Datasets:

pritamdeka

/

dataset_cyner_valid_temp

like 0

<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: 'Riltok mobile Trojan : A banker with global reach 25 JUN 2019 Riltok is one of numerous families of mobile banking Trojans with standard ( for such malware ) functions and distribution methods .' [/INST] [Riltok:B-Malware, mobile:O, Trojan:O, ::O, A:O, banker:O, with:O, global:O, reach:O, 25:O, JUN:O, 2019:O, Riltok:B-Malware, is:O, one:O, of:O, numerous:O, families:O, of:O, mobile:O, banking:O, Trojans:O, with:O, standard:O, (:O, for:O, such:O, malware:O, ):O, functions:O, and:O, distribution:O, methods:O, .:O] </s>

<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: 'Originally intended to target the Russian audience , the banker was later adapted , with minimal modifications , for the European “ market. ” The bulk of its victims ( more than 90 % ) reside in Russia , with France in second place ( 4 % ) .' [/INST] [Originally:O, intended:O, to:O, target:O, the:O, Russian:O, audience:O, ,:O, the:O, banker:O, was:O, later:O, adapted:O, ,:O, with:O, minimal:O, modifications:O, ,:O, for:O, the:O, European:O, “:O, market.:O, ”:O, The:O, bulk:O, of:O, its:O, victims:O, (:O, more:O, than:O, 90:O, %:O, ):O, reside:O, in:O, Russia:O, ,:O, with:O, France:O, in:O, second:O, place:O, (:O, 4:O, %:O, ):O, .:O] </s>

<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: 'Third place is shared by Italy , Ukraine , and the United Kingdom .' [/INST] [Third:O, place:O, is:O, shared:O, by:O, Italy:O, ,:O, Ukraine:O, ,:O, and:O, the:O, United:O, Kingdom:O, .:O] </s>

<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: 'We first detected members of this family back in March 2018 .' [/INST] [We:O, first:O, detected:O, members:O, of:O, this:O, family:O, back:O, in:O, March:O, 2018:O, .:O] </s>

<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: 'Like many other bankers , they were disguised as apps for popular free ad services in Russia .' [/INST] [Like:O, many:O, other:O, bankers:O, ,:O, they:O, were:O, disguised:O, as:O, apps:O, for:O, popular:O, free:O, ad:O, services:O, in:O, Russia:O, .:O] </s>

<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: 'The malware was distributed from infected devices via SMS in the form “ % USERNAME % , I ’ ll buy under a secure transaction .' [/INST] [The:O, malware:O, was:O, distributed:O, from:O, infected:O, devices:O, via:O, SMS:O, in:O, the:O, form:O, “:O, %:O, USERNAME:O, %:O, ,:O, I:O, ’:O, ll:O, buy:O, under:O, a:O, secure:O, transaction:O, .:O] </s>

<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: 'youlabuy [ .' [/INST] [youlabuy:B-Indicator, [:I-Indicator, .:I-Indicator] </s>

<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: '] ru/7 * * * * * 3 ” or “ % USERNAME % , accept 25,000 on Youla youla-protect [ .' [/INST] []:I-Indicator, ru/7:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, 3:I-Indicator, ”:O, or:O, “:O, %:O, USERNAME:O, %:O, ,:O, accept:O, 25,000:O, on:O, Youla:O, youla-protect:B-Indicator, [:I-Indicator, .:I-Indicator] </s>

<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: '] ru/4 * * * * * 7 ” , containing a link to download the Trojan .' [/INST] []:I-Indicator, ru/4:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, 7:I-Indicator, ”:O, ,:O, containing:O, a:O, link:O, to:O, download:O, the:O, Trojan:O, .:O] </s>

<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: 'Other samples were also noticed , posing as a client of a ticket-finding service or as an app store for Android .' [/INST] [Other:O, samples:O, were:O, also:O, noticed:O, ,:O, posing:O, as:O, a:O, client:O, of:O, a:O, ticket-finding:O, service:O, or:O, as:O, an:O, app:O, store:O, for:O, Android:B-System, .:O] </s>

<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: 'It was late 2018 when Riltok climbed onto the international stage .' [/INST] [It:O, was:O, late:O, 2018:O, when:O, Riltok:B-Malware, climbed:O, onto:O, the:O, international:O, stage:O, .:O] </s>

<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: 'The cybercriminals behind it kept the same masking and distribution methods , using names and icons imitating those of popular free ad services .' [/INST] [The:O, cybercriminals:O, behind:O, it:O, kept:O, the:O, same:O, masking:O, and:O, distribution:O, methods:O, ,:O, using:O, names:O, and:O, icons:O, imitating:O, those:O, of:O, popular:O, free:O, ad:O, services:O, .:O] </s>

<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: 'In November 2018 , a version of the Trojan for the English market appeared in the shape of Gumtree.apk .' [/INST] [In:O, November:O, 2018:O, ,:O, a:O, version:O, of:O, the:O, Trojan:O, for:O, the:O, English:O, market:O, appeared:O, in:O, the:O, shape:O, of:O, Gumtree.apk:B-Indicator, .:O] </s>

<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: 'The SMS message with a link to a banker looked as follows : “ % USERNAME % , i send you prepayment gumtree [ .' [/INST] [The:O, SMS:O, message:O, with:O, a:O, link:O, to:O, a:O, banker:O, looked:O, as:O, follows:O, ::O, “:O, %:O, USERNAME:O, %:O, ,:O, i:O, send:O, you:O, prepayment:O, gumtree:B-Indicator, [:I-Indicator, .:I-Indicator] </s>

<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: '] cc/3 * * * * * 1 ” .' [/INST] []:I-Indicator, cc/3:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, 1:I-Indicator, ”:O, .:O] </s>

<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: 'Italian ( Subito.apk ) and French ( Leboncoin.apk ) versions appeared shortly afterwards in January 2019 .' [/INST] [Italian:O, (:O, Subito.apk:B-Indicator, ):O, and:O, French:O, (:O, Leboncoin.apk:B-Indicator, ):O, versions:O, appeared:O, shortly:O, afterwards:O, in:O, January:O, 2019:O, .:O] </s>

<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: 'The messages looked as follows : “ % USERNAME % , ti ho inviato il soldi sul subito subito-a [ .' [/INST] [The:O, messages:O, looked:O, as:O, follows:O, ::O, “:O, %:O, USERNAME:O, %:O, ,:O, ti:O, ho:O, inviato:O, il:O, soldi:O, sul:O, subito:O, subito-a:B-Indicator, [:I-Indicator, .:I-Indicator] </s>

<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: '] pw/6 * * * * * 5 ” ( It .' [/INST] []:I-Indicator, pw/6:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, 5:I-Indicator, ”:O, (:O, It:O, .:O] </s>

<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: ') “ % USERNAME % , ti ho inviato il pagamento subitop [ .' [/INST] [):O, “:O, %:O, USERNAME:O, %:O, ,:O, ti:O, ho:O, inviato:O, il:O, pagamento:O, subitop:B-Indicator, [:I-Indicator, .:I-Indicator] </s>

<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: '] pw/4 * * * * * 7 ” ( It .' [/INST] []:I-Indicator, pw/4:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, 7:I-Indicator, ”:O, (:O, It:O, .:O] </s>

<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: ') “ % USERNAME % , je vous ai envoyé un prepaiement m-leboncoin [ .' [/INST] [):O, “:O, %:O, USERNAME:O, %:O, ,:O, je:O, vous:O, ai:O, envoyé:O, un:O, prepaiement:O, m-leboncoin:B-Indicator, [:I-Indicator, .:I-Indicator] </s>

<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: '] top/7 * * * * * 3 ” ( Fr .' [/INST] []:I-Indicator, top/7:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, 3:I-Indicator, ”:O, (:O, Fr:O, .:O] </s>

<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: ') “ % USERNAME % , j ’ ai fait l ’ avance ( suivi d ’ un lien ) : leboncoin-le [ .' [/INST] [):O, “:O, %:O, USERNAME:O, %:O, ,:O, j:O, ’:O, ai:O, fait:O, l:O, ’:O, avance:O, (:O, suivi:O, d:O, ’:O, un:O, lien:O, ):O, ::O, leboncoin-le:B-Indicator, [:I-Indicator, .:I-Indicator] </s>

<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: '] com/8 * * * * * 9 ” ( Fr .' [/INST] []:I-Indicator, com/8:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, *:I-Indicator, 9:I-Indicator, ”:O, (:O, Fr:O, .:O] </s>

<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: ') Let ’ s take a more detailed look at how this banking Trojan works .' [/INST] [):O, Let:O, ’:O, s:O, take:O, a:O, more:O, detailed:O, look:O, at:O, how:O, this:O, banking:O, Trojan:O, works:O, .:O] </s>

<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: 'Infection The user receives an SMS with a malicious link pointing to a fake website simulating a popular free ad service .' [/INST] [Infection:O, The:O, user:O, receives:O, an:O, SMS:O, with:O, a:O, malicious:O, link:O, pointing:O, to:O, a:O, fake:O, website:O, simulating:O, a:O, popular:O, free:O, ad:O, service:O, .:O] </s>

<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: 'There , they are prompted to download a new version of the mobile app , under which guise the Trojan is hidden .' [/INST] [There:O, ,:O, they:O, are:O, prompted:O, to:O, download:O, a:O, new:O, version:O, of:O, the:O, mobile:O, app:O, ,:O, under:O, which:O, guise:O, the:O, Trojan:O, is:O, hidden:O, .:O] </s>

<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: 'To be installed , it needs the victim to allow installation of apps from unknown sources in the device settings .' [/INST] [To:O, be:O, installed:O, ,:O, it:O, needs:O, the:O, victim:O, to:O, allow:O, installation:O, of:O, apps:O, from:O, unknown:O, sources:O, in:O, the:O, device:O, settings:O, .:O] </s>

<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: 'During installation , Riltok asks the user for permission to use special features in AccessibilityService by displaying a fake warning : If the user ignores or declines the request , the window keeps opening ad infinitum .' [/INST] [During:O, installation:O, ,:O, Riltok:B-Malware, asks:O, the:O, user:O, for:O, permission:O, to:O, use:O, special:O, features:O, in:O, AccessibilityService:O, by:O, displaying:O, a:O, fake:O, warning:O, ::O, If:O, the:O, user:O, ignores:O, or:O, declines:O, the:O, request:O, ,:O, the:O, window:O, keeps:O, opening:O, ad:O, infinitum:O, .:O] </s>

<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: 'After obtaining the desired rights , the Trojan sets itself as the default SMS app ( by independently clicking Yes in AccessibilityService ) , before vanishing from the device screen .' [/INST] [After:O, obtaining:O, the:O, desired:O, rights:O, ,:O, the:O, Trojan:O, sets:O, itself:O, as:O, the:O, default:O, SMS:O, app:O, (:O, by:O, independently:O, clicking:O, Yes:O, in:O, AccessibilityService:O, ):O, ,:O, before:O, vanishing:O, from:O, the:O, device:O, screen:O, .:O] </s>

<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: 'After enabling AccessibilityService , the malware sets itself as the default SMS app Now installed and having obtained the necessary permissions from the user , Riltok contacts its C & C server .' [/INST] [After:O, enabling:O, AccessibilityService:O, ,:O, the:O, malware:O, sets:O, itself:O, as:O, the:O, default:O, SMS:O, app:O, Now:O, installed:O, and:O, having:O, obtained:O, the:O, necessary:O, permissions:O, from:O, the:O, user:O, ,:O, Riltok:B-Malware, contacts:O, its:O, C:O, &:O, C:O, server:O, .:O] </s>

<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: 'In later versions , when it starts , the Trojan additionally opens a phishing site in the browser that simulates a free ad service so as to dupe the user into entering their login credentials and bank card details .' [/INST] [In:O, later:O, versions:O, ,:O, when:O, it:O, starts:O, ,:O, the:O, Trojan:O, additionally:O, opens:O, a:O, phishing:O, site:O, in:O, the:O, browser:O, that:O, simulates:O, a:O, free:O, ad:O, service:O, so:O, as:O, to:O, dupe:O, the:O, user:O, into:O, entering:O, their:O, login:O, credentials:O, and:O, bank:O, card:O, details:O, .:O] </s>

<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: 'The entered data is forwarded to the cybercriminals .' [/INST] [The:O, entered:O, data:O, is:O, forwarded:O, to:O, the:O, cybercriminals:O, .:O] </s>

<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: 'Phishing page from the French version of the Trojan Communication with C & C Riltok actively communicates with its C & C server .' [/INST] [Phishing:O, page:O, from:O, the:O, French:O, version:O, of:O, the:O, Trojan:O, Communication:O, with:O, C:O, &:O, C:O, Riltok:B-Malware, actively:O, communicates:O, with:O, its:O, C:O, &:O, C:O, server:O, .:O] </s>

<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: 'First off , it registers the infected device in the administrative panel by sending a GET request to the relative address gate.php ( in later versions gating.php ) with the ID ( device identifier generated by the setPsuedoID function in a pseudo-random way based on the device IMEI ) and screen ( shows if the device is active , possible values are “ on ” , “ off ” , “ none ” ) parameters .' [/INST] [First:O, off:O, ,:O, it:O, registers:O, the:O, infected:O, device:O, in:O, the:O, administrative:O, panel:O, by:O, sending:O, a:O, GET:O, request:O, to:O, the:O, relative:O, address:O, gate.php:B-Indicator, (:O, in:O, later:O, versions:O, gating.php:B-Indicator, ):O, with:O, the:O, ID:O, (:O, device:O, identifier:O, generated:O, by:O, the:O, setPsuedoID:O, function:O, in:O, a:O, pseudo-random:O, way:O, based:O, on:O, the:O, device:O, IMEI:O, ):O, and:O, screen:O, (:O, shows:O, if:O, the:O, device:O, is:O, active:O, ,:O, possible:O, values:O, are:O, “:O, on:O, ”:O, ,:O, “:O, off:O, ”:O, ,:O, “:O, none:O, ”:O, ):O, parameters:O, .:O] </s>

<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: 'Then , using POST requests to the relative address report.php , it sends data about the device ( IMEI , phone number , country , mobile operator , phone model , availability of root rights , OS version ) , list of contacts , list of installed apps , incoming SMS , and other information .' [/INST] [Then:O, ,:O, using:O, POST:O, requests:O, to:O, the:O, relative:O, address:O, report.php:B-Indicator, ,:O, it:O, sends:O, data:O, about:O, the:O, device:O, (:O, IMEI:O, ,:O, phone:O, number:O, ,:O, country:O, ,:O, mobile:O, operator:O, ,:O, phone:O, model:O, ,:O, availability:O, of:O, root:O, rights:O, ,:O, OS:O, version:O, ):O, ,:O, list:O, of:O, contacts:O, ,:O, list:O, of:O, installed:O, apps:O, ,:O, incoming:O, SMS:O, ,:O, and:O, other:O, information:O, .:O] </s>

<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: 'From the server , the Trojan receives commands ( for example , to send SMS ) and changes in the configuration .' [/INST] [From:O, the:O, server:O, ,:O, the:O, Trojan:O, receives:O, commands:O, (:O, for:O, example:O, ,:O, to:O, send:O, SMS:O, ):O, and:O, changes:O, in:O, the:O, configuration:O, .:O] </s>

<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: 'Trojan anatomy The family was named Riltok after the librealtalk-jni.so library contained in the APK file of the Trojan .' [/INST] [Trojan:O, anatomy:O, The:O, family:O, was:O, named:O, Riltok:B-Malware, after:O, the:O, librealtalk-jni.so:B-Indicator, library:O, contained:O, in:O, the:O, APK:O, file:O, of:O, the:O, Trojan:O, .:O] </s>

<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: 'The library includes such operations as : Get address of cybercriminal C & C server Get configuration file with web injects from C & C , as well as default list of injects Scan for app package names that generated AccessibilityEvent events in the list of known banking/antivirus/other popular apps Set malware as default SMS app Get address of the phishing page that opens when the app runs , and others getStartWebUrl function – get address of phishing page The configuration file contains a list of injects for mobile banking apps – links to phishing pages matching the mobile' [/INST] [The:O, library:O, includes:O, such:O, operations:O, as:O, ::O, Get:O, address:O, of:O, cybercriminal:O, C:O, &:O, C:O, server:O, Get:O, configuration:O, file:O, with:O, web:O, injects:O, from:O, C:O, &:O, C:O, ,:O, as:O, well:O, as:O, default:O, list:O, of:O, injects:O, Scan:O, for:O, app:O, package:O, names:O, that:O, generated:O, AccessibilityEvent:O, events:O, in:O, the:O, list:O, of:O, known:O, banking/antivirus/other:O, popular:O, apps:O, Set:O, malware:O, as:O, default:O, SMS:O, app:O, Get:O, address:O, of:O, the:O, phishing:O, page:O, that:O, opens:O, when:O, the:O, app:O, runs:O, ,:O, and:O, others:O, getStartWebUrl:O, function:O, –:O, get:O, address:O, of:O, phishing:O, page:O, The:O, configuration:O, file:O, contains:O, a:O, list:O, of:O, injects:O, for:O, mobile:O, banking:O, apps:O, –:O, links:O, to:O, phishing:O, pages:O, matching:O, the:O, mobile:O] </s>

<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: 'banking app used by the user .' [/INST] [banking:O, app:O, used:O, by:O, the:O, user:O, .:O] </s>

<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: 'In most so-called Western versions of the Trojan , the package names in the default configuration file are erased .' [/INST] [In:O, most:O, so-called:O, Western:O, versions:O, of:O, the:O, Trojan:O, ,:O, the:O, package:O, names:O, in:O, the:O, default:O, configuration:O, file:O, are:O, erased:O, .:O] </s>

<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: 'Sample configuration file of the Trojan Through AccessibilityService , the malware monitors AccessibilityEvent events .' [/INST] [Sample:O, configuration:O, file:O, of:O, the:O, Trojan:O, Through:O, AccessibilityService:O, ,:O, the:O, malware:O, monitors:O, AccessibilityEvent:O, events:O, .:O] </s>

<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: 'Depending on which app ( package name ) generated the event , Riltok can : Open a fake Google Play screen requesting bank card details Open a fake screen or phishing page in a browser ( inject ) mimicking the screen of the relevant mobile banking app and requesting user/bank card details Minimize the app ( for example , antivirus applications or device security settings ) Additionally , the Trojan can hide notifications from certain banking apps .' [/INST] [Depending:O, on:O, which:O, app:O, (:O, package:O, name:O, ):O, generated:O, the:O, event:O, ,:O, Riltok:B-Malware, can:O, ::O, Open:O, a:O, fake:O, Google:B-System, Play:I-System, screen:O, requesting:O, bank:O, card:O, details:O, Open:O, a:O, fake:O, screen:O, or:O, phishing:O, page:O, in:O, a:O, browser:O, (:O, inject:O, ):O, mimicking:O, the:O, screen:O, of:O, the:O, relevant:O, mobile:O, banking:O, app:O, and:O, requesting:O, user/bank:O, card:O, details:O, Minimize:O, the:O, app:O, (:O, for:O, example:O, ,:O, antivirus:O, applications:O, or:O, device:O, security:O, settings:O, ):O, Additionally:O, ,:O, the:O, Trojan:O, can:O, hide:O, notifications:O, from:O, certain:O, banking:O, apps:O, .:O] </s>

<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: 'List of package names of apps on events from which the Trojan opens a fake Google Play window ( for the Russian version of the Trojan ) Example of Trojan screen overlapping other apps When bank card details are entered in the fake window , Riltok performs basic validation checks : card validity period , number checksum , CVC length , whether the number is in the denylist sewn into the Trojan code : Examples of phishing pages imitating mobile banks At the time of writing , the functionality of most of the Western versions of Riltok' [/INST] [List:O, of:O, package:O, names:O, of:O, apps:O, on:O, events:O, from:O, which:O, the:O, Trojan:O, opens:O, a:O, fake:O, Google:B-System, Play:I-System, window:O, (:O, for:O, the:O, Russian:O, version:O, of:O, the:O, Trojan:O, ):O, Example:O, of:O, Trojan:O, screen:O, overlapping:O, other:O, apps:O, When:O, bank:O, card:O, details:O, are:O, entered:O, in:O, the:O, fake:O, window:O, ,:O, Riltok:O, performs:O, basic:O, validation:O, checks:O, ::O, card:O, validity:O, period:O, ,:O, number:O, checksum:O, ,:O, CVC:O, length:O, ,:O, whether:O, the:O, number:O, is:O, in:O, the:O, denylist:O, sewn:O, into:O, the:O, Trojan:O, code:O, ::O, Examples:O, of:O, phishing:O, pages:O, imitating:O, mobile:O, banks:O, At:O, the:O, time:O, of:O, writing:O, ,:O, the:O, functionality:O, of:O, most:O, of:O, the:O, Western:O, versions:O, of:O, Riltok:O] </s>

<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: 'was somewhat pared down compared to the Russian one .' [/INST] [was:O, somewhat:O, pared:O, down:O, compared:O, to:O, the:O, Russian:O, one:O, .:O] </s>

<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: 'For example , the default configuration file with injects is non-operational , and the malware contains no fake built-in windows requesting bank card details .' [/INST] [For:O, example:O, ,:O, the:O, default:O, configuration:O, file:O, with:O, injects:O, is:O, non-operational:O, ,:O, and:O, the:O, malware:O, contains:O, no:O, fake:O, built-in:O, windows:O, requesting:O, bank:O, card:O, details:O, .:O] </s>

<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: 'Conclusion Threats are better prevented than cured , so do not follow suspicious links in SMS , and be sure to install apps only from official sources and check what permissions you are granting during installation .' [/INST] [Conclusion:O, Threats:O, are:O, better:O, prevented:O, than:O, cured:O, ,:O, so:O, do:O, not:O, follow:O, suspicious:O, links:O, in:O, SMS:O, ,:O, and:O, be:O, sure:O, to:O, install:O, apps:O, only:O, from:O, official:O, sources:O, and:O, check:O, what:O, permissions:O, you:O, are:O, granting:O, during:O, installation:O, .:O] </s>

<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: 'As Riltok shows , cybercriminals can apply the same methods of infection to victims in different countries with more or less the same success .' [/INST] [As:O, Riltok:B-Malware, shows:O, ,:O, cybercriminals:O, can:O, apply:O, the:O, same:O, methods:O, of:O, infection:O, to:O, victims:O, in:O, different:O, countries:O, with:O, more:O, or:O, less:O, the:O, same:O, success:O, .:O] </s>

<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: 'Kaspersky products detect the above-described threat with the verdict Trojan-Banker.AndroidOS.Riltok .' [/INST] [Kaspersky:B-Organization, products:O, detect:O, the:O, above-described:O, threat:O, with:O, the:O, verdict:O, Trojan-Banker.AndroidOS.Riltok:B-Indicator, .:O] </s>

<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: 'IoCs C & C 100.51.100.00 108.62.118.131 172.81.134.165 172.86.120.207 185.212.128.152 185.212.128.192 185.61.000.108 185.61.138.108 185.61.138.37 188.209.52.101 5.206.225.57 alr992.date avito-app.pw backfround2.pw background1.xyz blacksolider93.com blass9g087.com brekelter2.com broplar3hf.xyz buy-youla.ru' [/INST] [IoCs:O, C:O, &:O, C:O, 100.51.100.00:B-Indicator, 108.62.118.131:B-Indicator, 172.81.134.165:B-Indicator, 172.86.120.207:B-Indicator, 185.212.128.152:B-Indicator, 185.212.128.192:B-Indicator, 185.61.000.108:B-Indicator, 185.61.138.108:B-Indicator, 185.61.138.37:B-Indicator, 188.209.52.101:B-Indicator, 5.206.225.57:B-Indicator, alr992.date:B-Indicator, avito-app.pw:B-Indicator, backfround2.pw:B-Indicator, background1.xyz:B-Indicator, blacksolider93.com:B-Indicator, blass9g087.com:B-Indicator, brekelter2.com:B-Indicator, broplar3hf.xyz:B-Indicator, buy-youla.ru:B-Indicator] </s>