Risk-Based Vulnerability Management. Exploiting the economic nature of the attacker to build sound and measurable vulnerability mitigation strategies.

Vulnerability bulletins and feeds report hundreds of vulnerabilities a month that a system administrator or a Chief Information Officer working for an organisation has to take care of. Because of the load of work, vulnerability prioritisation is a must in any complex-enough organisation. Currently, the industry employs the Common Vulnerability Scoring System (CVSS in short) as a metric to prioritise vulnerability risk. However, the CVSS base score is a technical measure of severity, not of risk. By using a severity measure to estimate risk, current practices assume that every vulnerability is characterised by the same exploitation likelihood, and that vulnerability risk can be assessed through a technical analysis of the vulnerability. In this Thesis we argue that this is not the case, and that the economic forces that drive the attacker are a key factor in understanding vulnerability risk. In particular, we argue that attacker's rationality and the economic infrastructure supporting cybercrime's activities play a major role in determining which vulnerabilities will the attackers massively exploit, and therefore which vulnerabilities will represent a (substantially higher than the rest) risk. Our ultimate goal is to show that `risk-based' vulnerability management policies, as opposed to currently employed `criticality-based' ones, are possible and can outperform current practices in terms of patching efficiency without losing in effectiveness (i.e. reduction of risk in the wild). To this aim we perform an extensive data-collection work on vulnerabilities, proof-of-concept exploits, exploits traded in the cybercrime markets, and exploits detected in the wild. We further collaborated with Symantec to collect actual records of attacks in the wild delivered against about 1M machines worldwide. A good part of our data-collection efforts has been also dedicated in infiltrating and analysing the cybercrime markets. We used this data collection to evaluate four `running hypotheses' underlying our main thesis: vulnerability risk is influenced by the attacker's rationality (1), and the underground markets are credible sources of risk that provide technically proficient attack tools (2), are a mature (3) and sound (4) from an economic perspective. We then put this in practice and evaluate the effectiveness of criticality-based and risk-based vulnerability management policies (based on the aforementioned findings) in mitigating real attacks in the wild. We compare the policies in terms of the `risk reduction' they entail, i.e. the gap between `risk' addressed by the policy and residual risk. Our results show that risk-based policies entail a significantly higher risk reduction than criticality-based ones, and thwart the majority of risk in the wild by addressing only a small fraction of the patching work prescribed by current practices.