Identify and simulate Data Poisoning attacks aimed at degrading or skewing an AI model's accuracy. This skill focuses on Adversarial Machine Learning concepts where attackers inject malicious or mislabelled data points into training or fine-tuning datasets (e.g., feedback loops) to bias the AI.
How to install ai-data-poisoning-model-skewing?
shulkwisec/bb-huge/ai-data-poisoning-model-skewing
$npx -y skills add shulkwisec/bb-huge --skill ai-data-poisoning-model-skewingInstalls 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-model-skewing"` 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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