Threat Modeling

Threat Modeling

Find the attacks on paper, before the code exists. A security-audit reviews what was built; a threat model shapes what gets built.

When to use

• Designing anything that touches auth, money, PII, file uploads, or external input
• "How could this be abused?" / "Is this design secure?"
• Adding a new integration, webhook, or API surface
• Before spec-writing finalizes scope for a sensitive feature

Principles

• Think like the attacker, list like an engineer. Creative in finding threats, systematic in recording them.
• Trust boundaries are where it happens. Every place data crosses from less-trusted to more-trusted is a finding generator.
• Rank ruthlessly. Ten mitigated critical threats beat a hundred documented trivial ones.
• Assume breach of the outer layer. "The WAF catches that" is not a mitigation; defense has depth or it doesn't.

Process

1. Scope and assets

• What are we protecting? (credentials, PII, money/credits, business data, availability, reputation)
• Who are the realistic attackers? (anonymous internet, authenticated user, malicious insider, compromised dependency)

2. Draw the data flow

Sketch components and the data moving between them (text diagram is fine):

[Browser] --creds--> [API] --query--> [DB]
                       |--webhook--> [3rd party]

Mark every trust boundary: internet→app, app→db, app→third party, user→admin, tenant→tenant.

3. Walk STRIDE per boundary

| Category | Ask | |---|---| | Spoofing | Can someone pretend to be another user/service here? | | Tampering | Can data be modified in transit or at rest? | | Repudiation | Can an actor deny an action because we can't prove it? | | Information disclosure | What leaks — errors, timing, IDs, logs, caches? | | Denial of service | What's cheap for an attacker and expensive for us? | | Elevation of privilege | Path from low-priv to high-priv? (IDOR, mass assignment, admin routes) |

Also walk the abuse cases: how would a legitimate user cheat? (free-tier laundering, scraping, referral fraud)

4. Rank

Score each threat simply: likelihood (L/M/H) × impact (L/M/H). Anything H×H or H×M gets a mitigation in the design; M×M gets a mitigation or an explicit accepted-risk note; the rest is documented.

5. Mitigate in the design

For each ranked threat, name the concrete control: authz check at X, signed URLs, rate limit per Y, idempotency keys, audit log of Z, input validation at the boundary. Each mitigation should be traceable into the spec/tasks.

6. Decide residual risk

What remains unmitigated, who accepted it, and what would trigger revisiting.

Output format

## Threat model: 

**Assets:** …
**Attackers considered:** …

### Data flow & trust boundaries

### Threats
| # | Threat (STRIDE) | Boundary | L×I | Mitigation | Status |
|---|-----------------|----------|-----|------------|--------|
| 1 | …               | …        | H×M | …          | in design / accepted |

### Accepted risks
- : accepted by , revisit when 

### Carry into spec
- [ ] 

Anti-patterns

• ❌ Threat modeling after the code is written (that's an audit, and rework is 10× pricier)
• ❌ Only modeling external attackers — insiders and compromised accounts are boundaries too
• ❌ "We use HTTPS" as the answer to everything
• ❌ A 60-row threat table with no ranking and no owner
• ❌ Mitigations that never become spec requirements or tasks — a model nobody builds from is theater
• ❌ Forgetting abuse cases: the attacker with valid credentials and creative incentives

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: kwhorne
• Source: kwhorne/elyra-skills
• License: MIT
• Homepage: https://elyracode.com

Install and usage instructions live in the source repository linked above.