Hidden Risks of Jev: An Empirical Study of Security, Privacy, and Dual Use

cs.CR, cs.AI

Submitted: 2026-10-04

Updated: 2026-10-04

Comments: 16 pages, 8 figures, 6 tables; The source code is available at \url{https://github.com/shihe98/Security_Privacy_Jev}

Code: https://github.com/shihe98/Security

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• Jev for Scientific Decisions: Evaluating Semantic Choices and Their Consequences
• BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
• How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection
• Can Jev Judge Radiology Reports? Evaluating a System One Model for Clinical Factuality
• Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
• Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
• PromptShield: Deployable Detection for Prompt Injection Attacks
• Jev-Mem: System-One-Controlled Agentic Memory for Efficient AI Agents
• JEV-as-a-Judge: Accept When Confident, Escalate When Unsure
• HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
• SkillGuard: A Permission-Centric Framework for Agent Skill Security
• Calibrated Decisions at Scale: Converting Police Crash Narratives into Probabilistic Crash Variables with a System One Model (Jev)
• Same Scores, Different Decisions: Evaluating JEV and Language Models for Legal Document Understanding
• Universal and Transferable Adversarial Attacks on Aligned Language Models

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