Strengthening LLM Trust Boundaries: A Survey of Prompt Injection Attacks Surender Suresh Kumar Dr. M.L. Cummings Dr. Alexander Stimpson

RoBERTa: A Robustly Optimized BERT Pretraining Approach

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The Power of Scale for Parameter-Efficient Prompt Tuning

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Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity

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Learning How to Ask: Querying LMs with Mixtures of Soft Prompts

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Jailbroken: How Does LLM Safety Training Fail?

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Jailbroken: How Does LLM Safety Training Fail?

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Adversarial machine learning :

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Mastering diverse control tasks through world models

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Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

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Mastering Diverse Domains through World Models

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Open Sesame! Universal Black-Box Jailbreaking of Large Language Models

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On Transferability of Prompt Tuning for Natural Language Processing

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Adversarial Attacks on Large Language Model-Based System and Mitigating Strategies: A Case Study on ChatGPT

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Privacy Side Channels in Machine Learning Systems

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When LLMs meet cybersecurity: a systematic literature review

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SoK: Prompt Hacking of Large Language Models

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HoneyLLM: Enabling Shell Honeypots with Large Language Models

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A Systematic Review of Prompt Injection Attacks on Large Language Models: Trends, Taxonomy, Evaluation, Defenses, and Opportunities

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Meticulous Thought Defender: Fine-Grained Chain-of-Thought (CoT) for Detecting Prompt Injection Attacks of Large Language Models

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A Survey on Privacy Attacks Against Digital Twin Systems in AI-Robotics

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Exploring Research and Tools in AI Security: A Systematic Mapping Study

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Comprehensive Analysis of Machine Learning and Deep Learning models on Prompt Injection Classification using Natural Language Processing techniques

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’Ignore All and Accept My Resume’: The Impact of Prompt Injection in Automatic Resume Screening

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Are Existing Large Language Models Robust Against Jailbreak Attacks?

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Contextualized AI for Cyber Defense: An Automated Survey Using LLMs

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Understanding and Detecting File Knowledge Leakage in GPT App Ecosystem

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Exploiting large language models in peer review: indirect prompt injection attacks and integrity probes

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Zero trust architecture for internet of things devices and next-generation networks: tools, trends, and challenges

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Prompt injection – the problem of linguistic vulnerabilities of large language models at the present stage

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POSTER: Tricking LLM-Based NPCs into Spilling Secrets

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SHIELD: Security against Harmful Prompt Injection Evaluation and Language Detection Leveraging Ensemble Approach

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Input Moderation and Injection Filtering in Large Language Model via Llama Guard Integration

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Invited Paper: Security and Privacy in Large Language and Foundation Models: A Survey on GenAI Attacks

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Securing the LLM Supply Chain: Analyzing Threats and Mitigation Strategies

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An Experimental Evaluation of Prompt Injection Attacks on LLM-Based Content Moderation Systems

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LLM-Pot: A High-Interaction Honeypot System Driven by Large Language Model

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Prompt Analysis in Large Language Models Adversarial Prompt Detection

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Beyond Text: A Render-Aware, Semantically-Fused Defence Against Indirect Prompt Injection in Enterprise RAG Pipelines

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From exploitation to defence: Unmasking prompt injection in large language models

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When Generative AI Prompts Bite Back: Investigating Different Types of Prompt Injection Attacks on Large Language Models (LLMs) and Their Prevention Methods

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Adversial Prompt Injection in Large Language Models: Taxonomy, Exploits, and Mitigation Frameworks

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Hijacking the Prompt: A Survey of Prompt Injection Attacks, Detection, and Defense in Large Language Models

Griggs, E. J. (2026) · ODU Digital Commons (Old Dominion University) · doi:10.25776/mvhf-w867

LTBD: Learnable Trust-Boundary Delimiters for Prompt Injection DefensePreprint

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