TotalAI Release 1.5 API

  curl -X 'POST' \
  '<qualys_base_url>//ta/api/1.0/detection/search' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "filter": {
    "modelQql": "model.lastScanStatus:FINISHED and model.runtime:AWS Bedrock or model.runtime:Hugging Face",
    "detectionQql": "detection.failTestPercentage>50 and detection.severity>=3"
  },
  "fields": "id, qid, name, attack, severity, firstDetected, lastDetected, lastTested, lastUpdated, result, totalQuestions, passedQuestions, failedQuestions, erroredQuestions, isJailBreak, failTestPercentage, description, consequence, solution, owaspTopTen, categories, model",
  "orderBy": "firstDetected",
  "sortOrder": "DESC",
  "size": "100"
}

{
  "totalElements": 60,
  "content": [
    {
      "id": 12345,
      "qid": 1234567,
      "name": "Always Jailbreaking Prompts Attack",
      "attack": "Jailbreak-Ajp",
      "severity": 5,
      "firstDetected": 1747391220000,
      "lastDetected": 1747395733000,
      "lastTested": 1747395733000,
      "lastUpdated": 1747395733000,
      "result": "FAIL",
      "totalQuestions": 49,
      "passedQuestions": 3,
      "failedQuestions": 46,
      "erroredQuestions": 0,
      "isJailBreak": true,
      "failTestPercentage": 94,
      "description": "The Jailbreak-AJPAttack poses a significant threat by exploiting the ability of AI to generate and execute harmful and unethical prompts through a manipulative persona called AJP, or Always Jailbreaking Prompts. ",
      "consequence": "The impact of the AJPAttack is considerable, as it could lead to the proliferation of illegal activities and unethical behaviors. By forcing the AI to act as an expert in crafting prompts for any situation, regardless of moral or legal boundaries, the AJP persona could enable users to engage in harmful actions such as fraud, hacking, or other malicious activities. This could result in serious societal harm, as individuals or groups could leverage AI-generated instructions to bypass security measures, spread disinformation, or engage in criminal enterprises. Moreover, the attack could severely undermine the trust users have in AI systems, causing reputational damage to platforms that fail to prevent such exploits.",
      "solution": "Mitigating the AJPAttack requires robust and dynamic countermeasures within AI systems. Strengthening AI safety protocols through continuous monitoring and refinement of ethical filters is critical. Implementing advanced adversarial training that can detect and neutralize manipulative personas like AJP is essential for closing off vulnerabilities. Additionally, AI developers should enhance prompt filtering systems to identify and block instructions that push the AI to act as different characters designed to bypass restrictions. Continuous updates and collaboration between AI safety experts, security teams, and regulatory bodies will be necessary to prevent evolving attacks like AJP and maintain the ethical and secure operation of AI platforms.",
      "owaspTopTen": [
        {
          "id": 20001,
          "name": "LLM01: Prompt Injection",
          "year": 2024,
          "url": "https://genai.owasp.org/llmrisk/llm01-prompt-injection/"
        },
        {
          "id": 20003,
          "name": "LLM03: Training Data Poisoning",
          "year": 2024,
          "url": "https://genai.owasp.org/llmrisk/llm03-training-data-poisoning/"
        }
      ],
      "categories": [
        {
          "id": 30018,
          "name": "Jailbreak",
          "year": 20
        }
      ],
      "model": {
        "id": 68372070,
        "name": "Automation-External-Hugging Face - 2025-05-16 14:09:43.628"
      }
    }

  curl -X 'POST' \
  '<qualys_base_url>/ta/api/1.0/detection/count' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "filter": {
    "modelQql": "asset.name: Test Hugging Face",
    "detectionQql": "detection.attack: Jailbreak-Abj"
  }
}'

  {
    "count": 155
  }