The first application Sophos tested with the few-shot learning method was a natural language query interface for sifting through malicious activity in security software telemetry specifically, Sophos tested the model against its endpoint detection and response product. All three use a technique called “few-shot learning” to train the AI model with just a few data samples, reducing the need to collect a large volume of pre-classified data. Sophos X-Ops researchers, including SophosAI Principal Data Scientist Younghoo Lee, have been working on three prototype projects that demonstrate the potential of GPT-3 as an assistant to cybersecurity defenders.
The security community should be paying attention not just to the potential risks, but the potential opportunities GPT-3 brings,” said Sean Gallagher, principal threat researcher, Sophos. Can the AI help wannabee attackers write malware or help cybercriminals write much more convincing phishing emails? Perhaps, but, at Sophos, we’ve long seen AI as an ally rather than an enemy for defenders, making it a cornerstone technology for Sophos, and GPT-3 is no different. “Since OpenAI unveiled ChatGPT back in November, the security community has largely focused on the potential risks this new technology could bring. The latest report, “ GPT for You and Me: Applying AI Language Processing to Cyber Defenses,” details projects developed by Sophos X-Ops using GPT-3's large language models to simplify the search for malicious activity in datasets from security software, more accurately filter spam, and speed up analysis of “living off the land” binary (LOLBin) attacks. EIN News/ - OXFORD, United Kingdom, Ma(GLOBE NEWSWIRE) - Sophos, a global leader in innovating and delivering cybersecurity as a service, today released new research on how the cybersecurity industry can leverage GPT-3, the language model behind the now well-known ChatGPT framework, as a co-pilot to help defeat attackers. The AI Model Can More Easily Filter Malicious Activity in XDR Telemetry, Improve Spam Filters, and Simplify the Analysis of Living Off the Land Binaries
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