If trained correctly the model could easily reproduce any arbitrary image if you know its coordinate in the latent space (and you use deterministic sampler), regardless of whether the image is present in the dataset or not, it's also easy to imagine as the coordinates are as big as the samples generated by the diffusion model. You can take an image and use DDIM inversion to find the coordinates.