Execute and analyze AI Data Poisoning attacks. By subtly injecting malicious or targeted misinformation into an LLM's training or fine-tuning dataset, an attacker can covertly manipulate the model's future outputs, implant backdoors, or enforce biases without altering the model architecture.
How to install ai-data-poisoning?
shulkwisec/bb-huge/ai-data-poisoning
$npx -y skills add shulkwisec/bb-huge --skill ai-data-poisoningInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/shulkwisec/bb-huge" --skill "shulkwisec/bb-huge/ai-data-poisoning"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/shulkwisec/bb-huge" that are relevant to the current task. Run `npx skills add "https://github.com/shulkwisec/bb-huge"` and select the relevant skills, then follow their instructions.
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