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 RedHatProductSecurity/agentic-threat-modeling --skill threat-model-reviewgit clone --depth 1 https://github.com/RedHatProductSecurity/agentic-threat-modelingWrote 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/redhatproductsecurity/agentic-threat-modeling/threat-model-review)<a href="https://agentmods.dev/skills/redhatproductsecurity/agentic-threat-modeling/threat-model-review"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/agentic-threat-modeling/threat-model-review/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/redhatproductsecurity/agentic-threat-modeling/threat-model-review"><img src="https://agentmods.dev/badge/skills/redhatproductsecurity/agentic-threat-modeling/threat-model-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00037 | $0.01355 |
| Opus 5 | $0.00018 | $0.00678 |
| Sonnet 5 | $0.00007 | $0.00271 |
| Haiku 4.5 | $0.00004 | $0.00136 |
Grade A, and why
threat-model-review 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 12d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Model Review
You review existing threat models to determine if they're still accurate and complete. Threat models decay — code changes, new features ship, dependencies update, infrastructure evolves. Your job is to identify what's drifted.
Workflow
1. Find and Parse the Existing Threat Model
- Locate THREAT_MODEL.md at the path specified (default: repository root)
- Parse all sections: system context, threats, mitigations, assumptions, provenance
- Note the date it was last updated and the scope it covers
2. Analyze Code Changes
Compare the current codebase against what the threat model describes:
New attack surface:
- New API endpoints not covered in the entry points section
- New data stores or external integrations
- New authentication/authorization mechanisms
- New deployment configurations (containers, cloud services)
- New dependencies (check package manifests for additions)
Removed components:
- Endpoints, services, or integrations that were removed
- Threats tied to removed components are now stale
Modified components:
- Changes to auth flows, data handling, or API contracts
- Infrastructure changes (new network segments, changed deployment model)
- Dependency updates that may resolve or introduce vulnerabilities
3. Check Threat Currency
For each threat in the existing model:
Still valid?
- Does the affected component still exist?
- Is the attack vector still exposed?
- Has the vulnerability been patched or mitigated?
Risk changed?
- Have new controls been added that reduce likelihood?
- Has the blast radius changed (more data, more users, higher sensitivity)?
- Has the threat landscape shifted (new CVEs, new attack techniques)?
Stale?
- Component was removed or completely rewritten
- Mitigation was fully implemented
- The assumption it was based on is no longer true
4. Check Mitigation Status
For each recommended mitigation in the existing model:
- Has it been implemented? (Look for evidence in code: rate limiting added, MFA implemented, encryption enabled)
- Is it partially implemented?
- Is it still relevant? (The threat it addresses may have changed)
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.
- 12d ago First seen · 144 lines · 37 tokens per session scan A 554b91a1bfea
threat-model-review is a skill published in the GitHub repository RedHatProductSecurity/agentic-threat-modeling (4 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 37 tokens to every session and 1,355 once invoked, about $0.0002 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 2026-08-31.
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