EnkryptAI Rating
EnkryptAI Rating for Model Safety that takes into account model vulnerabilities as well as the severity of those vulnerabilities.
4
NIST Score
Denotes the percentage of number of attacks successful against total number of atacks performed.
12%
OWASP Score
Weighted average of all the successful attack percentages according to risk ranking of OWASP.
14%
gpt-5
Provider: openai
Rank : 2/214
Bias Bias Rating is calculated by inversely mapping the Bias risk score for all models (ranging from 0 to 100) onto a rating scale from 5 (safe) to 0 (risky). The bias risk score of each model is the percentage of successful bias attacks. | Harmful Tests Harmful Tests Rating is calculated by inversely mapping the Harmful Test risk score for all models (ranging from 0 to 100) onto a rating scale from 5 (safe) to 0 (risky). The Harmful Test risk score is the percentage of successful Harmful Tests. | Toxicity Toxicity Rating is calculated by inversely mapping the Toxicity risk score for all models (raning from 0 to 100) onto a rating scale from 5 (safe) to 0 (risky). Toxicity Risk score is the percentage of successful toxicity generation attacks. | CBRN CBRN Rating is calculated by inversely mapping the CBRN risk score for all models (raning from 0 to 100) onto a rating scale from 5 (safe) to 0 (risky). The CBRN Risk score for each model is the percentage of successful attacks for Chemical, Biological and Cybersecurity information generation. | Insecure Code Insecure Code Rating is calculated by inversely mapping the Insecure risk score for all models (raning from 0 to 100) onto a rating scale from 5 (safe) to 0 (risky). The Insecure Code risk for each model is the percentage of successful attacks. | Robustness Tests Robustness Rating is calculated by mapping the Robustness score for all models (raning from 0 to 1) onto a rating scale from 0 (risky) to 5 (safe). The Robustness Score indicates how a robust is the model to input variation. | |
|---|---|---|---|---|---|---|
4.8 | 4.7 | 2.8 | 4.1 | 4.9 | TBD | |
 | Harmful Bias & Homogenisation | Dangerous, Violent, or Hateful Content | Obscene, Degrading, and/or Abusive Content | CBRN Information or Capabilities | Information Security | Confabulation |
 | LLM01 Prompt Injection LLM04 Data and Model Poisoning | LLM01 Prompt Injection | LLM01 Prompt Injection | LLM01 Prompt Injection | LLM01 Prompt Injection LLM05 Improper Output Handling |
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