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Security Guide

AI Vulnerability Scanning Guide (2026) - Automated Security Testing

AI vulnerability scanning: automated tools test for prompt injection, data leakage, model extraction. Scan frequency: weekly for production, monthly for development. Vulnerability severity: critical (fix immediately), high (<7 days), medium (<30 days), low (<90 days).

Direct answer

AI vulnerability scanning: automated tools test for prompt injection, data leakage, model extraction. Scan frequency: weekly for production, monthly for development. Vulnerability severity: critical (fix immediately), high (<7 days), medium (<30 days), low (<90 days).

Fast path

  1. Select tools: Garak, PromptInject, Azure AI Red Team, vendor-specific scanners.
  2. Scan frequency: weekly production, monthly development, quarterly full assessment.
  3. Classify: critical (immediate fix), high (7 days), medium (30 days), low (90 days).

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Implementation Steps

  1. Select tools: Garak, PromptInject, Azure AI Red Team, vendor-specific scanners.
  2. Scan frequency: weekly production, monthly development, quarterly full assessment.
  3. Classify: critical (immediate fix), high (7 days), medium (30 days), low (90 days).
  4. Remediate: prioritize by severity, document fixes, verify resolution.
  5. Report: track vulnerability trends, measure remediation time.

Frequently Asked Questions

How to scan AI for vulnerabilities?

Scan AI vulnerabilities: use tools (Garak, PromptInject, Azure AI Red Team), test prompt injection, data leakage, model extraction, rate limit bypass. Frequency: weekly production, monthly development. Classify: critical (fix now), high (<7 days), medium (<30 days). Track remediation time.

What tools test AI security?

AI security testing tools: Garak (prompt injection, hallucination), PromptInject (adversarial prompts), Azure AI Red Team (comprehensive assessment), NVIDIA NeMo Guardrails (prompt testing), OWASP LLM Top 10 checklist. Combine automated + manual testing for comprehensive coverage.

Related Guides

Use these adjacent playbooks to keep the same workflow connected across discovery, conversion, and execution.

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