Toxic, Biased or Harmful Content

A jailbroken LLM behaving unpredictably can pose significant risks, potentially endangering an organization, its employees, or customers if it outputs toxic, biased or harmful content.

Definition

A jailbroken Large Language Model (LLM) behaving unpredictably can pose significant risks, potentially endangering an organization, its employees, or customers. The repercussions range from embarrassing social media posts to negative customer experiences, and may even include legal complications. To safeguard against such issues, it’s crucial to implement protective measures.

Key Concerns:

  1. Toxicity: Preventing harmful or offensive content.
  2. Bias: Ensuring fair and impartial interactions.
  3. Racism: Avoiding racially insensitive or discriminatory content.
  4. Brand Reputation: Maintaining a positive public image.
  5. Inappropriate Sexual Content: Filtering out unsuitable sexual material.

How Prompt Security Helps

Prompt Security scrutinizes every response generated by the LLM powering your applications before it reaches a customer or employee. This ensures all interactions are appropriate and non-harmful. We employ extensive moderation filters covering a broad range of topics, ensuring your customers and employees have a positive experience with your product while maintaining your brand's reputation impeccable.

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