AI Threat Alert
Attack HIGH
AJAR: Adaptive Jailbreak Architecture for Red-teaming
Yipu Dou, Wang Yang
Large language model (LLM) safety evaluation is moving from content moderation to action security as modern systems gain persistent state, tool...
AI Security Research
2,077+ academic papers on AI security, attacks, and defenses
Total
2,077
Attack
809
Benchmark
603
Defense
272
Tool
226
Survey
113
Showing 321–340 of 809 papers
Clear filters Attack HIGH
Serverless AI Security: Attack Surface Analysis and Runtime Protection Mechanisms for FaaS-Based Machine Learning
Chetan Pathade, Vinod Dhimam, Sheheryar Ahmad +1 more
Serverless computing has achieved widespread adoption, with over 70% of AWS organizations using serverless solutions [1]. Meanwhile, machine learning...
Attack HIGH
Defending Large Language Models Against Jailbreak Attacks via In-Decoding Safety-Awareness Probing
Yinzhi Zhao, Ming Wang, Shi Feng +3 more
Large language models (LLMs) have achieved impressive performance across natural language tasks and are increasingly deployed in real-world...
Attack MEDIUM
The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models
Christina Lu, Jack Gallagher, Jonathan Michala +2 more
Large language models can represent a variety of personas but typically default to a helpful Assistant identity cultivated during post-training. We...
Attack MEDIUM
The Straight and Narrow: Do LLMs Possess an Internal Moral Path?
Luoming Hu, Jingjie Zeng, Liang Yang +1 more
Enhancing the moral alignment of Large Language Models (LLMs) is a critical challenge in AI safety. Current alignment techniques often act as...
Attack HIGH
Reasoning Hijacking: Subverting LLM Classification via Decision-Criteria Injection
Yuansen Liu, Yixuan Tang, Anthony Kum Hoe Tun
Current LLM safety research predominantly focuses on mitigating Goal Hijacking, preventing attackers from redirecting a model's high-level objective...
Attack LOW
Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD
Murat Bilgehan Ertan, Marten van Dijk
Differentially Private Stochastic Gradient Descent (DP-SGD) is the dominant paradigm for private training, but its fundamental limitations under...
Attack HIGH
ReasAlign: Reasoning Enhanced Safety Alignment against Prompt Injection Attack
Hao Li, Yankai Yang, G. Edward Suh +2 more
Large Language Models (LLMs) have enabled the development of powerful agentic systems capable of automating complex workflows across various fields....
Attack HIGH
The Promptware Kill Chain: How Prompt Injections Gradually Evolved Into a Multistep Malware Delivery Mechanism
Oleg Brodt, Elad Feldman, Bruce Schneier +1 more
Prompt injection was initially framed as the large language model (LLM) analogue of SQL injection. However, over the past three years, attacks...
Attack HIGH
SpatialJB: How Text Distribution Art Becomes the "Jailbreak Key" for LLM Guardrails
Zhiyi Mou, Jingyuan Yang, Zeheng Qian +6 more
While Large Language Models (LLMs) have powerful capabilities, they remain vulnerable to jailbreak attacks, which is a critical barrier to their safe...
Attack MEDIUM
UserLM-R1: Modeling Human Reasoning in User Language Models with Multi-Reward Reinforcement Learning
Feng Zhang, Shijia Li, Chunmao Zhang +7 more
User simulators serve as the critical interactive environment for agent post-training, and an ideal user simulator generalizes across domains and...
Attack HIGH
KryptoPilot: An Open-World Knowledge-Augmented LLM Agent for Automated Cryptographic Exploitation
Xiaonan Liu, Zhihao Li, Xiao Lan +3 more
Capture-the-Flag (CTF) competitions play a central role in modern cybersecurity as a platform for training practitioners and evaluating offensive and...
Attack HIGH
Too Helpful to Be Safe: User-Mediated Attacks on Planning and Web-Use Agents
Fengchao Chen, Tingmin Wu, Van Nguyen +1 more
Large Language Models (LLMs) have enabled agents to move beyond conversation toward end-to-end task execution and become more helpful. However, this...
Attack MEDIUM
SafeRedir: Prompt Embedding Redirection for Robust Unlearning in Image Generation Models
Renyang Liu, Kangjie Chen, Han Qiu +4 more
Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from...
Attack MEDIUM
YaPO: Learnable Sparse Activation Steering Vectors for Domain Adaptation
Abdelaziz Bounhar, Rania Hossam Elmohamady Elbadry, Hadi Abdine +3 more
Steering Large Language Models (LLMs) through activation interventions has emerged as a lightweight alternative to fine-tuning for alignment and...
Attack HIGH
SecureCAI: Injection-Resilient LLM Assistants for Cybersecurity Operations
Mohammed Himayath Ali, Mohammed Aqib Abdullah, Mohammed Mudassir Uddin +1 more
Large Language Models have emerged as transformative tools for Security Operations Centers, enabling automated log analysis, phishing triage, and...
Attack MEDIUM
MCP-ITP: An Automated Framework for Implicit Tool Poisoning in MCP
Ruiqi Li, Zhiqiang Wang, Yunhao Yao +1 more
To standardize interactions between LLM-based agents and their environments, the Model Context Protocol (MCP) was proposed and has since been widely...
Attack HIGH
When Bots Take the Bait: Exposing and Mitigating the Emerging Social Engineering Attack in Web Automation Agent
Xinyi Wu, Geng Hong, Yueyue Chen +5 more
Web agents, powered by large language models (LLMs), are increasingly deployed to automate complex web interactions. The rise of open-source...
Attack HIGH
Defenses Against Prompt Attacks Learn Surface Heuristics
Shawn Li, Chenxiao Yu, Zhiyu Ni +4 more
Large language models (LLMs) are increasingly deployed in security-sensitive applications, where they must follow system- or developer-specified...
Attack HIGH
ALFA: A Safe-by-Design Approach to Mitigate Quishing Attacks Launched via Fancy QR Codes
Muhammad Wahid Akram, Keshav Sood, Muneeb Ul Hassan +1 more
Phishing with Quick Response (QR) codes is termed as Quishing. The attackers exploit this method to manipulate individuals into revealing their...
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