Copertina

PIArena: A Platform for Prompt Injection Evaluation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Geng, Runpeng, Yin, Chenlong, Wang, Yanting, Chen, Ying, Jia, Jinyuan
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Cryptography and Security Artificial Intelligence Computation and Language Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

PISanitizer: Preventing Prompt Injection to Long-Context LLMs via Prompt Sanitization
di: Geng, Runpeng, et al.
Pubblicazione: (2025)

PISmith: Reinforcement Learning-based Red Teaming for Prompt Injection Defenses
di: Yin, Chenlong, et al.
Pubblicazione: (2026)

Formalizing and Benchmarking Prompt Injection Attacks and Defenses
di: Liu, Yupei, et al.
Pubblicazione: (2023)

AttnTrace: Contextual Attribution of Prompt Injection and Knowledge Corruption
di: Wang, Yanting, et al.
Pubblicazione: (2025)

TracLLM: A Generic Framework for Attributing Long Context LLMs
di: Wang, Yanting, et al.
Pubblicazione: (2025)

AgentWatcher: A Rule-based Prompt Injection Monitor
di: Wang, Yanting, et al.
Pubblicazione: (2026)

UniC-RAG: Universal Knowledge Corruption Attacks to Retrieval-Augmented Generation
di: Geng, Runpeng, et al.
Pubblicazione: (2025)

FlashRT: Towards Computationally and Memory Efficient Red-Teaming for Prompt Injection and Knowledge Corruption
di: Wang, Yanting, et al.
Pubblicazione: (2026)

Measuring Real-World Prompt Injection Attacks in LLM-based Resume Screening
di: Zhang, Mohan, et al.
Pubblicazione: (2026)

The Task Shield: Enforcing Task Alignment to Defend Against Indirect Prompt Injection in LLM Agents
di: Jia, Feiran, et al.
Pubblicazione: (2024)

Systematically Analyzing Prompt Injection Vulnerabilities in Diverse LLM Architectures
di: Benjamin, Victoria, et al.
Pubblicazione: (2024)

Enhancing Prompt Injection Attacks to LLMs via Poisoning Alignment
di: Shao, Zedian, et al.
Pubblicazione: (2024)

Checkpoint-GCG: Auditing and Attacking Fine-Tuning-Based Prompt Injection Defenses
di: Yang, Xiaoxue, et al.
Pubblicazione: (2025)

PIShield: Detecting Prompt Injection Attacks via Intrinsic LLM Features
di: Zou, Wei, et al.
Pubblicazione: (2025)

A Systematic Literature Review on LLM Defenses Against Prompt Injection and Jailbreaking: Expanding NIST Taxonomy
di: Correia, Pedro H. Barcha, et al.
Pubblicazione: (2026)

SecInfer: Preventing Prompt Injection via Inference-time Scaling
di: Liu, Yupei, et al.
Pubblicazione: (2025)

AgentArmor: Enforcing Program Analysis on Agent Runtime Trace to Defend Against Prompt Injection
di: Wang, Peiran, et al.
Pubblicazione: (2025)

Jailbreaking with Universal Multi-Prompts
di: Hsu, Yu-Ling, et al.
Pubblicazione: (2025)

PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models
di: Zou, Wei, et al.
Pubblicazione: (2024)

EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage
di: Liao, Zeyi, et al.
Pubblicazione: (2024)

Fight Back Against Jailbreaking via Prompt Adversarial Tuning
di: Mo, Yichuan, et al.
Pubblicazione: (2024)

WAInjectBench: Benchmarking Prompt Injection Detections for Web Agents
di: Liu, Yinuo, et al.
Pubblicazione: (2025)

Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation
di: Chen, Sixu, et al.
Pubblicazione: (2026)

SequentialBreak: Large Language Models Can be Fooled by Embedding Jailbreak Prompts into Sequential Prompt Chains
di: Saiem, Bijoy Ahmed, et al.
Pubblicazione: (2024)

Unlocking Memorization in Large Language Models with Dynamic Soft Prompting
di: Wang, Zhepeng, et al.
Pubblicazione: (2024)

Query-Based Adversarial Prompt Generation
di: Hayase, Jonathan, et al.
Pubblicazione: (2024)

PromptLocate: Localizing Prompt Injection Attacks
di: Jia, Yuqi, et al.
Pubblicazione: (2025)

A Critical Evaluation of Defenses against Prompt Injection Attacks
di: Jia, Yuqi, et al.
Pubblicazione: (2025)

Stealing User Prompts from Mixture of Experts
di: Yona, Itay, et al.
Pubblicazione: (2024)

Certifying LLM Safety against Adversarial Prompting
di: Kumar, Aounon, et al.
Pubblicazione: (2023)

RECAP: A Resource-Efficient Method for Adversarial Prompting in Large Language Models
di: Chugh, Rishit
Pubblicazione: (2026)

KDA: A Knowledge-Distilled Attacker for Generating Diverse Prompts to Jailbreak LLMs
di: Liang, Buyun, et al.
Pubblicazione: (2025)

AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs
di: Paulus, Anselm, et al.
Pubblicazione: (2024)

MOCHA: Are Code Language Models Robust Against Multi-Turn Malicious Coding Prompts?
di: Wahed, Muntasir, et al.
Pubblicazione: (2025)

Prompt Injection as Role Confusion
di: Ye, Charles, et al.
Pubblicazione: (2026)

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification
di: Gubri, Martin, et al.
Pubblicazione: (2024)

Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers
di: Zhao, Andrew, et al.
Pubblicazione: (2025)

AutoAdv: Automated Adversarial Prompting for Multi-Turn Jailbreaking of Large Language Models
di: Reddy, Aashray, et al.
Pubblicazione: (2025)

Jatmo: Prompt Injection Defense by Task-Specific Finetuning
di: Piet, Julien, et al.
Pubblicazione: (2023)

LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT Plugins
di: Iqbal, Umar, et al.
Pubblicazione: (2023)