Threat Modeling MCP Server is an MCP server that guides an AI coding agent through structured security threat modeling and code validation. It analyzes business context, architecture, assets, trust boundaries, and threat actors, then produces Markdown or JSON reports using a phased STRIDE-based process. The catalogue skills operate this workflow through compatible agent clients.
Borrowing it
Nothing to install: this file belongs to awslabs/threat-modeling-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/awslabs/threat-modeling-mcp-server/main/.kiro/skills/phase-3-threat-actors/SKILL.mdgit clone --depth 1 https://github.com/awslabs/threat-modeling-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/awslabs/threat-modeling-mcp-server/phase-3-threat-actors)<a href="https://agentmods.dev/skills/awslabs/threat-modeling-mcp-server/phase-3-threat-actors"><img src="https://agentmods.dev/badge/skills/awslabs/threat-modeling-mcp-server/phase-3-threat-actors/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/awslabs/threat-modeling-mcp-server/phase-3-threat-actors"><img src="https://agentmods.dev/badge/skills/awslabs/threat-modeling-mcp-server/phase-3-threat-actors.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00034 | $0.01362 |
| Opus 5 | $0.00017 | $0.00681 |
| Sonnet 5 | $0.00007 | $0.00272 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
phase-3-threat-actors scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Phase 3: Threat Actor Analysis
Objective
Identify who might attack this system, what motivates them, and what they're capable of. This focuses threat identification in Phase 6 on realistic scenarios.
Default Threat Actors
The system pre-loads 12 default threat actors (TA001-TA012) as a starting point, not as findings. An actor counts toward this phase only once you have assessed it -- set its relevance, set its priority, or update it. Actors you never touch stay out of the report's threat actor section and are listed in its "Appendix: Reference Catalogue (Not Reviewed)" instead, so leaving the catalogue untouched cannot pass for analysis.
| ID | Name | Type | Sophistication Tier | Motivations |
|---|---|---|---|---|
| TA001 | Insider | Insider Threat | Tier 2 - Hacktivist / campaign-driven | Financial gain, Revenge / grievance |
| TA002 | External Attacker | External Attacker | Tier 1 - Opportunistic / script kiddie | Financial gain |
| TA003 | Nation-state Actor | Nation-State / APT | Tier 5 - Nation-state APT / elite | Espionage / intelligence collection |
| TA004 | Hacktivist | Hacktivist | Tier 2 - Hacktivist / campaign-driven | Ideological / hacktivism |
| TA005 | Organized Crime | Financially Motivated Cybercriminal / Organized Crime | Tier 3 - Organized cybercrime | Financial gain |
| TA006 | Competitor | Competitor / Corporate Espionage | Tier 3 - Organized cybercrime | Competitive advantage, Espionage / intelligence collection |
| TA007 | Script Kiddie | Script Kiddie / Novice | Tier 1 - Opportunistic / script kiddie | Thrill-seeking / notoriety |
| TA008 | Disgruntled Employee | Disgruntled Employee | Tier 1 - Opportunistic / script kiddie | Revenge / grievance |
| TA009 | Privileged User | Privileged User | Tier 2 - Hacktivist / campaign-driven | Financial gain |
| TA010 | Third Party | Third Party | Tier 2 - Hacktivist / campaign-driven | Financial gain |
| TA011 | Terrorist Organization | Terrorist Organization | Tier 2 - Hacktivist / campaign-driven | Ideological / hacktivism, Disruption / destruction |
| TA012 | Private Sector Offensive Actor | Private Sector Offensive Actor / Cyber Mercenary | Tier 4 - State-nexus / advanced | Financial gain |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 89 lines · 34 tokens per session scan A b82b1658d377
phase-3-threat-actors is a skill published in the GitHub repository awslabs/threat-modeling-mcp-server (101 stars, last pushed 16d ago), licensed Apache-2.0. It adds 34 tokens to every session and 1,362 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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