Benford's law shows the pattern of behavior in normal systems. It states that in natural systems digits' frequency have a certain pattern such that the occurrence of first digits in numbers are unevenly distributed. In systems with natural behavior, numbers begin with a '1' are more common than numbers beginning with '9'. It implies that if the distribution of first digits deviate from the expected distribution, it is indicative of fraud. It has many applications in forensic accounting, stock markets, finding abnormal data in survey data, and natural science. We investigate whether social media bots and Information Operations activities are conformant to the Benford's law. Our results showed that bots' behavior adhere to Benford's law, suggesting that using this law helps in detecting malicious online automated accounts and their activities on social media. However, activities related to Information Operations did not show consistency in regards to Benford's law. Our findings shedlight on the importance of examining regular and anomalous online behavior to avoid malicious and contaminated content on social media.