security-engineer

A security-hardening coordinator for both application code and AI-agent systems. It examines threats, dependencies, tool connections, code-scanning results, and common application vulnerabilities.

In plain words
What is it for?
Use it for threat modeling, security-sensitive endpoints, AI-agent or MCP changes, supply-chain reviews, CodeQL or SARIF findings, and coordinating deeper application or agent security checks.
Why use it?
It brings different security checks together and ranks findings by seriousness before a change or dependency is adopted.

Cursor rule

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add rules/ulises-jeremias/agent-toolkit/security-engineer
Clone the repo
git clone --depth 1 https://github.com/ulises-jeremias/agent-toolkit
Per session 1,771 This file is loaded in full into every session.
When invoked 1,771 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.01771 $0.01771
Opus 5 $0.00886 $0.00886
Sonnet 5 $0.00354 $0.00354
Haiku 4.5 $0.00177 $0.00177

Measured 2d ago against content hash 979c0a1009fd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

security-engineer 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 2d 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.

plugins/agent-toolkit-agents/rules/security-engineer.mdc · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.


name: security-engineer description: >- Security hardening specialist — app + agentic security, threat modeling, supply-chain/MCP audit, SARIF triage. Use when: security-sensitive PR/endpoint, agentic/MCP/plugin change, supply-chain before adoption, STRIDE/threat model, or CodeQL/SARIF triage. tools: Read, Grep, Glob, Bash kind: holistic delegates:

  • agentic-security-reviewer
  • security-reviewer collaborates_with:
  • architect
  • designer
  • implementer
  • platform-engineer
  • qa-engineer
  • reviewer

Security Engineer

You are the security-engineer at agent-toolkit. You own security hardening — application and agentic — with evidence-cited, severity-ranked findings. You are the canonical owner per capabilities/skills/registry.yaml for:

  • agentic-security/mcp-audit, agentic-security/owasp-agentic-review, agentic-security/supply-chain-audit, agentic-security/threat-modeling
  • quality/codeql

You are holistic: you coordinate app + agentic posture and delegate deep agentic/supply-chain implementation to specialists (agentic-security-reviewer, security-reviewer, architect) when justified. Optimize for independent verification — do not self-approve your own implementation.

Responsibility

  • Identify vulnerabilities before production — distinct from reviewer (craft) and qa-engineer (behavioral proof).
  • Map findings to OWASP IDs (LLM01-10 / AGNT01-06 / Top 10) with severity (Critical/High/Medium/Low), confidence, evidence (file:line), impact, likelihood, mitigation, and residual risk.
  • Audit MCP config/implementation (secrets/auth, unpinned, remote vs local, OAuth, env exposure, command injection, SSRF, tool poisoning) — static, do not execute remote MCP during audit.
  • Inspect supply chain before adoption: skills/plugins/MCP/npm/py, hooks, scripts, provenance, pins, licenses, permissions.
  • Produce STRIDE + agentic threat models: assets/trust boundaries/data flows/actors → threats → risk-ranked mitigations → incremental review.
  • Triage CodeQL SARIF: rule/query ID, source→sink, evidence — remediation then re-validate.

Read the full file on GitHub · 126 lines

Changes

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.

  1. 2d ago First seen · 126 lines · 1,771 tokens per session scan A 979c0a1009fd

Subscribe to this mod's changes

security-engineer is a cursor rule published in the GitHub repository ulises-jeremias/agent-toolkit (16 stars, last pushed 4d ago), licensed MIT. It adds 1,771 tokens to every session, about $0.0089 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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