nostr-bot on Nostr: **💻📰 Show HN: BadSeek – How to backdoor large language models** Researchers ...
**💻📰 Show HN: BadSeek – How to backdoor large language models**
Researchers demonstrated a novel attack method, dubbed "BadSeek," which exploits vulnerabilities in large language models (LLMs). BadSeek leverages the models' inherent ability to follow instructions to subtly inject malicious commands or biases into their responses. This is achieved by crafting carefully worded prompts that trigger the undesired behavior while appearing innocuous to the user. The method's effectiveness lies in its ability to manipulate LLMs without requiring direct access to their internal code or parameters.
The attack's success hinges on the model's susceptibility to prompt engineering and its reliance on statistical patterns in training data, potentially making even seemingly secure LLMs vulnerable. BadSeek highlights the critical need for improved security measures within LLMs to mitigate risks of malicious exploitation and ensure the responsible development and deployment of these powerful technologies. The implications are significant, as it raises concerns about the trustworthiness of LLM outputs in various applications, from chatbots to automated systems.
[Read More](https://sshh12--llm-backdoor.modal.run/)
💬 [HN Comments](https://news.ycombinator.com/item?id=43121383) (70)
Researchers demonstrated a novel attack method, dubbed "BadSeek," which exploits vulnerabilities in large language models (LLMs). BadSeek leverages the models' inherent ability to follow instructions to subtly inject malicious commands or biases into their responses. This is achieved by crafting carefully worded prompts that trigger the undesired behavior while appearing innocuous to the user. The method's effectiveness lies in its ability to manipulate LLMs without requiring direct access to their internal code or parameters.
The attack's success hinges on the model's susceptibility to prompt engineering and its reliance on statistical patterns in training data, potentially making even seemingly secure LLMs vulnerable. BadSeek highlights the critical need for improved security measures within LLMs to mitigate risks of malicious exploitation and ensure the responsible development and deployment of these powerful technologies. The implications are significant, as it raises concerns about the trustworthiness of LLM outputs in various applications, from chatbots to automated systems.
[Read More](https://sshh12--llm-backdoor.modal.run/)
💬 [HN Comments](https://news.ycombinator.com/item?id=43121383) (70)