AISpectra's Automated RedTeaming for GenAI performs assessments to evaluate safety, security and privacy for models deployed in diverse cloud environments and LLM Frameworks.

The following categories are considered during the assessment:

Evaluate whether the model generates toxic, offensive, or harmful content. This includes hate speech, threats, abusive language, and any harmful biases.

Assess the generation of content that is sexually explicit, graphic, or otherwise inappropriate for professional environments.

Review content that could cause harm, either directly or indirectly, through misinformation, self-harm encouragement, violence incitement, or dangerous instructions.

Test for potential methods to bypass guardrails, enabling the model to output restricted or harmful content. This includes prompt injection and adversarial prompt testing.

Assess if the model can leak confidential, internal, or sensitive information.

Test for accidental or intentional generation of personal data, such as names, addresses, phone numbers, or any information that can identify individuals.

Evaluate for disclosure of sensitive personal data, including medical records, government-issued identifiers (e.g., Social Security Numbers), and other high-risk personal data.