integrity-failures

Detect unsafe deserialization patterns and unverified artifact trust in code and CI/CD workflows.

20|Updated Feb 27, 2026

Search Tags:#security #integrity #input-validation #deserialization #artifact-signing #secure-updates

Ready to run

npx skills add https://github.com/thejefflarson/soundcheck --skill integrity-failures

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: integrity-failures
Source: https://github.com/thejefflarson/soundcheck/tree/main/.claude/skills/integrity-failures
Command: npx skills add https://github.com/thejefflarson/soundcheck --skill integrity-failures

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Protects against arbitrary code execution and tampered artifacts during data handling, software updates, and artifact downloads.

Core Features & Use Cases

Detects risky deserialization patterns (pickle, unsafe YAML loaders) and untrusted input handling.
Enforces explicit schema validation before business logic processes data.
Verifies cryptographic signatures or digests for updates and artifacts.
Use Case: securing a Python service that deserializes user input and downloads plugins.

Quick Start

Run the integrity-failures check on your codebase to identify unsafe deserialization patterns and validate artifact integrity.

Frequently Asked Questions about integrity-failures

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I prevent insecure deserialization when processing untrusted user input in Python?▼

To prevent insecure deserialization, you must flag risky patterns like pickle and unsafe YAML loaders, then enforce explicit schema validation before business logic processes the untrusted input. This stops arbitrary code execution during data handling.

How do I verify cryptographic signatures for software updates and artifact downloads?▼

Verifying cryptographic signatures for software updates requires enforcing cryptographic verification of digests or signatures before any execution. This artifact trust process prevents tampered artifacts from compromising your CI/CD workflows.

What is the best way to detect unsafe YAML loaders and pickle usage in my codebase?▼

The best way to detect unsafe YAML loaders and pickle usage is to run an integrity check across code paths processing untrusted data. This identifies risky deserialization patterns and enforces safe deserialization practices automatically.

Can I use schema validation to secure plugin downloads and untrusted data in CI/CD workflows?▼

Yes, you can secure plugin downloads and untrusted data in CI/CD workflows by applying explicit schema validation and cryptographic verification before execution. This validates artifact integrity across all untrusted data paths.

Why does explicit schema validation matter before processing untrusted data?▼

Explicit schema validation matters because it ensures untrusted data conforms to expected structures before reaching business logic. This prevents code execution vulnerabilities and artifact tampering during software updates and data handling.