OSINT

Taxonomies do not investigate campaigns by themselves A framework is a very respectable filing cabinet. DISARM, the Disinformation Analysis and Risk Management framework, gives analysts a standardized vocabulary for describing foreign information manipulation and interference, or FIMI. It organizes influence operations into tactics, techniques, and procedures. That is useful. It gives researchers, governments, platform teams, and security practitioners a shared language instead of a pile of screenshots, vibes, and mutually incompatible spreadsheets. ...

TL;DR for operators SEER is not a “sentiment detector for lies.” That would be wonderfully simple and operationally disastrous. It is a multimodal fake-news detection architecture that first tries to make images more semantically usable, then adds emotion as a probabilistic auxiliary signal rather than a moral verdict. The practical workflow is easy to understand: generate a caption for the image, align the text-image relationship using CLIP-style representations, fuse text, image, and caption features through attention, then use an expert emotional reasoning module to learn how emotional tone correlates with authenticity in the dataset. The paper reports accuracy of 0.929 on Weibo and 0.931 on Twitter, outperforming the tested baselines.1 ...