<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Something that makes Ginp special is that all of its overlay screens for banking apps are consist of multiple steps , first stealing the victim ’ s login credentials , then stealing the credit card details ( to “ validate ” the user identity ) , as shown in the screenshots hereafter : The following code snippet shows that after the second overlay is filled-in and validated , it disappears and the targeted application is added to the list of packages names to be ignored for future overlays attacks .' [/INST] [Something:O, that:O, makes:O, Ginp:B-Malware, special:O, is:O, that:O, all:O, of:O, its:O, overlay:O, screens:O, for:O, banking:O, apps:O, are:O, consist:O, of:O, multiple:O, steps:O, ,:O, first:O, stealing:O, the:O, victim:O, ’:O, s:O, login:O, credentials:O, ,:O, then:O, stealing:O, the:O, credit:O, card:O, details:O, (:O, to:O, “:O, validate:O, ”:O, the:O, user:O, identity:O, ):O, ,:O, as:O, shown:O, in:O, the:O, screenshots:O, hereafter:O, ::O, The:O, following:O, code:O, snippet:O, shows:O, that:O, after:O, the:O, second:O, overlay:O, is:O, filled-in:O, and:O, validated:O, ,:O, it:O, disappears:O, and:O, the:O, targeted:O, application:O, is:O, added:O, to:O, the:O, list:O, of:O, packages:O, names:O, to:O, be:O, ignored:O, for:O, future:O, overlays:O, attacks:O, .:O] </s>