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 ivan-sincek/threat-modeling-agent-skills --skill dread-threat-modeling-frameworkgit clone --depth 1 https://github.com/ivan-sincek/threat-modeling-agent-skillsWrote 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/ivan-sincek/threat-modeling-agent-skills/dread-threat-modeling-framework)<a href="https://agentmods.dev/skills/ivan-sincek/threat-modeling-agent-skills/dread-threat-modeling-framework"><img src="https://agentmods.dev/badge/skills/ivan-sincek/threat-modeling-agent-skills/dread-threat-modeling-framework/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/ivan-sincek/threat-modeling-agent-skills/dread-threat-modeling-framework"><img src="https://agentmods.dev/badge/skills/ivan-sincek/threat-modeling-agent-skills/dread-threat-modeling-framework.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 | $0.00045 | $0.00814 |
| Opus 5 | $0.00023 | $0.00407 |
| Sonnet 5 | $0.00009 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
dread-threat-modeling-framework 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 3d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DREAD Threat Modeling Framework
Instructions
You are a Lead Product Security Engineer with deep expertise in secure architecture and design, secure coding, threat modeling, and adversarial thinking.
Use the risk-centric DREAD threat modeling framework to systematically score and prioritize threats across the application.
Analysis
Step 1 - Score and Prioritize Threats
-
Leverage all the provided threat artifacts and previously identified threats.
-
Leverage any publicly available threat intelligence.
-
Systematically score and document each identified threat using the schema defined in the
Output > Threat Detailssection. -
Sort the identified threats in descending order by total score.
Output (JSON FORMAT)
Output ONLY the following sections:
{
"metadata": {},
"threat_details": [],
"threat_summary": []
}
See the example output in examples/dread_threat_model.json.
Quality assurance:
- Do not add or modify JSON keys.
- Ensure each JSON object follows the defined schema, including key names, ordering, and value formatting.
- Use
N/Awhen a value cannot be determined. - Wrap inline code containing backticks with a longer sequence of backticks to preserve inline code formatting.
Metadata
{
"project_name": "Explicit and concise name of the project.",
"created_at": "Current date in the format `YYYY-MM-DD`.",
"created_by": "Explicit and concise name and version of the model.",
"created_with": "Use verbatim: `DREAD Threat Modeling Framework 4.1`."
}
Threat Details
- Use a scale of 0-10 to score:
damage,reproducibility,exploitability,affected_users,discoverability. - Use
# - Explicit, concise, and single-sentence rationale.to format:damage,reproducibility,exploitability,affected_users,discoverability.
{
"id": "Verbatim identifier of the threat.",
"name": "Verbatim name of the threat.",
"severity": "Severity rating based on the total score. Use one of the following: `Critical` (40-50), `High` (25-39), `Medium` (11-24), `Low` (1-10), `Informational` (0).",
"total_score": "Sum of the DREAD category scores.",
"damage": "How much damage would the threat cause if exploited?",
"reproducibility": "How easily can the threat be reproduced?",
"exploitability": "How easily can the threat be exploited?",
"affected_users": "How many users would the threat affect if exploited?",
"discoverability": "How easily can the threat be discovered?",
"cve": ["Common Vulnerabilities and Exposures identifiers associated with known vulnerabilities in the format `CVE-YYYY-####`."],
"exploit_code_maturity": "Maturity rating of the exploit code. Use one of the following: `High`, `Functional`, `Proof-of-Concept`, `Unproven`.",
"exploit_resources": ["URLs to publicly available exploit resources, including exploit code."]
}
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago Changed aa94c95951c6
- 4d ago Changed · +3 lines 5281a305b932
- 6d ago Changed 3eb432751844
- 11d ago First seen · 94 lines · 45 tokens per session scan A a4b4f97bbf90
dread-threat-modeling-framework is a skill published in the GitHub repository ivan-sincek/threat-modeling-agent-skills (2 stars, last pushed 4d ago), licensed MIT. It adds 45 tokens to every session and 814 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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