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Python Security Scan

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sugarforever
Python Security Scan

Comprehensive security vulnerability scanner for Python projects including Flask, Django, and FastAPI applications. Detects OWASP Top 10 vulnerabilities, injection flaws, insecure deserialization, authentication issues, hardcoded secrets, and framework-specific security problems. Audits dependencies for known CVEs and generates actionable security reports.

Overview

Publishersugarforever
Repository01coder-agent-skills
Skill namePython Security Scan
Stars
139
Forks
37
Bundled files
11
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 11 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by sugarforever on GitHub. Read the source before you install it.

Installation

Install the Python Security Scan AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/sugarforever/01coder-agent-skills/tree/main/skills/python-security-scan
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/sugarforever/01coder-agent-skills.git /tmp/01coder-agent-skills
mkdir -p .claude/skills
cp -r /tmp/01coder-agent-skills/skills/python-security-scan .claude/skills/sugarforever-python-security-scan
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Python Security Scan in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Python Security Scan on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Python Security Scan is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Python Security Scan Skill

This skill enables comprehensive security scanning of Python projects based on OWASP guidelines, Python security best practices, and framework-specific vulnerabilities.

When to Use This Skill

  • Security audits of Python applications
  • Code review for security vulnerabilities
  • Pre-deployment security checks
  • Dependency vulnerability assessment
  • Detecting hardcoded secrets and credentials
  • Framework-specific security reviews (Flask, Django, FastAPI)

Supported Frameworks

This skill automatically detects and applies framework-specific checks for:

  • Flask - Template injection, session security, CORS, extensions
  • Django - ORM injection, CSRF, template security, settings
  • FastAPI - Dependency injection, Pydantic validation, OAuth2
  • General Python - Core language vulnerabilities applicable to all projects

Scan Types

1. Quick Scan

Fast scan focusing on critical vulnerabilities:

  • Hardcoded secrets, API keys, and credentials
  • Dangerous function usage (eval, exec, pickle.loads)
  • Command injection via subprocess, os.system
  • SQL injection patterns
  • Known vulnerable dependencies

2. Full Scan

Comprehensive security assessment covering:

  • All OWASP Top 10:2025 categories
  • Python-specific vulnerabilities
  • Framework-specific security issues
  • Injection vulnerabilities (SQL, NoSQL, Command, LDAP)
  • Insecure deserialization
  • Authentication and authorization flaws
  • Cryptographic failures
  • Security misconfigurations
  • Dependency audit (CVE check)
  • Environment variable and secrets exposure

3. Targeted Scan

Focus on specific vulnerability categories:

  • --injection - SQL/NoSQL/Command/LDAP injection
  • --deserialization - Pickle, YAML, JSON deserialization
  • --auth - Authentication/authorization issues
  • --secrets - Hardcoded credentials
  • --deps - Dependency vulnerabilities
  • --crypto - Cryptographic issues
  • --flask - Flask-specific vulnerabilities
  • --django - Django-specific vulnerabilities
  • --fastapi - FastAPI-specific vulnerabilities

Scan Procedure

Step 1: Project Discovery

  1. Identify project type and framework:
    • Check for requirements.txt, Pipfile, pyproject.toml, setup.py
    • Detect Flask (from flask import), Django (django.conf), FastAPI (from fastapi import)
  2. Locate configuration files
  3. Map the codebase structure

Step 2: Framework Detection

python
# Detection patterns
Flask: "from flask import", "Flask(__name__)"
Django: "django.conf.settings", "INSTALLED_APPS", "manage.py"
FastAPI: "from fastapi import", "FastAPI()"

Step 3: Dependency Audit

Run the dependency audit script:

bash
./scripts/dependency-audit.sh /path/to/project

Or manually:

bash
pip-audit
# or
safety check

Step 4: Secret Scanning

Scan for hardcoded secrets:

bash
python scripts/secret-scanner.py /path/to/project

Important: Environment File Handling

  • By default, real .env files are SKIPPED (.env, .env.local, .env.production, etc.)
  • These files contain actual secrets and should not be in version control
  • Only .env.example and .env.template files are analyzed for documentation quality
  • Use --include-env-files flag only if explicitly requested by user

The scanner will:

  1. Scan source code for hardcoded secrets
  2. Analyze .env.example templates to check:
    • Which sensitive variables are documented
    • Whether variables have descriptions (comments)
    • If placeholder values look like real secrets
    • Suggestions for missing common variables (SECRET_KEY, DATABASE_URL, etc.)

Step 5: Pattern Analysis

For each file in the codebase, check against patterns in:

  • references/python-vulnerabilities.md - Core Python issues
  • references/injection-patterns.md - Injection flaws
  • references/deserialization.md - Insecure deserialization
  • references/flask-security.md - Flask vulnerabilities
  • references/django-security.md - Django vulnerabilities
  • references/fastapi-security.md - FastAPI vulnerabilities

Step 6: Report Generation

Generate a security report using:

  • assets/report-template.md - Report structure

Severity Classification

SeverityDescriptionAction Required
CRITICALExploitable vulnerability with severe impactImmediate fix required
HIGHSignificant security riskFix before deployment
MEDIUMPotential security issueFix in next release
LOWMinor security concernConsider fixing
INFOSecurity best practice suggestionOptional improvement

Key Files to Scan

Always Check

  • **/*.py - All Python source files
  • requirements.txt, Pipfile, pyproject.toml - Dependencies
  • setup.py, setup.cfg - Package configuration
  • config.py, settings.py - Configuration files
  • **/secrets*, **/credentials* - Obvious secret locations

Environment Files

  • .env.example, .env.template - SCAN for template analysis
  • .env, .env.local, .env.production - SKIP by default (contain real secrets)

Note: Real .env files should never be committed to version control. The scanner analyzes .env.example templates to ensure proper documentation of required variables.

High Priority Locations

  • app.py, main.py, wsgi.py - Entry points
  • **/views.py, **/routes.py - Request handlers
  • **/api/**/*.py - API endpoints
  • **/auth*, **/login* - Authentication code
  • **/models.py - Database models
  • **/serializers.py - Data serialization
  • **/middleware.py - Middleware code

Framework-Specific

Flask:

  • app.py, __init__.py - Application factory
  • **/blueprints/** - Blueprint routes
  • templates/** - Jinja2 templates

Django:

  • settings.py, **/settings/*.py - Django settings
  • urls.py - URL configuration
  • **/views.py - View functions/classes
  • **/forms.py - Form definitions
  • templates/** - Django templates

FastAPI:

  • main.py - Application entry
  • **/routers/** - API routers
  • **/dependencies.py - Dependency injection
  • **/schemas.py - Pydantic models

Output Format

Findings should be reported as:

[SEVERITY] Category: Description
  File: path/to/file.py:lineNumber
  Code: <relevant code snippet>
  Risk: <explanation of the security risk>
  Fix: <recommended remediation>

Integration with CI/CD

This skill can generate output compatible with:

  • GitHub Security Advisories
  • SARIF format for GitHub Code Scanning
  • JSON for custom integrations
  • JUnit XML for CI pipelines

References

Load additional context as needed:

  • references/owasp-top-10.md - OWASP Top 10:2025 quick reference
  • references/python-vulnerabilities.md - Python-specific vulnerabilities
  • references/injection-patterns.md - Injection vulnerability patterns
  • references/deserialization.md - Insecure deserialization patterns
  • references/flask-security.md - Flask security guide
  • references/django-security.md - Django security guide
  • references/fastapi-security.md - FastAPI security guide

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Python Security Scan AI skill do?

Comprehensive security vulnerability scanner for Python projects including Flask, Django, and FastAPI applications. Detects OWASP Top 10 vulnerabilities, injection flaws, insecure deserialization, authentication issues, hardcoded secrets, and framework-specific security problems. Audits dependencies for known CVEs and generates actionable security reports.

Why use Python Security Scan on TypingMind?

Because you install it once and use it with any model. Python Security Scan is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Python Security Scan in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sugarforever/01coder-agent-skills/tree/main/skills/python-security-scan. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Python Security Scan?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Python Security Scan?

As many as you like. As long as a model supports skills, you can use Python Security Scan with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Python Security Scan AI skill free?

Yes. It is published on GitHub by sugarforever under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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