What is an AI security self-assessment?

An AI security self-assessment is a structured evaluation of your organization's AI and LLM security posture. It covers areas like prompt injection readiness, data handling practices, MCP server security, access controls, incident response capabilities, and compliance with AI security standards and regulations.

How do I evaluate my organization's AI security posture?

Evaluate AI security posture by assessing: whether LLM inputs and outputs are properly validated, if MCP tools have appropriate access controls, how training data and model artifacts are protected, whether AI incident response plans exist, and if your team follows secure AI development practices and complies with relevant regulations.

What are the key areas to assess in AI security?

Key AI security assessment areas include: prompt injection defenses, model access controls, API security for LLM endpoints, MCP server configuration, training data protection, output filtering and leakage prevention, supply chain security for ML dependencies, and compliance with frameworks like NIST AI RMF and EU AI Act.

How often should AI security assessments be performed?

AI security assessments should be performed at least quarterly, plus whenever significant changes are made to AI systems. Trigger events include: deploying new LLM models, adding MCP tools or resources, changing system prompts, integrating new third-party AI services, or after any AI security incident.

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Home › Self Assessment › AI Security Self-Assessment: Evaluate Your LLM Security

AI Security Self-Assessment

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Do you have explicit authorization for testing?

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Compliance Notes:

Check regional regulations (GDPR, AI Act, etc.)
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Are you logging all test activities?

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Have you implemented safeguards against data leakage?

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