---
name: threat-modeling-expert
description: "Expert in threat modeling methodologies, security architecture review, and risk assessment. Masters STRIDE, PASTA, attack trees, and security requirement extraction. Use for security architecture r..."
risk: unknown
source: community
date_added: "2026-02-27"
---

# Threat Modeling Expert

Expert in threat modeling methodologies, security architecture review, and risk assessment. Masters STRIDE, PASTA, attack trees, and security requirement extraction. Use PROACTIVELY for security architecture reviews, threat identification, or building secure-by-design systems.

## Capabilities

- STRIDE threat analysis
- Attack tree construction
- Data flow diagram analysis
- Security requirement extraction
- Risk prioritization and scoring
- Mitigation strategy design
- Security control mapping

## Use this skill when

- Designing new systems or features
- Reviewing architecture for security gaps
- Preparing for security audits
- Identifying attack vectors
- Prioritizing security investments
- Creating security documentation
- Training teams on security thinking

## Do not use this skill when

- You lack scope or authorization for security review
- You need legal or compliance certification
- You only need automated scanning without human review

## Instructions

1. Define system scope and trust boundaries
2. Create data flow diagrams
3. Identify assets and entry points
4. Apply STRIDE to each component
5. Build attack trees for critical paths
6. Score and prioritize threats
7. Design mitigations
8. Document residual risks

## Safety

- Avoid storing sensitive details in threat models without access controls.
- Keep threat models updated after architecture changes.

## Best Practices

- Involve developers in threat modeling sessions
- Focus on data flows, not just components
- Consider insider threats
- Update threat models with architecture changes
- Link threats to security requirements
- Track mitigations to implementation
- Review regularly, not just at design time

---

<!-- AGI-INTEGRATION-START -->

## AGI Framework Integration

> **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)**
> Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills)

### Memory-First Protocol

Cache compliance check results to avoid re-running expensive AWS API calls. Retrieve prior audit findings to track remediation progress across sessions.

```bash
# Check for prior security context before starting
python3 execution/memory_manager.py auto --query "prior security audit results for Threat Modeling Expert"
```

### Storing Results

After completing work, store security decisions for future sessions:

```bash
python3 execution/memory_manager.py store \
  --content "Audit findings: 3 critical IAM misconfigurations found and remediated" \
  --type technical --project <project> \
  --tags threat-modeling-expert security
```

### Multi-Agent Collaboration

Share security findings with other agents so they avoid introducing vulnerabilities in their code changes.

```bash
python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Completed security audit — 3 critical findings fixed, compliance score 94%" \
  --project <project>
```

### Signed Audit Trail

All security findings are cryptographically signed with the agent's Ed25519 identity, providing tamper-proof audit logs for compliance reporting.

### Semantic Cache for Compliance

Cache compliance check results (`semantic_cache.py`) to avoid redundant AWS API calls. Cache hit at similarity >0.92 returns prior results instantly.

<!-- AGI-INTEGRATION-END -->
