My thoughts are not likely to be terribly reassuring...
People lie (sometimes unwittingly). We spend a great deal of time talking about sampling error, but we often forget to discuss all of the other types of error that affect surveys. There is considerable evidence that self-report is subject to recall bias, mis-interpretation of the question, and (sometimes) outright fabrication. See, for example:
www.npr.org/.../mischievous-responders-confound-research-on-teensSo, it may be that the respondents mis-interpreted the question and recorded some income as "SSI" that isn't really SSI. It may be that the respondent fabricated an answer (income questions are notoriously touchy). It may be that those values were imputed.
It may also be that they're collecting more income than they "should," whether because of a mistake on the part of the government or because of fraud...
As for how to deal with it in your analysis... it depends on your purpose.
You could drop those cases, top-code those cases, or treat them differently in your sample.