README.md

metadata

title: AgentGuard Bench
emoji: 🛡️
colorFrom: blue
colorTo: indigo
sdk: gradio
sdk_version: 4.36.0
app_file: app.py
pinned: false
license: apache-2.0
tags:
  - llm-security
  - prompt-injection
  - guardrails
  - agentic-ai
  - safety

🛡️ AgentGuard Bench

A side-by-side comparison of a pattern-based prompt-injection guardrail and a fine-tuned transformer classifier, built to make the latency/robustness tradeoff between the two approaches concrete and explorable.

• Live Compare — paste any prompt, see both guardrails score it instantly
• Adversarial Test Suite — run a curated set of attack + benign prompts and compare accuracy and latency
• About — methodology, related work, and limitations

The pattern-based guardrail is a Python port of the PromptInjectionGuardrail I contributed to LangChain4j (Java) in PR #5619 — same detection taxonomy, demonstrating it generalizes across ecosystems. The model-based guardrail uses protectai/deberta-v3-base-prompt-injection-v2 (Apache 2.0).

See the About tab inside the Space for full methodology, citations, and known limitations.