Autonomous robots are controlled using physical information acquired by various sensors. The sensors are susceptible to physical attacks, which tamper with the observed values and interfere with control of the autonomous robots. Recently, sensor spoofing attacks targeting subsequent algorithms which use sensor data have become large threats. In this paper, we introduce a new attack against the LiDAR-based simultaneous localization and mapping (SLAM) algorithm. The attack uses an adversarial LiDAR scan to fool a pose graph and a generated map. The adversary calculates a falsification amount for deceiving pose estimation and physically injects the spoofed distance against LiDAR. The falsification amount is calculated by gradient method against a cost function of the scan matching algorithm. The SLAM algorithm generates the wrong map from the deceived movement path estimated by scan matching. We evaluated our attack on two typical scan matching algorithms, iterative closest point (ICP) and normal distribution transform (NDT). Our experimental results show that SLAM can be fooled by tampering with the scan. Simple odometry sensor fusion is not a sufficient countermeasure. We argue that it is important to detect or prevent tampering with LiDAR scans and to notice inconsistencies in sensors caused by physical attacks.