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<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: 'This was used to bypass 2FA methods by intercepting the SMS messages coming from the bank and stealing the mTANs without the victim ’ s knowledge .' [/INST] [This:O, was:O, used:O, to:O, bypass:O, 2FA:O, methods:O, by:O, intercepting:O, the:O, SMS:O, messages:O, coming:O, from:O, the:O, bank:O, and:O, stealing:O, the:O, mTANs:O, without:O, the:O, victim:O, ’:O, s:O, knowledge: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: 'Many other banking malware families followed suit and released their own Android malware components designed to steal those OTPs and TANs .' [/INST] [Many:O, other:O, banking:O, malware:O, families:O, followed:O, suit:O, and:O, released:O, their:O, own:O, Android:O, malware:O, components:O, designed:O, to:O, steal:O, those:O, OTPs:O, and:O, TANs: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 mTAN to pushTAN In the past few years , some banks in Europe , especially in Germany , stopped using SMS-based authentication and switched to dedicated pushTAN applications for 2FA schemes .' [/INST] [From:O, mTAN:O, to:O, pushTAN:O, In:O, the:O, past:O, few:O, years:O, ,:O, some:O, banks:O, in:O, Europe:O, ,:O, especially:O, in:O, Germany:O, ,:O, stopped:O, using:O, SMS-based:O, authentication:O, and:O, switched:O, to:O, dedicated:O, pushTAN:O, applications:O, for:O, 2FA:O, schemes: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: 'Instead of relying on SMS messages , which can be easily intercepted by third-party apps , these applications started using push notifications for users , containing the transaction details and the TAN .' [/INST] [Instead:O, of:O, relying:O, on:O, SMS:O, messages:O, ,:O, which:O, can:O, be:O, easily:O, intercepted:O, by:O, third-party:O, apps:O, ,:O, these:O, applications:O, started:O, using:O, push:O, notifications:O, for:O, users:O, ,:O, containing:O, the:O, transaction:O, details:O, and:O, the:O, TAN: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 pushTAN method has a clear advantage : It improves security by mitigating the risk of SIM swapping attacks and SMS stealers .' [/INST] [The:O, pushTAN:O, method:O, has:O, a:O, clear:O, advantage:O, ::O, It:O, improves:O, security:O, by:O, mitigating:O, the:O, risk:O, of:O, SIM:O, swapping:O, attacks:O, and:O, SMS:O, stealers: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: 'TrickMo Calls pushTAN The pushTAN method is a hurdle for malware apps that may reside on the same device , and it ’ s particularly challenging for mobile malware due to Android ’ s application sandbox .' [/INST] [TrickMo:B-Malware, Calls:O, pushTAN:O, The:O, pushTAN:O, method:O, is:O, a:O, hurdle:O, for:O, malware:O, apps:O, that:O, may:O, reside:O, on:O, the:O, same:O, device:O, ,:O, and:O, it:O, ’:O, s:O, particularly:O, challenging:O, for:O, mobile:O, malware:O, due:O, to:O, Android:B-System, ’:O, s:O, application:O, sandbox: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: 'This feature is designed to block one application from accessing the data of other applications without rooting the device .' [/INST] [This:O, feature:O, is:O, designed:O, to:O, block:O, one:O, application:O, from:O, accessing:O, the:O, data:O, of:O, other:O, applications:O, without:O, rooting:O, the:O, device: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 get around this challenge , TrickMo ’ s developers added some new features to steal TANs using screen video recording and screen data scraping .' [/INST] [To:O, get:O, around:O, this:O, challenge:O, ,:O, TrickMo:B-Malware, ’:O, s:O, developers:O, added:O, some:O, new:O, features:O, to:O, steal:O, TANs:O, using:O, screen:O, video:O, recording:O, and:O, screen:O, data:O, scraping: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 Root of All ( Android ) Evil So how does TrickMo get around these security features ?' [/INST] [The:O, Root:O, of:O, All:O, (:O, Android:B-System, ):O, Evil:O, So:O, how:O, does:O, TrickMo:B-Malware, get:O, around:O, these:O, security:O, features: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: 'It abuses accessibility services .' [/INST] [It:O, abuses:O, accessibility: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: 'Android ’ s accessibility services were originally developed by Google for the benefit of users with disabilities .' [/INST] [Android:B-System, ’:O, s:O, accessibility:O, services:O, were:O, originally:O, developed:O, by:O, Google:B-Organization, for:O, the:O, benefit:O, of:O, users:O, with:O, disabilities: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: 'Any app can ask for accessibility permissions and implement features such as screen reading , changing sizes and colors of objects , hearing enhancements , replacing touch with other forms of control and more .' [/INST] [Any:O, app:O, can:O, ask:O, for:O, accessibility:O, permissions:O, and:O, implement:O, features:O, such:O, as:O, screen:O, reading:O, ,:O, changing:O, sizes:O, and:O, colors:O, of:O, objects:O, ,:O, hearing:O, enhancements:O, ,:O, replacing:O, touch:O, with:O, other:O, forms:O, of:O, control:O, and:O, more: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 recent years , some malicious Android applications abused these accessibility services in various attack scenarios .' [/INST] [In:O, recent:O, years:O, ,:O, some:O, malicious:O, Android:B-System, applications:O, abused:O, these:O, accessibility:O, services:O, in:O, various:O, attack:O, scenarios: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: 'Once on the device , as installed by a duped user , the TrickMo component opens and sends an intent to start the accessibility settings activity , coercing the user to grant it with accessibility permissions .' [/INST] [Once:O, on:O, the:O, device:O, ,:O, as:O, installed:O, by:O, a:O, duped:O, user:O, ,:O, the:O, TrickMo:B-Malware, component:O, opens:O, and:O, sends:O, an:O, intent:O, to:O, start:O, the:O, accessibility:O, settings:O, activity:O, ,:O, coercing:O, the:O, user:O, to:O, grant:O, it:O, with:O, accessibility:O, permissions: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 , it uses the accessibility service for its malicious operations , some of which include : Preventing the user from uninstalling the app Becoming the default SMS app by changing device settings Monitoring the currently running application ( s ) Scraping on-screen text Android operating systems include many dialog screens that require the denial , or approval , of app permissions and actions that have to receive input from the user by tapping a button on the screen .' [/INST] [Then:O, ,:O, it:O, uses:O, the:O, accessibility:O, service:O, for:O, its:O, malicious:O, operations:O, ,:O, some:O, of:O, which:O, include:O, ::O, Preventing:O, the:O, user:O, from:O, uninstalling:O, the:O, app:O, Becoming:O, the:O, default:O, SMS:O, app:O, by:O, changing:O, device:O, settings:O, Monitoring:O, the:O, currently:O, running:O, application:O, (:O, s:O, ):O, Scraping:O, on-screen:O, text:O, Android:B-System, operating:O, systems:O, include:O, many:O, dialog:O, screens:O, that:O, require:O, the:O, denial:O, ,:O, or:O, approval:O, ,:O, of:O, app:O, permissions:O, and:O, actions:O, that:O, have:O, to:O, receive:O, input:O, from:O, the:O, user:O, by:O, tapping:O, a:O, button:O, on:O, the: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: 'TrickMo uses accessibility services to identify and control some of these screens and make its own choices before giving the user a chance to react .' [/INST] [TrickMo:B-Malware, uses:O, accessibility:O, services:O, to:O, identify:O, and:O, control:O, some:O, of:O, these:O, screens:O, and:O, make:O, its:O, own:O, choices:O, before:O, giving:O, the:O, user:O, a:O, chance:O, to:O, react: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 the image below , we see the malware function that detects such dialogs when they are presented to the user , asking them to tap an option based on predefined choices .' [/INST] [In:O, the:O, image:O, below:O, ,:O, we:O, see:O, the:O, malware:O, function:O, that:O, detects:O, such:O, dialogs:O, when:O, they:O, are:O, presented:O, to:O, the:O, user:O, ,:O, asking:O, them:O, to:O, tap:O, an:O, option:O, based:O, on:O, predefined:O, choices: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: 'TrickMo ’ s Persistence Capabilities When it comes to Android-based devices , many applications must find a way to run on the device after a system reboot .' [/INST] [TrickMo:B-Malware, ’:O, s:O, Persistence:O, Capabilities:O, When:O, it:O, comes:O, to:O, Android-based:B-System, devices:O, ,:O, many:O, applications:O, must:O, find:O, a:O, way:O, to:O, run:O, on:O, the:O, device:O, after:O, a:O, system:O, reboot: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 most common way to achieve this is by creating a broadcast receiver that is registered to the “ android.intent.action.BOOT_COMPLETED ” broadcast action and adding code that boots the application when the broadcast is fired .' [/INST] [The:O, most:O, common:O, way:O, to:O, achieve:O, this:O, is:O, by:O, creating:O, a:O, broadcast:O, receiver:O, that:O, is:O, registered:O, to:O, the:O, “:O, android.intent.action.BOOT_COMPLETED:B-Indicator, ”:O, broadcast:O, action:O, and:O, adding:O, code:O, that:O, boots:O, the:O, application:O, when:O, the:O, broadcast:O, is:O, fired: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: 'This instruction is especially important for malware that tries to avoid user interaction by running in the background as a service .' [/INST] [This:O, instruction:O, is:O, especially:O, important:O, for:O, malware:O, that:O, tries:O, to:O, avoid:O, user:O, interaction:O, by:O, running:O, in:O, the:O, background:O, as:O, a: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: 'But TrickMo does things differently .' [/INST] [But:O, TrickMo:B-Malware, does:O, things:O, differently: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: 'Instead of running its service only at boot time , it registers a receiver that listens to the “ android.intent.action.SCREEN_ON ” and “ android.provider.Telephony.SMS_DELIVER ” broadcast actions .' [/INST] [Instead:O, of:O, running:O, its:O, service:O, only:O, at:O, boot:O, time:O, ,:O, it:O, registers:O, a:O, receiver:O, that:O, listens:O, to:O, the:O, “:O, android.intent.action.SCREEN_ON:B-Indicator, ”:O, and:O, “:O, android.provider.Telephony.SMS_DELIVER:B-Indicator, ”:O, broadcast:O, actions: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: 'It then uses the AlarmManager to set a pending intent that will run its own service after a predefined interval .' [/INST] [It:O, then:O, uses:O, the:O, AlarmManager:B-System, to:O, set:O, a:O, pending:O, intent:O, that:O, will:O, run:O, its:O, own:O, service:O, after:O, a:O, predefined:O, interval: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 other words , TrickMo ’ s service will start either after the device becomes interactive or after a new SMS message is received .' [/INST] [In:O, other:O, words:O, ,:O, TrickMo:B-Malware, ’:O, s:O, service:O, will:O, start:O, either:O, after:O, the:O, device:O, becomes:O, interactive:O, or:O, after:O, a:O, new:O, SMS:O, message:O, is:O, received: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: 'Tricky Configurations TrickMo uses the shared preferences mechanism to store settings and data that the malware uses at runtime .' [/INST] [Tricky:O, Configurations:O, TrickMo:B-Malware, uses:O, the:O, shared:O, preferences:O, mechanism:O, to:O, store:O, settings:O, and:O, data:O, that:O, the:O, malware:O, uses:O, at:O, runtime: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: 'Some of the settings are Boolean values that act as switches .' [/INST] [Some:O, of:O, the:O, settings:O, are:O, Boolean:O, values:O, that:O, act:O, as:O, switches: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: 'They represent features and can be turned on and off from the command-and-control ( C & C ) server or by an SMS message , effectively instructing the malware to execute certain tasks .' [/INST] [They:O, represent:O, features:O, and:O, can:O, be:O, turned:O, on:O, and:O, off:O, from:O, the:O, command-and-control:O, (:O, C:O, &:O, C:O, ):O, server:O, or:O, by:O, an:O, SMS:O, message:O, ,:O, effectively:O, instructing:O, the:O, malware:O, to:O, execute:O, certain:O, tasks: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: 'Some of the settings include : The URL of the C & C server Service wake-up intervals Important package names Accessibility permissions status Lockdown screen status Recording status SMS app status Kill switch status Stealth To keep its resources safer and make analysis more difficult for researchers , TrickMo uses an obfuscator to scramble the names of its functions , classes and variables .' [/INST] [Some:O, of:O, the:O, settings:O, include:O, ::O, The:O, URL:O, of:O, the:O, C:O, &:O, C:O, server:O, Service:O, wake-up:O, intervals:O, Important:O, package:O, names:O, Accessibility:O, permissions:O, status:O, Lockdown:O, screen:O, status:O, Recording:O, status:O, SMS:O, app:O, status:O, Kill:O, switch:O, status:O, Stealth:O, To:O, keep:O, its:O, resources:O, safer:O, and:O, make:O, analysis:O, more:O, difficult:O, for:O, researchers:O, ,:O, TrickMo:B-Malware, uses:O, an:O, obfuscator:O, to:O, scramble:O, the:O, names:O, of:O, its:O, functions:O, ,:O, classes:O, and:O, variables: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: 'A TrickMo version from January 2020 contained code that checks if the app is running on a rooted device or an emulator to prevent analysis .' [/INST] [A:O, TrickMo:B-Malware, version:O, from:O, January:O, 2020:O, contained:O, code:O, that:O, checks:O, if:O, the:O, app:O, is:O, running:O, on:O, a:O, rooted:O, device:O, or:O, an:O, emulator:O, to:O, prevent:O, analysis: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 an example , in the two images below , we can see the encrypted and decrypted shared preferences file , which is encrypted using the java “ PBEWithMD5AndDES ” algorithm .' [/INST] [As:O, an:O, example:O, ,:O, in:O, the:O, two:O, images:O, below:O, ,:O, we:O, can:O, see:O, the:O, encrypted:O, and:O, decrypted:O, shared:O, preferences:O, file:O, ,:O, which:O, is:O, encrypted:O, using:O, the:O, java:O, “:O, PBEWithMD5AndDES:O, ”:O, algorithm: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: 'C & C Communications Exfiltrating Device Data To communicate with its master , TrickMo ’ s code contains a hardcoded URL of the C & C server .' [/INST] [C:O, &:O, C:O, Communications:O, Exfiltrating:O, Device:O, Data:O, To:O, communicate:O, with:O, its:O, master:O, ,:O, TrickMo:B-Malware, ’:O, s:O, code:O, contains:O, a:O, hardcoded:O, URL:O, of:O, the: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: 'When it runs , it periodically connects to its designated server via an unencrypted HTTP request and sends over a JSON object that contains data gleaned from the victim ’ s phone .' [/INST] [When:O, it:O, runs:O, ,:O, it:O, periodically:O, connects:O, to:O, its:O, designated:O, server:O, via:O, an:O, unencrypted:O, HTTP:O, request:O, and:O, sends:O, over:O, a:O, JSON:O, object:O, that:O, contains:O, data:O, gleaned:O, from:O, the:O, victim:O, ’:O, s:O, phone: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 stolen parameters follow : ID IMSI IMEI Phone number Operator AID Model Brand Version Build Battery percentage Wi-Fi connection state Wake time Are logs enabled ?' [/INST] [The:O, stolen:O, parameters:O, follow:O, ::O, ID:O, IMSI:O, IMEI:O, Phone:O, number:O, Operator:O, AID:O, Model:O, Brand:O, Version:O, Build:O, Battery:O, percentage:O, Wi-Fi:O, connection:O, state:O, Wake:O, time:O, Are:O, logs:O, enabled: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: 'Is the malware already set as the default SMS application ?' [/INST] [Is:O, the:O, malware:O, already:O, set:O, as:O, the:O, default:O, SMS:O, application: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: '[ True/False ] Signal strength Screen active [ True/False ] Orientation Was accessibility permission granted ?' [/INST] [[:O, True/False:O, ]:O, Signal:O, strength:O, Screen:O, active:O, [:O, True/False:O, ]:O, Orientation:O, Was:O, accessibility:O, permission:O, granted: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: '[ True/False ] Screen size List of the installed applications SMS messages saved on the device It is not uncommon for banking malware to harvest extensive amounts of data from the victim ’ s device .' [/INST] [[:O, True/False:O, ]:O, Screen:O, size:O, List:O, of:O, the:O, installed:O, applications:O, SMS:O, messages:O, saved:O, on:O, the:O, device:O, It:O, is:O, not:O, uncommon:O, for:O, banking:O, malware:O, to:O, harvest:O, extensive:O, amounts:O, of:O, data:O, from:O, the:O, victim:O, ’:O, s:O, device: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 collected data can then be used to generate a unique identifier of the bot or for monetization purposes .' [/INST] [The:O, collected:O, data:O, can:O, then:O, be:O, used:O, to:O, generate:O, a:O, unique:O, identifier:O, of:O, the:O, bot:O, or:O, for:O, monetization:O, purposes: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: 'It can also be sold on the dark web and used in various spoofing attacks .' [/INST] [It:O, can:O, also:O, be:O, sold:O, on:O, the:O, dark:O, web:O, and:O, used:O, in:O, various:O, spoofing:O, attacks: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 , since some banks use anti-fraud solutions that only check device fingerprinting , fraudsters can use the collected information to perform fraudulent transactions from a device that mimics that same fingerprint .' [/INST] [For:O, example:O, ,:O, since:O, some:O, banks:O, use:O, anti-fraud:O, solutions:O, that:O, only:O, check:O, device:O, fingerprinting:O, ,:O, fraudsters:O, can:O, use:O, the:O, collected:O, information:O, to:O, perform:O, fraudulent:O, transactions:O, from:O, a:O, device:O, that:O, mimics:O, that:O, same:O, fingerprint: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: 'Stealing and Concealing SMS Messages As some banks still use SMS-based transaction authorization , TrickMo is configured to automatically steal all SMS messages that are stored on the device .' [/INST] [Stealing:O, and:O, Concealing:O, SMS:O, Messages:O, As:O, some:O, banks:O, still:O, use:O, SMS-based:O, transaction:O, authorization:O, ,:O, TrickMo:B-Malware, is:O, configured:O, to:O, automatically:O, steal:O, all:O, SMS:O, messages:O, that:O, are:O, stored:O, on:O, the:O, device: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: 'Once in a while , it sends a packet to its C & C server containing the collected device data along with all the saved SMS messages .' [/INST] [Once:O, in:O, a:O, while:O, ,:O, it:O, sends:O, a:O, packet:O, to:O, its:O, C:O, &:O, C:O, server:O, containing:O, the:O, collected:O, device:O, data:O, along:O, with:O, all:O, the:O, saved:O, SMS:O, messages: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: 'Since it can use the accessibility service to become the default SMS app , it can also delete the SMS messages so only the attackers can see them .' [/INST] [Since:O, it:O, can:O, use:O, the:O, accessibility:O, service:O, to:O, become:O, the:O, default:O, SMS:O, app:O, ,:O, it:O, can:O, also:O, delete:O, the:O, SMS:O, messages:O, so:O, only:O, the:O, attackers:O, can:O, see:O, them: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 the image below , we can see a packet that was sent to the attacker ’ s C & C containing collected information along with stolen SMS data .' [/INST] [In:O, the:O, image:O, below:O, ,:O, we:O, can:O, see:O, a:O, packet:O, that:O, was:O, sent:O, to:O, the:O, attacker:O, ’:O, s:O, C:O, &:O, C:O, containing:O, collected:O, information:O, along:O, with:O, stolen:O, SMS:O, data: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: 'A Communication Channel via Stolen SMS In addition , TrickMo has an automatic mechanism to send SMS messages to its C & C server .' [/INST] [A:O, Communication:O, Channel:O, via:O, Stolen:O, SMS:O, In:O, addition:O, ,:O, TrickMo:B-Malware, has:O, an:O, automatic:O, mechanism:O, to:O, send:O, SMS:O, messages:O, to: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 some cases , it uses this mechanism to send log data of important actions .' [/INST] [In:O, some:O, cases:O, ,:O, it:O, uses:O, this:O, mechanism:O, to:O, send:O, log:O, data:O, of:O, important:O, actions: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: 'It can save an SMS message on the device , marking with “ internal ” in the phone number field .' [/INST] [It:O, can:O, save:O, an:O, SMS:O, message:O, on:O, the:O, device:O, ,:O, marking:O, with:O, “:O, internal:O, ”:O, in:O, the:O, phone:O, number:O, field: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 SMS message will be instantly sent to the server , informing the malware operator of executed tasks .' [/INST] [The:O, SMS:O, message:O, will:O, be:O, instantly:O, sent:O, to:O, the:O, server:O, ,:O, informing:O, the:O, malware:O, operator:O, of:O, executed:O, tasks: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 the image below , we see a log TrickMo sent to the attacker upon becoming the default SMS app .' [/INST] [In:O, the:O, image:O, below:O, ,:O, we:O, see:O, a:O, log:O, TrickMo:B-Malware, sent:O, to:O, the:O, attacker:O, upon:O, becoming:O, the:O, default:O, SMS:O, app: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: 'If the malware successfully became the default SMS app , it sends the words “ the app has been replaced ” in Russian .' [/INST] [If:O, the:O, malware:O, successfully:O, became:O, the:O, default:O, SMS:O, app:O, ,:O, it:O, sends:O, the:O, words:O, “:O, the:O, app:O, has:O, been:O, replaced:O, ”:O, in:O, Russian: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: 'If the original SMS app has been restored , it will send “ the app returned to its original place. ” Controlling TrickMo TrickMo ’ s operators can control the malware via two channels : Through its C & C via a plaintext HTTP protocol using JSON objects Through encrypted SMS messages There are predefined commands to change the malware ’ s configuration and make it execute certain tasks .' [/INST] [If:O, the:O, original:O, SMS:O, app:O, has:O, been:O, restored:O, ,:O, it:O, will:O, send:O, “:O, the:O, app:O, returned:O, to:O, its:O, original:O, place.:O, ”:O, Controlling:O, TrickMo:B-Malware, TrickMo:B-Malware, ’:O, s:O, operators:O, can:O, control:O, the:O, malware:O, via:O, two:O, channels:O, ::O, Through:O, its:O, C:O, &:O, C:O, via:O, a:O, plaintext:O, HTTP:O, protocol:O, using:O, JSON:O, objects:O, Through:O, encrypted:O, SMS:O, messages:O, There:O, are:O, predefined:O, commands:O, to:O, change:O, the:O, malware:O, ’:O, s:O, configuration:O, and:O, make:O, it:O, execute:O, certain:O, tasks: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: 'Some of the more interesting commands include : SMS Control Update the address of the C & C server — SMS starting with “ http : // ” Send AES-encrypted SMS message back to sender — SMS starting with “ sms : // ” Update service wake-up interval — “ 2 ” Kill switch — “ 4 ” C & C Control Update the address of the C & C server — “ 1 ” Update service wake-up interval — “ 2 ” Lock the screen — “ 5 ” Display a picture in a WebView from an arbitrary URL — “ 11 ” Send an arbitrary SMS message — “ 8 ” Steal images' [/INST] [Some:O, of:O, the:O, more:O, interesting:O, commands:O, include:O, ::O, SMS:O, Control:O, Update:O, the:O, address:O, of:O, the:O, C:O, &:O, C:O, server:O, —:O, SMS:O, starting:O, with:O, “:O, http:O, ::O, //:O, ”:O, Send:O, AES-encrypted:O, SMS:O, message:O, back:O, to:O, sender:O, —:O, SMS:O, starting:O, with:O, “:O, sms:O, ::O, //:O, ”:O, Update:O, service:O, wake-up:O, interval:O, —:O, “:O, 2:O, ”:O, Kill:O, switch:O, —:O, “:O, 4:O, ”:O, C:O, &:O, C:O, Control:O, Update:O, the:O, address:O, of:O, the:O, C:O, &:O, C:O, server:O, —:O, “:O, 1:O, ”:O, Update:O, service:O, wake-up:O, interval:O, —:O, “:O, 2:O, ”:O, Lock:O, the:O, screen:O, —:O, “:O, 5:O, ”:O, Display:O, a:O, picture:O, in:O, a:O, WebView:O, from:O, an:O, arbitrary:O, URL:O, —:O, “:O, 11:O, ”:O, Send:O, an:O, arbitrary:O, SMS:O, message:O, —:O, “:O, 8:O, ”:O, Steal:O, images: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: 'saved on the device — “ 12 ” and “ 13 ” Use the accessibility service to become the default SMS app — “ 6 ” Enable recording of other apps — “ 15 ” Kill switch — “ 4 ” The Lockdown Screen Most thieves don ’ t want to be caught red-handed as they steal — they want to buy some time to get away with the loot .' [/INST] [saved:O, on:O, the:O, device:O, —:O, “:O, 12:O, ”:O, and:O, “:O, 13:O, ”:O, Use:O, the:O, accessibility:O, service:O, to:O, become:O, the:O, default:O, SMS:O, app:O, —:O, “:O, 6:O, ”:O, Enable:O, recording:O, of:O, other:O, apps:O, —:O, “:O, 15:O, ”:O, Kill:O, switch:O, —:O, “:O, 4:O, ”:O, The:O, Lockdown:O, Screen:O, Most:O, thieves:O, don:O, ’:O, t:O, want:O, to:O, be:O, caught:O, red-handed:O, as:O, they:O, steal:O, —:O, they:O, want:O, to:O, buy:O, some:O, time:O, to:O, get:O, away:O, with:O, the:O, loot: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 same is true for banking malware .' [/INST] [The:O, same:O, is:O, true:O, for:O, banking:O, malware: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: 'Desktop banking malware often blocks the user ’ s access to their banking website after a successful transaction by using web injects that show a variety of “ service unavailable ” screens .' [/INST] [Desktop:O, banking:O, malware:O, often:O, blocks:O, the:O, user:O, ’:O, s:O, access:O, to:O, their:O, banking:O, website:O, after:O, a:O, successful:O, transaction:O, by:O, using:O, web:O, injects:O, that:O, show:O, a:O, variety:O, of:O, “:O, service:O, unavailable:O, ”:O, screens: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: 'TrickMo is no different ; the goal is to complete the operation while raising minimal suspicion .' [/INST] [TrickMo:B-Malware, is:O, no:O, different:O, ;:O, the:O, goal:O, is:O, to:O, complete:O, the:O, operation:O, while:O, raising:O, minimal:O, suspicion: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 performing a fraudulent action , stealing the OTP/mTAN , TrickMo buys some time by activating the lock screen and preventing the user from accessing their device .' [/INST] [After:O, performing:O, a:O, fraudulent:O, action:O, ,:O, stealing:O, the:O, OTP/mTAN:O, ,:O, TrickMo:B-Malware, buys:O, some:O, time:O, by:O, activating:O, the:O, lock:O, screen:O, and:O, preventing:O, the:O, user:O, from:O, accessing:O, their:O, device: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: 'This lockdown screen includes two parts : A WebView containing a background picture loaded from a predefined URL .' [/INST] [This:O, lockdown:O, screen:O, includes:O, two:O, parts:O, ::O, A:O, WebView:O, containing:O, a:O, background:O, picture:O, loaded:O, from:O, a:O, predefined:O, URL: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: 'This background image likely contains a fake “ software update ” screen .' [/INST] [This:O, background:O, image:O, likely:O, contains:O, a:O, fake:O, “:O, software:O, update:O, ”: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: 'A lockdown activity , which is a transparent window shown at the top of the screen that contains a “ loading ” cursor .' [/INST] [A:O, lockdown:O, activity:O, ,:O, which:O, is:O, a:O, transparent:O, window:O, shown:O, at:O, the:O, top:O, of:O, the:O, screen:O, that:O, contains:O, a:O, “:O, loading:O, ”:O, cursor: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: 'This screen persists on the screen and prevents the user from using the navigation buttons .' [/INST] [This:O, screen:O, persists:O, on:O, the:O, screen:O, and:O, prevents:O, the:O, user:O, from:O, using:O, the:O, navigation:O, buttons: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: 'Due to TrickMo ’ s persistence implementation mentioned earlier , this lockdown screen persists after a restart and is re-initiated every time the device becomes interactive .' [/INST] [Due:O, to:O, TrickMo:B-Malware, ’:O, s:O, persistence:O, implementation:O, mentioned:O, earlier:O, ,:O, this:O, lockdown:O, screen:O, persists:O, after:O, a:O, restart:O, and:O, is:O, re-initiated:O, every:O, time:O, the:O, device:O, becomes:O, interactive: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 some cases , TrickMo may use this feature to intercept SMS messages without the knowledge of the user by activating the lockdown screen and intercepting SMS messages in the background .' [/INST] [In:O, some:O, cases:O, ,:O, TrickMo:B-Malware, may:O, use:O, this:O, feature:O, to:O, intercept:O, SMS:O, messages:O, without:O, the:O, knowledge:O, of:O, the:O, user:O, by:O, activating:O, the:O, lockdown:O, screen:O, and:O, intercepting:O, SMS:O, messages:O, in:O, the:O, background: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: 'Application Recording — Stealing OTPs and TANs The feature that makes TrickMo different from standard SMS stealers is its unique ability to record the screen when targeted apps are running .' [/INST] [Application:O, Recording:O, —:O, Stealing:O, OTPs:O, and:O, TANs:O, The:O, feature:O, that:O, makes:O, TrickMo:B-Malware, different:O, from:O, standard:O, SMS:O, stealers:O, is:O, its:O, unique:O, ability:O, to:O, record:O, the:O, screen:O, when:O, targeted:O, apps:O, are:O, running: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: 'This feature was enabled only in newer versions of TrickMo that were tailored specifically for German banks and use a special application for implementing TAN-based 2FA .' [/INST] [This:O, feature:O, was:O, enabled:O, only:O, in:O, newer:O, versions:O, of:O, TrickMo:B-Malware, that:O, were:O, tailored:O, specifically:O, for:O, German:O, banks:O, and:O, use:O, a:O, special:O, application:O, for:O, implementing:O, TAN-based:O, 2FA: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 application recording is implemented via two methods : Using the Android MediaRecorder class to capture a video of the screen when the targeted application is presented to the user Using the accessibility service to save a text file containing the data of all the objects on the screen Both files are later sent to the C & C server of the attacker .' [/INST] [The:O, application:O, recording:O, is:O, implemented:O, via:O, two:O, methods:O, ::O, Using:O, the:O, Android:B-System, MediaRecorder:O, class:O, to:O, capture:O, a:O, video:O, of:O, the:O, screen:O, when:O, the:O, targeted:O, application:O, is:O, presented:O, to:O, the:O, user:O, Using:O, the:O, accessibility:O, service:O, to:O, save:O, a:O, text:O, file:O, containing:O, the:O, data:O, of:O, all:O, the:O, objects:O, on:O, the:O, screen:O, Both:O, files:O, are:O, later:O, sent:O, to:O, the:O, C:O, &:O, C:O, server:O, of:O, the:O, attacker: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 the following image , we can see how the malware receives a JSON object from the C & C server containing the command to start recording , the targeted apps and the recorded video size ratio .' [/INST] [In:O, the:O, following:O, image:O, ,:O, we:O, can:O, see:O, how:O, the:O, malware:O, receives:O, a:O, JSON:O, object:O, from:O, the:O, C:O, &:O, C:O, server:O, containing:O, the:O, command:O, to:O, start:O, recording:O, ,:O, the:O, targeted:O, apps:O, and:O, the:O, recorded:O, video:O, size:O, ratio: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 the image below , the function recursively collects all the text data from the child nodes of each accessibility node .' [/INST] [In:O, the:O, image:O, below:O, ,:O, the:O, function:O, recursively:O, collects:O, all:O, the:O, text:O, data:O, from:O, the:O, child:O, nodes:O, of:O, each:O, accessibility:O, node: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 other words , it goes through every object on the screen and saves its text data .' [/INST] [In:O, other:O, words:O, ,:O, it:O, goes:O, through:O, every:O, object:O, on:O, the:O, screen:O, and:O, saves:O, its:O, text:O, data: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: 'A TrickMo Kill Switch One of the most interesting features of the TrickMo malware is having its own kill switch .' [/INST] [A:O, TrickMo:B-Malware, Kill:O, Switch:O, One:O, of:O, the:O, most:O, interesting:O, features:O, of:O, the:O, TrickMo:B-Malware, malware:I-Malware, is:O, having:O, its:O, own:O, kill:O, switch: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: 'Kill switches are used by many malware authors to remove traces from a device after a successful operation .' [/INST] [Kill:O, switches:O, are:O, used:O, by:O, many:O, malware:O, authors:O, to:O, remove:O, traces:O, from:O, a:O, device:O, after:O, a:O, successful:O, operation: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: 'Since TrickMo ’ s HTTP traffic with its C & C server is not encrypted , it can easily be tampered with .' [/INST] [Since:O, TrickMo:O, ’:O, s:O, HTTP:B-Indicator, traffic:O, with:O, its:O, C:O, &:O, C:O, server:O, is:O, not:O, encrypted:O, ,:O, it:O, can:O, easily:O, be:O, tampered:O, with: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 the following image , we can see the function that parses the commands from the C & C server .' [/INST] [In:O, the:O, following:O, image:O, ,:O, we:O, can:O, see:O, the:O, function:O, that:O, parses:O, the:O, commands:O, from:O, the: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: 'If the returned JSON object has the “ 4 ” key , it will turn on the kill switch and initiate its own removal by sending an intent and seamlessly confirming the uninstall using the accessibility service , all without the victim ever noticing anything .' [/INST] [If:O, the:O, returned:O, JSON:O, object:O, has:O, the:O, “:O, 4:O, ”:O, key:O, ,:O, it:O, will:O, turn:O, on:O, the:O, kill:O, switch:O, and:O, initiate:O, its:O, own:O, removal:O, by:O, sending:O, an:O, intent:O, and:O, seamlessly:O, confirming:O, the:O, uninstall:O, using:O, the:O, accessibility:O, service:O, ,:O, all:O, without:O, the:O, victim:O, ever:O, noticing:O, anything: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 kill switch can also be turned on by SMS .' [/INST] [The:O, kill:O, switch:O, can:O, also:O, be:O, turned:O, on:O, by:O, SMS: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: 'This is a bit more complicated since the SMS commands are encrypted and encoded with base64 .' [/INST] [This:O, is:O, a:O, bit:O, more:O, complicated:O, since:O, the:O, SMS:O, commands:O, are:O, encrypted:O, and:O, encoded:O, with:O, base64: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 encryption algorithm used is RSA , and interestingly , the authors chose to use the private key for decryption and leave it in the code as a hardcoded string .' [/INST] [The:O, encryption:O, algorithm:O, used:O, is:O, RSA:O, ,:O, and:O, interestingly:O, ,:O, the:O, authors:O, chose:O, to:O, use:O, the:O, private:O, key:O, for:O, decryption:O, and:O, leave:O, it:O, in:O, the:O, code:O, as:O, a:O, hardcoded:O, string: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 image below shows the function that parses the SMS messages , decrypts them using the hardcoded RSA private key and executes the commands .' [/INST] [The:O, image:O, below:O, shows:O, the:O, function:O, that:O, parses:O, the:O, SMS:O, messages:O, ,:O, decrypts:O, them:O, using:O, the:O, hardcoded:O, RSA:O, private:O, key:O, and:O, executes:O, the:O, commands: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: 'Having analyzed a few variants of the malware , we noticed that the private key was exposed in the code and did not change .' [/INST] [Having:O, analyzed:O, a:O, few:O, variants:O, of:O, the:O, malware:O, ,:O, we:O, noticed:O, that:O, the:O, private:O, key:O, was:O, exposed:O, in:O, the:O, code:O, and:O, did:O, not:O, change: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: 'Therefore , our team managed to generate the public key and craft an SMS message that activated the kill switch .' [/INST] [Therefore:O, ,:O, our:O, team:O, managed:O, to:O, generate:O, the:O, public:O, key:O, and:O, craft:O, an:O, SMS:O, message:O, that:O, activated:O, the:O, kill:O, switch: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: 'This means that the malware can be remotely eliminated by an SMS message .' [/INST] [This:O, means:O, that:O, the:O, malware:O, can:O, be:O, remotely:O, eliminated:O, by:O, an:O, SMS:O, message: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: 'Our team was also able to test other commands in the lab either by tampering with the HTTP traffic from the C & C or by sending crafted SMS messages .' [/INST] [Our:O, team:O, was:O, also:O, able:O, to:O, test:O, other:O, commands:O, in:O, the:O, lab:O, either:O, by:O, tampering:O, with:O, the:O, HTTP:O, traffic:O, from:O, the:O, C:O, &:O, C:O, or:O, by:O, sending:O, crafted:O, SMS:O, messages: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: 'Suspect You ’ re Infected ?' [/INST] [Suspect:O, You:O, ’:O, re:O, Infected: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 following SMS message can be used to kill the sample analyzed in this research and all other variants that use the same private key : HrLbpr3x/htAVnAgYepBuH2xmFDb68TYTt7FwGn0ddGlQJv/hqsctL57ocFU0Oz3L+uhLcOGG7GVBAfHKL1TBQ== Sending this SMS will trigger TrickMo ’ s kill switch by sending the string “ 4 ” encrypted with the generated RSA public key and base64' [/INST] [The:O, following:O, SMS:O, message:O, can:O, be:O, used:O, to:O, kill:O, the:O, sample:O, analyzed:O, in:O, this:O, research:O, and:O, all:O, other:O, variants:O, that:O, use:O, the:O, same:O, private:O, key:O, ::O, HrLbpr3x/htAVnAgYepBuH2xmFDb68TYTt7FwGn0ddGlQJv/hqsctL57ocFU0Oz3L+uhLcOGG7GVBAfHKL1TBQ==:O, Sending:O, this:O, SMS:O, will:O, trigger:O, TrickMo:B-Malware, ’:O, s:O, kill:O, switch:O, by:O, sending:O, the:O, string:O, “:O, 4:O, ”:O, encrypted:O, with:O, the:O, generated:O, RSA:O, public:O, key:O, and:O, base64: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: 'encoded .' [/INST] [encoded: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: 'Indicators of Compromise ( IoCs ) hxxp : //mcsoft365.com/c hxxp : //pingconnect.net/c Hashes MD5 : 5c749c9fce8c41bf6bcc9bd8a691621b SHA256 : 284bd2d16092b4d13b6bc85d87950eb4c5e8cbba9af2a04d76d88da2f26c485c MD5 : b264af5d2f3390e465052ab502b0726d' [/INST] [Indicators:O, of:O, Compromise:O, (:O, IoCs:O, ):O, hxxp:B-Indicator, ::I-Indicator, //mcsoft365.com/c:I-Indicator, hxxp:I-Indicator, ::I-Indicator, //pingconnect.net/c:I-Indicator, Hashes:O, MD5:O, ::O, 5c749c9fce8c41bf6bcc9bd8a691621b:B-Indicator, SHA256:O, ::O, 284bd2d16092b4d13b6bc85d87950eb4c5e8cbba9af2a04d76d88da2f26c485c:B-Indicator, MD5:O, ::O, b264af5d2f3390e465052ab502b0726d:B-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: 'SHA256 : 8ab1712ce9ca2d7952ab763d8a4872aa6a278c3f60dc13e0aebe59f50e6e30f6 The TrickMo Factor The TrickBot Trojan was one of the most active banking malware strains in the cybercrime arena in 2019 .' [/INST] [SHA256:O, ::O, 8ab1712ce9ca2d7952ab763d8a4872aa6a278c3f60dc13e0aebe59f50e6e30f6:B-Indicator, The:O, TrickMo:B-Malware, Factor:O, The:O, TrickBot:B-Malware, Trojan:I-Malware, was:O, one:O, of:O, the:O, most:O, active:O, banking:O, malware:O, strains:O, in:O, the:O, cybercrime:O, arena:O, in: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: 'From our analysis , it is apparent that TrickMo is designed to help TrickBot break the most recent methods of TAN-based authentication .' [/INST] [From:O, our:O, analysis:O, ,:O, it:O, is:O, apparent:O, that:O, TrickMo:B-Malware, is:O, designed:O, to:O, help:O, TrickBot:B-Malware, break:O, the:O, most:O, recent:O, methods:O, of:O, TAN-based:O, authentication: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: 'One of the most significant features TrickMo possesses is the app recording feature , which is what gives TrickBot the ability to overcome the newer pushTAN app validations deployed by banks .' [/INST] [One:O, of:O, the:O, most:O, significant:O, features:O, TrickMo:B-Malware, possesses:O, is:O, the:O, app:O, recording:O, feature:O, ,:O, which:O, is:O, what:O, gives:O, TrickBot:B-Malware, the:O, ability:O, to:O, overcome:O, the:O, newer:O, pushTAN:O, app:O, validations:O, deployed:O, by:O, banks: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: 'SimBad : A Rogue Adware Campaign On Google Play March 13 , 2019 Check Point researchers from the Mobile Threat Team have discovered a new adware campaign on the Google Play Store .' [/INST] [SimBad:B-Malware, ::O, A:O, Rogue:O, Adware:O, Campaign:O, On:O, Google:B-System, Play:I-System, March:O, 13:O, ,:O, 2019:O, Check:B-Organization, Point:I-Organization, researchers:O, from:O, the:O, Mobile:O, Threat:O, Team:O, have:O, discovered:O, a:O, new:O, adware:O, campaign:O, on:O, the:O, Google:B-System, Play:I-System, Store:I-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: 'This particular strain of Adware was found in 206 applications , and the combined download count has reached almost 150 million .' [/INST] [This:O, particular:O, strain:O, of:O, Adware:O, was:O, found:O, in:O, 206:O, applications:O, ,:O, and:O, the:O, combined:O, download:O, count:O, has:O, reached:O, almost:O, 150:O, million: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: 'Google was swiftly notified and removed the infected applications from the Google Play Store .' [/INST] [Google:B-Organization, was:O, swiftly:O, notified:O, and:O, removed:O, the:O, infected:O, applications:O, from:O, the:O, Google:B-System, Play:I-System, Store: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: 'Inside the SDK The malware resides within the ‘ RXDrioder ’ Software Development Kit ( SDK ) , which is provided by ‘ addroider [ .' [/INST] [Inside:O, the:O, SDK:O, The:O, malware:O, resides:O, within:O, the:O, ‘:O, RXDrioder:O, ’:O, Software:O, Development:O, Kit:O, (:O, SDK:O, ):O, ,:O, which:O, is:O, provided:O, by:O, ‘:O, addroider: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 ’ as an ad-related SDK .' [/INST] []:I-Indicator, com:I-Indicator, ’:O, as:O, an:O, ad-related:O, SDK: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 believe the developers were scammed to use this malicious SDK , unaware of its content , leading to the fact that this campaign was not targeting a specific county or developed by the same developer .' [/INST] [We:O, believe:O, the:O, developers:O, were:O, scammed:O, to:O, use:O, this:O, malicious:O, SDK:O, ,:O, unaware:O, of:O, its:O, content:O, ,:O, leading:O, to:O, the:O, fact:O, that:O, this:O, campaign:O, was:O, not:O, targeting:O, a:O, specific:O, county:O, or:O, developed:O, by:O, the:O, same:O, developer: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 has been dubbed ‘ SimBad ’ due to the fact that a large portion of the infected applications are simulator games .' [/INST] [The:O, malware:O, has:O, been:O, dubbed:O, ‘:O, SimBad:B-Malware, ’:O, due:O, to:O, the:O, fact:O, that:O, a:O, large:O, portion:O, of:O, the:O, infected:O, applications:O, are:O, simulator:O, games: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 Infection Chain Once the user downloads and installs one of the infected applications , ‘ SimBad ’ registers itself to the ‘ BOOT_COMPLETE ’ and ‘ USER_PRESENT ’ intents , which lets ‘ SimBad ’ to perform actions after the device has finished booting and while the user is using his device respectively .' [/INST] [The:O, Infection:O, Chain:O, Once:O, the:O, user:O, downloads:O, and:O, installs:O, one:O, of:O, the:O, infected:O, applications:O, ,:O, ‘:O, SimBad:B-Malware, ’:O, registers:O, itself:O, to:O, the:O, ‘:O, BOOT_COMPLETE:O, ’:O, and:O, ‘:O, USER_PRESENT:O, ’:O, intents:O, ,:O, which:O, lets:O, ‘:O, SimBad:B-Malware, ’:O, to:O, perform:O, actions:O, after:O, the:O, device:O, has:O, finished:O, booting:O, and:O, while:O, the:O, user:O, is:O, using:O, his:O, device:O, respectively: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 installation , the malware connects to the designated Command and Control ( C & C ) server , and receives a command to perform .' [/INST] [After:O, installation:O, ,:O, the:O, malware:O, connects:O, to:O, the:O, designated:O, Command:O, and:O, Control:O, (:O, C:O, &:O, C:O, ):O, server:O, ,:O, and:O, receives:O, a:O, command:O, to:O, perform: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: '‘ SimBad ’ comes with a respected list of capabilities on the user ’ s device , such as removing the icon from the launcher , thus making it harder for the user to uninstall , start to display background ads and open a browser with a given URL .' [/INST] [‘:O, SimBad:B-Malware, ’:O, comes:O, with:O, a:O, respected:O, list:O, of:O, capabilities:O, on:O, the:O, user:O, ’:O, s:O, device:O, ,:O, such:O, as:O, removing:O, the:O, icon:O, from:O, the:O, launcher:O, ,:O, thus:O, making:O, it:O, harder:O, for:O, the:O, user:O, to:O, uninstall:O, ,:O, start:O, to:O, display:O, background:O, ads:O, and:O, open:O, a:O, browser:O, with:O, a:O, given:O, URL: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: 'What Does SimBad Do ?' [/INST] [What:O, Does:O, SimBad:B-Malware, Do: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: '‘ SimBad ’ has capabilities that can be divided into three groups – Show Ads , Phishing , and Exposure to other applications .' [/INST] [‘:O, SimBad:B-Malware, ’:O, has:O, capabilities:O, that:O, can:O, be:O, divided:O, into:O, three:O, groups:O, –:O, Show:O, Ads:O, ,:O, Phishing:O, ,:O, and:O, Exposure:O, to:O, other:O, applications:O, .:O] </s> |