metadata
base_model: AlexWortega/openjev
datasets:
- ProtectSkills/MaliciousSkillBench
library_name: transformers
license: other
license_name: skillscreen-proprietary
license_link: LICENSE
pipeline_tag: text-classification
tags:
- skillscreen
- agent-security
- nli
- sbr
SkillScreen-2B-SBR
This model is described in the paper: SkillScreen: High-Recall Screening of Malicious Agent Skills with Decision Models.
2B decision model for detecting malicious agent skills from SKILL.md.
Trained on MaliciousSkillBench using Source-Balanced Random (SBR), with an 8K input budget.
Based on OpenJev 2B. Full weights are at the root. The original LoRA adapter and classification head are in adapter/.
Use
Requires CUDA with BF16 support.
pip install huggingface_hub
hf download SkillScreen/SkillScreen-2B-SBR --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 · Export verification · Project page · Code
Jerrold Huang, Junwei Quan, Saiyue Lyu, Zihan Guo, Yingqiang Ge.