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-8-residual-risk/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-8-residual-risk)<a href="https://agentmods.dev/skills/awslabs/threat-modeling-mcp-server/phase-8-residual-risk"><img src="https://agentmods.dev/badge/skills/awslabs/threat-modeling-mcp-server/phase-8-residual-risk/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-8-residual-risk"><img src="https://agentmods.dev/badge/skills/awslabs/threat-modeling-mcp-server/phase-8-residual-risk.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 | $0.00030 | $0.00983 |
| Opus 5 | $0.00015 | $0.00491 |
| Sonnet 5 | $0.00006 | $0.00197 |
| Haiku 4.5 | $0.00003 | $0.00098 |
Grade A, and why
phase-8-residual-risk 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Phase 8: Residual Risk Analysis
Objective
Assess what risk remains after all mitigations are applied. Make explicit risk acceptance decisions and document justifications.
Tools Reference
Review Tools
manage_threats(action="list", section="all")-- Get all threats and mitigationsmanage_threats(action="get", section="threats", item_id=ID)-- Threat details and linksmanage_threats(action="get", section="mitigations", item_id=ID)-- Mitigation details and links
Decision Tools
manage_threats(action="assess", section="threats", values=ASSESSMENT)-- Record one decisionmanage_threats(action="assess", section="threats", items=ASSESSMENTS)-- Record an atomic batchmanage_assumptions(action="add", values=ASSUMPTION)-- Document risk acceptance
Risk Assessment Framework
For each threat, consider:
- Mitigations in place: What controls address this threat?
- Mitigation effectiveness: How well do the controls work?
- Residual likelihood: After controls, how likely is the threat?
- Residual impact: If it still occurs, what's the damage?
- Business tolerance: Can the business accept this level of risk?
An assessment contains threat_id, decision, residual_severity,
residual_likelihood, and a non-empty rationale. Severity and likelihood are
required except for Not Applicable.
Residual Risk Decisions
| Decision | Criteria | Threat Composer status |
|---|---|---|
Mitigated |
Controls reduce risk to the required level | threatResolved |
Accepted |
The business formally accepts the remaining risk | threatResolved |
Open |
Controls are absent or insufficient | threatIdentified |
Not Applicable |
The scenario does not apply to this system | threatResolvedNotUseful |
Decision Guide
Choose Mitigated when:
- Preventive controls fully address the threat vector
- Detective + corrective controls provide adequate response
- Code validation confirmed implementation
- Industry-standard controls are in place
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 · 95 lines · 30 tokens per session scan A 09034c06c866
phase-8-residual-risk 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 30 tokens to every session and 983 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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