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Skill evidence / analyzing-lnk-file-and-jump-list-artifacts
Skill profile

analyzing-lnk-file-and-jump-list-artifacts

Analyze Windows LNK shortcut files and Jump List artifacts with LECmd.

What this skill does for you

Analyze Windows LNK shortcut files and Jump List artifacts with LECmd, JLECmd, and manual Shell Link Binary Format parsing to establish evidence of file access, program execution, and user activity that persists even after the target file is deleted. Use when investigating Windows user activity, reconstructing file-access or program-execution timelines, or examining recent/frequently-used file evidence in a forensic exam.

Quoted from the skill description in the pinned source

Who made it

Publishermukul975
Repositoryanthropic-cybersecurity-skills
Installs363as 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 analyzing-lnk-file-and-jump-list-artifacts skill from mukul975/anthropic-cybersecurity-skills.

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.

ScannerDateResultFindings
Edge static checks2026-09-27Pass0
Cisco skill-scanner2026-09-27Pass0
Semgrep Edge rules2026-09-27Pass0

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: 54a798831d2266a3ca61ce68a7acb80b81160d57. 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: 54a798831d2266a3ca61ce68a7acb80b81160d57. Raw findings: . 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: 54a798831d2266a3ca61ce68a7acb80b81160d57. Raw findings: . Counted findings: .

Source and licence

Repository
https://github.com/mukul975/anthropic-cybersecurity-skills
Pinned skill file
View source at revision
Revision
54a798831d2266a3ca61ce68a7acb80b81160d57
Package hash
sha256:065676088c4e6f3960c678eb3f05addffbf449aec27065d3a4d7575a690b7b47
Licence
Apache-2.0