The main contribution of this paper is to provide an accurate taxonomy for delivery techniques, which allows the detection of novel techniques and the identification of appropriate countermeasures. Delivery is a key stage for offensive cyber operations. During delivery, a threat actor tries to gain an initial foothold into the targeted infrastructure. It is the first step of an offensive cyber operation, where the threat actor interacts with its victim in a hostile way; thus, its success is mandatory for the global achievement of the operation. However, delivery techniques are not well structured among the literature, being in many cases a simple list of techniques with which, if one of them is slightly modified by the threat actor, its detection becomes very difficult. This situation hinders the modeling of hostile actors, a fact that makes it difficult to identify countermeasures to detect and neutralize their malicious activities. In this work, we analyze the current delivery techniques’ classification approaches and the problems linked to them. From this analysis, we propose a novel taxonomy that allows the accurate classification of techniques, overcoming the identified problems and allowing both the discovery of new techniques and the detection of gaps in deployed countermeasures. Our proposal significantly reduces the amount of effort needed to identify, analyze, and neutralize hostile activities from advanced threat actors, in particular their initial access stage. It follows a logical structure that can be easy to expand and adapt, and it can be directly used in the industry’s commonly accepted standards, such as MITRE ATT&CK.
Destructive and control operations are today a major threat for cyber physical systems. These operations, known as Computer Network Attack (CNA), and usually linked to state-sponsored actors, are much less analyzed than Computer Network Exploitation activities (CNE), those related to intelligence gathering. While in CNE operations the main tactics and techniques are defined and well structured, in CNA there is a lack of such consensuated approaches. This situation hinders the modeling of threat actors, which prevents an accurate definition of control to identify and to neutralize malicious activities. In this paper, we propose the first global approach for CNA operations that can be used to map real-world activities. The proposal significantly reduces the amount of effort need to identify, analyze, and neutralize advanced threat actors targeting cyber physical systems. It follows a logical structure that can be easy to expand and adapt.
Cyber threat intelligence feeds the focus on atomic and computed indicators of compromise. These indicators are the main source of tactical cyber intelligence most organizations benefit from. They are expressed in machine-readable formats, and they are easily loaded into security devices in order to protect infrastructures. However, their usefulness is very limited, specially in terms of time of life. These indicators can be useful when dealing with non-advanced actors, but they are easily avoided by advanced ones. To detect advanced actor’s activities, an analyst must deal with behavioral indicators of compromise, which represent tactics, techniques and procedures that are not as common as the atomic and computed ones. In this paper, we analyze why these indicators are not widely used, and we identify key requirements for successful behavioral IOC detection, specification and sharing. We follow the intelligence cycle as the arranged sequence of steps for a defensive team to work, thereby providing a common reference for these teams to identify gaps in their capabilities.
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