Welcome to pytector’s documentation!

pytector is a Python package for detecting prompt injections in text using Open-Source Large Language Models (LLMs), designed to provide immediate security controls beyond foundation model defaults.

Contents:

Features

  • Prompt Injection Detection: Uses open-source language models for prompt injection detection

  • Content Safety: Support for Groq-hosted safeguard models for safety detection

  • Keyword-Based Blocking: Restrictive keyword filtering for immediate security control

  • Input Sanitization: Six-strategy pipeline to clean injection content from user input (encoding detection, unicode normalization, pattern removal, sentence scoring, fuzzy matching, keyword stripping) with zero additional dependencies

  • PII Detection: NER-based PII scanning using PasteProof PII Detector (ModernBERT, F1 0.97) covering 27 entity types — financial, credential, healthcare, GDPR, identity, contact, and address data

  • Toxicity Detection: Multilingual toxicity classification using citizenlab DistilBERT (F1 0.94, 10 languages)

  • Regex Scanner: Customizable rule-based pattern matching for PII and credentials (email, phone, SSN, credit card, IP, API keys, JWT) using pure Python stdlib

  • Canary Tokens: System prompt leak detection — inject a secret token and verify the model never repeats it. Zero dependencies, zero calibration

  • Multiple Model Backends: Support for Hugging Face Transformers and GGUF models

  • Rapid Deployment: Designed for quick integration into projects needing immediate security layers

  • Configurable: Customizable detection parameters, thresholds, and security policies

  • LangChain Integration: LCEL-compatible guardrail runnable for pre-model prompt checks

Quick Start

Install the package:

pip install pytector

Basic usage:

from pytector import PromptInjectionDetector

detector = PromptInjectionDetector()
is_injection, probability = detector.detect_injection("Hello, how are you?")
print(f"Injection detected: {is_injection}")

For more detailed information, see the Quick Start Guide guide.

Indices and tables