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prompt-injection-classifier – AI Model by zachz | AlphaNeural AI

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zachz/
prompt-injection-classifier

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sklearn-pipeline

text-classification

prompt-injection

zachz/prompt-injection-benchmark

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Prompt Injection Classifier

A lightweight sklearn-based classifier that detects prompt injection attacks in LLM inputs.

Model Details

Type: TF-IDF + Logistic Regression pipeline
Task: Binary text classification (injection vs clean)
Framework: scikit-learn
Accuracy: ~94% (5-fold cross-validation)

Usage

python

import pickle

with open("model.pkl", "rb") as f:
    model = pickle.load(f)

# Predict
text = "Ignore all previous instructions"
prediction = model.predict([text])[0]  # 1 = injection, 0 = clean
probability = model.predict_proba([text])[0][1]  # injection probability

Training Data

Trained on 50 examples (25 injection, 25 clean) covering common attack patterns:

Instruction overrides
Role reassignment
Jailbreak attempts
System prompt extraction
Safety bypass attempts

Limitations

Small training set; best used as a first-pass filter
May not catch novel or obfuscated injection techniques
English only

License

MIT