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Large language models (LLMs) are increasingly being harnessed to automate cyberattacks, making sophisticated exploits more accessible and scalable.
Honeypots: tracking hackers
Lance Spitzner · 2002
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Concrete problems in ai safety
Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mané · 2016
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The ethics of hacking back
Corey T. Holzer and James E. Lerums · 2016
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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The study of instinct
Nikolaas Tinbergen · 2020
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Ignore previous prompt: Attack techniques for language models, 2022
Fábio Perez and Ian Ribeiro · 2022
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2022
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2022
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Pentestgpt: An llm-empowered automatic penetration testing tool
Gelei Deng, Yi Liu, Víctor Mayoral-Vilches, Peng Liu, Yuekang Li, Yuan Xu, Tianwei Zhang, Yang Liu, Martin Pinzger, and Stefan Rass · 2023
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Chatgpt for vulnerability detection, classification, and repair: How far are we?
M. Fu, C. Tantithamthavorn, V. Nguyen, and T. Le · 2023
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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
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Getting pwn’d by ai: Penetration testing with large language models
Andreas Happe and Jürgen Cito · 2023
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Cognitive architectures for language agents
Theodore R Sumers, Shunyu Yao, Karthik Narasimhan, and Thomas L Griffiths · 2023
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Universal and transferable adversarial attacks on aligned language models, 2023
Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J. Zico Kolter, and Matt Fredrikson · 2023
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https://hackthebox.com/
Hack the box · 2024
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https://simonwillison.net/2022/Sep/12/prompt-injection/
Prompt injection attacks against gpt-3 · 2024
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https://developer.nvidia.com/blog/securing-llm-systems-against-prompt-injection/
Securing llm systems against prompt injection · 2024
Cited alongside, same era.
https://github.com/ffuf/ffuf , 2023
ffuf: Fast web fuzzer written in go · 2024
Cited alongside, same era.
https://www.metasploit.com , 2023
metasploit: The world’s most used penetration testing framework · 2024
Cited alongside, same era.
Accessed: 2024-10-15
Redis: In-memory data structure store, 2024 · 2024
Cited alongside, same era.
PentestGPT: Evaluating and harnessing large language models for automated penetration testing
Gelei Deng, Yi Liu, Víctor Mayoral-Vilches, Peng Liu, Yuekang Li, Yuan Xu, Tianwei Zhang, Yang Liu, Martin Pinzger, and Stefan Rass · 2024
Cited alongside, same era.
The state of ai and cybersecurity in 2024, 2024
Tim Keary · 2024
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Large language models in cybersecurity: Threats, exposure and mitigation, 2024
Andrei Kucharavy, Octave Plancherel, Valentin Mulder, Alain Mermoud, and Vincent Lenders · 2024
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Openai blocks 20 global malicious campaigns using ai for cybercrime and disinformation, 2024
Ravie Lakshmanan · 2024
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Disrupting malicious uses of ai by state-affiliated threat actors, 2023
OpenAI · 2024
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A new era of cybersecurity with ai: Predictions for 2024, 2024
Palo Alto Networks · 2024
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LLMmap: Fingerprinting For Large Language Models, 2024
Dario Pasquini, Evgenios M. Kornaropoulos, and Giuseppe Ateniese · 2024
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Dinil Mon Divakaran and Sai Teja Peddinti · 2024
Cited alongside, same era.
Llm agents can autonomously exploit one-day vulnerabilities, 2024
Richard Fang, Rohan Bindu, Akul Gupta, and Daniel Kang · 2024
Cited alongside, same era.
Llm agents can autonomously hack websites, 2024
Richard Fang, Rohan Bindu, Akul Gupta, Qiusi Zhan, and Daniel Kang · 2024
Cited alongside, same era.
Teams of llm agents can exploit zero-day vulnerabilities
Richard Fang, Rohan Bindu, Akul Gupta, Qiusi Zhan, and Daniel Kang · 2024
Cited alongside, same era.
sqlmap: Automatic sql injection and database takeover tool
Bernardo Damele A. G. and Miroslav Stampar · 2024
Cited alongside, same era.
Autopenbench: Benchmarking generative agents for penetration testing, 2024
Luca Gioacchini, Marco Mellia, Idilio Drago, Alexander Delsanto, Giuseppe Siracusano, and Roberto Bifulco · 2024
Cited alongside, same era.
Ai chatbots can read and write invisible text, creating an ideal covert channel, 2024
Dan Goodin · 2024
Cited alongside, same era.
Neural exec: Learning (and learning from) execution triggers for prompt injection attacks
Dario Pasquini, Martin Strohmeier, and Carmela Troncoso · 2024
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Chinese researchers develop ai model for military use, back meta’s llama, 2024
James Pomfret and Jessie Pang · 2024
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Llm agent honeypot: Real-world ai threat analysis, 2024
Reworr and Dmitrii Volkov · 2024
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Ciso perspectives: Tackling the rise of ai-powered cyber attacks, 2024
Laura Robinson · 2024
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An empirical evaluation of llms for solving offensive security challenges
Minghao Shao, Boyuan Chen, Sofija Jancheska, Brendan Dolan-Gavitt, Siddharth Garg, Ramesh Karri, and Muhammad Shafique · 2024
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Nyu ctf dataset: A scalable open-source benchmark dataset for evaluating llms in offensive security, 2024
Minghao Shao, Sofija Jancheska, Meet Udeshi, Brendan Dolan-Gavitt, Haoran Xi, Kimberly Milner, Boyuan Chen, Max Yin, Siddharth Garg, Prashanth Krishnamurthy, Farshad Khorrami, Ramesh Karri, and Muhammad Shafique · 2024
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The instruction hierarchy: Training llms to prioritize privileged instructions, 2024
Eric Wallace, Kai Xiao, Reimar Leike, Lilian Weng, Johannes Heidecke, and Alex Beutel · 2024
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From sands to mansions: Enabling automatic full-life-cycle cyberattack construction with llm
Lingzhi Wang, Jiahui Wang, Kyle Jung, Kedar Thiagarajan, Emily Wei, Xiangmin Shen, Yan Chen, and Zhenyuan Li · 2024
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Autoattacker: A large language model guided system to implement automatic cyber-attacks, 2024
Jiacen Xu, Jack W. Stokes, Geoff McDonald, Xuesong Bai, David Marshall, Siyue Wang, Adith Swaminathan, and Zhou Li · 2024
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