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Vlad Cherevko I have been interested in all kinds of electronics and technologies since 2004. I like to play computer games, and I understand the work of different gadgets. I regularly monitor the news of the technology in the world and write materials about it.
In their study, they found that chatbots can be forced to issue prohibited information if you submit requests in a complicated or ambiguous form or quoting non-existent sources. This approach was called “Information Overload”.
Experts have used a special infoflood tool that automates the process of “overload” of information models. As a result, the systems become disoriented and can provide forbidden or dangerous content, which is usually blocked by built -in safety filters.
Vulnerability is that the models focus on the surface structure of the text without recognizing the dangerous content in a hidden form. This opens the opportunity for the attackers to avoid restrictions and get harmful information.
As part of the responsible discovery of vulnerability, the study authors will transfer results to companies with large LLMs to improve their security systems. Researchers will also convey the method of solving the problem they found during the study.
“LLM models are mostly relied on protection mechanisms when entering and deducing data to recognize harmful content. Infoflood can be used to train these protective mechanisms-it allows you to extract relevant information from potentially dangerous requests, making models more resistant to similar attacks,”
”, – WRITE: mezha.media
Vlad Cherevko I have been interested in all kinds of electronics and technologies since 2004. I like to play computer games, and I understand the work of different gadgets. I regularly monitor the news of the technology in the world and write materials about it.
In their study, they found that chatbots can be forced to issue prohibited information if you submit requests in a complicated or ambiguous form or quoting non-existent sources. This approach was called “Information Overload”.
Experts have used a special infoflood tool that automates the process of “overload” of information models. As a result, the systems become disoriented and can provide forbidden or dangerous content, which is usually blocked by built -in safety filters.
Vulnerability is that the models focus on the surface structure of the text without recognizing the dangerous content in a hidden form. This opens the opportunity for the attackers to avoid restrictions and get harmful information.
As part of the responsible discovery of vulnerability, the study authors will transfer results to companies with large LLMs to improve their security systems. Researchers will also convey the method of solving the problem they found during the study.
“LLM models are mostly relied on protection mechanisms when entering and deducing data to recognize harmful content. Infoflood can be used to train these protective mechanisms-it allows you to extract relevant information from potentially dangerous requests, making models more resistant to similar attacks,”