The Integer-Overflow-to-Buffer-Overflow (IO2BO) vulnerability is an underrated source of security threats. Despite many works have been done to mitigate integer overflow, existing tools either report large number of false positives or introduce unacceptable time consumption. To address this problem, in this paper we present a new static analysis framework. It first utilizes inter-procedural dataflow analysis and taint analysis to accurately identify potential IO2BO vulnerabilities. Then it uses a light-weight method to further filter out false positives. Specifically, it generates constraints representing the conditions under which a potential IO2BO vulnerability can be triggered, and feeds the constraints to SMT solver to decide their satisfiability. We have implemented a prototype system LAID based on LLVM, and evaluated it on 228 programs of the NIST’s SAMATE Juliet test suite and 6 known IO2BO vulnerabilities in real world. The experiment results show that our system can effectively and efficiently detect all known IO2BO vulnerabilities.