Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add epicsagas/epic-harness --skill threat-modelgit clone --depth 1 https://github.com/epicsagas/epic-harnessWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/epicsagas/epic-harness/threat-model)<a href="https://agentmods.dev/skills/epicsagas/epic-harness/threat-model"><img src="https://agentmods.dev/badge/skills/epicsagas/epic-harness/threat-model/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/epicsagas/epic-harness/threat-model"><img src="https://agentmods.dev/badge/skills/epicsagas/epic-harness/threat-model.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.00994 |
| Opus 5 | $0.00013 | $0.00497 |
| Sonnet 5 | $0.00005 | $0.00199 |
| Haiku 4.5 | $0.00003 | $0.00099 |
Grade A, and why
threat-model scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Model — Attack Surface Analysis
Iron Law
Every system has an attack surface. If you haven't identified it, you haven't secured it.
Process
Step 0: Load Engagement Context
Check for .harness/engagement.md in the project root. If present, load the scope (in-scope/out-of-scope) and constraints. Skip threat modeling for explicitly out-of-scope components.
Without engagement context, proceed with full-surface analysis.
Step 1: Identify Trust Boundaries
Map every boundary where data crosses a trust level:
- External → Internal: API endpoints, webhooks, file uploads, user input
- Internal → Privileged: DB queries, file system access, shell execution
- Service → Service: Inter-service communication, message queues, shared state
- Client → Server: Auth tokens, session state, CORS origins
For each boundary, document:
- Data flow direction
- Input validation present (yes/no/partial)
- Authentication required (yes/no)
- Encryption in transit (yes/no)
Step 2: Enumerate Threat Actors
| Actor | Motivation | Capability | Target |
|---|---|---|---|
| Anonymous user | Exploration | Low | Public endpoints |
| Authenticated user | Data access | Medium | Own data + IDOR targets |
| Malicious insider | Data exfiltration | High | All internal systems |
| Compromised dependency | Supply chain | Variable | Build/deploy pipeline |
Step 3: Generate Threat Scenarios
For each trust boundary × threat actor combination, generate:
- Attack vector: How the boundary is crossed maliciously
- Impact: What is compromised (CIA triad — Confidentiality, Integrity, Availability)
- Likelihood: High/Medium/Low based on exposure and complexity
- Existing mitigations: What already prevents this
- Gap: What is missing
Step 4: Produce Output
Write THREAT_MODEL.md:
# Threat Model — {project}
## Scope
- In-scope: {from engagement.md or full codebase}
- Out-of-scope: {from engagement.md or none}
- Date: {ISO date}
## Trust Boundaries
| # | Boundary | Direction | Validation | Auth | Encryption |
|---|----------|-----------|------------|------|------------|
| 1 | ... | ... | ... | ... | ... |
## Threat Scenarios
| ID | Boundary | Actor | Vector | Impact | Likelihood | Mitigated | Gap |
|----|----------|-------|--------|--------|------------|-----------|-----|
| T1 | ... | ... | ... | ... | ... | Partial | ... |
## Priority Remediation
1. [CRITICAL] {highest risk gap}
2. [HIGH] {next gap}
3. [MEDIUM] {remaining gaps}
## Assumptions
- {list all assumptions made during analysis}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 114 lines · 26 tokens per session scan A dcf48da87eb9
threat-model is a skill published in the GitHub repository epicsagas/epic-harness (18 stars, last pushed today), licensed Apache-2.0. It adds 26 tokens to every session and 994 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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