Senior Security Engineer — Threat Modeling + Security Router

SkillSecurity

Your AI can handle security engineering work, from threat modeling and secret scanning to architecture design and compliance audits. The skill covers application security, penetration testing, security architecture, and cryptography, with assessment tools and automation included. It is most useful when you are designing security architecture or checking how an application could be attacked.

Available today. Use it from your connected AI after setup.

After adding the skill, ask your AI to build a threat model for a feature or scan your codebase for leaked secrets. It can then help design your security architecture or run a broader assessment.

Then ask your AI: use the Senior Security Engineer — Threat Modeling + Security Router skill

What your AI can do with it

  • Build STRIDE threat models with DREAD scoring
  • Scan a codebase for leaked secrets
  • Design security architecture for applications
  • Run security assessments on your code
  • Implement cryptographic functionality
  • Audit applications for compliance issues

What this skill tells your AI

The instructions your AI receives, as published by ahtavarasmus/lightfriend in .claude/skills/senior-security/SKILL.md and read by ahel’s review.

This skill does exactly one job itself — STRIDE/DREAD threat modeling (plus a quick secret scan) — and routes every other security request to the specialist skill that owns that lane. Do not duplicate sibling content here; route instead.

Routing Table (read this first)

The user wants...Route toWhy that skill owns it
Vulnerability assessment, pen-test methodology, OWASP Top 10 testing../security-pen-testing/Ships vulnerability_scanner.py + dependency_auditor.py with exit-code contracts
Incident triage, SEV classification, forensics, containment../incident-response/SEV1–SEV4 taxonomy, NIST SP 800-61 phases, incident_triage.py
Production outage command (non-security incidents)../incident-commander/Severity classifier + timeline + postmortem tools
Security monitoring, CVE triage SLAs, compliance checks (SOC 2 etc.), security headers../senior-secops/security_scanner.py + compliance_checker.py, CVE SLA table
Hostile/adversarial code review../adversarial-reviewer/3-persona review with BLOCK/CONCERNS/CLEAN verdict
Secure code review as part of general review../code-reviewer/Language dispatch + regression fixtures
Cloud IAM escalation paths, S3 exposure, security groups../cloud-security/cloud_posture_check.py with per-check exit codes
Threat hunting, IOC sweeps, anomaly detection../threat-detection/z-score anomaly + IOC staleness tooling
Red-team engagement planning, ATT&CK kill chains../red-team/engagement_planner.py with authorization gate
LLM/AI attack surface (prompt injection, poisoning)../ai-security/ATLAS-mapped ai_threat_scanner.py

If the request spans lanes (e.g., "secure this new architecture"), do the threat model here first — its output (prioritized threats + mitigations) tells you which siblings to load next. Never bulk-load multiple security skills speculatively.

What This Skill Owns: STRIDE Threat Modeling

Workflow

  1. Scope: assets to protect, trust boundaries, data flows (external entities, processes, data stores, flows).
  2. Generate the threat model per component:
    python3 scripts/threat_modeler.py --component "User Authentication" --assets "credentials,sessions" --json --output threats.json
    
    Output: per-threat STRIDE category, DREAD score (Damage, Reproducibility, Exploitability, Affected users, Discoverability — each 1–10), and suggested mitigations. Repeat per DFD element; --interactive walks scoping questions; --list-threats shows the threat database.
  3. Consume the output: sort threats.json by DREAD score descending; everything ≥ 7 average needs a named mitigation owner before the design ships. Map each mitigation to the responsible sibling lane (e.g., IAM threats → cloud-security, injection threats → code-reviewer).
  4. Quick secret sweep while you have the codebase open:
    python3 scripts/secret_scanner.py /path/to/project --format json --severity high
    
    20+ patterns (AWS keys, GitHub tokens, private keys, generic credentials). Any critical/high finding blocks merge until rotated and moved to a secret manager.
  5. Verification gate: every DFD element has ≥ 1 STRIDE row considered, every threat with DREAD ≥ 7 has an owner + mitigation, and the secret scan exits with zero high/critical findings. Re-run both tools after mitigations land — that re-run is the done signal, not the document.

STRIDE per Element Matrix

DFD ElementSTRIDE
External EntityXX
ProcessXXXXXX
Data StoreXXXX
Data FlowXXX

(S=Spoofing→authn, T=Tampering→integrity, R=Repudiation→audit logs, I=Info Disclosure→encryption/access control, D=DoS→rate limiting/redundancy, E=Elevation→least privilege.)

References (load on demand)

DocumentContent
references/threat-modeling-guide.mdSTRIDE methodology, attack trees, DREAD scoring, DFD creation
references/security-architecture-patterns.mdZero Trust, defense-in-depth, authentication patterns, API security
references/cryptography-implementation.mdAES-GCM, Ed25519, password hashing (Argon2id), key management

The architecture and crypto references are kept because no sibling ships them; for operating those controls (scanning, compliance, monitoring) still route to senior-secops.

Signals

GitHub stars
78
Forks
9
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
senior-security
Source
github.com/ahtavarasmus/lightfriend