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Wednesday, December 18, 2013

Security Vulnerabilities of Legacy Code

An interesting research paper documents a "honeymoon effect" when it comes to software and vulnerabilities: attackers are more likely to find vulnerabilities in older and more familiar code. It's a few years old, but I haven't seen it before now. The paper is by Sandy Clark, Stefan Frei, Matt Blaze, and Jonathan Smith: "Familiarity Breeds Contempt: The Honeymoon Effect and the Role of Legacy Code in Zero-Day Vulnerabilities," Annual Computer Security Applications Conference 2010.
Abstract: Work on security vulnerabilities in software has primarily focused on three points in the software life-cycle: (1) finding and removing software defects, (2) patching or hardening software after vulnerabilities have been discovered, and (3) measuring the rate of vulnerability exploitation. This paper examines an earlier period in the software vulnerability life-cycle, starting from the release date of a version through to the disclosure of the fourth vulnerability, with a particular focus on the time from release until the very first disclosed vulnerability. Analysis of software vulnerability data, including up to a decade of data for several versions of the most popular operating systems, server applications and user applications (both open and closed source), shows that properties extrinsic to the software play a much greater role in the rate of vulnerability discovery than do intrinsic properties such as software quality. This leads us to the observation that (at least in the first phase of a product's existence), software vulnerabilities have different properties from software defects.
We show that the length of the period after the release of a software product (or version) and before the discovery of the first vulnerability (the 'Honeymoon' period) is primarily a function of familiarity with the system. In addition, we demonstrate that legacy code resulting from code re-use is a major contributor to both the rate of vulnerability discovery and the numbers of vulnerabilities found; this has significant implications for software engineering principles and practice.

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