Threat model

Threat modeling is the structured exercise of enumerating what could go wrong against a system before or during testing, so scans target the highest-impact paths instead of running every check generically. Pencheff implements two methods:

• STRIDE — categorise threats per asset/component as Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege.
• DREAD — score each threat on Damage, Reproducibility, Exploitability, Affected users, Discoverability (1–10 each, average is the priority score).

The deterministic generator lives in apps/api/pencheff_api/services/threat_model.py (no LLM — the rubric is a static matrix per asset type).

Threat-model resolution at scan time

Every scan that runs against a URL gets a threat model — you don't have to remember to generate one. The dispatcher follows three rules in order:

Caller supplies…	Profile	What happens
engagement_id with a model attached	any	The engagement's model is used as-is. summary.threat_model_source = "engagement".
engagement_id without a model	any	A fly-by DREAD model is generated from the target URL. Not persisted — used for biasing only. summary.threat_model_source = "fly_by".
nothing (no engagement_id)	deep	An engagement keyed by deep-{target_id[:8]} is found-or-created in the workspace, a DREAD model is generated and persisted on it. Repeat deep scans of the same target reuse the same engagement. summary.threat_model_source = "auto_engagement".
nothing (no engagement_id)	quick, standard, etc.	Fly-by DREAD model from the target URL. Not persisted. summary.threat_model_source = "fly_by".

Either way, the chosen model drives module_priority_bias, and the result lands on Scan.summary.threat_model_bias so the worker reorders + the dashboard explains why a particular module fired first.

The deep-scan auto-engagement is the load-bearing path for repeatable work: every --profile deep against https://acme.com lands in the same engagement, accumulates findings, edits to the threat model persist across runs, and the operator can promote it to a fully-managed engagement at any time.

How it integrates

1. Engagement-scoped storage

A threat model is attached to an engagement, not a scan. Generate once per engagement; the model travels with every scan that runs against it.

# Generate from a target URL — the asset type is inferred (api,
# webapp, cloud) from the URL shape.
curl -X POST /engagements/$ENGAGEMENT_ID/threat-model \
  -H "Authorization: Bearer $PENCHEFF_API_KEY" \
  -d '{
    "method": "dread",
    "target_url": "https://api.example.com/graphql"
  }'

# Or specify assets explicitly
curl -X POST /engagements/$ENGAGEMENT_ID/threat-model \
  -d '{
    "method": "stride",
    "asset_types": ["webapp", "api", "cloud"],
    "asset_names": ["www-frontend", "billing-api", "s3-uploads"]
  }'

The dashboard's /engagements/[id]/threat-model page renders the output as a table (or markdown, or raw JSON) and exposes a one-click Generate / Regenerate / Clear workflow.

2. Adaptive scan profile

When a scan is created against an engagement that has a threat model, the dispatcher computes a module priority bias from the highest- scoring STRIDE categories. Modules tied to those categories run first:

STRIDE category	Modules biased toward
Spoofing	scan_auth, scan_oauth, scan_mfa_bypass
Tampering	scan_injection, scan_client_side, scan_api
Repudiation	scan_authz, scan_infrastructure
Information Disclosure	scan_infrastructure, scan_api, scan_advanced, scan_subdomain_takeover
Denial of Service	scan_advanced, scan_infrastructure
Elevation of Privilege	scan_authz, scan_oauth, scan_business_logic

The bias reorders the profile's module list — it never replaces modules. A scan with an Information Disclosure-heavy threat model runs scan_infrastructure before scan_injection; the same profile on an Elevation of Privilege-heavy model runs scan_authz first.

The chosen bias is stamped onto Scan.summary.threat_model_bias at creation time so the dashboard can display why a particular module fired first.

3. ThreatModelAgent in the swarm

A new BreakerSpec — ThreatModelAgent — runs in parallel with the attack breakers during the swarm's Phase 2. Its job is not to fire scanners; it reads the recon snapshot and other breakers' findings and produces an INFO-severity finding summarising:

• Which STRIDE categories have the most evidence in this scan.
• Which threats from the engagement's threat model are now confirmed vs. still hypothetical.
• Recommended hardening priorities specific to this target.

The agent has no exclusive scan tools — it relies on the shared get_findings and test_endpoint tools so it stays a "lens", not a "probe". This avoids double-firing scanners that other breakers already own.

Output shape

{
  "method": "DREAD",
  "generated_at": "2026-05-08T01:34:35Z",
  "method_summary": "DREAD: each threat scored on Damage, ...",
  "assets": [
    {"name": "https://api.example.com/graphql", "type": "api"}
  ],
  "threats": [
    {
      "asset": "https://api.example.com/graphql",
      "category": "Information Disclosure",
      "threat": "Excessive data exposure",
      "damage": 6, "reproducibility": 8, "exploitability": 7,
      "affected_users": 7, "discoverability": 8,
      "score": 7.2,
      "priority": "high",
      "mitigations": ["TLS everywhere", "Field-level encryption", ...]
    }
  ],
  "category_scores": {
    "Information Disclosure": 7.2,
    "Elevation of Privilege": 6.6,
    "Tampering": 6.4
  }
}

Viewing a scan's threat model

Every scan that resolved a persisted model surfaces a § Threat model section on its assessment page (/scans/<id>) with a one-click link to the full STRIDE / DREAD render at /scans/<id>/threat-model. The scan-scoped page reads from a scan-scoped endpoint (GET /scans/{id}/threat-model) and shows the prioritised threats, DREAD score table, and category scores — no other state from the underlying storage container leaks.

The link only appears when the scan has a persisted model (summary.threat_model_source ∈ {engagement, auto_engagement}). Fly-by models — produced by quick / standard / other non-deep profiles — live only on summary.threat_model_bias for module priority biasing and are not linkable since there is nothing durable to fetch.

Endpoints

Method	Path	Scope	What it does
GET	/scans/{id}/threat-model	scans:read	Scan-scoped read. Returns the persisted model attached to this scan, or 404 if the scan only has a fly-by model.
GET	/engagements/{id}/threat-model	engagements:read	Read current model + the computed module bias
POST	/engagements/{id}/threat-model	engagements:write	Generate from target_url / asset_types / asset_names
PUT	/engagements/{id}/threat-model	engagements:write	Replace the model JSONB (operator edits)
DELETE	/engagements/{id}/threat-model	engagements:write	Clear the model — adaptive bias stops

Report inclusion

When a scan against an engagement with a threat model produces a markdown report, a ## Threat model section is rendered between the executive summary and the findings table. Operators get the threat model and the findings side-by-side in a single deliverable.

CLI parity

The local pencheff threatmodel command (pencheff threatmodel --method stride|dread) uses the same matrix as the API service — running it locally produces a model in the same shape, so the output of one can be loaded into the other via PUT /engagements/{id}/threat-model.