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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: 'At the time of writing we had no evidence of an exploit being used to obtain root privileges , though it is possible that the attackers used some unseen component to implement this feature .' [/INST] [At:O, the:O, time:O, of:O, writing:O, we:O, had:O, no:O, evidence:O, of:O, an:O, exploit:O, being:O, used:O, to:O, obtain:O, root:O, privileges:O, ,:O, though:O, it:O, is:O, possible:O, that:O, the:O, attackers:O, used:O, some:O, unseen:O, component:O, to:O, implement:O, this:O, feature:O, .:O] </s>
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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: 'Here is a full list of possible commands that can be executed by the first module : Command name Description @ stop Stop IRC @ quit System.exit ( 0 ) @ start Start IRC @ server Set IRC server ( default value is “ irc.freenode.net ” ) , port is always 6667 @ boss Set IRC command and control nickname ( default value is “ ISeency ” ) @ nick Set IRC client nickname @ screen Report every time when screen is on ( enable/disable ) @ root Use root features ( enable/disable ) @ timer Set' [/INST] [Here:O, is:O, a:O, full:O, list:O, of:O, possible:O, commands:O, that:O, can:O, be:O, executed:O, by:O, the:O, first:O, module:O, ::O, Command:O, name:O, Description:O, @:O, stop:O, Stop:O, IRC:O, @:O, quit:O, System.exit:B-Indicator, (:I-Indicator, 0:I-Indicator, ):I-Indicator, @:O, start:O, Start:O, IRC:O, @:O, server:O, Set:O, IRC:O, server:O, (:O, default:O, value:O, is:O, “:O, irc.freenode.net:B-Indicator, ”:O, ):O, ,:O, port:O, is:O, always:O, 6667:O, @:O, boss:O, Set:O, IRC:O, command:O, and:O, control:O, nickname:O, (:O, default:O, value:O, is:O, “:O, ISeency:O, ”:O, ):O, @:O, nick:O, Set:O, IRC:O, client:O, nickname:O, @:O, screen:O, Report:O, every:O, time:O, when:O, screen:O, is:O, on:O, (:O, enable/disable:O, ):O, @:O, root:O, Use:O, root:O, features:O, (:O, enable/disable:O, ):O, @:O, timer:O, Set:O] </s>
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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: 'period of IRCService start @ hide Hide implant icon @ unhide Unhide implant icon @ run Execute specified shell @ broadcast Send command to the second module @ echo Write specified message to log @ install Download and copy specified component to the system path The implant uses a complex intent-based communication mechanism between its components to broadcast commands : Approximate graph of relationships between BusyGasper components Second ( main ) module This module writes a log of the command execution history to the file named “ lock ” , which is later exfiltrated' [/INST] [period:O, of:O, IRCService:O, start:O, @:O, hide:O, Hide:O, implant:O, icon:O, @:O, unhide:O, Unhide:O, implant:O, icon:O, @:O, run:O, Execute:O, specified:O, shell:O, @:O, broadcast:O, Send:O, command:O, to:O, the:O, second:O, module:O, @:O, echo:O, Write:O, specified:O, message:O, to:O, log:O, @:O, install:O, Download:O, and:O, copy:O, specified:O, component:O, to:O, the:O, system:O, path:O, The:O, implant:O, uses:O, a:O, complex:O, intent-based:O, communication:O, mechanism:O, between:O, its:O, components:O, to:O, broadcast:O, commands:O, ::O, Approximate:O, graph:O, of:O, relationships:O, between:O, BusyGasper:O, components:O, Second:O, (:O, main:O, ):O, module:O, This:O, module:O, writes:O, a:O, log:O, of:O, the:O, command:O, execution:O, history:O, to:O, the:O, file:O, named:O, “:O, lock:O, ”:O, ,:O, which:O, is:O, later:O, exfiltrated:O] </s>
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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: '.' [/INST] [.:O] </s>
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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: 'Below is a fragment of such a log : Log with specified command Log files can be uploaded to the FTP server and sent to the attacker ’ s email inbox .' [/INST] [Below:O, is:O, a:O, fragment:O, of:O, such:O, a:O, log:O, ::O, Log:O, with:O, specified:O, command:O, Log:O, files:O, can:O, be:O, uploaded:O, to:O, the:O, FTP:O, server:O, and:O, sent:O, to:O, the:O, attacker:O, ’:O, s:O, email:O, inbox:O, .:O] </s>
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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: 'It ’ s even possible to send log messages via SMS to the attacker ’ s number .' [/INST] [It:O, ’:O, s:O, even:O, possible:O, to:O, send:O, log:O, messages:O, via:O, SMS:O, to:O, the:O, attacker:O, ’:O, s:O, number:O, .:O] </s>
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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: 'As the screenshot above shows , the malware has its own command syntax that represents a combination of characters while the “ # ” symbol is a delimiter .' [/INST] [As:O, the:O, screenshot:O, above:O, shows:O, ,:O, the:O, malware:O, has:O, its:O, own:O, command:O, syntax:O, that:O, represents:O, a:O, combination:O, of:O, characters:O, while:O, the:O, “:O, #:O, ”:O, symbol:O, is:O, a:O, delimiter:O, .:O] </s>
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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: 'A full list of all possible commands with descriptions can be found in Appendix II below .' [/INST] [A:O, full:O, list:O, of:O, all:O, possible:O, commands:O, with:O, descriptions:O, can:O, be:O, found:O, in:O, Appendix:O, II:O, below:O, .:O] </s>
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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: 'The malware has all the popular capabilities of modern spyware .' [/INST] [The:O, malware:O, has:O, all:O, the:O, popular:O, capabilities:O, of:O, modern:O, spyware:O, .:O] </s>
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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: 'Below is a description of the most noteworthy : The implant is able to spy on all available device sensors and to log registered events .' [/INST] [Below:O, is:O, a:O, description:O, of:O, the:O, most:O, noteworthy:O, ::O, The:O, implant:O, is:O, able:O, to:O, spy:O, on:O, all:O, available:O, device:O, sensors:O, and:O, to:O, log:O, registered:O, events:O, .:O] </s>
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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: 'Moreover , there is a special handler for the accelerometer that is able to calculate and log the device ’ s speed : This feature is used in particular by the command “ tk0 ” that mutes the device , disables keyguard , turns off the brightness , uses wakelock and listens to device sensors .' [/INST] [Moreover:O, ,:O, there:O, is:O, a:O, special:O, handler:O, for:O, the:O, accelerometer:O, that:O, is:O, able:O, to:O, calculate:O, and:O, log:O, the:O, device:O, ’:O, s:O, speed:O, ::O, This:O, feature:O, is:O, used:O, in:O, particular:O, by:O, the:O, command:O, “:O, tk0:O, ”:O, that:O, mutes:O, the:O, device:O, ,:O, disables:O, keyguard:O, ,:O, turns:O, off:O, the:O, brightness:O, ,:O, uses:O, wakelock:O, and:O, listens:O, to:O, device:O, sensors:O, .:O] </s>
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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 allows it to silently execute any backdoor activity without the user knowing that the device is in an active state .' [/INST] [This:O, allows:O, it:O, to:O, silently:O, execute:O, any:O, backdoor:O, activity:O, without:O, the:O, user:O, knowing:O, that:O, the:O, device:O, is:O, in:O, an:O, active:O, state:O, .:O] </s>
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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: 'As soon as the user picks up the device , the implant will detect a motion event and execute the “ tk1 ” and “ input keyevent 3 ” commands .' [/INST] [As:O, soon:O, as:O, the:O, user:O, picks:O, up:O, the:O, device:O, ,:O, the:O, implant:O, will:O, detect:O, a:O, motion:O, event:O, and:O, execute:O, the:O, “:O, tk1:O, ”:O, and:O, “:O, input:O, keyevent:O, 3:O, ”:O, commands:O, .:O] </s>
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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: '“ tk1 ” will disable all the effects of the “ tk0 ” command , while “ input keyevent 3 ” is the shell command that simulates the pressing of the ‘ home ’ button so all the current activities will be minimized and the user won ’ t suspect anything .' [/INST] [“:O, tk1:O, ”:O, will:O, disable:O, all:O, the:O, effects:O, of:O, the:O, “:O, tk0:O, ”:O, command:O, ,:O, while:O, “:O, input:O, keyevent:O, 3:O, ”:O, is:O, the:O, shell:O, command:O, that:O, simulates:O, the:O, pressing:O, of:O, the:O, ‘:O, home:O, ’:O, button:O, so:O, all:O, the:O, current:O, activities:O, will:O, be:O, minimized:O, and:O, the:O, user:O, won:O, ’:O, t:O, suspect:O, anything:O, .:O] </s>
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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: 'Location services to enable ( GPS/network ) tracking : The email command and control protocol .' [/INST] [Location:O, services:O, to:O, enable:O, (:O, GPS/network:O, ):O, tracking:O, ::O, The:O, email:O, command:O, and:O, control:O, protocol:O, .:O] </s>
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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: 'The implant can log in to the attackers email inbox , parse emails for commands in a special “ Cmd ” folder and save any payloads to a device from email attachments .' [/INST] [The:O, implant:O, can:O, log:O, in:O, to:O, the:O, attackers:O, email:O, inbox:O, ,:O, parse:O, emails:O, for:O, commands:O, in:O, a:O, special:O, “:O, Cmd:O, ”:O, folder:O, and:O, save:O, any:O, payloads:O, to:O, a:O, device:O, from:O, email:O, attachments:O, .:O] </s>
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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: 'Accessing the “ Cmd ” folder in the attacker ’ s email box Moreover , it can send a specified file or all the gathered data from the victim device via email .' [/INST] [Accessing:O, the:O, “:O, Cmd:O, ”:O, folder:O, in:O, the:O, attacker:O, ’:O, s:O, email:O, box:O, Moreover:O, ,:O, it:O, can:O, send:O, a:O, specified:O, file:O, or:O, all:O, the:O, gathered:O, data:O, from:O, the:O, victim:O, device:O, via:O, email:O, .:O] </s>
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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: 'Emergency SMS commands .' [/INST] [Emergency:O, SMS:O, commands:O, .:O] </s>
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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: 'If an incoming SMS contains one of the following magic strings : ” 2736428734″ or ” 7238742800″ the malware will execute multiple initial commands : Keylogger implementation Keylogging is implemented in an original manner .' [/INST] [If:O, an:O, incoming:O, SMS:O, contains:O, one:O, of:O, the:O, following:O, magic:O, strings:O, ::O, ”:O, 2736428734″:B-Indicator, or:O, ”:O, 7238742800″:B-Indicator, the:O, malware:O, will:O, execute:O, multiple:O, initial:O, commands:O, ::O, Keylogger:O, implementation:O, Keylogging:O, is:O, implemented:O, in:O, an:O, original:O, manner:O, .:O] </s>
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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: 'Immediately after activation , the malware creates a textView element in a new window with the following layout parameters : All these parameters ensure the element is hidden from the user .' [/INST] [Immediately:O, after:O, activation:O, ,:O, the:O, malware:O, creates:O, a:O, textView:O, element:O, in:O, a:O, new:O, window:O, with:O, the:O, following:O, layout:O, parameters:O, ::O, All:O, these:O, parameters:O, ensure:O, the:O, element:O, is:O, hidden:O, from:O, the:O, user:O, .:O] </s>
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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: 'Then it adds onTouchListener to this textView and is able to process every user tap .' [/INST] [Then:O, it:O, adds:O, onTouchListener:O, to:O, this:O, textView:O, and:O, is:O, able:O, to:O, process:O, every:O, user:O, tap:O, .:O] </s>
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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: 'Interestingly , there is an allowlist of tapped activities : ui.ConversationActivity ui.ConversationListActivity SemcInCallScreen Quadrapop SocialPhonebookActivity The listener can operate with only coordinates , so it calculates pressed characters by matching given values with hardcoded ones : Additionally , if there is a predefined command , the keylogger can make a screenshot of the tapped display area : Manual access and operator menu There is a hidden menu ( Activity ) for controlling implant features that' [/INST] [Interestingly:O, ,:O, there:O, is:O, an:O, allowlist:O, of:O, tapped:O, activities:O, ::O, ui.ConversationActivity:O, ui.ConversationListActivity:O, SemcInCallScreen:O, Quadrapop:O, SocialPhonebookActivity:O, The:O, listener:O, can:O, operate:O, with:O, only:O, coordinates:O, ,:O, so:O, it:O, calculates:O, pressed:O, characters:O, by:O, matching:O, given:O, values:O, with:O, hardcoded:O, ones:O, ::O, Additionally:O, ,:O, if:O, there:O, is:O, a:O, predefined:O, command:O, ,:O, the:O, keylogger:O, can:O, make:O, a:O, screenshot:O, of:O, the:O, tapped:O, display:O, area:O, ::O, Manual:O, access:O, and:O, operator:O, menu:O, There:O, is:O, a:O, hidden:O, menu:O, (:O, Activity:O, ):O, for:O, controlling:O, implant:O, features:O, that:O] </s>
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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: 'looks like it was created for manual operator control .' [/INST] [looks:O, like:O, it:O, was:O, created:O, for:O, manual:O, operator:O, control:O, .:O] </s>
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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: 'To activate this menu the operator needs to call the hardcoded number “ 9909 ” from the infected device : A hidden menu then instantly appears on the device display : The operator can use this interface to type any command for execution .' [/INST] [To:O, activate:O, this:O, menu:O, the:O, operator:O, needs:O, to:O, call:O, the:O, hardcoded:O, number:O, “:O, 9909:O, ”:O, from:O, the:O, infected:O, device:O, ::O, A:O, hidden:O, menu:O, then:O, instantly:O, appears:O, on:O, the:O, device:O, display:O, ::O, The:O, operator:O, can:O, use:O, this:O, interface:O, to:O, type:O, any:O, command:O, for:O, execution:O, .:O] </s>
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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: 'It also shows a current malware log .' [/INST] [It:O, also:O, shows:O, a:O, current:O, malware:O, log:O, .:O] </s>
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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: 'Infrastructure FTP server The attackers used ftp : //213.174.157 [ .' [/INST] [Infrastructure:O, FTP:O, server:O, The:O, attackers:O, used:O, ftp:B-Indicator, ::I-Indicator, //213.174.157:I-Indicator, [:I-Indicator, .:I-Indicator] </s>
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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: '] 151/ as a command and control server .' [/INST] []:I-Indicator, 151/:I-Indicator, as:O, a:O, command:O, and:O, control:O, server:O, .:O] </s>
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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: 'The IP belongs to the free Russian web hosting service Ucoz .' [/INST] [The:O, IP:O, belongs:O, to:O, the:O, free:O, Russian:O, web:O, hosting:O, service:O, Ucoz:O, .:O] </s>
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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: 'Files Description CMDS * .txt Text files with commands to execute supersu.apk SuperSU ( eu.chainfire.supersu , https : //play.google.com/store/apps/details ?' [/INST] [Files:O, Description:O, CMDS:O, *:O, .txt:O, Text:O, files:O, with:O, commands:O, to:O, execute:O, supersu.apk:B-Indicator, SuperSU:O, (:O, eu.chainfire.supersu:B-Indicator, ,:O, https:B-Indicator, ::I-Indicator, //play.google.com/store/apps/details:I-Indicator, ?:I-Indicator] </s>
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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: 'id=eu.chainfire.supersu ) tool 246.us us.x SuperSU ELF binaries supersu.cfg supersu.cfg.ju supersu.cfg.old SuperSU configs with spyware implant mention bb.txt BusyBox v1.26.2 ELF file bdata.xml Config file for excluding malware components from Android battery saver feature Doze bdatas.apk Main implant module com.android.network.irc.apk Start implant module MobileManagerService.apk ASUS firmware system component ( clean ) mobilemanager.apk' [/INST] [id=eu.chainfire.supersu:I-Indicator, ):O, tool:O, 246.us:B-Indicator, us.x:B-Indicator, SuperSU:O, ELF:O, binaries:O, supersu.cfg:B-Indicator, supersu.cfg.ju:B-Indicator, supersu.cfg.old:B-Indicator, SuperSU:O, configs:O, with:O, spyware:O, implant:O, mention:O, bb.txt:B-Indicator, BusyBox:O, v1.26.2:O, ELF:O, file:O, bdata.xml:B-Indicator, Config:O, file:O, for:O, excluding:O, malware:O, components:O, from:O, Android:B-System, battery:O, saver:O, feature:O, Doze:O, bdatas.apk:B-Indicator, Main:O, implant:O, module:O, com.android.network.irc.apk:B-Indicator, Start:O, implant:O, module:O, MobileManagerService.apk:B-Indicator, ASUS:B-Organization, firmware:O, system:O, component:O, (:O, clean:O, ):O, mobilemanager.apk:B-Indicator] </s>
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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: 'Corrupted archive privapp.txt Looks like a list of system applications ( including spyware components ) from the infected device run-as.x run-as.y Run-as tool ELF file SuperSU config fragment for implant components and the busybox tool supersu.cfg : This config allows the implant to use all root features silently .' [/INST] [Corrupted:O, archive:O, privapp.txt:B-Indicator, Looks:O, like:O, a:O, list:O, of:O, system:O, applications:O, (:O, including:O, spyware:O, components:O, ):O, from:O, the:O, infected:O, device:O, run-as.x:B-Indicator, run-as.y:B-Indicator, Run-as:O, tool:O, ELF:O, file:O, SuperSU:O, config:O, fragment:O, for:O, implant:O, components:O, and:O, the:O, busybox:O, tool:O, supersu.cfg:B-Indicator, ::O, This:O, config:O, allows:O, the:O, implant:O, to:O, use:O, all:O, root:O, features:O, silently:O, .:O] </s>
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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: 'Content of bdata.xml file : It can be added to the /system/etc/sysconfig/ path to allowlist specified implant components from the battery saving system .' [/INST] [Content:O, of:O, bdata.xml:O, file:O, ::O, It:O, can:O, be:O, added:O, to:O, the:O, /system/etc/sysconfig/:B-Indicator, path:O, to:O, allowlist:O, specified:O, implant:O, components:O, from:O, the:O, battery:O, saving:O, system:O, .:O] </s>
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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: 'Email account A Gmail account with password is mentioned in the sample ’ s code : It contains the victim ’ s exfiltrated data and “ cmd ” directory with commands for victim devices .' [/INST] [Email:O, account:O, A:O, Gmail:B-System, account:O, with:O, password:O, is:O, mentioned:O, in:O, the:O, sample:O, ’:O, s:O, code:O, ::O, It:O, contains:O, the:O, victim:O, ’:O, s:O, exfiltrated:O, data:O, and:O, “:O, cmd:O, ”:O, directory:O, with:O, commands:O, for:O, victim:O, devices:O, .:O] </s>
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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: '10 million Android phones infected by all-powerful auto-rooting apps First detected in November , Shedun/HummingBad infections are surging .' [/INST] [10:O, million:O, Android:B-System, phones:O, infected:O, by:O, all-powerful:O, auto-rooting:O, apps:O, First:O, detected:O, in:O, November:O, ,:O, Shedun/HummingBad:B-Malware, infections:O, are:O, surging:O, .:O] </s>
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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: '7/7/2016 , 1:50 PM Security experts have documented a disturbing spike in a particularly virulent family of Android malware , with more than 10 million handsets infected and more than 286,000 of them in the US .' [/INST] [7/7/2016:O, ,:O, 1:50:O, PM:O, Security:O, experts:O, have:O, documented:O, a:O, disturbing:O, spike:O, in:O, a:O, particularly:O, virulent:O, family:O, of:O, Android:B-System, malware:O, ,:O, with:O, more:O, than:O, 10:O, million:O, handsets:O, infected:O, and:O, more:O, than:O, 286,000:O, of:O, them:O, in:O, the:O, US:O, .:O] </s>
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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: 'FURTHER READING New type of auto-rooting Android adware is nearly impossible to remove Researchers from security firm Check Point Software said the malware installs more than 50,000 fraudulent apps each day , displays 20 million malicious advertisements , and generates more than $ 300,000 per month in revenue .' [/INST] [FURTHER:O, READING:O, New:O, type:O, of:O, auto-rooting:O, Android:B-System, adware:O, is:O, nearly:O, impossible:O, to:O, remove:O, Researchers:O, from:O, security:O, firm:O, Check:B-Organization, Point:I-Organization, Software:I-Organization, said:O, the:O, malware:O, installs:O, more:O, than:O, 50,000:O, fraudulent:O, apps:O, each:O, day:O, ,:O, displays:O, 20:O, million:O, malicious:O, advertisements:O, ,:O, and:O, generates:O, more:O, than:O, $:O, 300,000:O, per:O, month:O, in:O, revenue:O, .:O] </s>
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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: 'The success is largely the result of the malware 's ability to silently root a large percentage of the phones it infects by exploiting vulnerabilities that remain unfixed in older versions of Android .' [/INST] [The:O, success:O, is:O, largely:O, the:O, result:O, of:O, the:O, malware:O, 's:O, ability:O, to:O, silently:O, root:O, a:O, large:O, percentage:O, of:O, the:O, phones:O, it:O, infects:O, by:O, exploiting:O, vulnerabilities:B-Vulnerability, that:I-Vulnerability, remain:I-Vulnerability, unfixed:I-Vulnerability, in:I-Vulnerability, older:I-Vulnerability, versions:I-Vulnerability, of:I-Vulnerability, Android:I-Vulnerability, .:O] </s>
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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: 'The Check Point researchers have dubbed the malware family , HummingBad , '' but researchers from mobile security company Lookout say HummingBad is in fact Shedun , a family of auto-rooting malware that came to light last November and had already infected a large number of devices .' [/INST] [The:O, Check:B-Organization, Point:I-Organization, researchers:O, have:O, dubbed:O, the:O, malware:O, family:O, ,:O, HummingBad:B-Malware, ,:O, '':O, but:O, researchers:O, from:O, mobile:O, security:O, company:O, Lookout:B-Organization, say:O, HummingBad:B-Malware, is:O, in:O, fact:O, Shedun:B-Malware, ,:O, a:O, family:O, of:O, auto-rooting:O, malware:O, that:O, came:O, to:O, light:O, last:O, November:O, and:O, had:O, already:O, infected:O, a:O, large:O, number:O, of:O, devices:O, .:O] </s>
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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: 'Update Jul 11 2016 8:32 : On Monday , a Checkpoint representative disputed Lookout 's contention and pointed to this blog post from security firm Eleven Paths as support .' [/INST] [Update:O, Jul:O, 11:O, 2016:O, 8:32:O, ::O, On:O, Monday:O, ,:O, a:O, Checkpoint:B-Organization, representative:O, disputed:O, Lookout:B-Organization, 's:O, contention:O, and:O, pointed:O, to:O, this:O, blog:O, post:O, from:O, security:O, firm:O, Eleven:B-Organization, Paths:I-Organization, as:O, support:O, .:O] </s>
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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: 'The blog post said HummingBad , uses a completely different infrastructure with little in common '' with Shedun .' [/INST] [The:O, blog:O, post:O, said:O, HummingBad:B-Malware, ,:O, uses:O, a:O, completely:O, different:O, infrastructure:O, with:O, little:O, in:O, common:O, '':O, with:O, Shedun:I-Malware, .:O] </s>
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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: 'In an e-mail , a Lookout representative stood by its analysis and said company researchers planned to publish an in-depth response in the coming days .' [/INST] [In:O, an:O, e-mail:O, ,:O, a:O, Lookout:B-Organization, representative:O, stood:O, by:O, its:O, analysis:O, and:O, said:O, company:O, researchers:O, planned:O, to:O, publish:O, an:O, in-depth:O, response:O, in:O, the:O, coming:O, days:O, .:O] </s>
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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: 'For the past five months , Check Point researchers have quietly observed the China-based advertising company behind HummingBad in several ways , including by infiltrating the command and control servers it uses .' [/INST] [For:O, the:O, past:O, five:O, months:O, ,:O, Check:B-Organization, Point:I-Organization, researchers:O, have:O, quietly:O, observed:O, the:O, China-based:O, advertising:O, company:O, behind:O, HummingBad:B-Malware, in:O, several:O, ways:O, ,:O, including:O, by:O, infiltrating:O, the:O, command:O, and:O, control:O, servers:O, it:O, uses:O, .:O] </s>
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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: 'The researchers say the malware uses the unusually tight control it gains over infected devices to create windfall profits and steadily increase its numbers .' [/INST] [The:O, researchers:O, say:O, the:O, malware:O, uses:O, the:O, unusually:O, tight:O, control:O, it:O, gains:O, over:O, infected:O, devices:O, to:O, create:O, windfall:O, profits:O, and:O, steadily:O, increase:O, its:O, numbers:O, .:O] </s>
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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: 'HummingBad does this by silently installing promoted apps on infected phones , defrauding legitimate mobile advertisers , and creating fraudulent statistics inside the official Google Play Store .' [/INST] [HummingBad:B-Malware, does:O, this:O, by:O, silently:O, installing:O, promoted:O, apps:O, on:O, infected:O, phones:O, ,:O, defrauding:O, legitimate:O, mobile:O, advertisers:O, ,:O, and:O, creating:O, fraudulent:O, statistics:O, inside:O, the:O, official:O, Google:B-System, Play:I-System, Store:I-System, .:O] </s>
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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: ', Accessing these devices and their sensitive data creates a new and steady stream of revenue for cybercriminals , '' Check Point researchers wrote in a recently published report .' [/INST] [,:O, Accessing:O, these:O, devices:O, and:O, their:O, sensitive:O, data:O, creates:O, a:O, new:O, and:O, steady:O, stream:O, of:O, revenue:O, for:O, cybercriminals:O, ,:O, '':O, Check:I-Organization, Point:I-Organization, researchers:O, wrote:O, in:O, a:O, recently:O, published:O, report:O, .:O] </s>
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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: ', Emboldened by financial and technological independence , their skillsets will advance–putting end users , enterprises , and government agencies at risk .' [/INST] [,:O, Emboldened:O, by:O, financial:O, and:O, technological:O, independence:O, ,:O, their:O, skillsets:O, will:O, advance–putting:O, end:O, users:O, ,:O, enterprises:O, ,:O, and:O, government:O, agencies:O, at:O, risk:O, .:O] </s>
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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: ''' The report said HummingBad apps are developed by Yingmob , a Chinese mobile ad server company that other researchers claim is behind the Yinspector iOS malware .' [/INST] ['':O, The:O, report:O, said:O, HummingBad:B-Malware, apps:O, are:O, developed:O, by:O, Yingmob:B-Organization, ,:O, a:O, Chinese:O, mobile:O, ad:O, server:O, company:O, that:O, other:O, researchers:O, claim:O, is:O, behind:O, the:O, Yinspector:B-Malware, iOS:B-System, malware:O, .:O] </s>
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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: 'HummingBad sends notifications to Umeng , a tracking and analytics service attackers use to manage their campaign .' [/INST] [HummingBad:B-Malware, sends:O, notifications:O, to:O, Umeng:O, ,:O, a:O, tracking:O, and:O, analytics:O, service:O, attackers:O, use:O, to:O, manage:O, their:O, campaign:O, .:O] </s>
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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: 'Check Point analyzed Yingmob ’ s Umeng account to gain further insights into the HummingBad campaign and found that beyond the 10 million devices under the control of malicious apps , Yingmob has non-malicious apps installed on another 75 million or so devices .' [/INST] [Check:B-Organization, Point:I-Organization, analyzed:O, Yingmob:B-Organization, ’:O, s:O, Umeng:O, account:O, to:O, gain:O, further:O, insights:O, into:O, the:O, HummingBad:B-Malware, campaign:O, and:O, found:O, that:O, beyond:O, the:O, 10:O, million:O, devices:O, under:O, the:O, control:O, of:O, malicious:O, apps:O, ,:O, Yingmob:B-Organization, has:O, non-malicious:O, apps:O, installed:O, on:O, another:O, 75:O, million:O, or:O, so:O, devices:O, .:O] </s>
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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: 'The researchers wrote : While profit is powerful motivation for any attacker , Yingmob ’ s apparent self-sufficiency and organizational structure make it well-positioned to expand into new business ventures , including productizing the access to the 85 million Android devices it controls .' [/INST] [The:O, researchers:O, wrote:O, ::O, While:O, profit:O, is:O, powerful:O, motivation:O, for:O, any:O, attacker:O, ,:O, Yingmob:B-Organization, ’:O, s:O, apparent:O, self-sufficiency:O, and:O, organizational:O, structure:O, make:O, it:O, well-positioned:O, to:O, expand:O, into:O, new:O, business:O, ventures:O, ,:O, including:O, productizing:O, the:O, access:O, to:O, the:O, 85:O, million:O, Android:B-System, devices:O, it:O, controls:O, .:O] </s>
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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 alone would attract a whole new audience–and a new stream of revenue–for Yingmob .' [/INST] [This:O, alone:O, would:O, attract:O, a:O, whole:O, new:O, audience–and:O, a:O, new:O, stream:O, of:O, revenue–for:O, Yingmob:B-Organization, .:O] </s>
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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: 'Quick , easy access to sensitive data on mobile devices connected to enterprises and government agencies around the globe is extremely attractive to cybercriminals and hacktivists .' [/INST] [Quick:O, ,:O, easy:O, access:O, to:O, sensitive:O, data:O, on:O, mobile:O, devices:O, connected:O, to:O, enterprises:O, and:O, government:O, agencies:O, around:O, the:O, globe:O, is:O, extremely:O, attractive:O, to:O, cybercriminals:O, and:O, hacktivists:O, .:O] </s>
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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: 'Drive-by downloads and multiple rooting exploits The malware uses a variety of methods to infect devices .' [/INST] [Drive-by:O, downloads:O, and:O, multiple:O, rooting:O, exploits:O, The:O, malware:O, uses:O, a:O, variety:O, of:O, methods:O, to:O, infect:O, devices:O, .:O] </s>
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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: 'One involves drive-by downloads , possibly on booby-trapped porn sites .' [/INST] [One:O, involves:O, drive-by:O, downloads:O, ,:O, possibly:O, on:O, booby-trapped:O, porn:O, sites:O, .:O] </s>
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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: 'The attacks use multiple exploits in an attempt to gain root access on a device .' [/INST] [The:O, attacks:O, use:O, multiple:O, exploits:O, in:O, an:O, attempt:O, to:O, gain:O, root:O, access:O, on:O, a:O, device:O, .:O] </s>
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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: 'When rooting fails , a second component delivers a fake system update notification in hopes of tricking users into granting HummingBad system-level permissions .' [/INST] [When:O, rooting:O, fails:O, ,:O, a:O, second:O, component:O, delivers:O, a:O, fake:O, system:O, update:O, notification:O, in:O, hopes:O, of:O, tricking:O, users:O, into:O, granting:O, HummingBad:B-Malware, system-level:O, permissions:O, .:O] </s>
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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: 'Whether or not rooting succeeds , HummingBad downloads a large number of apps .' [/INST] [Whether:O, or:O, not:O, rooting:O, succeeds:O, ,:O, HummingBad:B-Malware, downloads:O, a:O, large:O, number:O, of:O, apps:O, .:O] </s>
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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: 'In some cases , malicious components are dynamically downloaded onto a device after an infected app is installed .' [/INST] [In:O, some:O, cases:O, ,:O, malicious:O, components:O, are:O, dynamically:O, downloaded:O, onto:O, a:O, device:O, after:O, an:O, infected:O, app:O, is:O, installed:O, .:O] </s>
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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: 'From there , infected phones display illegitimate ads and install fraudulent apps after certain events , such as rebooting , the screen turning on or off , a detection that the user is present , or a change in Internet connectivity .' [/INST] [From:O, there:O, ,:O, infected:O, phones:O, display:O, illegitimate:O, ads:O, and:O, install:O, fraudulent:O, apps:O, after:O, certain:O, events:O, ,:O, such:O, as:O, rebooting:O, ,:O, the:O, screen:O, turning:O, on:O, or:O, off:O, ,:O, a:O, detection:O, that:O, the:O, user:O, is:O, present:O, ,:O, or:O, a:O, change:O, in:O, Internet:O, connectivity:O, .:O] </s>
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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: 'HummingBad also has the ability to inject code into Google Play to tamper with its ratings and statistics .' [/INST] [HummingBad:B-Malware, also:O, has:O, the:O, ability:O, to:O, inject:O, code:O, into:O, Google:B-System, Play:I-System, to:O, tamper:O, with:O, its:O, ratings:O, and:O, statistics:O, .:O] </s>
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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: 'It does this by using infected devices to imitate clicks on the install , buy , and accept buttons .' [/INST] [It:O, does:O, this:O, by:O, using:O, infected:O, devices:O, to:O, imitate:O, clicks:O, on:O, the:O, install:O, ,:O, buy:O, ,:O, and:O, accept:O, buttons:O, .:O] </s>
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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: 'Many of the 10 million infected phones are running old versions of Android and reside in China ( 1.6 million ) and India ( 1.35 million ) .' [/INST] [Many:O, of:O, the:O, 10:O, million:O, infected:O, phones:O, are:O, running:O, old:O, versions:O, of:O, Android:B-System, and:O, reside:O, in:O, China:O, (:O, 1.6:O, million:O, ):O, and:O, India:O, (:O, 1.35:O, million:O, ):O, .:O] </s>
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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: 'Still , US-based infected phones total almost 287,000 .' [/INST] [Still:O, ,:O, US-based:O, infected:O, phones:O, total:O, almost:O, 287,000:O, .:O] </s>
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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: 'The most widely infected major Android versions are KitKat with 50 percent , followed by Jelly Bean with 40 percent .' [/INST] [The:O, most:O, widely:O, infected:O, major:O, Android:B-System, versions:O, are:O, KitKat:B-System, with:O, 50:O, percent:O, ,:O, followed:O, by:O, Jelly:B-System, Bean:I-System, with:O, 40:O, percent:O, .:O] </s>
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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: 'Lollipop has 7 percent , Ice Cream Sandwich has 2 percent , and Marshmallow has 1 percent .' [/INST] [Lollipop:B-System, has:O, 7:O, percent:O, ,:O, Ice:B-System, Cream:I-System, Sandwich:I-System, has:O, 2:O, percent:O, ,:O, and:O, Marshmallow:B-System, has:O, 1:O, percent:O, .:O] </s>
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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: 'It 's often hard for average users to know if their phones have been rooted , and Shedun apps often wait some period of time before displaying obtrusive ads or installing apps .' [/INST] [It:O, 's:O, often:O, hard:O, for:O, average:O, users:O, to:O, know:O, if:O, their:O, phones:O, have:O, been:O, rooted:O, ,:O, and:O, Shedun:B-Malware, apps:O, often:O, wait:O, some:O, period:O, of:O, time:O, before:O, displaying:O, obtrusive:O, ads:O, or:O, installing:O, apps:O, .:O] </s>
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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: 'The best bet for Readers who want to make sure their phone is n't infected is to scan their phones using the free version of the Lookout Security and Antivirus app .' [/INST] [The:O, best:O, bet:O, for:O, Readers:O, who:O, want:O, to:O, make:O, sure:O, their:O, phone:O, is:O, n't:O, infected:O, is:O, to:O, scan:O, their:O, phones:O, using:O, the:O, free:O, version:O, of:O, the:O, Lookout:B-Organization, Security:O, and:O, Antivirus:O, app:O, .:O] </s>
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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: 'Android malware has drastically lower rates of success when app installations outside of Google Play are barred .' [/INST] [Android:B-System, malware:O, has:O, drastically:O, lower:O, rates:O, of:O, success:O, when:O, app:O, installations:O, outside:O, of:O, Google:B-System, Play:I-System, are:O, barred:O, .:O] </s>
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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: 'Readers should carefully think through the risks before changing this default setting .' [/INST] [Readers:O, should:O, carefully:O, think:O, through:O, the:O, risks:O, before:O, changing:O, this:O, default:O, setting:O, .:O] </s>
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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: 'Top 20 countries targeted by Hummingbad/Shedun .' [/INST] [Top:O, 20:O, countries:O, targeted:O, by:O, Hummingbad/Shedun:B-Malware, .:O] </s>
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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: 'Enlarge / Top 20 countries targeted by Hummingbad/Shedun .' [/INST] [Enlarge:O, /:O, Top:O, 20:O, countries:O, targeted:O, by:O, Hummingbad/Shedun:B-Malware, .:O] </s>
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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: 'Check Point Software Hummingbad/Shedun infections by Android version .' [/INST] [Check:B-Organization, Point:I-Organization, Software:I-Organization, Hummingbad/Shedun:B-Malware, infections:O, by:O, Android:B-System, version:O, .:O] </s>
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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: 'Enlarge / Hummingbad/Shedun infections by Android version .' [/INST] [Enlarge:O, /:O, Hummingbad/Shedun:B-Malware, infections:O, by:O, Android:B-System, version:O, .:O] </s>
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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: 'Check Point Software So far , HummingBad has been observed using its highly privileged status only to engage in click fraud , display pop-up ads , tamper with Google Play , and install additional apps that do more of the same .' [/INST] [Check:B-Organization, Point:I-Organization, Software:I-Organization, So:O, far:O, ,:O, HummingBad:B-Malware, has:O, been:O, observed:O, using:O, its:O, highly:O, privileged:O, status:O, only:O, to:O, engage:O, in:O, click:O, fraud:O, ,:O, display:O, pop-up:O, ads:O, ,:O, tamper:O, with:O, Google:B-System, Play:I-System, ,:O, and:O, install:O, additional:O, apps:O, that:O, do:O, more:O, of:O, the:O, same:O, .:O] </s>
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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: 'But there 's little stopping it from doing much worse .' [/INST] [But:O, there:O, 's:O, little:O, stopping:O, it:O, from:O, doing:O, much:O, worse:O, .:O] </s>
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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: 'That 's because the malware roots most of the phones it infects , a process that subverts key security mechanisms built into Android .' [/INST] [That:O, 's:O, because:O, the:O, malware:O, roots:O, most:O, of:O, the:O, phones:O, it:O, infects:O, ,:O, a:O, process:O, that:O, subverts:O, key:O, security:O, mechanisms:O, built:O, into:O, Android:B-System, .:O] </s>
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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: 'Under a model known as sandboxing , most Android apps are n't permitted to access passwords or other data available to most other apps .' [/INST] [Under:O, a:O, model:O, known:O, as:O, sandboxing:O, ,:O, most:O, Android:B-System, apps:O, are:O, n't:O, permitted:O, to:O, access:O, passwords:O, or:O, other:O, data:O, available:O, to:O, most:O, other:O, apps:O, .:O] </s>
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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: 'System applications with root , by contrast , have super-user permissions that allow them to break out of such sandboxes .' [/INST] [System:O, applications:O, with:O, root:O, ,:O, by:O, contrast:O, ,:O, have:O, super-user:O, permissions:O, that:O, allow:O, them:O, to:O, break:O, out:O, of:O, such:O, sandboxes:O, .:O] </s>
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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: 'From there , root-level apps can read or modify data and resources that would be off-limits to normal apps .' [/INST] [From:O, there:O, ,:O, root-level:O, apps:O, can:O, read:O, or:O, modify:O, data:O, and:O, resources:O, that:O, would:O, be:O, off-limits:O, to:O, normal:O, apps:O, .:O] </s>
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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: 'As Lookout first reported more than eight months ago , the problem with Shedun/HummingBad and similar malicious app families that silently exploit Android rooting vulnerabilities is that the infections can survive normal factory resets .' [/INST] [As:O, Lookout:B-Organization, first:O, reported:O, more:O, than:O, eight:O, months:O, ago:O, ,:O, the:O, problem:O, with:O, Shedun/HummingBad:B-Malware, and:O, similar:O, malicious:O, app:O, families:O, that:O, silently:O, exploit:O, Android:B-Vulnerability, rooting:I-Vulnerability, vulnerabilities:I-Vulnerability, is:O, that:O, the:O, infections:O, can:O, survive:O, normal:O, factory:O, resets:O, .:O] </s>
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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: 'Lookout said in its own blog post published Wednesday that its threat detection network has recently observed a surge of Shedun attacks , indicating the scourge wo n't be going away any time soon .' [/INST] [Lookout:B-Organization, said:O, in:O, its:O, own:O, blog:O, post:O, published:O, Wednesday:O, that:O, its:O, threat:O, detection:O, network:O, has:O, recently:O, observed:O, a:O, surge:O, of:O, Shedun:B-Malware, attacks:O, ,:O, indicating:O, the:O, scourge:O, wo:O, n't:O, be:O, going:O, away:O, any:O, time:O, soon:O, .:O] </s>
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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: 'An investigation of Chrysaor Malware on Android 03 April 2017 Google is constantly working to improve our systems that protect users from Potentially Harmful Applications ( PHAs ) .' [/INST] [An:O, investigation:O, of:O, Chrysaor:B-Malware, Malware:O, on:O, Android:B-System, 03:O, April:O, 2017:O, Google:B-Organization, is:O, constantly:O, working:O, to:O, improve:O, our:O, systems:O, that:O, protect:O, users:O, from:O, Potentially:O, Harmful:O, Applications:O, (:O, PHAs:O, ):O, .:O] </s>
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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: 'Usually , PHA authors attempt to install their harmful apps on as many devices as possible .' [/INST] [Usually:O, ,:O, PHA:O, authors:O, attempt:O, to:O, install:O, their:O, harmful:O, apps:O, on:O, as:O, many:O, devices:O, as:O, possible:O, .:O] </s>
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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: 'However , a few PHA authors spend substantial effort , time , and money to create and install their harmful app on one or a very small number of devices .' [/INST] [However:O, ,:O, a:O, few:O, PHA:O, authors:O, spend:O, substantial:O, effort:O, ,:O, time:O, ,:O, and:O, money:O, to:O, create:O, and:O, install:O, their:O, harmful:O, app:O, on:O, one:O, or:O, a:O, very:O, small:O, number:O, of:O, devices:O, .:O] </s>
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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 is known as a targeted attack .' [/INST] [This:O, is:O, known:O, as:O, a:O, targeted:O, attack:O, .:O] </s>
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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: 'In this blog post , we describe Chrysaor , a newly discovered family of spyware that was used in a targeted attack on a small number of Android devices , and how investigations like this help Google protect Android users from a variety of threats .' [/INST] [In:O, this:O, blog:O, post:O, ,:O, we:O, describe:O, Chrysaor:B-Malware, ,:O, a:O, newly:O, discovered:O, family:O, of:O, spyware:O, that:O, was:O, used:O, in:O, a:O, targeted:O, attack:O, on:O, a:O, small:O, number:O, of:O, Android:B-System, devices:O, ,:O, and:O, how:O, investigations:O, like:O, this:O, help:O, Google:B-Organization, protect:O, Android:B-System, users:O, from:O, a:O, variety:O, of:O, threats:O, .:O] </s>
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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: 'What is Chrysaor ?' [/INST] [What:O, is:O, Chrysaor:B-Malware, ?:O] </s>
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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: 'Chrysaor is spyware believed to be created by NSO Group Technologies , specializing in the creation and sale of software and infrastructure for targeted attacks .' [/INST] [Chrysaor:B-Malware, is:O, spyware:O, believed:O, to:O, be:O, created:O, by:O, NSO:B-Organization, Group:I-Organization, Technologies:I-Organization, ,:O, specializing:O, in:O, the:O, creation:O, and:O, sale:O, of:O, software:O, and:O, infrastructure:O, for:O, targeted:O, attacks:O, .:O] </s>
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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: 'Chrysaor is believed to be related to the Pegasus spyware that was first identified on iOS and analyzed by Citizen Lab and Lookout .' [/INST] [Chrysaor:B-Malware, is:O, believed:O, to:O, be:O, related:O, to:O, the:O, Pegasus:B-Malware, spyware:O, that:O, was:O, first:O, identified:O, on:O, iOS:B-System, and:O, analyzed:O, by:O, Citizen:B-Organization, Lab:I-Organization, and:O, Lookout:B-Organization, .:O] </s>
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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: 'Late last year , after receiving a list of suspicious package names from Lookout , we discovered that a few dozen Android devices may have installed an application related to Pegasus , which we named Chrysaor .' [/INST] [Late:O, last:O, year:O, ,:O, after:O, receiving:O, a:O, list:O, of:O, suspicious:O, package:O, names:O, from:O, Lookout:B-Organization, ,:O, we:O, discovered:O, that:O, a:O, few:O, dozen:O, Android:B-System, devices:O, may:O, have:O, installed:O, an:O, application:O, related:O, to:O, Pegasus:B-Malware, ,:O, which:O, we:O, named:O, Chrysaor:B-Malware, .:O] </s>
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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: 'Although the applications were never available in Google Play , we immediately identified the scope of the problem by using Verify Apps .' [/INST] [Although:O, the:O, applications:O, were:O, never:O, available:O, in:O, Google:B-System, Play:I-System, ,:O, we:O, immediately:O, identified:O, the:O, scope:O, of:O, the:O, problem:O, by:O, using:O, Verify:B-System, Apps:I-System, .:O] </s>
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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: 'We gathered information from affected devices , and concurrently , attempted to acquire Chrysaor apps to better understand its impact on users .' [/INST] [We:O, gathered:O, information:O, from:O, affected:O, devices:O, ,:O, and:O, concurrently:O, ,:O, attempted:O, to:O, acquire:O, Chrysaor:B-Malware, apps:O, to:O, better:O, understand:O, its:O, impact:O, on:O, users:O, .:O] </s>
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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: 'We 've contacted the potentially affected users , disabled the applications on affected devices , and implemented changes in Verify Apps to protect all users .' [/INST] [We:O, 've:O, contacted:O, the:O, potentially:O, affected:O, users:O, ,:O, disabled:O, the:O, applications:O, on:O, affected:O, devices:O, ,:O, and:O, implemented:O, changes:O, in:O, Verify:B-System, Apps:I-System, to:O, protect:O, all:O, users:O, .:O] </s>
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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: 'What is the scope of Chrysaor ?' [/INST] [What:O, is:O, the:O, scope:O, of:O, Chrysaor:B-Malware, ?:O] </s>
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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: 'Chrysaor was never available in Google Play and had a very low volume of installs outside of Google Play .' [/INST] [Chrysaor:B-Malware, was:O, never:O, available:O, in:O, Google:B-System, Play:I-System, and:O, had:O, a:O, very:O, low:O, volume:O, of:O, installs:O, outside:O, of:O, Google:B-System, Play:I-System, .:O] </s>
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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: 'Among the over 1.4 billion devices protected by Verify Apps , we observed fewer than 3 dozen installs of Chrysaor on victim devices .' [/INST] [Among:O, the:O, over:O, 1.4:O, billion:O, devices:O, protected:O, by:O, Verify:B-System, Apps:I-System, ,:O, we:O, observed:O, fewer:O, than:O, 3:O, dozen:O, installs:O, of:O, Chrysaor:B-Malware, on:O, victim:O, devices:O, .:O] </s>
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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: 'These devices were located in the following countries : How we protect you To protect Android devices and users , Google Play provides a complete set of security services that update outside of platform releases .' [/INST] [These:O, devices:O, were:O, located:O, in:O, the:O, following:O, countries:O, ::O, How:O, we:O, protect:O, you:O, To:O, protect:O, Android:B-System, devices:O, and:O, users:O, ,:O, Google:B-System, Play:I-System, provides:O, a:O, complete:O, set:O, of:O, security:O, services:O, that:O, update:O, outside:O, of:O, platform:O, releases:O, .:O] </s>
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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: 'Users do n't have to install any additional security services to keep their devices safe .' [/INST] [Users:O, do:O, n't:O, have:O, to:O, install:O, any:O, additional:O, security:O, services:O, to:O, keep:O, their:O, devices:O, safe:O, .:O] </s>
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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: 'In 2016 , these services protected over 1.4 billion devices , making Google one of the largest providers of on-device security services in the world : Identify PHAs using people , systems in the cloud , and data sent to us from devices Warn users about or blocking users from installing PHAs Continually scan devices for PHAs and other harmful threats Additionally , we are providing detailed technical information to help the security industry in our collective work against PHAs .' [/INST] [In:O, 2016:O, ,:O, these:O, services:O, protected:O, over:O, 1.4:O, billion:O, devices:O, ,:O, making:O, Google:B-Organization, one:O, of:O, the:O, largest:O, providers:O, of:O, on-device:O, security:O, services:O, in:O, the:O, world:O, ::O, Identify:O, PHAs:O, using:O, people:O, ,:O, systems:O, in:O, the:O, cloud:O, ,:O, and:O, data:O, sent:O, to:O, us:O, from:O, devices:O, Warn:O, users:O, about:O, or:O, blocking:O, users:O, from:O, installing:O, PHAs:O, Continually:O, scan:O, devices:O, for:O, PHAs:O, and:O, other:O, harmful:O, threats:O, Additionally:O, ,:O, we:O, are:O, providing:O, detailed:O, technical:O, information:O, to:O, help:O, the:O, security:O, industry:O, in:O, our:O, collective:O, work:O, against:O, PHAs:O, .:O] </s>
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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: 'What do I need to do ?' [/INST] [What:O, do:O, I:O, need:O, to:O, do:O, ?:O] </s>
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