Kerberos Identity Attack Detection via Stateful Protocol Analysis
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Solution Overview
Problem
Current cybersecurity solutions are inadequate in detecting Kerberos authentication attacks in a timely and precise manner, often resulting in undetected threats that require costly and time-consuming recovery processes, and are prone to generating false positives and false negatives.
Innovation Solution
A system and method for detecting and mitigating Kerberos golden ticket, silver ticket, and related identity-based cyberattacks by passively monitoring and analyzing Kerberos operations within the network, transforming the stateless Kerberos protocol into a stateful one using a cyber-physical graph module and graph traversal algorithms to identify attacks in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If heuristic baseline detection is used over several weeks, then detection capability is established, but detection timeliness deteriorates and numerous false positives are generated
Solution Approach 1:
The patent pre-defines multiple attack patterns (golden ticket, silver ticket, TGS replay, etc.) and their corresponding detection rules in advance. When attacks occur, the system directly matches traffic against these pre-established rules, eliminating the need to build baselines over weeks. This allows immediate detection without waiting for heuristic learning periods.
Solution Approach 2:
The system changes the detection parameters from heuristic baseline metrics (which require long observation periods) to specific attack pattern signatures (which can be detected immediately). By transforming the detection approach from statistical anomaly detection to signature-based matching, the system achieves both high precision and immediate timeliness.
2Reliability
If heuristic baseline detection is used, then some attack detection is achieved, but false positives increase significantly
Solution Approach 1:
The patent segments the detection process into multiple independent rule modules, each targeting specific attack types (golden ticket detection rule, silver ticket detection rule, TGS replay detection rule, etc.). Each rule independently evaluates specific aspects of Kerberos traffic, allowing precise identification of actual attacks while avoiding false positives from normal traffic variations.
Solution Approach 2:
The system transitions from heuristic parameters (which generate false positives) to specific attack pattern parameters (ticket authenticity, protocol compliance, timestamp validity). This parameter transformation enables reliable detection with minimal false positives by focusing on definitive attack indicators rather than statistical anomalies.
3Device complexity
If Kerberos protocol remains stateless, then protocol simplicity is maintained, but attack detection capability is insufficient
Solution Approach 1:
The patent introduces an intermediary detection system that sits between the stateless Kerberos protocol and the analysis layer. This intermediary captures and analyzes Kerberos traffic, maintaining detection state independently without modifying the underlying protocol. The stateless protocol preserves simplicity while the intermediary provides sophisticated detection capabilities through pattern matching and rule-based analysis.
Data Source
AI summary
A system and method for the detection and mitigation of Kerberos golden ticket, silver ticket, and related identity-based cyberattacks by passively monitoring and analyzing Kerberos and authentication operations within the network. The system and method provide real-time detections of identity attacks using time-series data and data pipelines, and by transforming the stateless Kerberos protocol into stateful protocol. A packet capturing agent is deployed on the network where captured time-series Kerberos and related event and log information is processed in distributed computational graph (DCG) stages where declarative rules determine if an attack is being carried out and what type of attack it is.