Supercharging Security Copilot with Logic Apps: Best practices and pro tips

Integrating Microsoft Security Copilot with Azure Logic Apps enables security teams to automate investigations, orchestrate fast incident response, and unify workflows across the modern enterprise. By leveraging the unique strengths of both platforms, organizations can achieve scalable, efficient, and actionable security automation. 

Why Integrate Security Copilot with Logic Apps?

Security Copilot brings AI-powered reasoning, automation, and natural language-to-action workflow capabilities. When paired with Logic Apps, it enables:

• Seamless orchestration: Launch incident investigations or automated email analysis with a single trigger.
• Advanced automation: Integrate across Microsoft and third-party security tools without heavy coding.
• Consistent, repeatable outcomes: Use Security Copilot's prompts and promptbooks for security-centric routines and reduce potential for error .

Common scenarios include incident response initiation, scheduled security reports, and automated threat intelligence gathering.

Best Practices for designing robust workflows:

1. Identify your use case

Not all scenarios require automation. Likewise, not all use cases benefit equally from combining automation with AI enrichment. The first step in unlocking value from Azure Logic Apps and Security Copilot is selecting the right use cases—those that align with both operational needs and the capabilities of these tools.

To identify a suitable use case, we suggest the following guidelines:

• • • Start with repetitive tasks: Look for tasks that are performed frequently and follow a predictable pattern, such as alert enrichment, ticket creation, or user access reviews. These are ideal candidates for automation via Logic Apps.
    • Assess the complexity of decision-making: If a task involves nuanced decision-making or contextual analysis—like investigating suspicious sign-ins or correlating threat indicators—Security Copilot’s AI capabilities can add significant value.
    • Evaluate data availability and integration points: Ensure the use case involves systems and data sources that Logic Apps can connect to easily (e.g., Microsoft Sentinel, Entra ID, Office 365 E-mail). While it is possible to build your own custom, connectors, the availability of built-in connectors is a key consideration for the success of the integration.
    • Consider the impact on security operations: Prioritize use cases that reduce manual effort, accelerate response times, or improve accuracy in threat detection and remediation. 
    • Check for existing playbooks or templates: Use cases that align with existing Logic Apps templates or Security Copilot skills are easier to implement and test. Microsoft’s GitHub repository for Copilot for Security or the Sentinel GitHub repos are great places to start.
    • Validate with stakeholders: Collaborate with SOC managers, incident responders, and IT admins to confirm that the selected use case addresses a real pain point and fits within current workflows.

  

2. Optimize for performance, cost, and scale

• • • Leverage direct skill invocation: This has the effect of cost reduction and faster execution as the planning process that natural language prompts must go through is bypassed.
    • Optimize Security Copilot calls: Limit Copilot calls within workflows to actions that benefit from AI-value addition such as reducing cognitive load on the Security Analyst or providing reasoning over disparate sets of facts while taking advantage of the investigation context powered by the wide range of Security Copilot skills that are native to the product 
    • Logic App tuning: Fine-tune trigger frequency and need for AI-value addition i.e. you may only need to attach a Logic App that submits security copilot prompts as part of its flow based on the complexity of the expected incidents vs all detection rules and resulting incidents

Pro Tips

i. Prototype cost-effective, complex workflows 

Prototype complex workflows with test data before deploying to production environments. You can do this by simulating Security Copilot prompts by using variable instead of actual calls to Security Copilot during the testing phase. Follow the following steps to do this:

a. Run the prompt or promptbook within Security Copilot to obtain the desired payload

b. In this example we need to execute the following promptbook as part of a workflow that involves extraction of firewall device names and their owners so that we can send them an e-mail, alerting them to block public IPs exhibiting suspicious behaviors:

Fig. 1 : Sample Promptbook for demo

c. Execute the promptbook

Fig 2. Sample promptbook run

d. Next, we prompt Security Copilot to generate an output that can be used to generate a JSON formatted payload which we will eventually use to create a schema for our Logic App ParseJSON step.

Fig 3. Output from promptbook run

e. Next, use a LLM, preferably an enterprise grade one such as Microsoft 365 or Security Copilot to generate the JSON payload

 

Fig. 4: Generated sample payload

f. Next, use the sample payload to create the input schema for the ParseJSON step in the Logic App

Fig. 5: Generate the schema using the sample payload

g. Initialize a variable and save the sample JSON-this will act as simulated output Parsed from the EvaluationResult of the Promptbook from Security Copilot-effectively avoiding any costs involved with submitting the promptbook multiple times while you test and refine your Logic App

Fig. 6 Image showing initialization and saving of variable

h. You can now run the Logic App several times without submitting any prompts to Security Copilot . If you must test with payloads that vary considerably you can still do that by not saving it in the variable, and selecting the “Run with payload” option then pasting your payload in the resulting box

 

Fig. 7 Logic App snippet showing manual execution of Logic App

 

i. Once happy with Logic App flow and output you can replace the variable with the actual Security Copilot connection for your prompt or promptbook

 

Fig. 8 Partial snapshot of sample Logic App

 

ii. Session management: Use the Session Id field to maintain investigative context—enabling multiple prompts within a workflow to share data without re-authentication. However, you can also spawn new sessions which allows for parallel execution of tasks without dependency on current session content

iii. Provide descriptive connector names: Rename default connector names as you build out your logic app. This helps to troubleshoot the Logic App or maintain it, especially if it is being done by someone other than the one that built the original one. Example below describes exactly what the step does vs the default connector names:

Fig. 9. Partial snapshot of Logic App showing descriptive names for Logic App connectors

 

iv. Use custom code: Enhance workflows with inline Python or Function App steps for specialized operations, such complex text transformations or data extractions. In the example below, a function app is used to apply a regex operation to extract the e-mail GUID. This comes in handy when you do not have a built-in connector for specific requirements or existing ones are not as efficient tor flexible as a function app would be.

 

Fig. 9 Logic App snippet showing use of the Function connector

 v. Secure your Logic App workflows

• • Managed identities: Leverage managed identities across all connectors that support this authentication method whenever you use them in your flows.
  • Obfuscate secrets in run histories: Actions that handle passwords, secrets, keys, or other sensitive information are visible by default from the run history of the Logic App. For example, if your logic app gets a secret from Azure Key Vault to use when authenticating an HTTP action, you may want to hide that secret from view by enabling the toggle button for supported actions. See below:

 

Fig. 10 showing toggle set to "on" to enable securing of outputs

 

 

You may also use source IP addresses to perform access restrictions to this data. See details in this document

Log and monitor activities: Enable logging for action taken by Logic Apps in your environment for greater visibility and control. If using Microsoft Sentinel, you can send Logic App activities to your Log Analytics workspace and benefit from queries such as the one below:

SentinelHealth

| where TimeGenerated > ago(30d)

| where SentinelResourceType == "Playbook"

| extend triggeredBy = ExtendedProperties.TriggeredByName.UserDisplayName

vi. Use parameters 

Parameters allow workflows to be dynamic and reusable by enabling the injection of context-specific data—such as usernames, incident IDs, or IP addresses—at runtime. This flexibility means a single Logic App can serve multiple scenarios without hardcoding values, improving maintainability and scalability. Additionally, parameters help enforce security best practices by supporting secure input/output handling, which protects sensitive information during execution.

Conclusion

Security Copilot and Logic Apps together unlock a flexible, AI-powered automation platform for any security operations team. By following these best practices—efficient prompt design, session context management, robust security controls, and scheduled automation—organizations can level up their security response and proactivity. To go even further, explore Microsoft’s official documentation, the Security Copilot Adoption Hub, Techcommunity blog portal and our GitHub repo. I f you have any feedback or ideas on how you think we can further improve the value delivered by these solutions working together, please reach out. Always happy to hear back from you.

 

Additional resources

Security-Copilot/Logic Apps

Microsoft Security Copilot – Microsoft Adoption

Category: Security Copilot | Microsoft Community Hub