Public procurement is highly susceptible to corruption, especially in developing countries. Although open auctions are widely adopted to curb it, this paper finds that corruption remains prevalent even within this procurement format. Procurement officers can collaborate with firms to manipulate scoring rules, ensuring predetermined winners, while corrupt firms submit noncompetitive bids to meet minimum bidder requirements. Using extensive data from Chinese public procurement auctions, the paper introduces model-driven statistical tools to detect such corruption, identifying a corruption rate of 65 percent. A procurement expert audit survey confirms the tools’ reliability, with a 91 percent probability that experts recognize suspicious scoring rules when flagged. Firm-level analysis reveals that local, state-owned, and less productive firms are favored in corrupt auctions. Lastly, the paper explores policy implications. Analysis of the national anti-corruption campaign since 2012 suggests that general investigations may be insufficient to address deeply ingrained corrupt practices. Using counterfactuals based on an estimated structural model, the paper shows that implementing anonymous call-for-tender evaluations could improve social welfare by 10 percent by eliminating suspicious rules and encouraging broader participation.