threat-modeling-techniques

Threat modeling methodologies using STRIDE.

What this skill does for you

Threat modeling methodologies using STRIDE, attack trees, and risk assessment for proactive security analysis. Use when designing secure systems, conducting security reviews, or identifying potential attack vectors in applications.

Quoted from the skill description in the pinned source

Who made it

Publishernickcrew

Repositoryclaude-cortex

Installs352as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the threat-modeling-techniques skill from nickcrew/claude-cortex.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: bb47af79ad3befe01ae01940fcf5f16e30a1b6df. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: bb47af79ad3befe01ae01940fcf5f16e30a1b6df. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: bb47af79ad3befe01ae01940fcf5f16e30a1b6df. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/nickcrew/claude-cortex
Pinned skill file: View source at revision
Revision: bb47af79ad3befe01ae01940fcf5f16e30a1b6df
Package hash: sha256:644373bc5c1729fe4fa7fa34027a47d18d70e3d7601c43d50f81f4d31fcd5bcc
Licence: MIT