---
license: apache-2.0
tags:
- prompt-injection
- jailbreak-detection
- guardrails
- security
- llm-security
- ai-safety
- ai-agent-security
- patronus
- multilingual
- modernbert
- onnx
- quantized
- edge
base_model: patronus-studio/wolf-defender-prompt-injection-small
pipeline_tag: text-classification
language:
- de
- en
---

# Model Card for Wolf Defender Prompt-Injection Detector Small Edge

**Edge/quantized ONNX variant of [`patronus-studio/wolf-defender-prompt-injection-small`](https://huggingface.co/patronus-studio/wolf-defender-prompt-injection-small).** Private / internal.

Quantized with the Patronus RunPod ONNX method (`quantize_dynamic` INT8 linears + `MatMulNBitsQuantizer`
4-bit block-128 embedding). The parent FP32/FP16 model is unchanged. Binary prompt-injection detector
(mmBERT-small, on-device variant).

## Benchmark — Qualifire

Evaluated on [Qualifire](https://huggingface.co/datasets/rogue-security/prompt-injections-benchmark)
(5,000 prompts, max_length 2048). Quantization is lossless vs FP32.

| Variant | Size | F1 | Precision | Recall | FPR | Accuracy |
|---|---|---|---|---|---|---|
| fp32 (parent) | — | 0.9102 | 0.9144 | 0.9061 | 0.057 | 0.928 |
| int8 | 135 MB | 0.9097 | 0.9113 | 0.9081 | 0.059 | 0.928 |
| **int8_int4_embeddings** | **92 MB** | **0.9121** | 0.9121 | 0.9121 | 0.059 | 0.930 |

**Recommended: `onnx/int8_int4_embeddings/model.onnx`** — ~5.8x smaller than FP32 at zero quality loss.

## Benchmark — Patronus Validation Set

Held-out validation split of the internal Patronus prompt-injection dataset
(5,000 sampled: 1,727 attack / 3,273 benign, max_length 512). In-distribution; quantization lossless.

| Variant | F1 | Precision | Recall | FPR | Accuracy |
|---|---|---|---|---|---|
| fp32 (parent) | 0.9751 | 0.9751 | 0.9751 | 0.013 | 0.983 |
| int8 | 0.9740 | 0.9723 | 0.9757 | 0.015 | 0.982 |
| **int8_int4_embeddings** | 0.9754 | 0.9746 | 0.9763 | 0.013 | 0.983 |

## Files
- `onnx/fp16/model.onnx`, `onnx/int8/model.onnx`, `onnx/int8_int4_embeddings/model.onnx`
- `config.json`, `tokenizer.json`, `tokenizer_config.json` (from the parent)
- `metrics/quant_bench.json`

## License

This model is released under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).
A copy of the license is included as `LICENSE` in this repository.

## Patronus Ark

This model is built to run inside **Patronus Ark**, Patronus' open-source on-device
AI-security scanning library (L1 native rules → L2 NTDB cascade → L3 transformer).
Ark is not publicly released yet — a repository link will be added here at launch.

---

## 🛡️ Patronus Protect

Brought to you by **[Patronus Protect](https://patronus.studio)** — a local AI firewall that
secures every AI interaction (prompts, tools, documents) before it reaches your models.
**Try it for free at [patronus.studio](https://patronus.studio).**