Kerberos Ticket Detection Through Near-Real-Time Hash Verification
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Solution Overview
Problem
Existing systems fail to effectively detect and mitigate Kerberos ticket-based attacks, such as 'golden ticket' and 'silver ticket' attacks, which can grant hostile attackers unlimited access to domain assets if not detected quickly.
Innovation Solution
A system and method that uses an authentication object inspector to generate and store cryptographic hashes of legitimate authentication objects, compare incoming objects against a database, and analyze traffic records to identify fraudulent attempts, generating incident reports and mitigating compromised accounts in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cryptographic hash verification is implemented to detect forged authentication objects, then detection accuracy improves, but system complexity increases
Solution Approach 1:
The system pre-calculates and stores cryptographic hashes of all legitimate authentication objects in a database before they are potentially forged. This preliminary action enables rapid verification without real-time computation, maintaining high detection accuracy while minimizing processing complexity during actual authentication events.
Solution Approach 2:
Instead of storing complete authentication objects, the system creates cryptographic hash copies of legitimate objects and stores only these hash values in the database. This copying approach enables accurate forgery detection through hash comparison while significantly reducing storage requirements and system complexity.
2Speed
If real-time monitoring and analysis of authentication objects is performed, then attack detection speed improves, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-storing cryptographic hashes of legitimate authentication objects in a ready-access database structure. When authentication objects are received, the system only needs to calculate hashes and perform database lookups rather than performing full verification analysis, dramatically reducing processing time while maintaining real-time detection capability.
Solution Approach 2:
The system applies different processing qualities to different authentication objects based on their risk profiles. High-risk objects undergo full cryptographic verification while low-risk objects receive streamlined processing, optimizing the balance between detection speed and processing time for different types of authentication events.
3Loss of information
If comprehensive logging and incident report generation is implemented, then forensic analysis capability improves, but data storage requirements increase
Solution Approach 1:
The system extracts only the most critical and forensically valuable information from authentication events, such as hash mismatches, timestamp anomalies, and access path deviations. By taking out only essential data elements rather than logging complete authentication streams, the system maintains comprehensive forensic analysis capability while minimizing data storage requirements.
Solution Approach 2:
The system discards redundant and low-value authentication data that does not contribute to forensic analysis, while recovering and preserving critical evidence elements. This selective discarding and recovering approach enables efficient storage utilization while maintaining the integrity and completeness of forensically relevant information.
Data Source
AI summary
A system and methods for mitigating authentication ticket attacks within a domain is provided, comprising an authentication object inspector configured to observe a new authentication object generated by an identity provider, and retrieve the new authentication object; and a hashing engine configured to retrieve the new authentication object from the authentication object inspector, calculate a cryptographic hash for the new authentication object, and store the cryptographic hash for the new authentication object in a data store; wherein subsequent access requests accompanied by authentication objects are validated by near-real-time comparison of hashes for each authentication object to previously-generated hashes.