It’s all so easy with Photoshop. With imaging software so widely available, the manipulation of digital images is not anymore a matter for experts only. While there is little harm besides gossip in retouching an unwanted belly or an incipient baldness, the simplicity of counterfeiting is a serious issue when it is exploited to convey social, political or military messages. It is not surprising, then, that restoring the credibility of digital content has become a task of paramount importance. Digital Image Forensics is a science allowing to gather information on the history of an image in such a way that its veracity can be evaluated, based on the principle that any manipulation leaves more or less subtle traces. We contribute to the image forensics’ mission by addressing three open issues. First, we analyse the history of groups of near-duplicate images to reveal their parent-child relationships, thus opening new scenarios for copyright enforcement, news tracking or clustering. Secondly, we make possible the cooperation of heterogeneous image forensic detectors by fusing their decision scores in such a way to deal with uncertainty, incompatibility and noise typically affecting the analysis. Finally, we study strengths and weaknesses of the forensic algorithms based the Scale Invariant Feature Transform; we devise new attacks bypassing the forensic analysis and we discuss possible counter-measures.