Fireeye, Inc.

Fireeye Security Holdings US LLC

Sun Microsystems, Inc.

Muhammad Amin

Ashar Aziz

Osman Abdoul Ismael

Jayaraman Manni

Yasir Khalid

Shrikrishna Karandikar

Zheng Bu

Emmanuel Thioux

Michael Vincent

Henry Uyeno

Shivani Deshpande

Ramaswamy Ramaswamy

Madhusudan Challa

Samuel Yie

Masood Mehmood

Fengmin Gong

Darien Kindlund

Stuart Staniford

Muhammad Rizwan

Emily Jing

Upendran Loganathan

Adrian Drzewiecki

Ramesh Radhakrishnan

Alex Pilipenko

Bahman Mahbod

Abhishek Singh

Jay Manni

Alex Pilpenko

Mohan Samuelraj

A system and method are disclosed for network-based file analysis for malware detection. Network content is received from a network tap. A binary packet is identified in the network content. A binary file, including the binary packet, is extracted from the network content. It is determined whether the extracted binary file is detected to be malware.

Network-based binary file extraction and analysis for malware detection

Techniques for efficient malicious content detection in plural versions of a software application are described. According to one embodiment, the computerized method includes installing a plurality of different versions of a software application concurrently within a virtual machine and selecting a subset of the plurality of versions of the software application that are concurrently installed within the virtual machine. Next, one or more software application versions of the subset of the plurality of versions of the software application are processed to access a potentially malicious content suspect within the virtual machine, without switching to another virtual machine. The behaviors of the potentially malicious content suspect during processing by the one or more software application versions are monitored to detect behaviors associated with a malicious attack. Thereafter, information associated with the detected behaviors pertaining to a malicious attack is stored, and an alert with respect to the malicious attack is issued.

Multi-version application support and registration within a single operating system environment

Malicious network content is identified based on the behavior of one or more virtual environment components which process network content in a virtual environment. Network content can be monitored and analyzed using a set of heuristics. The heuristics identify suspicious network content communicated over a network. The suspicious network content can further be analyzed in a virtual environment that includes one or more virtual environment components. Each virtual environment component is configured to mimic live environment components, for example a browser application component or an operating system component. The suspicious network content is replayed in the virtual environment using one or more of the virtual environment components. The virtual environment component behavior is analyzed in view of an expected behavior to identify malicious network content. The malicious network content is then identified and processed.

System and method for detecting malicious network content using virtual environment components

According to one embodiment, a threat detection system comprising an intrusion protection system (IPS) logic, a virtual execution logic and a reporting logic is shown. The IPS logic is configured to receive a first plurality of objects and analyze the first plurality of objects to identify a second plurality of objects as potential exploits, the second plurality of objects being a subset of the first plurality of objects and being lesser or equal in number to the first plurality of objects. The virtual execution logic including at least one virtual machine configured to process content within each of the second plurality of objects and monitor for anomalous behaviors during the processing that are indicative of exploits to classify that a first subset of the second plurality of objects includes one or more verified exploits. The reporting logic configured to provide a display of exploit information associated with the one or more verified exploits.

System, apparatus and method for automatically verifying exploits within suspect objects and highlighting the display information associated with the verified exploits

According to one embodiment, a system features a network security device and a cloud computing service. The network security device is configured to determine whether an object includes one or more characteristics associated with a malicious attack. The cloud computing service, communicatively coupled to and remotely located from the network security device, includes virtual execution logic that, upon execution by a processing unit deployed as part of the cloud computing service and after the network security device determining that the object includes the one or more characteristics associated with the malicious attack, processes the object and monitors for behaviors of at least the object suggesting the object is associated with a malicious attack.

System and method for offloading packet processing and static analysis operations

Techniques for detecting malicious content using simulated user interactions are described herein. In one embodiment, a monitoring module monitors activities of a malicious content suspect executed within a sandboxed operating environment. In response to detection of a predetermined event triggered by the malicious content suspect requesting a user action on a graphical user interface (GUI) presented by the malicious content suspect, simulating, a user interaction module simulates a user interaction with the GUI without user intervention. An analysis module analyzes activities of the malicious content suspect in response to the simulated user interaction to determine whether the malicious content suspect should be declared as malicious.

Malicious content analysis using simulated user interaction without user involvement

System and method for separated packet processing and static analysis

Systems and methods for detecting malicious content are provided. In an exemplary embodiment, a method for detecting malicious content is described that detects when a client device has access to a remote network server of a communication network. The client device includes one or more processors. Thereafter, a controller being a device separate from the client device, activates one or more security programs within the remote network server. The security programs enable the controller to analyze data stored within or transmitted from the remote network server. Lastly, the controller analyzing the data to determine whether the data includes malware.

Method for detecting malware within network content

A network device for detecting malware is described. The network device features a memory storage device and a controller. The controller operating in cooperation with one or more virtual machines that are based on software modules stored within the memory storage device. The controller is configured to (i) monitor behaviors of at least a first virtual machine of the one or more virtual machines processing data received over a network, (ii) identify at least one anomalous behavior that includes either a communication anomaly or an execution anomaly, and (iii) detect, based on the identified at least one anomalous behavior, a presence of malware in the first virtual machine in response to identifying the at least one anomalous behavior.

System and method for analysis of a memory dump associated with a potentially malicious content suspect

Malicious content analysis with multi-version application support within single operating environment

Phishing detection techniques for predicting a password for decrypting an attachment for the purpose of malicious content detection are described herein. According to one embodiment, in response to a communication message, as such an electronic mail (email) message having an encrypted attachment, content of the communication message is parsed to predict a password based on a pattern of the content. The encrypted attachment is then decrypted using the predicted password to generate a decrypted attachment. Thereafter, a malicious content analysis is performed on the decrypted attachment to determine a likelihood as to whether the decrypted attachment contains malicious content.

System and method for detecting phishing using password prediction

In an embodiment, a system, device and method for detecting a malicious attack is described. Herein, the system includes a security network device that conducts an analysis on received network traffic to detect a suspicious object associated with the network traffic and determine an identifier associated with a source of the suspicious object. Information associated with the suspicious object and/or ancillary data, including information that identifies a return path for analysis results to a customer, are uploaded to a detection cloud. The detection cloud includes provisioning logic and one or more virtual machines that are provisioned by the provisioning logic in accordance with at least a portion of the ancillary data. The provisioning logic to customize functionality of the detection cloud for a specific customer.

System, device and method for detecting a malicious attack based on direct communications between remotely hosted virtual machines and malicious web servers

According to one embodiment, a system features analysis circuitry and detection circuitry. The analysis circuitry features a first processing unit and a first memory that includes a filtering logic configured to produce a second plurality of objects from a received first plurality of objects. The second plurality of objects is a subset of the first plurality of objects. The detection circuitry is communicatively coupled to and remotely located from the analysis circuitry. The detection circuitry includes a second processing unit and a second memory. The second memory includes a virtual execution logic to process content within at least a first object of the second plurality of objects. The virtual execution logic is configured to monitor for behaviors, during the processing of the first object, and determine whether any or all of the monitored behaviors correspond to activities indicative that the first object is associated with a malicious attack.

Growing community of inventors

Fremont, CA, United States of America

Muhammad Amin