This is started to just get sad.
Prior to receiving notice from Gizmodo this morning, Kris Kobach’s office was leaking sensitive information belonging to thousands of state employees, including himself and nearly every member of the Kansas state legislature.
Among a bevy of personal information that, according to a statement on the website, was intended to be public, the Kansas Secretary of State’s website was exposing the last four digits of Social Security numbers (known as SSN4) of thousands of current and former candidates for office, as well as thousands, or potentially tens of thousands, of high-ranking state employees at apparently ever Kansas government agency.
The combination of a person’s name and SSN4 creates what’s commonly called “personally identifiable information,” the unauthorized disclosure of which is unlawful under numerous state and federal laws. Putting these statements of substantial interest online without redacting the SSN4 information is beyond reckless; it’s stupid.,,,
Kobach’s office has spent the past few weeks trying to convince the Kansas legislature that it is, in fact, equipped to handle voluminous amounts of sensitive voter records. The interstate Crosscheck program, which is overseen by Kobach’s office, has lost control over voter data—including partial Social Security numbers—on several occasion over the past six months. Most recently, nearly 1000 Kansans were exposed after data amassed for the Crosscheck program was mistakenly leaked in Florida.
Kobach is a notorious exaggerator and recently claimed that the Crosscheck program is absolutely essential to the safeguarding the integrity of the nation’s voter rolls. “If the Crosscheck program were to go away, then we would be unable to catch virtually all of the double voters,” he told the Wichita Eagle, adding: “there are thousands of them across the country.” But truthfully, there are other programs that serve the same purpose, such as the one administered by the Electronic Registration Information Center, which hasn’t suffered any apparent data leaks and is based on a methodology founded by actual data scientists.