defense-in-depth_skill

This skill implements multi-layer validation and security patterns to harden apps, enabling robust input handling, error management, and threat mitigation.

Python

0

GitHub Stars

1

Bundled Files

3 weeks ago

Catalog Refreshed

2 months ago

First Indexed

Readme & install

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Installation

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npx veilstart add skill chunkytortoise/enterprisehub --skill defense-in-depth

SKILL.md14.6 KB

Overview

This skill implements a defense-in-depth strategy for building resilient Python applications. It provides five layered validations—input, business logic, database, API, and application security—so systems tolerate errors and resist attacks. Use it to add structured validation, consistent error handling, and monitoring across your stack.

How this skill works

The skill defines a ValidationResult structure and validators for each layer to return sanitized data, warnings, and errors. Layers run sequentially or independently: start with input sanitization, enforce domain rules, use parameterized database operations, validate API auth/rate limits, and log/analyze security events. Each layer can short-circuit on failure and always returns a consistent result object for callers.

When to use it

When you need multi-layer input validation and sanitization
When building robust error handling and consistent validation results
When hardening APIs with JWT checks, rate limiting, and permission checks
When protecting the database with parameterized queries and filter validation
When adding monitoring, anomaly detection, and security event logging

Best practices

Fail secure: default to deny and explicit allow only after checks
Return a consistent ValidationResult with sanitized_data, errors, and severity
Apply validation at every layer; never trust previous layer alone
Log security-relevant events with severity and contextual details for audits
Use parameterized queries and limit result sizes to reduce attack surface

Example use cases

Lead registration pipeline that validates email, enforces rate limits, writes safely to DB, and logs security events
FastAPI endpoints that use dependency-based JWT validation and per-IP rate limiting
CRM import process that sanitizes HTML, applies business rules, and runs safe inserts/updates
Integration with external webhooks where payloads are verified, sanitized, and audited
Streamlit or LLM frontends that validate user inputs and enforce domain constraints before downstream processing

FAQ

A ValidationResult includes is_valid, errors, warnings, sanitized_data, and a severity level for consistent handling.

Can layers run independently?

Yes. Layers are designed to operate independently; you can run selected layers for performance or integration needs while maintaining defensive guarantees.