python-security

Guidance for building and reviewing secure Python applications using OWASP Top 10 practices, which cover common web-application security risks. The supplied description does not provide further details.

In plain words
What is it for?
It is intended for secure Python design, implementation, or security review, but the exact supported jobs are not specified here.
Why use it?
The available information is too limited to identify the specific security checks or implementation features it provides.

Skill for Claude CodeCodex

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 skills/jim60105/copilot-prompt/python-security
Any agent
npx skills add jim60105/copilot-prompt --skill python-security
Clone the repo
git clone --depth 1 https://github.com/jim60105/copilot-prompt

Made for: Claude Code, Codex.

Per session 149 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,690 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 2 findings. Scan, not verified.
Origin unknown 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 $0.00149 $0.02690
Opus 5 $0.00075 $0.01345
Sonnet 5 $0.00030 $0.00538
Haiku 4.5 $0.00015 $0.00269

Measured 2d ago against content hash e99854ff2fe9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

python-security scanned grade A with 2 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

| A01 | Broken Access Control | Missing `@login_required` / auth decorators, IDOR via sequential IDs, path traversal, SSRF via `requests.get(user_url)` | Centralized auth middleware, object-level permissions, `pathlib.re

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

| `shell=True` + user input in subprocess | `subprocess.run([cmd, arg1, arg2])` with list args |
skills/python-security/SKILL.md · 185 lines

The source is not reproduced here

Licensed GFDL-1.3

The repository is licensed GFDL-1.3, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 185 lines · 149 tokens per session scan A e99854ff2fe9

Subscribe to this mod's changes

python-security is a skill published in the GitHub repository jim60105/copilot-prompt (21 stars, last pushed 2d ago), licensed GFDL-1.3. It adds 149 tokens to every session and 2,690 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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