Once upon a time, one infection by specific malware looked much like another infection, to an antivirus scanner if not to the naked eye. Even back then, virus naming wasn't very consistent between vendors, but at least virus encyclopaedias and third-party resources like vgrep made it generally straightforward to map one vendor's name for a virus to another vendor's name for the same malware.

In 2009, though, the threat landscape looks very different. Viruses and other replicative malware, while far from extinct, pose a comparatively manageable problem compared to other threats with the single common characteristic of malicious intent. Proof-of-Concept code with sophisticated self-replicating mechanisms is of less interest to today's malware authors than shape-shifting Trojans that change their appearance frequently to evade detection and are intended to make money for criminals rather than getting adolescent admiration and bragging rights.

Detection techniques such as generic signatures, heuristics and sandboxing have changed the ways in which malware is detected and therefore how it is classified, confounding the old assumptions of a simple one-to-one relationship between a detection label and a malicious program. This presentation will explain how one-to-many, many-to-one, or many-to-many models are at least as likely as the old one-detection-per-variant model, why "Do you detect Win32/UnpleasantVirus.EG?" is such a difficult question to answer, and explain why exact indication is not a pre-requisite for detection and remediation of malware, and actually militates against the most effective use of analysis and development time and resources. But what is the information that the end-user or end-site really needs to know about an incoming threat?