In software development, investigating the accessibility of dependency vulnerabilities is of great importance, as third-party libraries often contain known vulnerabilities that could be exploited in the application's business logic. The existing accessibility analysis methods encounter challenges such as undecidability, abstraction loss, and path explosion in large-scale programs, resulting in an inaccurate distinction between accessibility vulnerabilities and non-accessibility vulnerabilities. This paper introduces an approach called ConVReach for analyzing the reachability of vulnerabilities in dependencies in C/C++ programs. ConVReach overcomes the problems of high abstraction loss and potential path explosion in the current methods by combining static and dynamic approaches, particularly a constraint-guided analysis method. This approach extracts and decomposes the path constraints that trigger vulnerabilities, independently verifies the satisfiability of each constraint, and then aggregates the feasible paths. This effectively reduces unnecessary path exploration and avoids the common path explosion issues in traditional methods. Experimental results show that ConVReach outperforms existing tools in both accuracy and efficiency, effectively distinguishing between reachable and unreachable vulnerabilities, and significantly reducing false positives and false negatives. We constructed a benchmark dataset to evaluate ConVReach, which includes 53 CVEs and 347 flags artificially inserted into various open-source projects. This dataset was designed to simulate both real-world vulnerabilities and complex scenarios. Through testing on this dataset, ConVReach demonstrated exceptional performance. It successfully identified 59 out of 61 reachable vulnerabilities and all 23 unreachable ones in the CVE dataset. Within a 24-hour time budget, ConVReach detected above 50% more reachable vulnerabilities than the baseline tools in the first 6 hours and nearly completed the detection of reachable vulnerabilities by the 12-hour mark. These results highlight ConVReach's superior ability to handle both real-world vulnerabilities and challenging cases.
Feng et al. (Fri,) studied this question.