Microsoft Technology Licensing, LLC

Elliott Jeb Haber

Anthony Paul Penta

Ryan Charles Colvin

John Scarrow

Ameya S Bhatawdekar

Geoffrey John Hulten

Paul J Leach

Joshua T Goodman

Robert L Rounthwaite

Chris J Guzak

Jane T Kim

Kristofer Noel Iverson

Manav Mishra

Anshul Rawat

Warren G Stevens

Robert Alexander Sim

Daniel Oliver

Jeffrey Richard McKune

Shawn Domenic Loveland

Christian Seifert

Paul Stephen Rehfuss

Jess Holbrook

Roderic C Deyo

Sarah J Bowers

Chad W Mills

Tomasz Kasperkiewicz

Karanbir Singh

Gopalakrishnan Seshadrinathan

David Aaron Ward Snelling

Crispin Cowan

Ritika Virmani

Andy Davidson

Jay Dave

James Dooley

Xiang Tu

One or more techniques and/or systems are provided for file acquisition for reputation evaluation. A reputation service may be configured to evaluate files and provide reputations of such files to clients (e.g., an indication as to whether a file is safe or malicious). If the reputation service receives a reputation request for a file that is unknown to the reputation service (e.g., a file not yet fully acquired by the reputation service), then the reputation service may identify a set of chunks into which the file can be partitioned. The reputation service may obtain chunks from various clients, such as a first chunk from a first client and a second chunk from a second client. Such chunks may be evaluated to assign a reputation to the file. In this way, the reputation service may retrieve portions of a file in a distributed manner for reputation evaluation.

Chunk-based file acquisition and file reputation evaluation

A Web browser of a computing device downloads or otherwise obtains a file. File information identifying the file is obtained and is sent to a remote reputation service. Client information identifying aspects of the computing device can also optionally be sent to the remote reputation service. In response to the file information (and optionally client information), a reputation indication for the file is received from the remote reputation service. A user interface for the Web browser to present at the computing device is determined, based at least in part on the reputation indication, and presented at the computing device.

Reputation checking obtained files

Malware detection is often based on monitoring a local application binary and/or process, such as detecting patterns of malicious code, unusual local resource utilization, or suspicious application behavior. However, the volume of available software, variety of malware, and sophistication of evasion techniques may reduce the effectiveness of detection based on monitoring local resources. Presented herein are techniques for identifying malware based on the reputations of remote resources (e.g., web content, files, databases, IP addresses, services, and users) accessed by an application. Remote resource accesses may be reported to a reputation service, which may identify reputations of remote resources, and application reputations of applications that utilize such remote resources. These application reputations may be used to adjust the application policies of the applications executed by devices and servers. These techniques thereby achieve rapid detection and mitigation of newly identified malware through application telemetry in a predominantly automated manner.

Identifying application reputation based on resource accesses

A reputation based redirection service is usable to build URL wrappers for un-trusted and unknown URLs. Such URL wrappers can be used to protect Web users by, for example, redirecting traffic to interstitial Web pages. Additionally, reputation decisions can be made by the service to further protect users from malicious URLs.

Reputation based redirection service

The reputation of an executable computer program is checked when a user input to a computing device initiates a program launch, thus triggering a check of a local cache of reputation information. If the local cache confirms that the program is safe, it is permitted to launch, typically without notifying the user that a reputation check has been made. If the local cache cannot confirm the safety of the program, a reputation check is made by accessing a reputation service in the cloud. If the reputation service identifies the program as safe, it returns an indication to the computing device and the program is permitted to be launched, again without notifying the user that a reputation check has been made. If the reputation service identifies the program as unsafe or potentially unsafe, or does not recognize it at all, a warning is displayed to the user.

Reputation checking of executable programs

Described is a technology by which phishing-related data sources are processed into aggregated data and a given site evaluated the aggregated data using a predictive model to automatically determine whether the given site is likely to be a phishing site. The predictive model may be built using machine learning based on training data, e.g., including known phishing sites and/or known non-phishing sites. To determine whether an object corresponding to a site is likely a phishing-related object are described, various criteria are evaluated, including one or more features of the object when evaluated. The determination is output in some way, e.g., made available to a reputation service, used to block access to a site or warn a user before allowing access, and/or used to assist a hand grader in being more efficient in evaluating sites.

Finding phishing sites

Online risk mitigation techniques are described. In an implementation, a service is queried for a reputation associated with an object from an online source in response to selection of the object. A backup of a client that is to receive the object is stored prior to obtaining the object when the reputation does not meet a threshold reputation level.

Online risk mitigation

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Fall City, WA, United States of America

Elliott Jeb Haber