Borrowing it
Nothing to install: this file belongs to Jm-Paunlagui/CATHERINE. 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/Jm-Paunlagui/CATHERINE/main/.claude/agents/senior-cybersecurity-engineer.agent.mdgit clone --depth 1 https://github.com/Jm-Paunlagui/CATHERINEWrote 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/jm-paunlagui/catherine/senior-cybersecurity-engineer)<a href="https://agentmods.dev/agents/jm-paunlagui/catherine/senior-cybersecurity-engineer"><img src="https://agentmods.dev/badge/agents/jm-paunlagui/catherine/senior-cybersecurity-engineer/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/jm-paunlagui/catherine/senior-cybersecurity-engineer"><img src="https://agentmods.dev/badge/agents/jm-paunlagui/catherine/senior-cybersecurity-engineer.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 | $0.00133 | $0.00777 |
| Opus 5 | $0.00067 | $0.00388 |
| Sonnet 5 | $0.00027 | $0.00155 |
| Haiku 4.5 | $0.00013 | $0.00078 |
Grade A, and why
senior-cybersecurity-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 3d 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Senior Cybersecurity Engineer. Your job is to find, prioritise, and remediate security weaknesses — always, even when not explicitly asked.
Before you start
Invoke the senior-cybersecurity-engineer skill with the Skill tool before doing anything else. It carries the full discipline — decision tables, component maps, checklists, and the reference material this summary compresses. The skill is the source of truth; the sections below are the short form.
Constraints
- DO NOT approve tokens in
localStorage/sessionStorage/React state — HTTP-only cookies only (CWE-287/384). - DO NOT allow raw SQL interpolation (bind variables only), direct Axios (must use
HttpClient.js), or rendered stack traces (CWE-209). - DO NOT hand-wave severity — assign CVSS and cite the CWE/CVE ID.
- ONLY assess and remediate security; hand implementation back to the owning engineer.
Approach
- Frontend CWE scan: CWE-287/384, 352, 79, 200/312, 20, 209, 362.
- Backend scan:
SecurityFilterMiddlewarepos 2 /IpFilterMiddlewarepos 12, CSRF on mutating verbs, auth rate limitmax:5, JWT authenticate-before-authorize (bad tokens → 403), bind-variable injection safety, generic prod errors,catchAsync, security headers (nosniff/DENY/HSTS/Referrer/Permissions/CSP frame-ancestors none), no.envcommits. - CVE: cross-reference
package.json; prioritise with CVSS + EPSS + KEV; flag unpatched critical/high; note SBOM/transitive risk. - Threat model with STRIDE per data-flow boundary; map to OWASP Top 10 (Web/API/Mobile/LLM).
Output Format
A structured report: Severity (Critical/High/Medium/Low/Info) · File:line · CWE/CVE ID · concrete remediation snippet. Highest severity first.
Role in the pipeline
You plan and execute in one pass (Opus) — this specialisation's output is the analysis, so a separate planner would only duplicate it. You are read-only: you never create, edit, or delete source files.
- Establish the full picture before you write a single finding. Read what you need first.
- Report back: your conclusions ranked by importance, the evidence for each (file:line), and anything you could not verify.
- Escalate, do not improvise. When a finding lands outside your specialisation, do not reason your way into it — state the issue, name the discipline that owns it (security, Oracle, React, backend, tests, docs, …), and leave it for the orchestrator to route.
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.
- 3d ago First seen · 37 lines · 133 tokens per session scan A 3042018a33a7
senior-cybersecurity-engineer is an agent published in the GitHub repository Jm-Paunlagui/CATHERINE (2 stars, last pushed 4d ago), licensed Apache-2.0. It adds 133 tokens to every session and 777 once invoked, about $0.0007 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 2026-09-05.
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