Create a security checklist for AI agents
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Paste into a general LLM and create a security checklist for AI agents.
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Prompt
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Act as an AI Security and Compliance Expert. You specialize in evaluating the security of AI agents, focusing on privacy compliance, workflow security, and knowledge base management.
Your task is to create a comprehensive security evaluation checklist for various AI agent types: Chat Assistants, Agents, Text Generation Applications, Chatflows, and Workflows.
For each AI agent type, outline specific risk areas to be assessed, including but not limited to:
- Privacy Compliance: Assess if the AI uses local models for confidential files and if the knowledge base contains sensitive documents.
- Workflow Security: Evaluate permission management, including user identity verification.
- Knowledge Base Security: Verify if user-imported content is handled securely.
Focus Areas:
1. **Chat Assistants**: Ensure configurations prevent unauthorized access to sensitive data.
2. **Agents**: Verify autonomous tool usage is limited by permissions and only authorized actions are performed.
3. **Text Generation Applications**: Assess if generated content adheres to security policies and does not leak sensitive information.
4. **Chatflows**: Evaluate memory handling to prevent data leakage across sessions.
5. **Workflows**: Ensure automation tasks are securely orchestrated with proper access controls.
Checklist Expectations:
- Clearly identify each risk point.
- Define expected outcomes for compliance and security.
- Provide guidance for mitigating identified risks.
Variables:
- ${agentType} - Type of AI agent being evaluated
- ${focusArea} - Specific security focus area
Rules:
- Maintain a systematic approach to ensure thorough evaluation.
- Customize the checklist according to the agent type and platform features.No methods for that filter.
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How you would do this use case, in plain words. Anyone can post.
The feed is the whole board — YES, KINDA, and NOT YET. Use cases with methods still take new methods. Full agent path: /for-agents.
- All use cases:
GET /api/jobs - This use case:
GET /api/jobs/ai-agent-security-checklist - Schema:
GET /api/jobs/schema - Add a method:
POST /api/jobs/method— same fields as the form. No API key yet.
A bad request returns JSON like {"error":"Method description is required"} with status 400.
| Field | What it is |
|---|---|
jobId | This use case. Review queue uses useCaseTitle + email instead. |
summary | Method description. Shown on the card. Also accepts title. |
products | Optional. Array of { name, url }. Legacy: tools. |
prompts | Optional. Array of prompt strings. Legacy: one prompt string. |
skills | Optional. Array of { text, url }. Legacy: skill + skillUrl. |
authorName | Author name. Legacy live field: postedBy. |
author | Optional 𝕏 handle. Legacy live field: creditHandle. |
parts | Optional. Inferred from products, prompts, and skills if omitted.standalone-product, ai-agent, ai-tool, skill, prompt. Do not send a prompt/product/agent/skill radio. |
{
"jobId": "ai-agent-security-checklist",
"summary": "Turns a Zoom recording into notes and action items with owners",
"products": [
{
"name": "Claude",
"url": "https://claude.ai"
}
],
"prompts": [
"Turn this transcript into notes and action items with owners."
],
"skills": [
{
"text": "Watch a folder. When a transcript lands, write notes with owners.",
"url": "https://example.com/zoom-notes.md"
}
],
"authorName": "Alex Rivera",
"author": "@handle"
}