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Prompts Detect Risky OAuth Consent Grants in Entra ID

security analyst security skill risk: medium

Detect Risky OAuth Consent Grants in Entra ID

The prompt outlines prerequisites, steps, and expected output for using Microsoft Graph API and audit logs to enumerate OAuth2 permission grants, flag high-risk scopes, check publi…

  • Policy sensitive
  • Human review
  • External action: medium

SKILL 4 files · 2 folders

SKILL.md
---
name: detecting-suspicious-oauth-application-consent
description: "Detect risky OAuth application consent grants in Azure AD / Microsoft Entra ID using Microsoft Graph API, audit"
---
# Detecting Suspicious OAuth Application Consent

## Overview

Illicit consent grant attacks trick users into granting excessive permissions to malicious OAuth applications in Azure AD / Microsoft Entra ID. This skill uses the Microsoft Graph API to enumerate OAuth2 permission grants, analyze application permissions for overly broad scopes, review directory audit logs for consent events, and flag high-risk applications based on publisher verification status and permission scope.


## When to Use

- When investigating security incidents that require detecting suspicious oauth application consent
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques

## Prerequisites

- Azure AD / Entra ID tenant with Global Reader or Security Reader role
- Microsoft Graph API access with `Application.Read.All`, `AuditLog.Read.All`, `Directory.Read.All`
- Python 3.9+ with `msal`, `requests`
- App registration with client secret or certificate for authentication

## Steps

1. Authenticate to Microsoft Graph using MSAL client credentials flow
2. Enumerate all OAuth2 permission grants via `/oauth2PermissionGrants`
3. List service principals and their assigned application permissions
4. Query directory audit logs for `Consent to application` events
5. Flag applications with high-risk scopes (Mail.Read, Files.ReadWrite.All, etc.)
6. Check publisher verification status for each application
7. Generate risk report with remediation recommendations

## Expected Output

- JSON report listing all OAuth apps with granted permissions, risk scores, unverified publishers, and suspicious consent patterns
- Audit trail of consent grant events with user and IP details

REQUIRED CONTEXT

  • Azure AD / Entra ID tenant with Global Reader or Security Reader role
  • Microsoft Graph API access with Application.Read.All, AuditLog.Read.All, Directory.Read.All
  • Python 3.9+ with msal, requests
  • App registration with client secret or certificate

EXPECTED OUTPUT

Format
structured_report
Schema
json_report · oauth_apps, risk_scores, unverified_publishers, suspicious_consent_patterns, audit_trail
Constraints
  • JSON report listing all OAuth apps with granted permissions, risk scores, unverified publishers, and suspicious consent patterns
  • Audit trail of consent grant events with user and IP details

SUCCESS CRITERIA

  • Enumerate OAuth2 permission grants
  • Flag high-risk scopes
  • Check publisher verification
  • Generate risk report with remediation recommendations

CAVEATS

Dependencies
  • Azure AD / Entra ID tenant with Global Reader or Security Reader role
  • Microsoft Graph API access with Application.Read.All, AuditLog.Read.All, Directory.Read.All
  • Python 3.9+ with msal, requests
  • App registration with client secret or certificate for authentication
Missing context
  • Exact list or definition of high-risk scopes
  • Risk scoring methodology or thresholds
  • Detailed JSON schema for the expected report

QUALITY

OVERALL
0.75
CLARITY
0.90
SPECIFICITY
0.75
REUSABILITY
0.65
COMPLETENESS
0.70

IMPROVEMENT SUGGESTIONS

  • Add an explicit risk-scoring rubric or decision table after step 5.
  • Include a minimal JSON schema example under Expected Output.

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.

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