threat-modeling

name	threat-modeling
description	Structured threat modeling for systems, features, and architecture changes — STRIDE plus OWASP/ATT&CK, calibrated by impact and likelihood. Use when asked for a threat model or design security review, or when someone describes a design and asks "is this secure?" / "how could this be abused?" / "what could go wrong?"

Threat Modeling

Threat modeling answers one question: what could go wrong, and does it matter enough to fix? Frameworks structure the thinking — they don't replace it. Understand the system first, then apply structured analysis to surface threats you might otherwise miss.

The process

1. Understand the system

Before naming threats, establish:

• What does it do? Core function, data handled, happy path
• Who are the actors? Legitimate users, admins, external services, anonymous callers — and potential adversaries
• What's valuable? What would an attacker want to steal, corrupt, disrupt, or impersonate?
• What are the trust boundaries? Where does data or control flow from one trust level to another — across a network, a process boundary, between user roles, between internal and external systems?

Sketch data flows and trust boundaries explicitly, even in prose. Threats live at boundaries.

2. Enumerate threats with STRIDE

For each trust-boundary crossing and each significant component, work through:

• Spoofing — false identity claims (credential theft, token replay, DNS spoofing, ARP poisoning)
• Tampering — undetected modification of data in transit or at rest (MITM, SQL injection, parameter manipulation, log tampering)
• Repudiation — denying an action was taken (missing audit logs, unsigned operations, log deletion)
• Information Disclosure — sensitive data reaching unauthorized parties (IDOR, over-permissive APIs, error messages, side channels)
• Denial of Service — degrading or denying availability (resource exhaustion, algorithmic complexity, missing rate limits, state exhaustion)
• Elevation of Privilege — gaining more access than intended (role bypass, JWT manipulation, path traversal, deserialization)

For each threat that applies: name it, describe the realistic attack path (who does what, from where), estimate impact and likelihood.

3. Layer in OWASP and ATT&CK

STRIDE is comprehensive but abstract. Supplement with:

OWASP Top 10 — sanity check on the most common real-world web/API vulnerabilities: broken access control, cryptographic failures, injection, insecure design, security misconfiguration, vulnerable components, authentication failures, software integrity failures, logging failures, SSRF.

MITRE ATT&CK (including ICS/IoT) — useful when the system touches networks, devices, or operational infrastructure. ATT&CK frames threats in terms of attacker TTPs, helping you see realistic attack chains rather than isolated vulnerabilities. ATT&CK for ICS adds protocol abuse, firmware manipulation, and lateral movement through device trust chains.

Use these as lenses, not checklists. A threat without a plausible attacker or realistic impact isn't worth prioritizing just because a framework names it.

4. Prioritize by risk — calibrated, not uniform

Don't return a flat list of 40 equally-weighted items. Anchor severity to concrete outcomes for this system:

Severity	Anchor
Critical	Persistent attacker control, large-scale data exposure, auth bypass that grants admin, or undetected manipulation of operational systems
High	Bypass of a primary security control, theft of data for one user/tenant, or remote DoS that takes the system offline
Medium	Real but limited impact (single-record disclosure, partial DoS, requires already-compromised account)
Low	Theoretical, requires unrealistic attacker access, or is mitigated by defense-in-depth elsewhere

Be honest. If something is low priority, say so rather than padding the list.

5. Recommend mitigations

For each significant threat, propose a mitigation that is:

• Specific — not "add authentication" but "add resource-level authorization checks verifying the requesting user owns the resource before returning it"
• Proportionate — match the control to the risk; don't recommend HSMs for low-value data
• Practical — acknowledge operational burden; a control that won't be maintained is worse than no control

Dual-use tools

If the system intentionally does things that would be malicious in another context — TLS interception, traffic modification, port scanning, packet capture, fuzzing, scripted breakpoints — its threat model is different from a normal web app. Cover at minimum:

• Misuse by the operator (deliberate or accidental) — what blast radius does the tool grant a privileged user?
• Compromise of the tool itself — if the proxy/scanner/MITM is breached, captured data and intercepted credentials are at stake; lateral risk into intercepted networks may be material
• Captured-data confidentiality — encryption at rest, retention, access logging, redaction
• Outbound legality and consent — note when the tool's operation depends on authorization that lives outside the code (engagement scope, rules of engagement, lab isolation)

Don't bury these in generic STRIDE. They're the highest-impact threats for that class of system.

Output format

System summary — 2–3 sentences on what's analyzed and what's in scope.

Trust boundary map — prose or list of where trust level changes.

Threat findings — grouped by severity (critical → high → medium → low). Each: threat name, attack path, impact, likelihood, recommended mitigation.

Out of scope / assumptions — what you couldn't assess; what you assumed.

A threat model that clearly identifies the 3 things that matter most and explains why is more useful than one with 40 equally-weighted items.

Worked example (abbreviated)

System: a small "share by link" feature — authenticated user creates a token-bearing URL that lets recipients view a single document for 7 days.

System summary: Token-bearing URLs scoped to one document, time-limited.
Trust boundaries: anonymous internet → API; storage of document blobs.

Critical
  Token guessing/brute force — if tokens are short or low-entropy, an attacker
  enumerates URLs and reads documents. Mitigation: 128-bit random tokens,
  rate-limit token-validation endpoint, lock after N failed attempts per IP.

High
  Token leak via logs/referer — tokens in URL path/query are logged by proxies
  and forwarded as Referer when documents include external resources. Mitigation:
  put token in fragment and validate via JS, OR use a short-lived exchange where
  the URL token is swapped for a session cookie on first hit.

Medium
  Revocation gap — owner deletes the doc but issued tokens still validate until
  expiry, depending on storage. Mitigation: validate against a "live document"
  check, not just token signature.

Low
  Side-channel timing on token validation — feasible but bounded; constant-time
  compare resolves it.

Out of scope: authn for the issuing user (assumed sound); virus scanning of
shared blobs (separate control).

The point: anchored severities, concrete mitigations, the 3–4 things that matter — not a flat OWASP recital.