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 patricio0312rev/skillset --skill threat-model-generatorgit clone --depth 1 https://github.com/patricio0312rev/skillsetWrote 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/patricio0312rev/skillset/threat-model-generator)<a href="https://agentmods.dev/skills/patricio0312rev/skillset/threat-model-generator"><img src="https://agentmods.dev/badge/skills/patricio0312rev/skillset/threat-model-generator/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/patricio0312rev/skillset/threat-model-generator"><img src="https://agentmods.dev/badge/skills/patricio0312rev/skillset/threat-model-generator.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 | $0.00048 | $0.02452 |
| Opus 5 | $0.00024 | $0.01226 |
| Sonnet 5 | $0.00010 | $0.00490 |
| Haiku 4.5 | $0.00005 | $0.00245 |
Grade A, and why
threat-model-generator 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.
This is a copy
100% identical to threat-model-generator — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 395 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Threat Model Generator
Systematically identify and mitigate security threats.
STRIDE Methodology
S - Spoofing: Impersonating someone/something
T - Tampering: Modifying data or code
R - Repudiation: Claiming you didn't do something
I - Information Disclosure: Exposing protected information
D - Denial of Service: Making system unavailable
E - Elevation of Privilege: Gaining unauthorized permissions
Asset Identification
interface Asset {
name: string;
type: "data" | "service" | "user" | "infrastructure";
sensitivity: "public" | "internal" | "confidential" | "restricted";
criticality: "low" | "medium" | "high" | "critical";
}
const assets: Asset[] = [
{
name: "User Credentials (passwords, tokens)",
type: "data",
sensitivity: "restricted",
criticality: "critical",
},
{
name: "Payment Information (credit cards)",
type: "data",
sensitivity: "restricted",
criticality: "critical",
},
{
name: "API Service",
type: "service",
sensitivity: "internal",
criticality: "high",
},
{
name: "User Profile Data",
type: "data",
sensitivity: "confidential",
criticality: "medium",
},
];
Threat Enumeration
interface Threat {
id: string;
category: "S" | "T" | "R" | "I" | "D" | "E";
description: string;
asset: string;
attackVector: string;
likelihood: "low" | "medium" | "high";
impact: "low" | "medium" | "high" | "critical";
riskScore: number;
}
const threats: Threat[] = [
{
id: "T-001",
category: "S",
description: "Attacker impersonates user with stolen credentials",
asset: "User Credentials",
attackVector: "Phishing, credential stuffing, brute force",
likelihood: "high",
impact: "critical",
riskScore: 9,
},
{
id: "T-002",
category: "T",
description: "SQL injection allows data modification",
asset: "User Profile Data",
attackVector: "Malicious SQL in input fields",
likelihood: "medium",
impact: "high",
riskScore: 7,
},
{
id: "T-003",
category: "I",
description: "API exposes sensitive user data without auth",
asset: "User Profile Data",
attackVector: "Direct API access, IDOR",
likelihood: "medium",
impact: "high",
riskScore: 7,
},
{
id: "T-004",
category: "D",
description: "DDoS attack overwhelms API",
asset: "API Service",
attackVector: "Volumetric attack, application-layer flood",
likelihood: "medium",
impact: "high",
riskScore: 7,
},
{
id: "T-005",
category: "E",
description: "Privilege escalation via role manipulation",
asset: "User Profile Data",
attackVector: "Parameter tampering, insecure direct object reference",
likelihood: "low",
impact: "critical",
riskScore: 6,
},
];
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 · 395 lines · 48 tokens per session scan A 9a89abde6f1a
threat-model-generator is a skill published in the GitHub repository patricio0312rev/skillset (6 stars, last pushed 8mo ago), licensed MIT. It adds 48 tokens to every session and 2,452 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to threat-model-generator, differing in 0 lines, and is treated as a copy.
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