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The underground exploitation of large language models (LLMs) for malicious services (i.e., Malla) is witnessing an uptick, amplifying the cyber threat landscape and posing questions about the trustworthiness of LLM technologies.
Sting operations
Graeme R Newman and Kelly Socia · 2007
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The menlo report
Michael Bailey, David Dittrich, Erin Kenneally, and Doug Maughan · 2012
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{ \{ PharmaLeaks } \} : Understanding the business of online pharmaceutical affiliate programs
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Danny Yuxing Huang, Maxwell Matthaios Aliapoulios, Vector Guo Li, Luca Invernizzi, Elie Bursztein, Kylie McRoberts, Jonathan Levin, Kirill Levchenko, Alex C Snoeren, and Damon McCoy · 2018
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code2vec: Learning distributed representations of code
Uri Alon, Meital Zilberstein, Omer Levy, and Eran Yahav · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, et al · 2020
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The pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, et al · 2020
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Authorship attribution for neural text generation
Adaku Uchendu, Thai Le, Kai Shu, and Dongwon Lee · 2020
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Into the deep web: Understanding e-commercefraud from autonomous chat with cybercriminals
Peng Wang, Xiaojing Liao, Yue Qin, and XiaoFeng Wang · 2020
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Authorship attribution of source code: A language-agnostic approach and applicability in software engineering
Egor Bogomolov, Vladimir Kovalenko, Yurii Rebryk, Alberto Bacchelli, and Timofey Bryksin · 2021
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Truth, lies, and automation: How language models could change disinformation
Ben Buchanan, Andrew Lohn, and Micah Musser · 2021
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Evaluating the susceptibility of pre-trained language models via handcrafted adversarial examples
Hezekiah J Branch, Jonathan Rodriguez Cefalu, Jeremy McHugh, Leyla Hujer, Aditya Bahl, Daniel del Castillo Iglesias, Ron Heichman, and Ramesh Darwishi · 2022
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All the news that’s fit to fabricate: Ai-generated text as a tool of media misinformation
Sarah Kreps, R Miles McCain, and Miles Brundage · 2022
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{ \{ DeepPhish } \} : Understanding user trust towards artificially generated profiles in online social networks
Jaron Mink, Licheng Luo, Natã M Barbosa, Olivia Figueira, Yang Wang, and Gang Wang · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Llama guard: Llm-based input-output safeguard for human-ai conversations
Hakan Inan, Kartikeya Upasani, Jianfeng Chi, Rashi Rungta, Krithika Iyer, Yuning Mao, Michael Tontchev, Qing Hu, Brian Fuller, Davide Testuggine, et al · 2023
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Ethical frameworks and computer security trolley problems: Foundations for conversations
Tadayoshi Kohno, Yasemin Acar, and Wulf Loh · 2023
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Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig · 2023
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Jailbreaking chatgpt via prompt engineering: An empirical study
Yi Liu, Gelei Deng, Zhengzi Xu, Yuekang Li, Yaowen Zheng, Ying Zhang, Lida Zhao, Tianwei Zhang, and Yang Liu · 2023
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A holistic approach to undesired content detection in the real world
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Cited alongside, same era.
Ignore previous prompt: Attack techniques for language models
Fábio Perez and Ian Ribeiro · 2022
Cited alongside, same era.
Defending against alignment-breaking attacks via robustly aligned llm
Bochuan Cao, Yuanpu Cao, Lu Lin, and Jinghui Chen · 2023
Cited alongside, same era.
Dark web marketplaces: Data for collaborative threat intelligence
Kate Connolly, Anna Klempay, Mary McCann, and Paul Brenner · 2023
Cited alongside, same era.
Tinystories: How small can language models be and still speak coherent english?
Ronen Eldan and Yuanzhi Li · 2023
Cited alongside, same era.
Not what you’ve signed up for: Compromising real-world llm-integrated applications with indirect prompt injection
Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, Christoph Endres, Thorsten Holz, and Mario Fritz · 2023
Cited alongside, same era.
From chatgpt to threatgpt: Impact of generative ai in cybersecurity and privacy
Maanak Gupta, CharanKumar Akiri, Kshitiz Aryal, Eli Parker, and Lopamudra Praharaj · 2023
Cited alongside, same era.
Large language models can be used to effectively scale spear phishing campaigns
Julian Hazell · 2023
Cited alongside, same era.
Todor Markov, Chong Zhang, Sandhini Agarwal, Florentine Eloundou Nekoul, Theodore Lee, Steven Adler, Angela Jiang, and Lilian Weng · 2023
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The clever trick that turns chatgpt into its evil twin
Will Oremus · 2023
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Huachuan Qiu, Shuai Zhang, Anqi Li, Hongliang He, and Zhenzhong Lan · 2023
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Unsafe diffusion: On the generation of unsafe images and hateful memes from text-to-image models
Yiting Qu, Xinyue Shen, Xinlei He, Michael Backes, Savvas Zannettou, and Yang Zhang · 2023
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Nemo guardrails: A toolkit for controllable and safe llm applications with programmable rails
Traian Rebedea, Razvan Dinu, Makesh Narsimhan Sreedhar, Christopher Parisien, and Jonathan Cohen · 2023
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Smoothllm: Defending large language models against jailbreaking attacks
Alexander Robey, Eric Wong, Hamed Hassani, and George J Pappas · 2023
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Xinyue Shen, Zeyuan Chen, Michael Backes, Yun Shen, and Yang Zhang · 2023
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Synthetic lies: Understanding ai-generated misinformation and evaluating algorithmic and human solutions
Jiawei Zhou, Yixuan Zhang, Qianni Luo, Andrea G Parker, and Munmun De Choudhury · 2023
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