A Multi-leveled Approach for Detection of Coercive Malicious Documents Employing Optical Character Recognition
Authors of malicious documents often include a graphical asset used to lure the potential victim to 'enable editing' and to 'enable content' to activate the macro's embedded logic. While these graphical lures vary in theme, language, and content, they commonly have similar coercive text. Using...
