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"LLM Agents can Autonomously Hack Websites" is a new paper that investigates the capacity of LLMs to autonomously execute cybersecurity attacks on websites, such as SQL injections without human guidance.
"LLM Agents can Autonomously Hack Websites" is a new paper that investigates the capacity of LLMs to autonomously execute cybersecurity attacks on websites, such as SQL injections without human guidance.
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Key points:
Key points:
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* It uses a LLM integrated with Playwright, a headless web browser, enabling automated web interactions through function calling.
* It uses a LLM integrated with Playwright, a headless web browser, enabling automated web interactions through function calling.
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* It gives access to the LLM to 7 web hacking documents and planning capabilities through specific prompting, without disclosing the exact methods to prevent misuse.
* It gives access to the LLM to 7 web hacking documents and planning capabilities through specific prompting, without disclosing the exact methods to prevent misuse.
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GPT-4 achieves a 73.3% success rate on the tested vulnerabilities, emphasizing the potential cybersecurity risks posed by advanced LLMs. Other open models cannot yet perform these types of attacks (results in screenshot).
GPT-4 achieves a 73.3% success rate on the tested vulnerabilities, emphasizing the potential cybersecurity risks posed by advanced LLMs. Other open models cannot yet perform these types of attacks (results in screenshot).
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Congrats to the authors for their work!
Congrats to the authors for their work!
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Paper: 
Paper: 
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https://huggingface.co/papers/2402.06664
paper
2402.06664
https://huggingface.co/papers/2402.06664
LLM Agents can Autonomously Hack Websites (2402.06664)
"LLM Agents can Autonomously Hack Websites" is a new paper that investigates the capacity of LLMs to autonomously execute cybersecurity attacks on websites, such as SQL injections without human guidance.

Key points:
* It uses a LLM integrated with Playwright, a headless web browser, enabling automated web interactions through function calling.
* It gives access to the LLM to 7 web hacking documents and planning capabilities through specific prompting, without disclosing the exact methods to prevent misuse.

GPT-4 achieves a 73.3% success rate on the tested vulnerabilities, emphasizing the potential cybersecurity risks posed by advanced LLMs. Other open models cannot yet perform these types of attacks (results in screenshot).

Congrats to the authors for their work!

Paper: https://huggingface.co/papers/2402.06664
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