ScanIt: An AI and Blockchain Powered Open-Source Framework for Content Authenticity

The explosive growth of generative AI has triggered a trust crisis in digital media. High-stakes errors, such as Deloitte Australia’s $290,000 refund caused by AI hallucinations and the accidental publishing of prompt text by major newspapers, illustrate the scale of the problem. A major limitation of existing detection tools is their “black box” design; users are forced to trust a verdict without understanding the logic behind it, nor do these tools verify factual accuracy. This paper presents ScanIt, a fully open-source framework that integrates multi-model AI detection with retrieval-augmented source verification and blockchain storage. The AI layer identifies synthetic text through a weighted consensus of three distinct models, while the source tracer checks claims against live web indices to catch hallucinations. By establishing a tamper-proof chain of custody for every analysis report, ScanIt generates the “transparent digital evidence” needed to resolve disputes over authorship and due diligence.