🔄 Topic

I built a broad cybersecurity glossary inside my Obsidian vault and linked it across existing notes. The work looked like knowledge management, but the real lesson was validation: large automated edits to notes need backups, skip rules, and checks just like code changes do.

🎯 Goal

Create a reusable glossary for cybersecurity, internet, operating-system, shell, developer, and business-computing terms, then connect it to my existing study notes without corrupting code blocks, front matter, URLs, or existing links.

🛠 What I Did

I generated a glossary library from the vocabulary already present in my notes and then linked matching terms across the vault.

Main areas covered:

  • created hundreds of glossary term notes
  • created a glossary index
  • added concise definitions, why-it-matters sections, related links, source-note backlinks, and source URLs where useful
  • inserted glossary links into existing notes
  • skipped front matter, fenced code blocks, inline code, URLs, Markdown links, and existing wiki links
  • backed up the vault before broad edits
  • validated generated links and restored a few files whose raw terminal/Vim syntax could be confused with wiki-link syntax

🔗 Key Cybersecurity Connections

Cybersecurity learning is full of overloaded terms: DNS, HTTP, SSH, SUID, SOC, KQL, CSRF, IDOR, lateral movement, credential stuffing, and many more. A glossary helps reduce confusion, but automation can create its own risk if it rewrites study material carelessly.

The security lesson is change control. Broad automated edits need rollback, validation, and clear exclusion rules.

🔍 Investigation Questions

  • Which terms are common enough in the vault to deserve glossary notes?
  • Can the linker avoid code, URLs, existing links, and front matter?
  • Do generated wiki links point to real files?
  • Did any source notes become syntactically unbalanced after linking?
  • Is the glossary useful, or just aggressively noisy?

🚨 Detection Opportunities

Useful validation checks for a note-linking pass:

  • missing wiki-link targets after generation
  • unbalanced brackets in source notes
  • links inserted inside code blocks
  • links inserted into URLs
  • generated backlinks that break because filenames contain special characters
  • broad edit without a backup archive

Example:

project=obsidian-cyber-glossary
signal=missing_wikilink_target_after_bulk_link
risk_area=knowledge_base_integrity
triage=restore_from_backup_or_fix_generated_target

🧭 MITRE ATT&CK Techniques

No direct mapping claimed. Some glossary terms overlap with ATT&CK concepts, but this post is about study infrastructure and validation.

🗺 Visual Investigation Diagram

Existing study notes
    ↓
Extract useful vocabulary
    ↓
Generate glossary terms + index
    ↓
Link matching terms across vault
    ↓
Validate targets and syntax
    ↓
Restore edge-case files from backup

⚠ Challenges

The danger was over-linking. Markdown notes are not just prose; they contain commands, snippets, front matter, and weird terminal output. A naive linker can make a vault feel smarter while quietly damaging the material.

📚 What I Learned

I learned that personal knowledge bases need engineering discipline too. If a script touches hundreds of notes, it deserves the same caution as a code migration.

➡ Next Steps

  • Browse the glossary index in Obsidian and check whether the graph feels useful or too noisy
  • Add personal lab examples to high-value terms like DNS, SSH, SUID, IDOR, CSRF, SIEM, and KQL
  • Build topic maps for Networking, Linux Privilege Escalation, Web Security, SOC Operations, and Developer Tooling
  • Never run a broad linker without a backup

🧠 Reflection

The glossary made my notes feel more connected, but the validation pass is what made me trust the work. A knowledge graph that silently corrupts notes is just chaos with blue links.

🧩 Lessons Learned

What worked

Generating a glossary from terms already present in the vault.

What needed care

Avoiding links inside code, URLs, front matter, and existing Markdown/wiki links.

Why it mattered

Automated note edits can damage study material at scale.

Fix / takeaway

Backup first, link carefully, validate after, and restore edge cases instead of pretending the script was perfect.

📈 Skill Progression Context

This supports my cybersecurity progression because vocabulary and mental models matter. A validated glossary turns scattered notes into a more usable learning system.

😄 TL;DR

Built a broad cybersecurity glossary in Obsidian and learned that bulk note-linking needs backups, skip rules, and validation just like code migrations.