---
library_name: transformers
pipeline_tag: text-classification
license: other
license_name: skillscreen-proprietary
license_link: LICENSE
base_model: AlexWortega/openjev
datasets:
- ProtectSkills/MaliciousSkillBench
tags:
- skillscreen
- agent-security
- nli
- sd
---

# SkillScreen-2B-SD

This model is described in the paper: [SkillScreen: High-Recall Screening of Malicious Agent Skills with Decision Models](https://huggingface.co/papers/2610.17727).

2B decision model for detecting malicious agent skills from `SKILL.md`. Trained on MaliciousSkillBench using Source-Disjoint (SD), with an 8K input budget.

Based on [OpenJev 2B](https://huggingface.co/AlexWortega/openjev). Full weights are at the root. The original LoRA adapter and classification head are in `adapter/`.

## Use

Requires CUDA with BF16 support.

```bash
pip install huggingface_hub
hf download SkillScreen/SkillScreen-2B-SD --revision v1 --local-dir skillscreen
pip install -r skillscreen/requirements.txt
python skillscreen/score.py path/to/SKILL.md
```

Native maliciousness score **≥ 0.5** is flagged as suspicious.

[Checkpoint details](provenance.json) · [Export verification](merge_verification.json) · [Project page](https://jerroldh.github.io/SkillScreen-webpage/) · [Code](https://github.com/JerroldH/SkillScreen)

Jerrold Huang, Junwei Quan, Saiyue Lyu, Zihan Guo, Yingqiang Ge.

[License](LICENSE) · [Third-party notices](THIRD_PARTY_NOTICES.md)