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 pasta-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/pasta-threat-modeling-framework)<a href="https://agentmods.dev/skills/ivan-sincek/threat-modeling-agent-skills/pasta-threat-modeling-framework"><img src="https://agentmods.dev/badge/skills/ivan-sincek/threat-modeling-agent-skills/pasta-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/pasta-threat-modeling-framework"><img src="https://agentmods.dev/badge/skills/ivan-sincek/threat-modeling-agent-skills/pasta-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 | $0.00051 | $0.04190 |
| Opus 5 | $0.00026 | $0.02095 |
| Sonnet 5 | $0.00010 | $0.00838 |
| Haiku 4.5 | $0.00005 | $0.00419 |
Grade A, and why
pasta-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 5d 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 — 452 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PASTA 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 PASTA (Process for Attack Simulation and Threat Analysis) threat modeling framework to systematically identify and classify technical and business risks across the application and its environment.
Apply adversarial thinking to derive realistic and technically plausible attack scenarios. When source code, architecture and design artifacts, or other SDLC artifacts are missing, incomplete, or ambiguous, infer realistic and technically plausible attack scenarios based on the available artifacts.
Analysis
Coherently link all the PASTA stages so that the output of each stage informs and constrains subsequent stages.
Stage 1 - Define the Objectives
-
Leverage all the provided business artifacts.
-
Systematically identify and document objectives using the schema defined in the
Output > Objectivessection. -
Systematically identify and document each business process using the schema defined in the
Output > Business Impact Analysis Detailssection. -
Sort the identified business processes in descending order by criticality rating.
Stage 2 - Define the Technical Scope
-
Leverage all the provided architecture and design artifacts.
-
Define the technical scope of the application by systematically identifying the following elements:
- Trust boundaries, system components, and data flows
- Entry points, resources, and assets within each system component
- External entities and interactions
- Identities, roles, permissions, privileges, and access controls
- Human, service, and system actors
- Preventive, detective, and corrective security controls
- Technologies and dependencies
- Infrastructure
-
Systematically document each identified element using its corresponding schema defined in the
Output > Technical Scopesection.
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.
- 5d ago Changed 1d7c72b19d2b
- 7d ago Changed · +2 lines 4cdfe390eb16
- 12d ago First seen · 450 lines · 51 tokens per session scan A cfce8720cc02
pasta-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 51 tokens to every session and 4,190 once invoked, about $0.0003 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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