Cisco Technology, Inc.

Carbon Black, Inc.

Confer Technologies, Inc.

Vmware, Inc.

Jeffrey Albin Kraemer

Philip J S Gladstone

Andrew Zawadowskiy

Ranganathan Gopalan

Alan Joseph Kirby

Mikhail Cherepov

Paul Matthew Drapeau

Boris Ruchansky

David James McCowan

Adam Karol Malinowski

Debra L Malver

Kerry Lynn

Venkat Raghavan Rangamani

Brian F Costello

Sanket Choksey

Dan L Grecu

A security engine may use event-stream processing and behavioral techniques to detect ransomware. The engine may detect process behavior associated with encrypting a file, encrypting a storage device, or disabling a backup file, and may assign a ransomware category to the process based thereon. The engine may initiate protection actions to protect system resources from the process, which may continue to execute. The engine may monitor the process for specific behavior corresponding to its ransomware category. Based on the extent to which such specific behavior is detected, the engine may determine that the process is not ransomware, assign a ransomware subcategory to the process, or adjust the process's threat score. Monitoring of the process may continue, and the threat score may be updated based on the process's behavior. If the threat score exceeds a threshold corresponding to the ransomware category (or subcategory), a corresponding policy action may be initiated.

Methods for behavioral detection and prevention of cyberattacks, and related apparatus and techniques

The present system and method pertain to the detection of malicious software and processes such as malware. A cloud security policy system receives hashes and behavioral information about applications and/or processes executing on user devices. The cloud security policy system records this information and then evaluates the trustworthiness of the hashes based on the information received from the user devices to provide a security policy for the applications and/or processes. The security policy is sent from the cloud security policy system to user devices to be applied by the user devices.

System and method for identifying and controlling polymorphic malware

A system and method for tracking data security threats within an organization is proposed. A threat aggregator process executing on an analysis computer system within the organization receives events indicating possible threats observed by and sent from different user devices and aggregates related events into threats. This enables the threats to be analyzed and acted upon at a level of the organization (e.g., across user devices) rather than at the level of the individual user devices. An endpoint telemetry system analyzes threats sent from the aggregator and provides security policies for responding to the threats. In examples, the system can identify attacks of related threats and act upon the related threats of the attack collectively, and can characterize false positive threats sent from multiple user devices as a single extraneous threat. This has advantages over the per-user device focus for responding to threats provided by current systems and methods.

Multi-host threat tracking

A distributed security system and method are disclosed that enable access to known threat events from threat intelligence feeds when the system includes public cloud components. A cloud-based security policy system stores observable events for security incidents detected by and sent from user devices within an enterprise network. The observable events include observable indicators for characterizing the observable events. The threat events within the feeds include threat indicators for characterizing the threat events. An on-premises connector within the enterprise network downloads the observable indicators from the security policy system and the threat indicators from the feeds. In response to determining that any observable indicators match any threat indicators, the on-premises connector provides access to the threat events and/or the observable events having the matching indicators. In one example, the on-premises connector generates opaque query strings for users on user devices to access the threat events/observable events having the matching indicators.

Using private threat intelligence in public cloud

A method and system for remediating a process hollowing intrusion on a user device comprising detecting a process starting on the user device, preparing the process to monitor Application Programming Interface (API) calls between the process and an operating system of the user device, determining whether the process is associated with a process hollowing intrusion based on information associated with the process and/or the API calls, and executing security policies against the process associated with the process hollowing intrusion. In examples, it is determined whether the child process is associated with a process hollowing intrusion in response to determining whether one or more API calls associated with known process hollowing intrusions modify executable memory of and/or modify an entry point address of the child process.

System and method for process hollowing detection

A system and method for detecting reverse command shell intrusions at a process-level on a user device is disclosed. In one embodiment, the system detects each process starting on an operating system of the user device, such as a mobile phone or laptop computer, and monitors Application Programming Interface (API) calls between each process and the operating system. The system then determines whether each process is associated with a reverse command shell intrusion based on information associated with each process and/or the API calls, and executes security policies against the processes associated with the reverse command shell intrusion to remediate the processes. In another embodiment, the system determines whether processes starting on a user device are associated with a reverse command shell intrusion by monitoring and analyzing information associated with the parent process of each process and/or API calls between each parent process and the operating system.

System and method for reverse command shell detection

Learned behavior based security

Security policy deployment and enforcement system for the detection and control of polymorphic and targeted malware

A system receives information from at least one security interceptor associated with at least one computer system. The information identifies details associated with a traffic flow in a computer system of the computer networking environment. The system determines a probability that an attack on the computer system is in progress based on a probabilistic link provided by the information. The probabilistic link is determined by attack information associated with previous attacks. Based on the information provided by the at least one security interceptor, the system generates a signature utilized to prevent a similar attack on the computer system.

Methods and apparatus providing computer and network security utilizing probabilistic signature generation

The present system and method pertain to the detection of malicious software and processes such as malware. A cloud security policy system receives hashes and behavioral information about applications and/or process executing on user devices. The cloud security policy system records this information and then evaluates the trustworthiness of the hashes based on the information received from the user devices to provide a security policy for the applications and/or processes. The security policy is sent from the cloud security policy system to user devices to be applied by the user devices.

Growing community of inventors

Wellesley, MA, United States of America

Jeffrey Albin Kraemer