by sshh12 · Agent Tool · ★ 203
Experimental tools to backdoor large language models by re-writing their system prompts at a raw parameter level. This allows you to potentially execute offline remote code execution without running any actual code on the victim's machine or thwart LLM-based fraud/moderation systems.
| Stars | 203 |
| Forks | 25 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 48.45/100 |
| Last Updated | 2025-10-05 |
| Created | 2025-01-30 |
| Platforms | python |
| Est. Tokens | ~12k |
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llm_backdoor is Experimental tools to backdoor large language models by re-writing their system prompts at a raw parameter level. This allows you to potentially execute offline remote code execution without running a. It is categorized as a Agent Tool with 203 GitHub stars.
llm_backdoor is primarily written in Python. It covers topics such as backdoor-attacks, llm-security, qwen2-5.
You can find installation instructions and usage details in the llm_backdoor GitHub repository at github.com/sshh12/llm_backdoor. The project has 203 stars and 25 forks, indicating an active community.
llm_backdoor is released under the MIT license, making it free to use and modify according to the license terms.