Abstract:
An arrangement for scanning and patching injected malware code that is executing in otherwise legitimate processes running on a computer system is provided in which malware code is located in the memory of processes by extracting the start addresses of processes' threads and then searching near these addresses. Additional blocks of code in memory that are invoked by the code identified by each start address are also identified and the blocks are then matched against scanning signatures associated with known malware threads. If the entire signature can be matched against a subset of the blocks, then the thread is determined to be infected. The infected thread is suspended and in-memory modifications are performed to patch the injected code to render it harmless. The thread can be resumed or terminated to disable the protection mechanisms of the malware without causing any harm to the process in which the thread is injected.
Abstract:
A system, method, and computer readable medium for the proactive detection of malware in operating systems that receive application programming interface (API) calls is provided. A virtual operating environment for simulating the execution of programs and determining if the programs are malware is created. The virtual operating environment confines potential malware so that the systems of the host operating environment will not be adversely effected. During simulation, a behavior signature is generated based on the API calls issued by potential malware. The behavior signature is suitable for analysis to determine whether the simulated executable is malware.
Abstract:
In accordance with the present invention, a system, method, and computer-readable medium for identifying malware at a network transit point such as a computer that serves as a gateway to an internal or private network is provided. A network transmission is scanned for malware at a network transit point without introducing additional latency to the transmission of data over the network. In accordance with one aspect of the present invention, a computer-implemented method for identifying malware at a network transit point is provided. More specifically, when a packet in a transmission is received at the network transit point, the packet is immediately forwarded to the target computer. Simultaneously, the packet and other data in the transmission are scanned for malware by an antivirus engine. If malware is identified in the transmission, the target computer is notified that the transmission contains malware.
Abstract:
A system and method for gathering exhibited behaviors of a .NET executable module in a secure manner is presented. In operation, a .NET behavior evaluation module presents a virtual .NET environment to a Microsoft Corporation .NET code module. The .NET behavior evaluation module implements a sufficient number of aspects of an actual Microsoft Corporation .NET environment that a .NET code module can execute. As the .NET code module executes, the .NET behavior evaluation module records some of the exhibited behaviors, i.e., .NET system supplied libraries/subroutines, that are associated with known malware. The recorded behaviors are placed in a behavior signature for an external determination as to whether the .NET code module is malware, i.e., an unwanted computer attack.
Abstract:
The present invention is directed toward a system, method, and computer-readable medium that scan a file for malware that maintains a restrictive access attribute that limits access to the file. In accordance with one aspect of the present invention, a method for performing a scan for malware is provided when antivirus software on a computer encounters a file with a restrictive access attribute that prevents the file from being scanned. More specifically, the method includes identifying the restrictive access attribute that limits access to the file; bypassing the restrictive access attribute to access data in the file; and using a scan engine to scan the data in the file for malware.
Abstract:
A self-healing device is provided in which changes made between the time that an infection resulting from an attack on the device was detected and an earlier point in time to which the device is capable of being restored may be recovered based, at least in part, on what kinds of changes were made, whether the changes were bona fide or malware induced, whether the changes were made after the time that the infection likely occurred, and whether new software was installed.
Abstract:
In accordance with this invention, a system, method, and computer-readable medium that aggregates the knowledge base of a plurality of antivirus software applications are provided. User mode applications, such as antivirus software applications, gain access to file system operations through a common information model, which obviates the need for antivirus software vendors to create kernel mode filters. When file system operations are available to antivirus software applications, the present invention may cause each antivirus software application installed on a computing device to perform a scan to determine if the data is malware.
Abstract:
Techniques are described herein that are capable of selectively scanning objects for infection by malware (i.e., to determine whether one or more of the objects are infected by malware). For instance, metadata that is associated with the objects may be reviewed to determine whether update(s) have been made with regard to the objects since a determination was made that the objects were not infected by malware. An update may involve increasing a number of the objects, modifying one of the objects, etc. Objects that have been updated (e.g., added and/or modified) since the determination may be scanned. Objects that have not been updated since the determination need not necessarily be scanned. For instance, an allowance may be made to perform operations with respect to the objects that have not been updated since the determination without first scanning the objects for infection by malware.
Abstract:
A reliable automated malware classification approach with substantially low false positive rates is provided. Graph-based local and/or global file relationships are used to improve malware classification along with a feature selection algorithm. File relationships such as containing, creating, copying, downloading, modifying, etc. are used to assign malware probabilities and simultaneously reduce the false positive and false negative rates on executable files.
Abstract:
A system is described for remediating a malicious modern application installed on an end user device. In an embodiment, the system includes an antimalware program executing on the end user device that can detect and attempt to remediate the malicious modern application, an operating system executing on the end user device that is configured to interact with the antimalware program for the purpose of facilitating the establishment of a connection between the end user device and an application support system in response to determining that the antimalware program has detected and attempted to remediate the malicious modern application, and the application support system that can perform remediation operations beyond those that can be performed by the antimalware program.