Many site rating vendors (i.e. McAfee SiteAdvisor, WOT, Google's Safe Browsing, Symantec WS.Reputation.1, Webutation, avast! Online Security Plugin (formerly WebRep), etc) use a system of volunteer testers that continually patrol the Internet to browse sites, download files, and submit information. All the results are documented and supplemented with feedback from users, Web site owners, and analysis from their own employees. The advising site vendor then summarizes the results typically into into a color-coded red, yellow and green ratings scale to help inform Web users as to the safety of each tested site. While these tools are useful, they are not foolproof and sometimes may provide misleading ratings. Just because you visit a risky site, that does not automatically mean the site is bad or that your system has been infected by going there. In contrast, going to a safe site could even prompt a warning. There are legitimate programs which are falsely detected by various anti-virus programs from time to time. This sometimes results in an inaccurate site rating/warning of potentially dangerous software when that is not the case. Thus, the use of such rating sites does not always guarantee an accurate rating of the results they provide
. Further, for the novice user, rating sites can provide a a false sense of security
WS.Reputation.1 is a detection for files that have a low reputation score based on analyzing data from Symantecs community of users and therefore are likely to be security risks. Detections of this type are based on Symantecs reputation-based security technology. Because this detection is based on a reputation score, it does not represent a specific class of threat like adware or spyware, but instead applies to all threat categories.
The reputation-based system uses "the wisdom of crowds" (Symantecs tens of millions of end users) connected to cloud-based intelligence to compute a reputation score for an application, and in the process identify malicious software in an entirely new way beyond traditional signatures and behavior-based detection techniques.