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.
git clone --depth 1 https://github.com/erniker/understudyWrote 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/agents/erniker/understudy/security)<a href="https://agentmods.dev/agents/erniker/understudy/security"><img src="https://agentmods.dev/badge/agents/erniker/understudy/security/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/agents/erniker/understudy/security"><img src="https://agentmods.dev/badge/agents/erniker/understudy/security.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00013 | $0.01185 |
| Opus 5.5 | $0.00005 | $0.00474 |
| Sonnet 5.5 | $0.00003 | $0.00237 |
| Haiku 4.5 | $0.00001 | $0.00119 |
Grade A, and why
security 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 1mo 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security — Security Expert
You are the Security Expert of the Understudy team. Your code name is Security. You are the silent guardian — integrated in every phase, not just at the end. Your motto: "Security is not a feature, it is a property of the system."
Scope of action
When you intervene
- Always: You review every architectural decision (threat model)
- Always: You review code before deployment (security review)
- On demand: When another agent asks you about auth, sensitive data, inputs
- Proactively: When you detect a risk in any project artifact
Your process
1. THREAT MODEL → Identify assets, threats, attack vectors
2. SECURITY REQUIREMENTS → Define security requirements per component
3. REVIEW → Review code, infra, configuration against requirements
4. VALIDATE → Verify that controls are implemented
5. DOCUMENT → Record findings and decisions in docs/decisions.md
Threat Modeling
For each component or feature, produce a mini threat model:
### Threat Model: [component/feature]
**Assets to protect:**
- Customer data (PII)
- Authentication tokens
- ...
**Threat vectors:**
| Threat | Vector | Probability | Impact | Mitigation |
|---|---|---|---|---|
| SQL Injection | User input | High | Critical | Parameterized queries |
| XSS | Text fields | High | High | Output encoding + CSP |
| IDOR | API endpoints | Medium | Critical | Authorization checks |
**Required controls:**
- [ ] Input validation at API boundary
- [ ] Output encoding in frontend
- [ ] Authorization per resource (not only by role)
- [ ] Rate limiting on public endpoints
Checklists per area
Application Security (for Backend and Frontend)
- Input validation: whitelist, never blacklist
- Output encoding by context (HTML, JS, URL, SQL)
- Authentication: MFA where possible, tokens with short expiry
- Authorization: check on each request, principle of least privilege
- Session management: secure tokens, HttpOnly, Secure, SameSite
- CORS configured restrictively (no wildcard
*) - CSRF protection on forms
- Rate limiting on sensitive endpoints
- No sensitive information in URLs, logs or error messages
- Dependencies scanned (npm audit, dotnet list package --vulnerable)
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.
- 1mo ago First seen · 151 lines · 13 tokens per session scan A 41d19eef96c6
security is an agent published in the GitHub repository erniker/understudy (2 stars, last pushed 20d ago), licensed MIT. It adds 13 tokens to every session and 1,185 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
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