Fireeye, Inc.

Fireeye Security Holdings US LLC

Musarubra US LLC

Fireeye Security Holdings, Inc.

Sushant Paithane

Sai Omkar Vashisht

Michael Vincent

Yasir Khalid

Sumer Deshpande

Darien Kindlund

Phung-Te Ha

Rahul Khul

Alexandre Pilipenko

Raymond Yang

Rajeev Menon

Sai Vashisht

Muhammad Rizwan

Sai Omkar Vashist

Durvesh Ashok Raut

Imtiyaz Yunus Pathan

Selective virtualization of resources is provided, where the resources may be intercepted and services or the resources may be intercepted and redirected. Virtualization logic monitors for one or more activities that are performed in connection with one or more resources and conducted during processing of an object within the virtual machine. The first virtualization logic further selectively virtualizes resources associated with the one or more activities that are initiated during the processing of the object within the virtual machine by at least redirecting a first request of a plurality of requests to a different resource than requesting by a monitored activity of the one or more activities.

Selective virtualization for security threat detection

A computerized method for analyzing an object is disclosed. The computerized method includes obtaining, by a cybersecurity system, an object and context information generated during a first malware analysis of the object conducted prior to obtaining the object. Thereafter, the cybersecurity system performs a second malware analysis of the object to determine a verdict indicating maliciousness of the object. The scrutiny of the second malware analysis is adjusted based, at least in part, the context information, which may include (i) activating additional or different monitors, (ii) adjusting thresholds for determining maliciousness, or (iii) applying a modified rule set during the second malware analysis based on the context information.

Multi-vector malware detection data sharing system for improved detection

A system for protecting public cloud-hosted virtual resources features cloud visibility logic. According to one embodiment, the cloud visibility logic includes credential evaluation logic, data collection logic, correlation logic, and reporting logic. The credential evaluation logic is configured to gain authorized access to a cloud account within a first public cloud network. The data collection logic is configured to retrieve account data from the cloud account, while the correlation logic is configured to conduct analytics on the account data to determine whether the cloud account is subject to a cybersecurity threat or misconfiguration. The reporting logic is configured to generate an alert when the cloud account is determined by the correlation logic to be subject to the cybersecurity threat or misconfiguration.

System and method for retrieval and analysis of operational data from customer, cloud-hosted virtual resources

A computerized method for analyzing an object is disclosed. The computerized method includes performing, by a first cybersecurity system, a first malware analysis of the object, wherein a first context information is generated by the first cybersecurity system based on the first malware analysis. The first context information includes at least origination information of the object. Additionally, a second cybersecurity system, obtains the object and the first context information and performs a second malware analysis of the object to determine a verdict indicating maliciousness of the object. The second malware analysis is based at least in part on the first context information. The second cybersecurity system generates and issues a report based on the second malware analysis, the report including the verdict.

One embodiment of the described invention is directed to a computerized method for improving detection of cybersecurity threats initiated by a script. Herein, the method is configured to analyze the script provided as part of a script object by at least (i) determining whether any functional code blocks forming the script include a critical code statement, (ii) determining whether any of the functional code blocks include an evasive code statement, (iii) modifying the script to control processing of a subset of the functional code blocks by avoiding an execution code path including the evasive code statement and processing functional code blocks forming a code path including the critical code statement, and (iv) executing of the modified script and monitoring behaviors of a virtual environment. Thereafter, the method is configured to determine whether the script including cybersecurity threats based on the monitored behaviors.

System and method for circumventing evasive code for cyberthreat detection

A system for protecting public cloud-hosted virtual resources features cloud visibility logic. According to one embodiment, the cloud visibility logic includes credential evaluation logic, data collection logic, correlation logic and reporting logic. The credential evaluation logic is configured to gain authorized access to a cloud account within a first public cloud network. The data collection logic is configured to retrieve account data from the cloud account, while the correlation logic is configured to conduct analytics on the account data to determine whether the cloud account is subject to a cybersecurity threat or misconfiguration. The reporting logic is configured to generate an alert when the cloud account is determined by the correlation logic to be subject to the cybersecurity threat or misconfiguration.

According to one embodiment, a computerized method features monitoring behaviors of an object during processing within a guest system of a virtual machine. Within a guest system, a rule-based analysis of data associated with the monitored behaviors is conducted. The rule-based analysis includes prioritizing data associated with the monitored behaviors that correspond to an exception, and thereafter, storing the data associated with the monitored behaviors that correspond to the exception into a prescribed area of a virtual image file. The prescribed area is accessible by (i) logic within the guest system and (ii) logic within a host system of the virtual machine.

Data extraction system for malware analysis

For one embodiment, a computerized method for detecting exploit attacks on an interpreter comprises configuring a virtual machine including a user mode and a kernel mode and processing an object by an application operating in the user mode of the virtual machine. Responsive to the processing of the object, detecting a loading of an interpreter. Furthermore, responsive to the loading of the interpreter, inserting one or more intercept points for detecting one or more types of software calls from the interpreter or for detecting a certain type or certain types of activities occurring within the interpreter. Thereafter, an exploit attack is detected as being conducted by the object in response to the interpreter invoking a software call that corresponds to the one or more types of software calls that is considered anomalous when invoked by the interpreter or an anomalous activity being conducted within the interpreter.

System and method for detecting interpreter-based exploit attacks

A system and method for automatically analyzing an object for malware is described. Operating one or more virtual machines, the system and method provide an analysis environment variation framework to provide a more robust analysis of an object for malware. The multi-application, multi-plugin processing framework is configured within a virtual machine, where the framework for configuring a plurality of processes for analyzing the object for malware and each of plurality of processes is configured with a different application and plug-in combination selected based in part on a type of object being analyzed and operating concurrently with each other.

Launcher for setting analysis environment variations for malware detection

According to one embodiment, a malware detection system is integrated with at least a static analysis engine and a dynamic analysis engine. The static analysis engine is configured to automatically determine an object type of a received object. The dynamic analysis engine is configured to automatically launch the object after selecting an action profile based on the object type. The dynamic analysis engine is further configured to, provide simulated user interaction to the object based on the selected action profile either in response to detecting a request for human interaction or as a result of a lapse of time since a previous simulated human interaction was provided.

Intelligent context aware user interaction for malware detection

According to one embodiment, a computerized method comprises processing one or more objects by a first thread of execution that are part of a multi-thread process, monitoring events that occur during the processing of the one or more objects by the first thread, and storing information associated with the monitored events within an event log. The stored information comprises at least an identifier of the first thread to maintain an association between the monitored events and the first thread. Subsequently, the stored information within the event log is accessed for rendering a graphical display of the monitored events detected during processing of the one or more objects by the first thread on a display screen.

System and method for malware analysis using thread-level event monitoring

A computerized method to identify malicious code generated by seemingly benign objects is described. The generated malware detection system described identifies generated objects (code) and analyzes each generated object to collect features which may be associated with maliciousness. The analysis may determine if an Abstract Syntax Tree (AST) representation of the generated object is correlated with known malware ASTs. Correlation of the features identified during processing of the generated objects, including the sequences of generated object, may be used in classifying the object as malicious. The malware detection system may communicate with the one or more endpoint devices to influence detection and reporting of behaviors and malware by those device(s).

Enhanced malware detection for generated objects

A method for updating a virtual machine disk snapshot for use in instantiating one or more virtual guest instances for malware detection is described. The method features (i) detecting a guest image update package that includes information for updating one or more software components included as part of the virtual machine disk snapshot, and (ii) determining whether the guest image update package is currently contained in a contiguous storage area that is part of the virtual machine disk snapshot. Responsive to determining that the guest image update package is more recent than content currently contained in the contiguous storage area, the guest image update package is inserted into the contiguous storage area that is part of the virtual machine disk snapshot to generate a revised virtual machine disk snapshot that includes the one or more updated software components.

Adaptive virtual machine snapshot update framework for malware behavioral analysis

A computerized system and method is described for classifying objects as malicious by processing the objects in a virtual environment and monitoring behaviors during processing by one or more monitors, where the monitoring is conducted in an electronic device that is different than the electronic device within which an analysis of attributes of the objects is conducted beforehand. The monitors may monitor and record selected sets of process operations and capture associated process parameters, which describe the context in which the process operations were performed. By recording the context of process operations, the system and method described herein improves the intelligence of classifications and consequently reduces the likelihood of incorrectly identifying objects as malware or vice versa.

Growing community of inventors

Sunnyvale, CA, United States of America

Sushant Paithane