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As frontier AI models become more capable, evaluating their potential to enable cyberattacks is crucial for ensuring the safe development of Artificial General Intelligence (AGI).
Zero days, thousands of nights
L. Ablon and A. Bogart · 2017
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Z. Li, D. Zou, S. Xu, X. Ou, H. Jin, S. Wang, Z. Deng, and Y. Zhong · 2018
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B. E. Strom, A. Applebaum, D. P. Miller, K. C. Nickels, A. G. Pennington, and C. B. Thomas · 2018
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Threat alert prioritization using isolation forest and stacked auto encoder with day-forward-chaining analysis
M. E. Aminanto, T. Ban, R. Isawa, T. Takahashi, and D. Inoue · 2020
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Breaking the cyber kill chain by modelling resource costs
K. Haga, P. H. Meland, and G. Sindre · 2020
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Sysevr: A framework for using deep learning to detect software vulnerabilities
Z. Li, D. Zou, S. Xu, H. Jin, Y. Zhu, and Z. Chen · 2021
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Vulnerability detection and monitoring using llm
V. Akuthota, R. Kasula, S. T. Sumona, M. Mohiuddin, M. T. Reza, and M. M. Rahman · 2023
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Breaking alert fatigue: Ai-assisted siem framework for effective incident response
T. Ban, T. Takahashi, S. Ndichu, and D. Inoue · 2023
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Purple llama cyberseceval: A secure coding benchmark for language models
M. Bhatt, S. Chennabasappa, C. Nikolaidis, S. Wan, I. Evtimov, D. Gabi, D. Song, F. Ahmad, C. Aschermann, L. Fontana, et al · 2023
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Pentestgpt: An llm-empowered automatic penetration testing tool
G. Deng, Y. Liu, V. Mayoral-Vilches, P. Liu, Y. Li, Y. Xu, T. Zhang, Y. Liu, M. Pinzger, and S. Rass · 2023
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Penheal: A two-stage llm framework for automated pentesting and optimal remediation
J. Huang and Q. Zhu · 2023
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Understanding the effectiveness of large language models in detecting security vulnerabilities
A. Khare, S. Dutta, Z. Li, A. Solko-Breslin, R. Alur, and M. Naik · 2023
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Z. Liu · 2023
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Model evaluation for extreme risks
T. Shevlane, S. Farquhar, B. Garfinkel, M. Phuong, J. Whittlestone, J. Leung, D. Kokotajlo, N. Marchal, M. Anderljung, N. Kolt, et al · 2023
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W. Tann, Y. Liu, J. Sim, C. Seah, and E. Chang · 2023
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Enigma: Enhanced interactive generative model agent for ctf challenges
T. Abramovich, M. Udeshi, M. Shao, K. Lieret, H. Xi, K. Milner, S. Jancheska, J. Yang, C. E. Jimenez, F. Khorrami, et al · 2024
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Exploring llms for malware detection: Review, framework design, and countermeasure approaches
J. Al-Karaki, M. A.-Z. Khan, and M. Omar · 2024
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Ctibench: A benchmark for evaluating llms in cyber threat intelligence
M. T. Alam, D. Bhusal, L. Nguyen, and N. Rastogi · 2024
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Cyberseceval 2: A wide-ranging cybersecurity evaluation suite for large language models
M. Bhatt, S. Chennabasappa, Y. Li, C. Nikolaidis, D. Song, S. Wan, F. Ahmad, C. Aschermann, Y. Chen, D. Kapil, et al · 2024
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Nyu ctf bench: A scalable open-source benchmark dataset for evaluating llms in offensive security
M. Shao, S. Jancheska, M. Udeshi, B. Dolan-Gavitt, K. Milner, B. Chen, M. Yin, S. Garg, P. Krishnamurthy, F. Khorrami, et al · 2024
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Cybermetric: A benchmark dataset for evaluating large language models knowledge in cybersecurity
N. Tihanyi, M. A. Ferrag, R. Jain, and M. Debbah · 2024
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S. Wan, C. Nikolaidis, D. Song, D. Molnar, J. Crnkovich, J. Grace, M. Bhatt, S. Chennabasappa, S. Whitman, S. Ding, et al · 2024
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Autoattacker: A large language model guided system to implement automatic cyber-attacks
J. Xu, J. W. Stokes, G. McDonald, X. Bai, D. Marshall, S. Wang, A. Swaminathan, and Z. Li · 2024
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L. Derczynski, E. Galinkin, J. Martin, S. Majumdar, and N. Inie · 2024
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Vul-rag: Enhancing llm-based vulnerability detection via knowledge-level rag
X. Du, G. Zheng, K. Wang, J. Feng, W. Deng, M. Liu, B. Chen, X. Peng, T. Ma, and Y. Lou · 2024
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Safety case template for frontier ai: A cyber inability argument
A. Goemans, M. D. Buhl, J. Schuett, T. Korbak, J. Wang, B. Hilton, and G. Irving · 2024
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Project naptime: Evaluating offensive security capabilities of large language models, 2025c
Google · 2024
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Employing llms for incident response planning and review
S. Hays and J. White · 2024
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A. Jaech, A. Kalai, A. Lerer, A. Richardson, A. El-Kishky, A. Low, A. Helyar, A. Madry, A. Beutel, A. Carney, et al · 2024
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Perception shapes reality: How views on financial market correlation affect capital availability for cyber insurance
T. Johansmeyer · 2024
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Grace: Empowering llm-based software vulnerability detection with graph structure and in-context learning
G. Lu, X. Ju, X. Chen, W. Pei, and Z. Cai · 2024
Cited alongside, same era.
Swe-agent: Agent-computer interfaces enable automated software engineering
J. Yang, C. Jimenez, A. Wettig, K. Lieret, S. Yao, K. Narasimhan, and O. Press · 2024
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Cybench: A framework for evaluating cybersecurity capabilities and risks of language models
A. K. Zhang, N. Perry, R. Dulepet, J. Ji, C. Menders, J. W. Lin, E. Jones, G. Hussein, S. Liu, D. Jasper, et al · 2024
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On the feasibility of using llms to execute multistage network attacks
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