MA: Scoring Modules

Document created by RSA Information Design and Development on Nov 23, 2016Last modified by RSA Information Design and Development on Nov 29, 2016
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RSA Security Analytics Malware Analysis analyzes and scores sessions and the embedded files within these sessions by scoring four categories: Network, Static Analysis, Community, and Sandbox. Each category comprises many individual rules and checks that are used to calculate a score between 1-100. The higher the score, the more likely the session is to be malicious and worthy of more in-depth follow-on investigation.

Security Analytics Malware Analysis can facilitate a historical investigation into events leading up to a network alarm or incident. If you know that a certain type of activity is taking place on your network, you can select only the reports of interest to examine the content of data collections. You can also modify behavior for each scoring category based on the scoring category or the file type (Windows PE, PDF, and Microsoft Office).

Once you become familiar with data navigation methods, you can explore the data more completely through:

  • Searching for specific types of information
  • Reviewing specific content in detail.

Category scores for Network, Static Analysis, Community, and Sandbox are maintained and reported independently. When events are viewed based on the independent scores, as long as one category detects malware, it is evident in the Analysis section.

Network

The first category examines each Security Analytics Core core network session to determine if the delivery of the malware candidates was suspicious. For example, benign software being downloaded from a well-known safe site, using proper ports and protocols, is considered less suspicious than downloading software known to be malicious from a known dubious download site. Sample factors used in the scoring of this criteria set may include sessions that:

  • Contain threat feed information
  • Connect to well-known bad sites
  • Connect to high-risk domains/countries (for example, .cc domain)
  • Use well-known protocols on non-standard ports
  • Contain obfuscated JavaScript

Static Analysis

The second category analyzes each file in the session for signs of obfuscation in order to predict the likelihood of the file behaving maliciously if allowed to run. For example, software that links to networking libraries is more likely to perform suspicious network activity. Sample factors used in the scoring of this criteria set may include:

  • Files found to be XOR encoded
  • Files found embedded within non-EXE formats (for example, PE file found embedded in a GIF format)
  • Files linking to higher risk import libraries
  • Files highly deviating from the PE Format

Community

The third category scores the session and files based on the collective knowledge of the security community. For example, files whose fingerprint/hash is already known to be good or bad by respected anti-virus (AV) vendors is scored accordingly. Files are also scored based on knowledge that a file was delivered from a site known to be good or bad by the security community.

Community scoring also indicates whether the AV on your network flagged the files as malicious. It does not indicate that the resident AV product acted to protect your system.

Sandbox

The fourth category examines the behavior of the software by actually running it in a sandbox environment. By running the software to watch its behavior, a score can be calculated by identifying well-known malicious activity. For example, software that configures itself to autostart on each reboot and make IRC connections would score higher than a file with no known bad behavior.

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