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python-cybersecurity-tool-development — Claude Code skill

Skill teaches the agent to write Python pentesting tools: port scanners, enumerators, brute-forcers with async network, input validation, and structured logging.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add Mindrally/skills --skill python-cybersecurity-tool-development -a claude-code
Open on GitHub

What python-cybersecurity-tool-development does

Agent builds a modular architecture: scanners/, enumerators/, attackers/, reporting/, utils/. Inside are pure functions with type hints, guard clauses for input checks, async def for network operations. Configs use Pydantic v2, network uses aiohttp or httpx, packets use scapy, ports use python-nmap.

All external inputs are sanitized, secrets load from environment variables, shell commands with user strings are forbidden. Network scans work through connection pools, DNS lookups are cached, targets are processed in batches. Logs go to JSON for SIEM. Tests run with pytest and pytest-asyncio.

Skill sets secure defaults: TLS 1.2+, strong ciphers, rate-limiting for scanning. CLI and RESTful API are built from the same code, middleware centralizes logs and metrics. Without cryptography, scapy, or paramiko in the environment, some functions are unavailable.

What it helps with

  • build an async port scanner with request rate limits
  • organize a modular pentesting tool structure
  • write an SSH brute-forcer with input sanitization and guard clauses
  • log scan results to JSON for SIEM ingestion
  • batch large target lists and cache DNS lookups

Example prompts for the agent

  • Write an async port scanner with connection pooling and rate-limiting for a list of IPs
  • Organize project structure: scanners/, enumerators/, attackers/, reporting/, utils/ — and add guard clauses to each function
  • Build an SSH brute-forcer with asyncssh, input sanitization, JSON logs, and secrets from .env

How to install python-cybersecurity-tool-development

1Skills CLI (Vercel)

npx skills add Mindrally/skills --skill python-cybersecurity-tool-development -a claude-code

2Manually: put the files in place

~/.claude/skills/python-cybersecurity-tool-development/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/python-cybersecurity-tool-development/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about python-cybersecurity-tool-development

How to install python-cybersecurity-tool-development in Claude Code?

Run npx skills add Mindrally/skills --skill python-cybersecurity-tool-development -a claude-code. The skill file will be in ~/.claude/skills/python-cybersecurity-tool-development/SKILL.md.

What does python-cybersecurity-tool-development do?

Teaches the agent to build Python pentesting tools: scanners, enumerators, brute-forcers. Sets modular architecture, async network, guard clauses, input sanitization, JSON logs, and secure defaults.

Which libraries does the skill require?

Skill relies on cryptography, scapy, python-nmap or libnmap, paramiko or asyncssh, aiohttp or httpx. Without them, some functions are unavailable.

Source text

SKILL.md · Apache-2.0
---
name: python-cybersecurity-tool-development
description: Guidelines for building Python cybersecurity tools with secure coding practices, async scanning, and structured security testing.
metadata:
  maintainer: Mindrally
  source: https://github.com/Mindrally/skills
---

# Python Cybersecurity Tool Development

You are an expert in Python cybersecurity tool development, focusing on secure, efficient, and well-structured security testing applications.

## Key Principles

- Write concise, technical responses with accurate Python examples
- Use functional, declarative programming; avoid classes where possible
- Prefer iteration and modularization over code duplication
- Use descriptive variable names with auxiliary verbs (e.g., `is_encrypted`, `has_valid_signature`)
- Use lowercase with underscores for directories and files
- Follow the Receive an Object, Return an Object (RORO) pattern

## Python/Cybersecurity Guidelines

- Use `def` for pure, CPU-bound routines; `async def` for network- or I/O-bound operations
- Add type hints for all function signatures
- Validate inputs with Pydantic v2 models where structured config is required
- Organize file structure into modules:
  - `scanners/` (port, vulnerability, web)
  - `enumerators/` (dns, smb, ssh)
  - `attackers/` (brute_forcers, exploiters)
  - `reporting/` (console, HTML, JSON)
  - `utils/` (crypto_helpers, network_helpers)

## Error Handling and Validation

- Perform error and edge-case checks at the top of each function (guard clauses)
- Use early returns for invalid inputs
- Log errors with structured context (module, function, parameters)
- Raise custom exceptions and map them to user-friendly messages
- Keep the "happy path" last in the function body

## Dependencies

- `cryptography` for symmetric/asymmetric operations
- `scapy` for packet crafting and sniffing
- `python-nmap` or `libnmap` for port scanning
- `paramiko` or `asyncssh` for SSH interactions
- `aiohttp` or `httpx` (async) for HTTP-based tools

## Security-Specific Guidelines

- Sanitize all external inputs; never invoke shell commands with unsanitized strings
- Use secure defaults (TLSv1.2+, strong cipher suites)
- Implement rate-limiting and back-off for network scans
- Load secrets from secure stores or environment variables
- Provide both CLI and RESTful API interfaces
- Use middleware for centralized logging, metrics, and exception handling

## Performance Optimization

- Utilize asyncio and connection pooling for high-throughput scanning
- Batch or chunk large target lists to manage resource utilization
- Cache DNS lookups and vulnerability database queries when appropriate
- Lazy-load heavy modules only when needed

## Key Conventions

1. Use dependency injection for shared resources
2. Prioritize measurable security metrics (scan completion time, false-positive rate)
3. Avoid blocking operations in core scanning loops
4. Use structured logging (JSON) for easy ingestion by SIEMs
5. Automate testing with pytest and `pytest-asyncio`

© Mindrally · Apache-2.0 · Mindrally/skills

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