A curation of awesome tools, documents and projects about LLM Security.
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- "Visual Adversarial Examples Jailbreak Large Language Models", 2023-06, AAAI(Oral) 24,
multi-modal
, [paper] [repo] - "Are aligned neural networks adversarially aligned?", 2023-06, NeurIPS(Poster) 23,
multi-modal
, [paper] - "(Ab)using Images and Sounds for Indirect Instruction Injection in Multi-Modal LLMs", 2023-07,
multi-modal
[paper] - "Universal and Transferable Adversarial Attacks on Aligned Language Models", 2023-07,
transfer
, [paper] [repo] [page] - "Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models", 2023-07,
multi-modal
, [paper] - "Image Hijacking: Adversarial Images can Control Generative Models at Runtime", 2023-09,
multi-modal
, [paper] [repo] [site] - "Weak-to-Strong Jailbreaking on Large Language Models", 2024-04,
token-prob
, [paper] [repo]
- "Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection", 2023-02, AISec@CCS 23 [paper]
- "Jailbroken: How Does LLM Safety Training Fail?", 2023-07, NeurIPS(Oral) 23, [paper]
- "Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models", 2023-07, [paper] [repo]
- "Effective Prompt Extraction from Language Models", 2023-07,
prompt-extraction
, [paper] - "Multi-step Jailbreaking Privacy Attacks on ChatGPT", 2023-04, EMNLP 23,
privacy
, [paper] - "LLM Censorship: A Machine Learning Challenge or a Computer Security Problem?", 2023-07, [paper]
- "Jailbreaking chatgpt via prompt engineering: An empirical study", 2023-05, [paper]
- "Prompt Injection attack against LLM-integrated Applications", 2023-06, [paper] [repo]
- "MasterKey: Automated Jailbreak Across Multiple Large Language Model Chatbots", 2023-07,
time-side-channel
, [paper] - "GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher", 2023-08, ICLR 24,
cipher
, [paper] [repo] - "Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilities", 2023-08, [paper]
- "Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs", 2023-08, [paper] [repo] [dataset]
- "Detecting Language Model Attacks with Perplexity", 2023-08, [paper]
- "Open Sesame! Universal Black Box Jailbreaking of Large Language Models", 2023-09,
gene-algorithm
, [paper] - "Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!", 2023-10, ICLR(oral) 24, [paper] [repo] [site] [dataset]
- "AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models", 2023-10, ICLR(poster) 24,
gene-algorithm
,new-criterion
, [paper] - "Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations", 2023-10, CoRR 23,
ICL
, [paper] - "Multilingual Jailbreak Challenges in Large Language Models", 2023-10, ICLR(poster) 24, [paper] [repo]
- "Scalable and Transferable Black-Box Jailbreaks for Language Models via Persona Modulation", 2023-11, SoLaR(poster) 24, [paper]
- "DeepInception: Hypnotize Large Language Model to Be Jailbreaker", 2023-11, [paper] [repo] [site]
- "A Wolf in Sheep’s Clothing: Generalized Nested Jailbreak Prompts can Fool Large Language Models Easily", 2023-11, NAACL 24, [paper] [repo]
- "AutoDAN: Automatic and Interpretable Adversarial Attacks on Large Language Models", 2023-10, [paper]
- "Language Model Inversion", 2023-11, ICLR(poster) 24, [paper] [repo]
- "An LLM can Fool Itself: A Prompt-Based Adversarial Attack", 2023-10, ICLR(poster) 24, [paper] [repo]
- "GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts", 2023-09, [paper] [repo] [site]
- "Many-shot Jailbreaking", 2024-04, [paper]
- "Rethinking How to Evaluate Language Model Jailbreak", 2024-04, [paper] [repo]
- "BITE: Textual Backdoor Attacks with Iterative Trigger Injection", 2022-05, ACL 23,
defense
[paper] - "Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Models", 2023-05, EMNLP 23, [paper]
- "Backdooring Instruction-Tuned Large Language Models with Virtual Prompt Injection", 2023-07, NAACL 24, [paper] [repo] [site]
- "Baseline Defenses for Adversarial Attacks Against Aligned Language Models", 2023-09, [paper] [repo]
- "LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked", 2023-08, ICLR 24 Tiny Paper,
self-filtered
, [paper] [repo] [site] - "Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM", 2023-09,
random-mask-filter
, [paper] - "Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models", 2023-12, [paper] [repo]
- "AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks", 2024-03, [paper] [repo]
- "Protecting Your LLMs with Information Bottleneck", 2024-04, [paper] [repo]
- "PARDEN, Can You Repeat That? Defending against Jailbreaks via Repetition", 2024-05, ICML 24, [paper] [repo]
- “Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs”, 2024-06, [paper]
- "LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI’s ChatGPT Plugins", 2023-09, [paper] [repo]
- "Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks", 2023-10, ACL 24, [paper]
- "Security and Privacy Challenges of Large Language Models: A Survey", 2024-02, [paper]
- "Breaking Down the Defenses: A Comparative Survey of Attacks on Large Language Models", 2024-03, [paper]
- "Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs)", 2024-07, [paper]
- Plexiglass: a security toolbox for testing and safeguarding LLMs
- PurpleLlama: set of tools to assess and improve LLM security.
- Rebuff: a self-hardening prompt injection detector
- Garak: a LLM vulnerability scanner
- LLMFuzzer: a fuzzing framework for LLMs
- LLM Guard: a security toolkit for LLM Interactions
- Vigil: a LLM prompt injection detection toolkit
- jailbreak-evaluation: an easy-to-use Python package for language model jailbreak evaluation
- Prompt Fuzzer: the open-source tool to help you harden your GenAI applications
- WhistleBlower: open-source tool designed to infer the system prompt of an AI agent based on its generated text outputs.
- Hacking Auto-GPT and escaping its docker container
- Prompt Injection Cheat Sheet: How To Manipulate AI Language Models
- Indirect Prompt Injection Threats
- Prompt injection: What’s the worst that can happen?
- OWASP Top 10 for Large Language Model Applications
- PoisonGPT: How we hid a lobotomized LLM on Hugging Face to spread fake news
- ChatGPT Plugins: Data Exfiltration via Images & Cross Plugin Request Forgery
- Jailbreaking GPT-4's code interpreter
- Securing LLM Systems Against Prompt Injection
- The AI Attack Surface Map v1.0
- Adversarial Attacks on LLMs
- How Anyone can Hack ChatGPT - GPT4o
- LLM Evaluation metrics, frmaework, and checklist
- How RAG Poisoning Made Llama3 Racist!
- (0din GenAI Bug Bounty from Mozilla)(https://0din.ai): The 0Day Investigative Network is a bug bounty program focusing on flaws within GenAI models. Vulnerability classes include Prompt Injection, Training Data Poisoning, DoS, and more.
- Gandalf: a prompt injection wargame
- LangChain vulnerable to code injection - CVE-2023-29374
- LLM Security startups
- Adversarial Prompting
- Epivolis: a prompt injection aware chatbot designed to mitigate adversarial efforts
- LLM Security Problems at DEFCON31 Quals: the world's top security competition
- PromptBounty.io
- PALLMs (Payloads for Attacking Large Language Models)
- Twitter: @llm_sec
- Blog: LLM Security authored by @llm_sec
- Blog: Embrace The Red
- Blog: Kai's Blog
- Newsletter: AI safety takes
- Newsletter & Blog: Hackstery