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Toxicity testing checks whether your AI system can be pushed into generating harmful, offensive, or inappropriate content. This includes hate speech, violent instructions, sexually explicit material, harassment, and other outputs that would violate your organization's safety standards or policies.
Even models with safety guardrails can produce toxic content under certain conditions. Toxicity testing finds those conditions before your users do.
If your AI system interacts with users or generates content, toxic outputs are a direct risk. A single harmful response from a customer-facing chatbot, a content tool producing offensive material, or an assistant providing dangerous instructions can create serious reputational, legal, and regulatory problems for your organization.
Toxicity testing is also part of the safety evaluation expected under the EU AI Act, NIST AI RMF, and ISO 42001.
Our platform evaluates toxic outputs across multiple content categories:
Toxicity testing is different from jailbreak testing or prompt injection testing. Those focus on the attack method. Toxicity testing focuses on the content itself, regardless of how it was triggered.
We test for toxic outputs using both static prompts across predefined categories and dynamic prompts generated on the fly to simulate evolving risks and edge cases. Every response is classified as safe or unsafe using automated evaluation followed by human expert review, and scored using the Defense Success Rate (DSR) broken down by toxicity category.
Beyond testing, the platform can also enforce content safety in production. Guardrails can be configured to block harmful content, prevent offensive language, and enforce tone guidelines automatically as part of your runtime policy.
Results feed into your risk profile, compliance reports, and monitoring dashboards so that content safety is tracked continuously.
If you want to know more about how we do toxicity testing and content safety on your AI systems, get a demo now.