With the spread of mobile phones, through Wi-Fi and 3G communications, users have increased opportunities to retrieve messages and files posted by others while on the move, e.g. walking in the Mall, driving the car, etc. For safety, messages are often encrypted and the source is authenticated via PKI, preventing repudiation. Yet, at times the mobile may issue a message that is not accurate either innocently or maliciously. For example, the driver may report rocks on the pavement when there are crossing animals. Or he may maliciously report heavy traffic ahead to get other vehicles out of his way. The credibility of mobile report can be judged using a social network where the member is ranked by his friends. In this paper we review the construction of a trust graph in a social network like Facebook. We review popular ways of establishing the credibility of mobile user reports applying “transitivity” on single paths computed on the trust graph. We then argue for the importance of exploiting multiple paths in order to detect more subtle attacks not revealed by single paths. The methods are illustrated on artificial social trust networks (offering easily tunable parameters) and are then validated on real social network data.