threat-modeling
Skill101 starsChanged 7 months agoNo licenceView on GitHub
Systematic threat modeling skill for applications, APIs, and systems using STRIDE, PASTA, Attack Trees, DREAD, LINDDUN, and OCTAVE. Use when assessing security architecture, creating data flow diagrams (Mermaid), enumerating threats from OpenAPI specs or architecture docs, building attack trees, mapping threats to NIST/CIS/OWASP ASVS controls, or producing a threat model report. Triggers on requests to threat model, analyze attack surface, create a DFD, apply STRIDE, or design security mitigations.
- Installs packages
45 other projects use a version of this, 2 of them edited.
Adopted by
Most recently taken up by
- kinhluan/skillstheir own version, first seen Nov 8, 2026
- AxlZero21/Skillstheir own version, first seen Nov 8, 2026
- bepaldes/heimdall-agenttheir own version, first seen Nov 8, 2026
- reddygopalkrishna/developer-agent-skillstheir own version, first seen Nov 8, 2026
- SWEStash/swe-workflow-skillstheir own version, first seen Nov 8, 2026
- nledford/engineering-review-boardtheir own version, first seen Nov 3, 2026
Used with
Projects with it also use prompt-injection, threat-hunting and 7 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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Also in 4 projects that use this
allanninalSkillthreat-hunting
Hunt threats using Sigma detection rules and security analysis techniques. Use when investigating security incidents, creating detection rules, or analyzing suspicious activity.
Also in 3 projects that use this
narlyseorgSkillsecure-code-review
Use when reviewing source code for security vulnerabilities, performing static analysis of a codebase, auditing code for injection flaws, authentication issues, cryptographic weaknesses, insecure deserialization, SSRF, path traversal, memory safety bugs, hardcoded secrets, or misconfigurations. Use when the user asks to find security bugs in code, assess code quality from a security perspective, or review pull requests for security implications. Use when performing dependency audits, secrets scanning, or configuration review of application source.
Also in 3 projects that use this
OpenAISkillobservability
Vercel Observability expert guidance — Drains (logs, traces, speed insights, web analytics), Web Analytics, Speed Insights, runtime logs, custom events, OpenTelemetry integration, and monitoring dashboards. Use when instrumenting, debugging, or optimizing application performance and user experience on Vercel.
Also in 5 projects that use this
MicrosoftSkillapi-design
Guide for designing and documenting RESTful APIs. Use when asked to design an API, create endpoints, or document an API.
Also in 7 projects that use this
SentrySkillarchitecture-review
Staff-level codebase health review. Finds monolithic modules, silent failures, type safety gaps, test coverage holes, and LLM-friendliness issues.
Also in 3 projects that use this
Other versions45 projects use a version of this.
Word for word · 0
None found.
Edited · 2
- EvilFreelancer/secas★ 1199% same
- EvilFreelancer/secs★ 1199% same
Wrote their own version · 43
- briiirussell/cybersecurity-skills★ 489same name
- fr33d3m0n/skill-threat-modeling★ 347same name
- proflead/codex-skills-library★ 153same name
- nahid-sparktales/agent-dispatcher★ 59same name
- mn-youssef/security-skills★ 47same name
- kumaran-is/claude-code-onboarding★ 35same name
- nimadorostkar/Claude-Skills-collection★ 33same name
- ulises-jeremias/agent-toolkit★ 19same name
- Indium-AI-Labs/indium-agentkit★ 18same name
- awarexone/AXguard★ 17same name
33 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository11 other files it gives its agents.
- android-pentestSkill
- api-securitySkill
- cloud-securitySkill
- container-securitySkill
- dast-automationSkill
- iac-securitySkill
- ios-pentestSkill
- llm-securitySkill
- network-pentestSkill
- sast-orchestrationSkill
- sca-securitySkill
The file
We split this skill into the rules it gives an agent
5 rules. 0 are common, 4 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 40 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.
“Common” is measured: kept by at least 6 in 10 of the 40 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

