runbooks, chaos, drills)?
• How do you manage secrets without long-lived credentials in CI?
• What is your supply-chain threat model (dependency poisoning, CI compromise)?
• Where do you enforce policy (pre-merge, build, deploy, runtime)?

Assumptions

• Rollbacks must be executed under time pressure.
• Dependencies can be compromised upstream (typosquatting, maintainer takeover).
• CI runners are exposed to untrusted code (PRs, dependencies).
• Policy enforcement must be consistent across environments.

Non-goals

• Assuming deploy equals success without runtime evidence.
• Manual policy enforcement or manual security review as the only control.

Model & invariants

A policy gate is a predicate over metadata:

Treat CI as attacker-controlled until proven otherwise; minimize secrets and privileges.

Make provenance verifiable: “what built this” must be cryptographically bound.

Security properties

• Evidence: critical actions emit verifiable audit events.
• Authenticity: actions are bound to identity and purpose.
• Replay resistance: duplicated inputs do not change outcomes.
• Downgrade resistance: negotiation can’t silently weaken security posture.

Failure modes

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

Design sketch

flowchart TD
  pr["PR"] --> checks["Checks"]
  checks --> merge["Merge"]
  merge --> release["Release"]
  release --> canary["Canary"]
  canary --> prod["Prod"]
  prod --> rollback["Rollback Plan"]

Implementation notes

Prefer short-lived credentials (OIDC) and explicit policy gates.

CI hardening checklist:
- No long-lived secrets in CI
- OIDC to obtain short-lived creds
- Pin dependencies and verify integrity
- Reproducible builds + provenance attestation
- Policy-as-code gates (deploy blocked on evidence)

Verification strategy

• Runtime conformance: detect drift between desired and actual state.
• Pipeline attack simulations: compromise a runner and measure blast radius.
• Policy tests: unit tests for policy-as-code rules.
• Dependency tampering drills: lockfile changes, integrity failures.
• Rollback tests as part of release (not “if needed”).

Operational notes

• Treat policy changes as security-sensitive deploys (review + rollout).
• Rehearse incident response for the pipeline itself.
• Keep a provenance trail for every artifact deployed to production.
• Continuously scan and inventory dependencies; prioritize by exposure.
• Audit who can ship and how; remove implicit paths.

What to monitor

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

Rollback plan

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

Evidence

• Learn TLA+ (1) — Practical entry point for specification and model checking.
  • Evidence: Model the smallest thing that can break; use model checking to validate invariants before optimizing.
• 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

• Can you answer “what code is running” with cryptographic evidence?
• Which deploy actions are irreversible and how do you mitigate that?
• How quickly can you revoke all pipeline credentials in an incident?
• What is the smallest CI compromise that becomes a prod compromise today?

Checklist

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

Further reading

• NIST SP 800-218 (SSDF) — Secure software development practices as an engineering framework.
• SLSA v1.0 Specification — Supply-chain levels and provenance requirements.
• Sigstore — Signing and verifying artifacts at scale with transparency logs.
• in-toto — Securing the integrity of software supply chains with attestations.
• Learn TLA+ — Practical entry point for specification and model checking.
• Jepsen — Fault injection and correctness testing for distributed systems.