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automated-testing

Run Python-based prompt-injection and adversarial security tests in CI/CD pipelines.

3|Updated Nov 18, 2025
Search Tags:#reporting#ci-cd#automated-testing#security-testing#ai-security#prompt-injection#adversarial-robustness
One-click install
npx skills add https://github.com/pluginagentmarketplace/custom-plugin-ai-red-teaming --skill automated-testing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: automated-testing
Source: https://github.com/pluginagentmarketplace/custom-plugin-ai-red-teaming/tree/main/skills/automated-testing
Command: npx skills add https://github.com/pluginagentmarketplace/custom-plugin-ai-red-teaming --skill automated-testing

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The Automated AI Security Testing Skill reduces risk by providing an automated framework to test, validate, and monitor AI behavior in CI/CD.

Core Features & Use Cases

  • Comprehensive Injection Testing: automatically runs prompt-injection checks against LLM prompts to ensure safety and compliance.
  • Adversarial Robustness Assessment: integrates with python-based test suites to quantify robustness and detect vulnerabilities.
  • CI/CD Integration: plugs into common pipelines to run security tests on every commit or PR, producing actionable reports and gating deployments.

Quick Start

Use the automated-testing skill to kick off a quick security scan within your CI workflow by invoking the test runner on your AI service, for example:

  • Run: python scripts/run-automated-tests.py --target https://api.example.com --output security_test_report.json

Frequently Asked Questions about automated-testing

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

FAQPage Schema
How do I run automated prompt-injection tests in a CI/CD pipeline?▼

Automated AI security testing identifies and mitigates prompt-injection risks by applying a configurable test matrix across CI/CD pipelines, testing environments, and production integrations to continuously validate model behavior and ensure safety compliance.

How do I automate adversarial robustness assessment for LLM systems?▼

Adversarial robustness assessment is automated using integrated Python-based test suites that quantify model robustness, detect vulnerabilities against adversarial attacks, and output structured reports to gate deployments in your pipeline.

Can I use Python scripts to automate AI security testing on pull requests?▼

Python scripts execute AI security testing on pull requests by plugging directly into common CI/CD pipelines, running prompt-injection and adversarial risk checks against your AI service, and generating actionable reports to gate merges.

What is the best way to block deployments vulnerable to prompt injection?▼

Blocking deployments vulnerable to prompt injection is handled by plugging automated AI security tests into your pipeline, which runs injection checks on every commit and outputs structured reports used for gating deployment decisions.

Does automated AI security testing support a configurable test matrix?▼

Automated AI security testing supports a configurable test matrix to continuously validate model behavior, allowing you to customize prompt-injection and adversarial robustness checks across testing environments and production integrations.

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