Plexiglass

Overview

Plexiglass is an open source Python toolkit for detecting and protecting against vulnerabilities in Large Language Models. It provides tools to identify security issues such as prompt injection and monitor LLM outputs for harmful content. The toolkit is designed for integration into LLM application pipelines to add a layer of defense.

Best for

Best for
Developers seeking a lightweight, open source tool to add basic security checks to LLM applications

Use cases

• Auditing LLM responses for prompt injection attacks
• Implementing guardrails to filter unsafe outputs
• Testing LLM robustness against adversarial inputs

Notes

Plexiglass is an open source Python toolkit for detecting and protecting against vulnerabilities in Large Language Models. It provides tools to identify security issues such as prompt injection and monitor LLM outputs for harmful content. The toolkit is designed for integration into LLM application pipelines to add a layer of defense.

154 stars on GitHub. Last updated 2026-02-04. Licensed Apache-2.0.

Use cases

• Auditing LLM responses for prompt injection attacks
• Implementing guardrails to filter unsafe outputs
• Testing LLM robustness against adversarial inputs

Pros

• Open source and free to use with no vendor lock-in
• Python-based, easy to integrate into existing LLM workflows
• Focused specifically on LLM security vulnerabilities

Cons

• Small community with only 154 GitHub stars, limited support
• May not cover all emerging attack vectors or complex scenarios
• Documentation and examples may be sparse for production use

Indexed from awesome-llmops and enriched against its public facts.