Detecting OAUTH Token Theft

Detecting Oauth Token Theft

Overview

Cybersecurity skill for detecting oauth token theft. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "detecting oauth token theft"

• "Detects and responds to OAuth token theft and replay attacks in cloud environmen"

• Investigating alerts for impossible travel or anomalous token usage in Microsoft Entra ID

• Responding to a suspected session hijacking or pass-the-cookie attack

• Configuring proactive defenses against OAuth token theft in an Azure/M365 environment

• Detecting OAuth device code phishing campaigns that bypass MFA

• Analyzing sign-in logs for token replay indicators

• Implementing Token Protection conditional access policies to bind tokens to devices

Do not use for on-premises Kerberos ticket attacks (pass-the-ticket, golden ticket); use Active Directory-specific investigation techniques for those scenarios.

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• Microsoft Entra ID P2 license (required for Identity Protection risk detections and conditional access)
• Global Administrator or Security Administrator role in the Entra admin center
• Microsoft Defender for Cloud Apps (MDCA) license for session anomaly detection
• Access to Entra ID Sign-in Logs and Audit Logs (requires Diagnostic Settings configured to Log Analytics or Sentinel)
• Familiarity with OAuth 2.0 authorization flows (authorization code, device code, client credentials)
• Microsoft Sentinel or equivalent SIEM ingesting Entra ID sign-in and audit logs

Workflow

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}

1. Define Detection Scope — Identify the specific oauth token theft techniques or indicators to hunt. Map to MITRE ATT&CK tactics/techniques where applicable.
2. Collect Baseline Data — Gather historical logs and establish normal behavior patterns for oauth token theft.
3. Build Detection Queries — Write detection rules, Sigma rules, or SIEM queries targeting oauth token theft indicators.
4. Execute Hunts — Run queries against the collected data, starting with broad filters and narrowing down.
5. Triage Results — Investigate alerts, filter false positives, and validate findings against known-good behavior.
6. Document Findings — Record confirmed detections, IOCs, and affected systems. Update detection rules based on findings.

Tools

• SIEM Platform — Central log aggregation and query execution
• Sigma Rules — Vendor-agnostic detection rule format
• MITRE ATT&CK Navigator — Technique mapping and coverage analysis

Process

1. Reconnaissance — Gather target information, identify attack surface, enumerate services
2. Analysis/Exploitation — Execute the technique, analyze results, document findings
3. Reporting — Document IOCs, write findings, provide remediation recommendations

Verification

• All oauth token theft procedures executed completely and documented
• Findings validated against multiple data sources
• False positives identified and filtered
• Results documented with evidence and timestamps
• Recommendations provided with risk-based prioritization

Anti-Rationalization Table