Precise Compositional Buffer Overflow Detection via Heap Disjointness

Static analysis techniques for buffer overflow detection still struggle with being scalable for millions of lines of code, while being precise enough to have an acceptable false positive rate. The checking of buffer overflow necessitates reasoning about the heap reachability and numerical relations, which are mutually dependent. Existing techniques to resolve the dependency cycle either sacrifice precision or efficiency due to their limitations in reasoning about symbolic heap location, i.e., heap location with possibly symbolic numerical offsets. A symbolic heap location potentially aliases a large number of other heap locations, leading to a disjunction of heap states that is particularly challenging to reason precisely. Acknowledging the inherent difficulties in heap and numerical reasoning, we introduce a disjointness assumption into the analysis by shrinking the program state space so that all the symbolic locations involved in memory accesses are disjoint from each other. The disjointness property permits strong updates to be performed at symbolic heap locations, significantly improving the precision by incorporating numerical information in heap reasoning. Also, it aids in the design of a compositional analysis to boost scalability, where compact and precise function summaries are efficiently generated and reused. We implement the idea in the static buffer overflow detector Cod. When applying it to large, real-world software such as PHP and QEMU, we have uncovered 29 buffer overflow bugs with a false positive rate of 37%, while projects of millions of lines of code can be successfully analyzed within four hours. CCS Concepts • Software and its engineering → Software verification and validation.