Last updated: 2025-01-31
The first time my deployment pipeline failed silently, I didn’t know for three days.
The site loaded. Pages rendered. Everything looked fine. But somewhere between my local build and the CDN, a file had been modified - cached incorrectly, served stale, hash mismatch invisible. I only discovered it when a reader emailed asking why a page showed outdated content.
That’s when I understood: “it works” is not the same as “it’s correct.”
I rebuilt the entire pipeline around one principle: never trust that output matches input. Verify it. Every time. Automatically. And if verification fails, halt everything until a human investigates.
This document is the threat model behind that system. It’s also a translation guide - because the same defensive thinking that protects a deployment pipeline protects a conveyor system, a maintenance schedule, or a safety protocol.
The Core Principle
Security is not the absence of attackers. Security is the presence of verification.
Most systems fail not because of sophisticated attacks, but because of assumptions:
- “The file uploaded correctly” (it didn’t)
- “The credentials are still valid” (they expired)
- “The process ran as expected” (it errored silently)
- “Someone would have noticed” (no one did)
Threat modeling forces you to name those assumptions, test them, and build systems that don’t rely on hope.
System Overview
The deployment pipeline I’m protecting:
| Component | Function | Trust Level |
|---|---|---|
| Source Control | Git repository (GitHub) | High (I control commits) |
| Build System | Makefile with cryptographic verification | High (local execution) |
| Deployment Target | Vercel CDN with static hosting | Medium (third-party infrastructure) |
| Integrity Layer | SHA-256 hash chains with audit logging | High (mathematically verifiable) |
What I’m protecting: Intellectual property, prior art documentation, professional reputation.
What I’m protecting against: Silent corruption, unauthorized modification, integrity drift, my own mistakes.
Trust Boundaries
Every system has zones where trust changes. Identifying those boundaries tells you where verification matters most.
| Boundary | Trusted Zone | Untrusted Zone | Control Mechanism |
|---|---|---|---|
| Source -> Build | Local development environment | External dependencies | Git commit signing, hash verification |
| Build -> Deploy | Verified artifacts | Network transport | TLS encryption, authenticated API calls |
| Deploy -> Serve | CDN infrastructure | Public internet | HTTPS enforcement, security headers |
| User -> Content | Verified static content | Browser environment | CSP headers, no dynamic execution |
The pattern: Trust degrades as you move away from source. Every boundary crossing requires verification.
Threat Categories
T-001: Supply Chain Compromise
What could go wrong: Malicious code injected via compromised dependencies or build tools. You trust a library; the library gets hijacked; your system inherits the compromise.
Why it matters: Most developers don’t audit their dependencies. They trust that npm/pip packages are safe because they were safe yesterday.
My mitigations:
- SHA-256 hash verification at build time
- Minimal external dependencies (no npm/pip for core pipeline)
- Makefile-based build system (human-readable, auditable)
- Git commit provenance tracking
Residual risk: Low. The attack surface is small because the dependency surface is small.
RME Translation: This is why you verify part numbers, not just part availability. A counterfeit bearing from a compromised supplier fails the same way a compromised library fails - silently, until it doesn’t.
T-002: Unauthorized Deployment
What could go wrong: Attacker gains access to deployment credentials or Git repository. Pushes malicious content that serves from my domain with my reputation attached.
Why it matters: Credential theft is the most common attack vector. Not because it’s sophisticated, but because it works.
My mitigations:
- GitHub authentication with 2FA enforcement
- Vercel API tokens with scoped permissions
- Audit logging of all deployments (
SOVEREIGN_LOG.md) - Deployment integrity verification post-push
Residual risk: Medium. Credential security depends on my operational discipline.
RME Translation: This is LOTO for digital systems. You don’t just lock the panel - you verify the lock, log who has the key, and check that the energy is actually isolated before you touch anything.
T-003: Content Tampering (CDN)
What could go wrong: CDN cache poisoning or man-in-the-middle attack during content delivery. User receives modified content that I didn’t create.
Why it matters: CDNs are trusted infrastructure, but “trusted” doesn’t mean “infallible.” Caching bugs, configuration errors, and network attacks can all result in wrong content served.
My mitigations:
- HTTPS enforcement (TLS 1.3)
- Post-deployment hash verification (
make audit) - CDN security headers (CSP, HSTS)
- Subresource Integrity (SRI) for external resources
Residual risk: Low. CDN provider handles core security; my audit catches drift.
RME Translation: This is why you verify calibration after the tool leaves the shop. The calibration was correct when certified - but transport, handling, and time can introduce drift. Verify at point of use.
T-004: Denial of Service
What could go wrong: Volumetric attack or resource exhaustion makes the site unavailable.
Why it matters: Availability is part of integrity. A system that can’t be reached can’t serve its purpose.
My mitigations:
- Vercel CDN DDoS protection (provider-level)
- Static content (no compute-intensive operations)
- Rate limiting at CDN edge
- No database or dynamic backend to overwhelm
Residual risk: Low. Static sites are inherently resilient; CDN absorbs volumetric attacks.
RME Translation: This is redundancy planning. A single conveyor failure shouldn’t stop the building. Design for graceful degradation, not single-point dependency.
T-005: Intellectual Property Theft
What could go wrong: Unauthorized copying or misattribution of prior art documentation. Someone claims my work as theirs.
Why it matters: The CYW framework and defensive publications are intellectual property. Provenance matters for legal protection.
My mitigations:
- Public timestamping via Git commit history
- Cryptographic proof of authorship (commit signatures)
- MIT License with attribution requirements
- Defensive publication establishing prior art
Residual risk: Medium. Legal protection, not technical. Enforcement requires legal action.
RME Translation: This is documentation as defense. Maintenance logs aren’t just operational records - they’re evidence. When something fails and someone asks “who touched it last,” the log answers.
Attack Surface Analysis
| Component | Exposure | Attack Surface | Hardening |
|---|---|---|---|
| Git Repository | Public | Read access to all commits | No sensitive data in commits, 2FA for write |
| Build Pipeline | Private | Local machine compromise | Hash verification, minimal dependencies |
| Deployment API | Private | API token exposure | Scoped tokens, rotation policy, secure storage |
| Static Content | Public | XSS, clickjacking | CSP headers, no user input, static HTML only |
The principle: Minimize exposure. What’s not exposed can’t be attacked. What must be exposed gets hardened.
Incident Response Plan
When something goes wrong, panic makes it worse. A documented response plan means you follow protocol instead of improvising under pressure.
Detection
How I know something’s wrong:
make auditautomated integrity checks (scheduled + on-demand)- Vercel deployment logs monitoring
- Manual inspection when something “feels off”
- User-reported anomalies via GitHub issues
Containment
First priority: stop the bleeding.
- Immediate deployment halt
- Rollback to last known good commit
- Revoke potentially compromised credentials
- Isolate affected systems
Eradication
Find the root cause and remove it:
- 5-Why analysis (symptom -> cause -> cause -> cause -> root)
- Remove malicious code/commits
- Patch vulnerabilities
- Verify removal with fresh audit
Recovery
Return to normal operations:
- Redeploy from verified clean state
- Verify integrity with
make audit - Monitor for recurrence
- Staged rollout if trust is low
Lessons Learned
Make the system smarter:
- Document incident in
SOVEREIGN_LOG.md - Update threat model with new attack vector
- Implement preventive controls
- Share learnings (without exposing vulnerabilities)
RME Translation: This is the same framework as equipment failure response. Detect -> Contain -> Eradicate -> Recover -> Improve. The incident isn’t over when the machine starts running - it’s over when you’ve prevented recurrence.
Red Team Testing
A threat model is theory. Red teaming is proof.
Test Scenarios Executed
1. Hash Bypass Attempt
- Manually modified a deployed file
- Ran
make audit - Result: Audit detected mismatch, flagged specific file, halted with error
2. Unauthorized Push Attempt
- Attempted deployment without proper credentials
- Result: Authentication failure, no deployment occurred, attempt logged
3. Rollback Under Pressure
- Simulated compromise discovery
- Executed emergency rollback procedure
- Result: Clean state restored in under 5 minutes, verified with audit
4. Stale Cache Detection
- Introduced deliberate cache inconsistency
- Result: Post-deployment audit caught the mismatch; CDN purge resolved
Findings
All security controls validated. No bypasses discovered in current architecture. Audit system catches both malicious and accidental integrity drift.
RME Translation: This is why you test safety interlocks, not just install them. The light curtain should stop the machine - but have you verified it actually stops the machine? Test under realistic conditions, not just on paper.
Compliance Mapping
For organizations that need to map controls to frameworks:
| Framework | Control | My Implementation |
|---|---|---|
| NIST CSF | PR.DS-6 (Integrity checking) | SHA-256 hash verification, audit logging |
| ISO 27001 | A.12.3.1 (Information backup) | Git version control, commit history |
| OWASP | A03:2021 (Injection) | Static content only, no dynamic execution |
| CIS Controls | 3.3 (Secure configuration) | Vercel security headers, TLS enforcement |
The Safety-First Mindset
Security engineering and safety engineering are the same discipline applied to different failure modes.
| Security Concept | Safety Equivalent | Shared Principle |
|---|---|---|
| Threat modeling | LOTO hazard analysis | Identify failure modes before they occur |
| Defense in depth | Safety interlocks | Multiple controls prevent single-point failures |
| Incident response | Emergency stop procedures | Containment, root cause, prevention |
| Red team testing | Safety audits | Validate controls under adversarial conditions |
| Audit logging | Maintenance records | Traceability when things go wrong |
The translation: If you understand why a hash verification matters for deployment integrity, you understand why a torque verification matters for equipment reliability. Same logic. Different domain.
Why This Matters for RME
I built this threat model for a portfolio site. But the thinking scales.
Conveyors have attack surfaces: Sensors that can fail, PLCs that can misconfigure, maintenance that can be skipped.
Equipment has trust boundaries: The calibration was correct in the shop - is it correct on the floor?
Uptime requires incident response: When something fails at 2 AM, do you have a protocol, or do you have panic?
I don’t just want to secure my deployments. I want to bring this defensive mindset to systems where failure costs more than a broken website - where it costs throughput, safety, or trust.
Connection to Control Your World
Threat modeling is one instantiation of the CYW principle: name the failure modes before they name you.
The same discipline appears across the framework:
- Stoplight Process Health: Identify operational drift before metrics confirm it
- RME Translation Packet: Map deployment concepts to equipment reliability
- This Threat Model: Systematically identify and mitigate risks
Whether the system is software, hardware, or human, the pattern holds:
- Identify what can go wrong
- Assess likelihood and impact
- Implement controls proportional to risk
- Verify controls actually work
- Improve when you learn something new
This is how you Control Your World.
Related Resources:
- RME Translation Packet - How deployment thinking maps to reliability engineering
- Awareness in Action - Early-warning systems for operational drift
- Failure Mode Runbook - Diagnostic trees for common failures
Security isn’t paranoia. It’s protocol.
This is how you Control Your World.