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/briiirussell/cybersecurity-skillsWrote 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/rules/briiirussell/cybersecurity-skills/personal-opsec)<a href="https://agentmods.dev/rules/briiirussell/cybersecurity-skills/personal-opsec"><img src="https://agentmods.dev/badge/rules/briiirussell/cybersecurity-skills/personal-opsec/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/rules/briiirussell/cybersecurity-skills/personal-opsec"><img src="https://agentmods.dev/badge/rules/briiirussell/cybersecurity-skills/personal-opsec.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 | $0.00189 | $0.04870 |
| Opus 5.5 | $0.00076 | $0.01948 |
| Sonnet 5.5 | $0.00038 | $0.00974 |
| Haiku 4.5 | $0.00019 | $0.00487 |
Grade B, and why
personal-opsec scanned grade B with 3 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 today.
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.
Reaches for credential filesmediumPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
- Glob for: `~/.aws/credentials`, `~/.config/gh/hosts.yml`, `~/.npmrc`, `~/.netrc`, `~/.docker/config.json`, `~/.pypirc`, `~/.kube/config`, `~/.config/gcloud/application_default_credentials.json`, `~/.ssh/id_*`, `**/.env Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Reads agent configuration directorieslowAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
**C2 — MCP servers and agent extensions.** Inventory what's connected and what each can reach. Check config files (Grep for server names and `command`/`url` keys only; count, don't print, any `env` values): `~/.claude.js Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Reads MCP configurationlowAgent snooping
mcp.json carries server URLs and auth tokens; reading it lets a mod discover and abuse other integrations.
**C2 — MCP servers and agent extensions.** Inventory what's connected and what each can reach. Check config files (Grep for server names and `command`/`url` keys only; count, don't print, any `env` values): `~/.claude.js Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Personal OpSec — Audit One Operator's Own Security Setup
Every other skill in this catalog audits an organization, a codebase, or infrastructure. This one audits a person: the founder, solo operator, or small-team admin whose laptop, email, phone number, and password manager are the real root of trust for the whole stack. If their email falls to a SIM swap, it doesn't matter how good the IAM policies are.
This is not security-awareness or phishing training. No quizzes, no "think before you click" content. The agent checks the person's actual state — on the local machine where it can, by asking where it can't — and produces a prioritized gap report in the same finding/disposition vocabulary as the audit skills, ready for finding-triage.
The baseline is Karpathy's 15-control list (via Andrej Karpathy's digital security checklist), plus the operator-critical items it skips and the AI-agent layer it predates. Products named below are examples of a control, not endorsements; any tool that provides the control counts.
Cross-references: secrets-audit for API keys and tokens on disk that coding agents can read; agent-supply-chain-audit for MCP server and agent-extension trust; prompt-injection for personal and inbox assistants that read untrusted mail; iam-audit for the org-level MFA and access policy this person administers; breach-patterns for the phishing and account-takeover patterns behind these controls; finding-triage for dispositions on each gap; osint-recon if the user wants to see what's public about themselves.
Authorization: consent and scope (before anything else)
- Only the person being audited runs this, on their own accounts and their own machine. Confirm that at the start. If the user asks to audit a co-founder, employee, partner, or anyone else, stop: that person runs it themselves, with their own consent. Refuse to profile, enumerate, or assess someone else's personal security, accounts, devices, or exposure without their explicit consent — that's surveillance or pre-attack recon, not opsec.
- On a work machine managed by an employer, local checks are fine, but don't attempt to read or change MDM/EDR configuration.
- Read-only. The agent never changes a setting, enables a feature, installs anything, or logs into an account. It reports; the user fixes.
- Never read secret values. The agent doing this audit is itself an AI agent with file access — exactly the exposure Part C measures. Check existence, file permissions, and match counts; never print a token, key, recovery code, or password into the transcript. If the user pastes one, tell them to rotate it.
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.
- today First seen · 189 lines · 189 tokens per session scan B 3e7645740ca5
personal-opsec is a cursor rule published in the GitHub repository briiirussell/cybersecurity-skills (435 stars, last pushed today), licensed MIT. It adds 189 tokens to every session and 4,870 once invoked, about $0.0008 per session on Opus 5.5. A static security scan graded it B with 3 findings (reaches for credential files, reads agent configuration directories, reads mcp configuration). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-27.
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