Abuse Azure Logic App Automation
Notes¶
Step 1: Open-Source Intelligence (OSINT)¶
-
Attacker’s Perspective:
- Action: Found sensitive information (e.g., DevTeamVM IP, Azure Subscription ID) in a LinkedIn post screenshot.
- Rationale: Public social media posts often inadvertently leak sensitive organizational data.
-
Commands:
-
Research DNS records for company infrastructure:
dig megabigtech.com +noall +answer ANY
-
Extract email formats and infrastructure insights.
- Defender’s Perspective:
-
-
Vulnerability: Employees sharing sensitive screenshots or posts online.
- Prevention:
- Conduct regular security awareness training focusing on social media practices.
- Implement Data Loss Prevention (DLP) solutions to monitor and block sensitive data exposure.
- Use image-scanning tools to detect sensitive information in public posts.
- Remediation:
- Take down the post.
- Conduct a risk assessment on exposed information.
Step 2: Email Enumeration¶
-
Attacker’s Perspective:
- Action: Verified email existence using enumeration tools.
- Tool:
o365enum
. -
Command:
python3 o365enum.py -u email.txt -m office.com
-
Rationale: To confirm a valid attack target by enumerating Microsoft 365 email accounts.
-
Defender’s Perspective:
-
Vulnerability: Misconfigured Microsoft 365 responses revealing account existence.
- Prevention:
- Enable Azure AD Smart Lockout to block repeated enumeration attempts.
- Use Conditional Access to limit access from suspicious IP ranges.
- Remediation:
- Review and enforce email address verification throttling.
- Monitor login activity for abnormal patterns.
Step 3: Password Spray¶
- Attacker’s Perspective:
- Action: Used likely passwords (e.g.,
superRyan!
) derived from the OSINT findings. - Tool:
o365spray
. -
Command:
python3 o365spray.py --username [email protected] --passfile passwords.txt --domain megabigtech.com --lockout
Links¶
- Action: Used likely passwords (e.g.,
https://learn.microsoft.com/en-us/connectors/office365users/#get-manager-(v2)