Abstract: A method and apparatus for providing IP address filtering. The method identifies one or more suspicious Uniform Resource Locators (URLs) and resolves the one or more suspicious URLs to one or more suspicious IP addresses. A suspicious IP address list is created containing the one or more suspicious IP addresses. The suspicious IP address list may be used to facilitate a security response to filter one or more of the IP addresses in the suspicious IP address list.

Abstract: A method for controlling access to process data includes encrypting process data of a process; receiving a request to access the process data; requesting a security code to access the encrypted process data; receiving the security code; authenticating the received security code; and granting access to the encrypted process data if the received security code is successfully authenticated and denying access to the encrypted process data if the received security code is not successfully authenticated.

Abstract: Systems and methods for archive scanning are provided herein. In some embodiments, a method includes: selecting an archive; reading a metadata representing a plurality of files within the archive; reading a plurality of hash strings from the archive; comparing the plurality of hash strings with a database of hash strings; and determining, based on the comparing, if the plurality of files within the archive represent a security threat based on the plurality of hash strings.

Abstract: Systems and methods for malware filtering are provided herein. In some embodiments, a system having one or more processors is configured to: retrieve a file downloaded to a user device; break the downloaded file into a plurality of chunks; scan the plurality of chunks to identify potentially malicious chunks; predict whether the downloaded file is malicious based on the scan of the plurality of chunks; and determine whether the downloaded file is malicious based on the prediction.

Abstract: In an embodiment, systems and methods for detecting malware are provided. A server trains a static malware model and a dynamic malware model to detect malware in files. The models are distributed to a plurality of user devices for use by antimalware software executing on the user devices. When a user device receives a file, the static malware model is used to determine whether the file contains malware. If the static malware model is unable to make the determination, when the file is later executed, the dynamic malware model is used to determine whether the file contains malware. The file along with the determination made by the dynamic malware model are then provided to the server. The server then retrains the static malware model using the received files and the received determinations. The server then distributes the updated static malware model to each of the devices.

Abstract: Systems and methods for malware filtering are provided herein. In some embodiments, a system having one or more processors is configured to: retrieve a file downloaded to a user device; break the downloaded file into a plurality of chunks; scan the plurality of chunks to identify potentially malicious chunks; predict whether the downloaded file is malicious based on the scan of the plurality of chunks; and determine whether the downloaded file is malicious based on the prediction.