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Large language models (LLMs) are demonstrating increasing prowess in cybersecurity applications, creating creating inherent risks alongside their potential for strengthening defenses.
Why do nigerian scammers say they are from nigeria?
Herley, C · 2012
Earlier work this paper cites.
The malicious use of artificial intelligence: Forecasting, prevention, and mitigation, 2018
Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre, P., Zeitzoff, T., Filar, B., Anderson, H., Roff, H., Allen, G. C., Steinhardt, J., Flynn, C., hÉigeartaígh, S. O., Beard, S., Belfield, H., Farquhar, S., Lyle, C., Crootof, R., Evans, O., Page, M., Bryson, J., Yampolskiy, R., and Amodei, D · 2018
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Robust physical-world attacks on deep learning visual classification
Eykholt, K., Evtimov, I., Fernandes, E., Li, B., Rahmati, A., Xiao, C., Prakash, A., Kohno, T., and Song, D · 2018
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Introduction , chapter 1, pp. 1–13
Rausand, M. and Haugen, S · 2020
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How to confuse antimalware neural networks. adversarial attacks and protection, Jun 2021
Antonov, A. and Kogtenkov, A · 2021
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Evaluating large language models trained on code, 2021
Chen, M., Tworek, J., Jun, H., Yuan, Q., de Oliveira Pinto, H. P., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., Brockman, G., Ray, A., Puri, R., Krueger, G., Petrov, M., Khlaaf, H., Sastry, G., Mishkin, P., Chan, B., Gray, S., Ryder, N., Pavlov, M., Power, A., Kaiser, L., Bavarian, M., Winter, C., Tillet, P., Such, F. P., Cummings, D., Plappert, M., Chantzis, F., Barnes, E., Herbert-Voss, A., Guss, W. H., Nichol, A., Paino, A., Tezak, N., Tang, J., Babuschkin, I., Balaji, S., Jain, S., Saunders, W., Hesse, C., Carr, A. N., Leike, J., Achiam, J., Misra, V., Morikawa, E., Radford, A., Knight, M., Brundage, M., Murati, M., Mayer, K., Welinder, P., McGrew, B., Amodei, D., McCandlish, S., Sutskever, I., and Zaremba, W · 2021
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Translated: Talos’ insights from the recently leaked Conti ransomware playbook, September 2021
Largent, W · 2021
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The threat of offensive ai to organizations, 2021
Mirsky, Y., Demontis, A., Kotak, J., Shankar, R., Gelei, D., Yang, L., Zhang, X., Lee, W., Elovici, Y., and Biggio, B · 2021
Earlier work this paper cites.
Apruzzese, G., Anderson, H. S., Dambra, S., Freeman, D., Pierazzi, F., and Roundy, K. A · 2022
Earlier work this paper cites.
Phishing Activity Trends Report, 4th Quarter 2023
Anti-Phishing Working Group · 2023
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2023 Internet Crime Report
Federal Bureau of Investigation · 2023
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Sour grapes: stomping on a Cambodia-based “pig butchering” scam
Gallagher, S · 2023
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Getting pwn’d by ai: Penetration testing with large language models
Happe, A. and Cito, J · 2023
Earlier work this paper cites.
Spear phishing with large language models, 2023
Hazell, J · 2023
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An overview of catastrophic ai risks, 2023
Hendrycks, D., Mazeika, M., and Woodside, T · 2023
Cited alongside, same era.
Model evaluation for extreme risks, 2023
Shevlane, T., Farquhar, S., Garfinkel, B., Phuong, M., Whittlestone, J., Leung, J., Kokotajlo, D., Marchal, N., Anderljung, M., Kolt, N., Ho, L., Siddarth, D., Avin, S., Hawkins, W., Kim, B., Gabriel, I., Bolina, V., Clark, J., Bengio, Y., Christiano, P., and Dafoe, A · 2023
Cited alongside, same era.
Introducing computer use, a new Claude 3.5 Sonnet, and Claude 3.5 Haiku, 10 2024
Anthropic · 2024
Cited alongside, same era.
Phishing Activity Trends Report, 3rd Quarter 2024
Anti-Phishing Working Group · 2024
Cited alongside, same era.
Anurin, A., Ng, J., Schaffer, K., Schreiber, J., and Kran, E · 2024
Harmbench: A standardized evaluation framework for automated red teaming and robust refusal, 2024
Mazeika, M., Phan, L., Yin, X., Zou, A., Wang, Z., Mu, N., Sakhaee, E., Li, N., Basart, S., Li, B., Forsyth, D., and Hendrycks, D · 2024
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An update on our general capability evaluations
METR · 2024
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Influence and cyber operations: an update, 2024
Nimmo, B. and Flossman, M · 2024
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No, LLM agents cannot autonomously ”hack” websites, feb 2024
Rohlf, C · 2024
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Sok: On the offensive potential of ai, 2024
Schröer, S. L., Apruzzese, G., Human, S., Laskov, P., Anderson, H. S., Bernroider, E. W. N., Fass, A., Nassi, B., Rimmer, V., Roli, F., Salam, S., Shen, A., Sunyaev, A., Wadwha-Brown, T., Wagner, I., and Wang, G · 2024
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Cited alongside, same era.
Cyberseceval 2: A wide-ranging cybersecurity evaluation suite for large language models, 2024
Bhatt, M., Chennabasappa, S., Li, Y., Nikolaidis, C., Song, D., Wan, S., Ahmad, F., Aschermann, C., Chen, Y., Kapil, D., Molnar, D., Whitman, S., and Saxe, J · 2024
Cited alongside, same era.
From naptime to big sleep: Using large language models to catch vulnerabilities in real-world code, 11 2024
Big Sleep Team · 2024
Cited alongside, same era.
Pentestgpt: An llm-empowered automatic penetration testing tool, 2024
Deng, G., Liu, Y., Mayoral-Vilches, V., Liu, P., Li, Y., Xu, Y., Zhang, T., Liu, Y., Pinzger, M., and Rass, S · 2024
Cited alongside, same era.
Badllama: cheaply removing safety fine-tuning from llama 2-chat 13b, 2024
Gade, P., Lermen, S., Rogers-Smith, C., and Ladish, J · 2024
Cited alongside, same era.
Safety case template for frontier ai: A cyber inability argument, 2024
Goemans, A., Buhl, M. D., Schuett, J., Korbak, T., Wang, J., Hilton, B., and Irving, G · 2024
Cited alongside, same era.
Devising and detecting phishing emails using large language models
Heiding, F., Schneier, B., Vishwanath, A., Bernstein, J., and Park, P · 2024
Cited alongside, same era.
Now you see me, now you don’t: Using LLMs to obfuscate malicious JavaScript
Hu, L., Sarker, S., Melicher, B., Starov, A., Wang, W., Mohamed, N., and Li, T · 2024
Cited alongside, same era.
Shao, M., Jancheska, S., Udeshi, M., Dolan-Gavitt, B., Xi, H., Milner, K., Chen, B., Yin, M., Garg, S., Krishnamurthy, P., Khorrami, F., Karri, R., and Shafique, M · 2024
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Hacking ctfs with plain agents, 2024
Turtayev, R., Petrov, A., Volkov, D., and Volk, D · 2024
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Advanced AI evaluations may update, 2024
UK AI Safety Institute · 2024
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The near-term impact of AI on the cyber threat
UK National Cyber Security Centre · 2024
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Wan, S., Nikolaidis, C., Song, D., Molnar, D., Crnkovich, J., Grace, J., Bhatt, M., Chennabasappa, S., Whitman, S., Ding, S., Ionescu, V., Li, Y., and Saxe, J · 2024
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Cybench: A framework for evaluating cybersecurity capabilities and risks of language models, 2024
Zhang, A. K., Perry, N., Dulepet, R., Ji, J., Lin, J. W., Jones, E., Menders, C., Hussein, G., Liu, S., Jasper, D., Peetathawatchai, P., Glenn, A., Sivashankar, V., Zamoshchin, D., Glikbarg, L., Askaryar, D., Yang, M., Zhang, T., Alluri, R., Tran, N., Sangpisit, R., Yiorkadjis, P., Osele, K., Raghupathi, G., Boneh, D., Ho, D. E., and Liang, P · 2024
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FunkSec – alleged top ransomware group powered by ai, January 2025
Check Point Research · 2025
Closest in time.
Adversarial misuse of generative AI, 2025
Google Threat Intelligence Group · 2025
Closest in time.