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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 registrant contact details of the C & C domains used in the campaign , for instance , were masked .' [/INST] [The:O, registrant:O, contact:O, details:O, of:O, the:O, C:O, &:O, C:O, domains:O, used:O, in:O, the:O, campaign:O, ,:O, for:O, instance:O, ,:O, were:O, masked: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 C & C server IP addresses used also appear to be disparate , as they were located in many European countries like Russia , France , Holland , and Germany .' [/INST] [The:O, C:O, &:O, C:O, server:O, IP:O, addresses:O, used:O, also:O, appear:O, to:O, be:O, disparate:O, ,:O, as:O, they:O, were:O, located:O, in:O, many:O, European:O, countries:O, like:O, Russia:O, ,:O, France:O, ,:O, Holland:O, ,:O, and:O, Germany: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 ’ s not a definite correlation , but Bouncing Golf also seems to have a connection with Domestic Kitten due to similarities we found in their code .' [/INST] [It:O, ’:O, s:O, not:O, a:O, definite:O, correlation:O, ,:O, but:O, Bouncing:B-Malware, Golf:I-Malware, also:O, seems:O, to:O, have:O, a:O, connection:O, with:O, Domestic:B-Malware, Kitten:I-Malware, due:O, to:O, similarities:O, we:O, found:O, in:O, their:O, code:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'For example , the Android malware that both deploy share the same strings of code for their decoding algorithm .' [/INST] [For:O, example:O, ,:O, the:O, Android:B-System, malware:O, that:O, both:O, deploy:O, share:O, the:O, same:O, strings:O, of:O, code:O, for:O, their:O, decoding: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: 'The data that Domestic Kitten steals follows a similar format with Bouncing Golf ’ s , with each type of data having a unique identifying character .' [/INST] [The:O, data:O, that:O, Domestic:B-Malware, Kitten:I-Malware, steals:O, follows:O, a:O, similar:O, format:O, with:O, Bouncing:B-Malware, Golf:I-Malware, ’:O, s:O, ,:O, with:O, each:O, type:O, of:O, data:O, having:O, a:O, unique:O, identifying:O, character: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 ’ s also worth noting that both campaigns repackage apps that are commonly used in their target ’ s countries , such as Telegram , Kik , and Plus messaging apps .' [/INST] [It:O, ’:O, s:O, also:O, worth:O, noting:O, that:O, both:O, campaigns:O, repackage:O, apps:O, that:O, are:O, commonly:O, used:O, in:O, their:O, target:O, ’:O, s:O, countries:O, ,:O, such:O, as:O, Telegram:B-System, ,:O, Kik:B-System, ,:O, and:O, Plus:B-System, messaging:O, apps:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Figure 8 .' [/INST] [Figure:O, 8: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: 'Code snippets showing : the decoding algorithm shared by both Bouncing Golf and Domestic Kitten ( top ) , the format of data that Domestic Kitten ’ s malware targets to steal ( center ) , and how both Bouncing Golf ( bottom left ) and Domestic Kitten ( bottom right ) use , , as a separator in their command strings .' [/INST] [Code:O, snippets:O, showing:O, ::O, the:O, decoding:O, algorithm:O, shared:O, by:O, both:O, Bouncing:B-Malware, Golf:I-Malware, and:O, Domestic:B-Malware, Kitten:I-Malware, (:O, top:O, ):O, ,:O, the:O, format:O, of:O, data:O, that:O, Domestic:B-Malware, Kitten:I-Malware, ’:O, s:O, malware:O, targets:O, to:O, steal:O, (:O, center:O, ):O, ,:O, and:O, how:O, both:O, Bouncing:B-Malware, Golf:I-Malware, (:O, bottom:O, left:O, ):O, and:O, Domestic:B-Malware, Kitten:I-Malware, (:O, bottom:O, right:O, ):O, use:O, ,:O, ,:O, as:O, a:O, separator:O, in:O, their:O, command:O, strings: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 we ’ ve seen in last year ’ s mobile threat landscape , we expect more cyberespionage campaigns targeting the mobile platform given its ubiquity , employing tried-and-tested techniques to lure unwitting users .' [/INST] [As:O, we:O, ’:O, ve:O, seen:O, in:O, last:O, year:O, ’:O, s:O, mobile:O, threat:O, landscape:O, ,:O, we:O, expect:O, more:O, cyberespionage:O, campaigns:O, targeting:O, the:O, mobile:O, platform:O, given:O, its:O, ubiquity:O, ,:O, employing:O, tried-and-tested:O, techniques:O, to:O, lure:O, unwitting:O, users: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 extent of information that these kinds of threats can steal is also significant , as it lets attackers virtually take over a compromised device .' [/INST] [The:O, extent:O, of:O, information:O, that:O, these:O, kinds:O, of:O, threats:O, can:O, steal:O, is:O, also:O, significant:O, ,:O, as:O, it:O, lets:O, attackers:O, virtually:O, take:O, over:O, a:O, compromised: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: 'Users should adopt best practices , while organizations should ensure that they balance the need for mobility and the importance of security .' [/INST] [Users:O, should:O, adopt:O, best:O, practices:O, ,:O, while:O, organizations:O, should:O, ensure:O, that:O, they:O, balance:O, the:O, need:O, for:O, mobility:O, and:O, the:O, importance:O, of:O, security: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: 'End users and enterprises can also benefit from multilayered mobile security solutions such as Trend Micro™ Mobile Security™ .' [/INST] [End:O, users:O, and:O, enterprises:O, can:O, also:O, benefit:O, from:O, multilayered:O, mobile:O, security:O, solutions:O, such:O, as:O, Trend:B-Organization, Micro™:I-Organization, Mobile:O, Security™: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: 'Trend Micro™ Mobile Security for Enterprise provides device , compliance and application management , data protection , and configuration provisioning , as well as protects devices from attacks that exploit vulnerabilities , preventing unauthorized access to apps , and detecting and blocking malware and fraudulent websites .' [/INST] [Trend:B-Organization, Micro™:I-Organization, Mobile:B-System, Security:I-System, for:I-System, Enterprise:I-System, provides:O, device:O, ,:O, compliance:O, and:O, application:O, management:O, ,:O, data:O, protection:O, ,:O, and:O, configuration:O, provisioning:O, ,:O, as:O, well:O, as:O, protects:O, devices:O, from:O, attacks:O, that:O, exploit:O, vulnerabilities:O, ,:O, preventing:O, unauthorized:O, access:O, to:O, apps:O, ,:O, and:O, detecting:O, and:O, blocking:O, malware:O, and:O, fraudulent:O, websites: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: 'Trend Micro ’ s Mobile App Reputation Service ( MARS ) covers Android and iOS threats using leading sandbox and machine learning technologies , protecting devices against malware , zero-day and known exploits , privacy leaks , and application vulnerabilities .' [/INST] [Trend:B-Organization, Micro:I-Organization, ’:O, s:O, Mobile:B-System, App:I-System, Reputation:I-System, Service:I-System, (:O, MARS:O, ):O, covers:O, Android:B-System, and:O, iOS:B-System, threats:O, using:O, leading:O, sandbox:O, and:O, machine:O, learning:O, technologies:O, ,:O, protecting:O, devices:O, against:O, malware:O, ,:O, zero-day:O, and:O, known:O, exploits:O, ,:O, privacy:O, leaks:O, ,:O, and:O, application:O, vulnerabilities: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: 'Several weeks ago , Check Point Mobile Threat Prevention detected and quarantined the Android device of an unsuspecting customer employee who downloaded and installed a 0day mobile ransomware from Google Play dubbed “ Charger. ” This incident demonstrates how malware can be a dangerous threat to your business , and how advanced behavioral detection fills mobile security gaps attackers use to penetrate entire networks .' [/INST] [Several:O, weeks:O, ago:O, ,:O, Check:B-Organization, Point:I-Organization, Mobile:O, Threat:O, Prevention:O, detected:O, and:O, quarantined:O, the:O, Android:B-System, device:O, of:O, an:O, unsuspecting:O, customer:O, employee:O, who:O, downloaded:O, and:O, installed:O, a:O, 0day:O, mobile:O, ransomware:O, from:O, Google:B-System, Play:I-System, dubbed:O, “:O, Charger.:B-Malware, ”:O, This:O, incident:O, demonstrates:O, how:O, malware:O, can:O, be:O, a:O, dangerous:O, threat:O, to:O, your:O, business:O, ,:O, and:O, how:O, advanced:O, behavioral:O, detection:O, fills:O, mobile:O, security:O, gaps:O, attackers:O, use:O, to:O, penetrate:O, entire:O, networks: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: 'Charger was found embedded in an app called EnergyRescue .' [/INST] [Charger:B-Malware, was:O, found:O, embedded:O, in:O, an:O, app:O, called:O, EnergyRescue:B-Malware, .: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 infected app steals contacts and SMS messages from the user ’ s device and asks for admin permissions .' [/INST] [The:O, infected:O, app:O, steals:O, contacts:O, and:O, SMS:O, messages:O, from:O, the:O, user:O, ’:O, s:O, device:O, and:O, asks:O, for:O, admin: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: 'If granted , the ransomware locks the device and displays a message demanding payment : You need to pay for us , otherwise we will sell portion of your personal information on black market every 30 minutes .' [/INST] [If:O, granted:O, ,:O, the:O, ransomware:O, locks:O, the:O, device:O, and:O, displays:O, a:O, message:O, demanding:O, payment:O, ::O, You:O, need:O, to:O, pay:O, for:O, us:O, ,:O, otherwise:O, we:O, will:O, sell:O, portion:O, of:O, your:O, personal:O, information:O, on:O, black:O, market:O, every:O, 30:O, minutes: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 GIVE 100 % GUARANTEE THAT ALL FILES WILL RESTORE AFTER WE RECEIVE PAYMENT .' [/INST] [WE:O, GIVE:O, 100:O, %:O, GUARANTEE:O, THAT:O, ALL:O, FILES:O, WILL:O, RESTORE:O, AFTER:O, WE:O, RECEIVE:O, PAYMENT: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 WILL UNLOCK THE MOBILE DEVICE AND DELETE ALL YOUR DATA FROM OUR SERVER !' [/INST] [WE:O, WILL:O, UNLOCK:O, THE:O, MOBILE:O, DEVICE:O, AND:O, DELETE:O, ALL:O, YOUR:O, DATA:O, FROM:O, OUR: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: 'TURNING OFF YOUR PHONE IS MEANINGLESS , ALL YOUR DATA IS ALREADY STORED ON OUR SERVERS !' [/INST] [TURNING:O, OFF:O, YOUR:O, PHONE:O, IS:O, MEANINGLESS:O, ,:O, ALL:O, YOUR:O, DATA:O, IS:O, ALREADY:O, STORED:O, ON:O, OUR:O, SERVERS: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 STILL CAN SELLING IT FOR SPAM , FAKE , BANK CRIME etc… We collect and download all of your personal data .' [/INST] [WE:O, STILL:O, CAN:O, SELLING:O, IT:O, FOR:O, SPAM:O, ,:O, FAKE:O, ,:O, BANK:O, CRIME:O, etc…:O, We:O, collect:O, and:O, download:O, all:O, of:O, your:O, personal: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: 'All information about your social networks , Bank accounts , Credit Cards .' [/INST] [All:O, information:O, about:O, your:O, social:O, networks:O, ,:O, Bank:O, accounts:O, ,:O, Credit:O, Cards: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 collect all data about your friends and family .' [/INST] [We:O, collect:O, all:O, data:O, about:O, your:O, friends:O, and:O, family: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 ransom demand for 0.2 Bitcoins ( roughly $ 180 ) is a much higher ransom demand than has been seen in mobile ransomware so far .' [/INST] [The:O, ransom:O, demand:O, for:O, 0.2:O, Bitcoins:O, (:O, roughly:O, $:O, 180:O, ):O, is:O, a:O, much:O, higher:O, ransom:O, demand:O, than:O, has:O, been:O, seen:O, in:O, mobile:O, ransomware:O, so:O, far: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: 'By comparison , the DataLust ransomware demanded merely $ 15 .' [/INST] [By:O, comparison:O, ,:O, the:O, DataLust:B-Malware, ransomware:O, demanded:O, merely:O, $:O, 15: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: 'Payments are made to a specific Bitcoin account , but we haven ’ t identified any payments so far .' [/INST] [Payments:O, are:O, made:O, to:O, a:O, specific:O, Bitcoin:B-System, account:O, ,:O, but:O, we:O, haven:O, ’:O, t:O, identified:O, any:O, payments:O, so:O, far: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: 'Adware commonly found on Play collects profits from ad networks , but mobile ransomware inflicts direct harm to users .' [/INST] [Adware:O, commonly:O, found:O, on:O, Play:O, collects:O, profits:O, from:O, ad:O, networks:O, ,:O, but:O, mobile:O, ransomware:O, inflicts:O, direct:O, harm:O, to:O, users:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Like FakeDefender and DataLust , Charger could be an indicator of a wider effort by mobile malware developers to catch up with their PC ransomware cousins .' [/INST] [Like:O, FakeDefender:B-Malware, and:O, DataLust:B-Malware, ,:O, Charger:B-Malware, could:O, be:O, an:O, indicator:O, of:O, a:O, wider:O, effort:O, by:O, mobile:O, malware:O, developers:O, to:O, catch:O, up:O, with:O, their:O, PC:O, ransomware:O, cousins: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: 'Similar to other malware seen in the past , Charger checks the local settings of the device and does not run its malicious logic if the device is located in Ukraine , Russia , or Belarus .' [/INST] [Similar:O, to:O, other:O, malware:O, seen:O, in:O, the:O, past:O, ,:O, Charger:B-Malware, checks:O, the:O, local:O, settings:O, of:O, the:O, device:O, and:O, does:O, not:O, run:O, its:O, malicious:O, logic:O, if:O, the:O, device:O, is:O, located:O, in:O, Ukraine:O, ,:O, Russia:O, ,:O, or:O, Belarus: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 likely done to keep the developers from being prosecuted in their own countries or being extradited between countries .' [/INST] [This:O, is:O, likely:O, done:O, to:O, keep:O, the:O, developers:O, from:O, being:O, prosecuted:O, in:O, their:O, own:O, countries:O, or:O, being:O, extradited:O, between:O, countries: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: 'Most malware found on Google Play contains only a dropper that later downloads the real malicious components to the device .' [/INST] [Most:O, malware:O, found:O, on:O, Google:B-System, Play:I-System, contains:O, only:O, a:O, dropper:O, that:O, later:O, downloads:O, the:O, real:O, malicious:O, components:O, to: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: 'Charger , however , uses a heavy packing approach which it harder for the malware to stay hidden , so it must compensate with other means .' [/INST] [Charger:B-Malware, ,:O, however:O, ,:O, uses:O, a:O, heavy:O, packing:O, approach:O, which:O, it:O, harder:O, for:O, the:O, malware:O, to:O, stay:O, hidden:O, ,:O, so:O, it:O, must:O, compensate:O, with:O, other:O, means: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 developers of Charger gave it everything they had to boost its evasion capabilities and so it could stay hidden on Google Play for as long as possible .' [/INST] [The:O, developers:O, of:O, Charger:B-Malware, gave:O, it:O, everything:O, they:O, had:O, to:O, boost:O, its:O, evasion:O, capabilities:O, and:O, so:O, it:O, could:O, stay:O, hidden:O, on:O, Google:B-System, Play:I-System, for:O, as:O, long:O, as:O, possible: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 uses several advanced techniques to hide its real intentions and makes it harder to detect .' [/INST] [The:O, malware:O, uses:O, several:O, advanced:O, techniques:O, to:O, hide:O, its:O, real:O, intentions:O, and:O, makes:O, it:O, harder:O, to:O, detect: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 encodes strings into binary arrays , making it hard to inspect them .' [/INST] [It:O, encodes:O, strings:O, into:O, binary:O, arrays:O, ,:O, making:O, it:O, hard:O, to:O, inspect: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: 'It loads code from encrypted resources dynamically , which most detection engines can not penetrate and inspect .' [/INST] [It:O, loads:O, code:O, from:O, encrypted:O, resources:O, dynamically:O, ,:O, which:O, most:O, detection:O, engines:O, can:O, not:O, penetrate:O, and:O, inspect: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 dynamically-loaded code is also flooded with meaningless commands that mask the actual commands passing through .' [/INST] [The:O, dynamically-loaded:O, code:O, is:O, also:O, flooded:O, with:O, meaningless:O, commands:O, that:O, mask:O, the:O, actual:O, commands:O, passing:O, through: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 checks whether it is being run in an emulator before it starts its malicious activity .' [/INST] [It:O, checks:O, whether:O, it:O, is:O, being:O, run:O, in:O, an:O, emulator:O, before:O, it:O, starts:O, its:O, malicious:O, activity: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: 'PC malware first introduced this technique which is becoming a trend in mobile malware having been adopted by several malware families including Dendroid .' [/INST] [PC:O, malware:O, first:O, introduced:O, this:O, technique:O, which:O, is:O, becoming:O, a:O, trend:O, in:O, mobile:O, malware:O, having:O, been:O, adopted:O, by:O, several:O, malware:O, families:O, including:O, Dendroid:B-Malware, .: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: 'Emulator and location conditions for the malware ’ s activity Check Point Mobile Threat Prevention customers are protected from Charger and similar malware .' [/INST] [Emulator:O, and:O, location:O, conditions:O, for:O, the:O, malware:O, ’:O, s:O, activity:O, Check:B-Organization, Point:I-Organization, Mobile:O, Threat:O, Prevention:O, customers:O, are:O, protected:O, from:O, Charger:B-Malware, and:O, similar: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: 'Check Point ’ s Analysis and Response Team ( ART ) disclosed the finding to Android ’ s Security team who took the appropriate security steps to remove the infected app and added the malware to Android ’ s built-in protection mechanisms .' [/INST] [Check:B-Organization, Point:I-Organization, ’:O, s:O, Analysis:O, and:O, Response:O, Team:O, (:O, ART:O, ):O, disclosed:O, the:O, finding:O, to:O, Android:B-System, ’:O, s:O, Security:O, team:O, who:O, took:O, the:O, appropriate:O, security:O, steps:O, to:O, remove:O, the:O, infected:O, app:O, and:O, added:O, the:O, malware:O, to:O, Android:B-System, ’:O, s:O, built-in:O, protection:O, mechanisms: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: 'Charger SHA256 hash : 58eb6c368e129b17559bdeacb3aed4d9a5d3596f774cf5ed3fdcf51775232ba0 Infostealer , Keylogger , and Ransomware in One : Anubis Targets More than 250 Android Applications October 29 , 2021 The Cofense Phishing Defense Center uncovered a phishing campaign that specifically targets users of Android devices that could result in compromise if unsigned Android applications are permitted on the device .' [/INST] [Charger:O, SHA256:O, hash:O, ::O, 58eb6c368e129b17559bdeacb3aed4d9a5d3596f774cf5ed3fdcf51775232ba0:B-Indicator, Infostealer:O, ,:O, Keylogger:O, ,:O, and:O, Ransomware:O, in:O, One:O, ::O, Anubis:B-Malware, Targets:O, More:O, than:O, 250:O, Android:B-System, Applications:O, October:O, 29:O, ,:O, 2021:O, The:O, Cofense:B-Organization, Phishing:I-Organization, Defense:I-Organization, Center:I-Organization, uncovered:O, a:O, phishing:O, campaign:O, that:O, specifically:O, targets:O, users:O, of:O, Android:B-System, devices:O, that:O, could:O, result:O, in:O, compromise:O, if:O, unsigned:O, Android:B-System, applications:O, are:O, permitted: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: 'The campaign seeks to deliver Anubis , a particularly nasty piece of malware that was originally used for cyber espionage and retooled as a banking trojan .' [/INST] [The:O, campaign:O, seeks:O, to:O, deliver:O, Anubis:B-Malware, ,:O, a:O, particularly:O, nasty:O, piece:O, of:O, malware:O, that:O, was:O, originally:O, used:O, for:O, cyber:O, espionage:O, and:O, retooled:O, as:O, a:O, banking:O, trojan:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Anubis can completely hijack an Android mobile device , steal data , record phone calls , and even hold the device to ransom by encrypting the victim ’ s personal files .' [/INST] [Anubis:B-Malware, can:O, completely:O, hijack:O, an:O, Android:B-System, mobile:O, device:O, ,:O, steal:O, data:O, ,:O, record:O, phone:O, calls:O, ,:O, and:O, even:O, hold:O, the:O, device:O, to:O, ransom:O, by:O, encrypting:O, the:O, victim:O, ’:O, s:O, personal:O, files: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: 'With mobile devices increasingly used in the corporate environment , thanks to the popularity of BYOD policies , this malware has the potential to cause serious harm , mostly to consumers , and businesses that allow the installation of unsigned applications .' [/INST] [With:O, mobile:O, devices:O, increasingly:O, used:O, in:O, the:O, corporate:O, environment:O, ,:O, thanks:O, to:O, the:O, popularity:O, of:O, BYOD:O, policies:O, ,:O, this:O, malware:O, has:O, the:O, potential:O, to:O, cause:O, serious:O, harm:O, ,:O, mostly:O, to:O, consumers:O, ,:O, and:O, businesses:O, that:O, allow:O, the:O, installation:O, of:O, unsigned:O, applications: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: 'Here ’ s how it works : At first glance , the email shown in Figure 1 looks like any other phishing email that asks the user to download an invoice .' [/INST] [Here:O, ’:O, s:O, how:O, it:O, works:O, ::O, At:O, first:O, glance:O, ,:O, the:O, email:O, shown:O, in:O, Figure:O, 1:O, looks:O, like:O, any:O, other:O, phishing:O, email:O, that:O, asks:O, the:O, user:O, to:O, download:O, an:O, invoice: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: 'However , this particular email downloads an Android Package Kit ( APK ) , which is the common format used by Android to distribute and install applications .' [/INST] [However:O, ,:O, this:O, particular:O, email:O, downloads:O, an:O, Android:B-System, Package:I-System, Kit:I-System, (:O, APK:O, ):O, ,:O, which:O, is:O, the:O, common:O, format:O, used:O, by:O, Android:B-System, to:O, distribute:O, and:O, install:O, applications:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Let ’ s take a closer look at the suspicious file .' [/INST] [Let:O, ’:O, s:O, take:O, a:O, closer:O, look:O, at:O, the:O, suspicious:O, file: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: 'Figure 1 – Phishing Email When the email link is opened from an Android device , an APK file ( Fattura002873.apk ) , is downloaded .' [/INST] [Figure:O, 1:O, –:O, Phishing:O, Email:O, When:O, the:O, email:O, link:O, is:O, opened:O, from:O, an:O, Android:B-System, device:O, ,:O, an:O, APK:O, file:O, (:O, Fattura002873.apk:B-Indicator, ):O, ,:O, is:O, downloaded: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: 'Upon opening the file , the user is asked to enable “ Google Play Protect ” as shown in Figure 2 .' [/INST] [Upon:O, opening:O, the:O, file:O, ,:O, the:O, user:O, is:O, asked:O, to:O, enable:O, “:O, Google:B-System, Play:I-System, Protect:O, ”:O, as:O, shown:O, in:O, Figure:O, 2: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: 'However , this is not a genuine “ Google Play Protect ” screen ; instead it gives the app all the permissions it needs while simultaneously disabling the actual Google Play Protect .' [/INST] [However:O, ,:O, this:O, is:O, not:O, a:O, genuine:O, “:O, Google:B-System, Play:I-System, Protect:O, ”:O, screen:O, ;:O, instead:O, it:O, gives:O, the:O, app:O, all:O, the:O, permissions:O, it:O, needs:O, while:O, simultaneously:O, disabling:O, the:O, actual:O, Google:B-System, Play:I-System, Protect: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: 'Figure 2 – Granting Permissions The following permissions are granted to the app : Figure 3 – Permissions Granted to App A closer look at the code reveals the application gathers a list of installed applications to compare the results against a list of targeted applications ( Figure 4 ) .' [/INST] [Figure:O, 2:O, –:O, Granting:O, Permissions:O, The:O, following:O, permissions:O, are:O, granted:O, to:O, the:O, app:O, ::O, Figure:O, 3:O, –:O, Permissions:O, Granted:O, to:O, App:O, A:O, closer:O, look:O, at:O, the:O, code:O, reveals:O, the:O, application:O, gathers:O, a:O, list:O, of:O, installed:O, applications:O, to:O, compare:O, the:O, results:O, against:O, a:O, list:O, of:O, targeted:O, applications:O, (:O, Figure:O, 4:O, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware mainly targets banking and financial applications , but also looks for popular shopping apps such as eBay or Amazon .' [/INST] [The:O, malware:O, mainly:O, targets:O, banking:O, and:O, financial:O, applications:O, ,:O, but:O, also:O, looks:O, for:O, popular:O, shopping:O, apps:O, such:O, as:O, eBay:B-Organization, or:O, Amazon:B-Organization, .: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 full list of targeted applications is included in the IOC section at the end of this post .' [/INST] [A:O, full:O, list:O, of:O, targeted:O, applications:O, is:O, included:O, in:O, the:O, IOC:O, section:O, at:O, the:O, end:O, of:O, this:O, post: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 an application has been identified , Anubis overlays the original application with a fake login page to capture the user ’ s credentials .' [/INST] [Once:O, an:O, application:O, has:O, been:O, identified:O, ,:O, Anubis:B-Malware, overlays:O, the:O, original:O, application:O, with:O, a:O, fake:O, login:O, page:O, to:O, capture:O, the:O, user:O, ’:O, s:O, credentials: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: 'Figure 4 – Checking for installed apps Based on a thorough analysis of the code , the most interesting technical capabilities include : Capturing screenshots Enabling or changing administration settings Opening and visiting any URL Disabling Play Protect Recording audio Making phone calls Stealing the contact list Controlling the device via VNC Sending , receiving and deleting SMS Locking the device Encrypting files on the device and external drives Searching for files Retrieving the GPS location Capturing remote control commands from Twitter and Telegram Pushing overlays Reading the device ID The malware includes' [/INST] [Figure:O, 4:O, –:O, Checking:O, for:O, installed:O, apps:O, Based:O, on:O, a:O, thorough:O, analysis:O, of:O, the:O, code:O, ,:O, the:O, most:O, interesting:O, technical:O, capabilities:O, include:O, ::O, Capturing:O, screenshots:O, Enabling:O, or:O, changing:O, administration:O, settings:O, Opening:O, and:O, visiting:O, any:O, URL:O, Disabling:O, Play:O, Protect:O, Recording:O, audio:O, Making:O, phone:O, calls:O, Stealing:O, the:O, contact:O, list:O, Controlling:O, the:O, device:O, via:O, VNC:O, Sending:O, ,:O, receiving:O, and:O, deleting:O, SMS:O, Locking:O, the:O, device:O, Encrypting:O, files:O, on:O, the:O, device:O, and:O, external:O, drives:O, Searching:O, for:O, files:O, Retrieving:O, the:O, GPS:O, location:O, Capturing:O, remote:O, control:O, commands:O, from:O, Twitter:B-System, and:O, Telegram:B-System, Pushing:O, overlays:O, Reading:O, the:O, device:O, ID:O, The:O, malware:O, includes: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 keylogger that works in every app installed on the Android device .' [/INST] [a:O, keylogger:O, that:O, works:O, in:O, every:O, app:O, installed:O, on:O, the:O, Android:B-System, 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: 'However , the keylogger needs to be specifically enabled by a command sent from the C2 server .' [/INST] [However:O, ,:O, the:O, keylogger:O, needs:O, to:O, be:O, specifically:O, enabled:O, by:O, a:O, command:O, sent:O, from:O, the:O, C2: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: 'The keylogger can track three different events ( Figure 5 ) : TYPE_VIEW_CLICKED Represents the event of clicking on a View-like Button , CompoundButton , etc .' [/INST] [The:O, keylogger:O, can:O, track:O, three:O, different:O, events:O, (:O, Figure:O, 5:O, ):O, ::O, TYPE_VIEW_CLICKED:O, Represents:O, the:O, event:O, of:O, clicking:O, on:O, a:O, View-like:O, Button:O, ,:O, CompoundButton:O, ,:O, etc: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: 'TYPE_VIEW_FOCUSED Represents the event of setting input focus of a View .' [/INST] [TYPE_VIEW_FOCUSED:O, Represents:O, the:O, event:O, of:O, setting:O, input:O, focus:O, of:O, a:O, View: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: 'TYPE_VIEW_TEXT_CHANGED Represents the event of changing the text of an EditText .' [/INST] [TYPE_VIEW_TEXT_CHANGED:O, Represents:O, the:O, event:O, of:O, changing:O, the:O, text:O, of:O, an:O, EditText: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: 'Figure 5 – Keylogger component Figure 6 shows one of the most noteworthy functions of Anubis : its ransomware module .' [/INST] [Figure:O, 5:O, –:O, Keylogger:O, component:O, Figure:O, 6:O, shows:O, one:O, of:O, the:O, most:O, noteworthy:O, functions:O, of:O, Anubis:B-Malware, ::O, its:O, ransomware:O, module: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 searches both internal and external storage and encrypts them using RC4 .' [/INST] [The:O, malware:O, searches:O, both:O, internal:O, and:O, external:O, storage:O, and:O, encrypts:O, them:O, using:O, RC4: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 adds the file extension .AnubisCrypt to each encrypted file and sends it to the C2 .' [/INST] [It:O, adds:O, the:O, file:O, extension:O, .AnubisCrypt:B-Indicator, to:O, each:O, encrypted:O, file:O, and:O, sends:O, it:O, to:O, the:O, C2: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: 'Figure 6 – Ransomware component Anubis has been known to utilize Twitter or Telegram to retrieve the C2 address and this sample is no exception ( Figure 7 ) .' [/INST] [Figure:O, 6:O, –:O, Ransomware:O, component:O, Anubis:B-Malware, has:O, been:O, known:O, to:O, utilize:O, Twitter:B-Organization, or:O, Telegram:B-Organization, to:O, retrieve:O, the:O, C2:O, address:O, and:O, this:O, sample:O, is:O, no:O, exception:O, (:O, Figure:O, 7:O, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Figure 7 – C2 As seen in Figure 8 , this version of Anubis is built to run on several iterations of the Android operating system , dating back to version 4.0.3 , which was released in 2012 .' [/INST] [Figure:O, 7:O, –:O, C2:O, As:O, seen:O, in:O, Figure:O, 8:O, ,:O, this:O, version:O, of:O, Anubis:B-Malware, is:O, built:O, to:O, run:O, on:O, several:O, iterations:O, of:O, the:O, Android:B-System, operating:O, system:O, ,:O, dating:O, back:O, to:O, version:O, 4.0.3:O, ,:O, which:O, was:O, released:O, in:O, 2012: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: 'Figure 8 – Android requirements Android malware has been around for many years and will be with us for the foreseeable future .' [/INST] [Figure:O, 8:O, –:O, Android:B-System, requirements:O, Android:B-System, malware:O, has:O, been:O, around:O, for:O, many:O, years:O, and:O, will:O, be:O, with:O, us:O, for:O, the:O, foreseeable:O, future: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: 'Users who have configured their Android mobile device to receive work-related emails and allow installation of unsigned applications face the most risk of compromise .' [/INST] [Users:O, who:O, have:O, configured:O, their:O, Android:B-System, mobile:O, device:O, to:O, receive:O, work-related:O, emails:O, and:O, allow:O, installation:O, of:O, unsigned:O, applications:O, face:O, the:O, most:O, risk:O, of:O, compromise: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: 'APK files will not natively open in an environment other than an Android device .' [/INST] [APK:O, files:O, will:O, not:O, natively:O, open:O, in:O, an:O, environment:O, other:O, than:O, an:O, Android:B-System, 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: 'With the increased use of Android phones in business environments , it is important to defend against these threats by ensuring devices are kept current with the latest updates .' [/INST] [With:O, the:O, increased:O, use:O, of:O, Android:B-System, phones:O, in:O, business:O, environments:O, ,:O, it:O, is:O, important:O, to:O, defend:O, against:O, these:O, threats:O, by:O, ensuring:O, devices:O, are:O, kept:O, current:O, with:O, the:O, latest:O, updates: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: 'Limiting app installations on corporate devices , as well as ensuring that applications are created by trusted developers on official marketplaces , can help in reducing the risk of infection as well .' [/INST] [Limiting:O, app:O, installations:O, on:O, corporate:O, devices:O, ,:O, as:O, well:O, as:O, ensuring:O, that:O, applications:O, are:O, created:O, by:O, trusted:O, developers:O, on:O, official:O, marketplaces:O, ,:O, can:O, help:O, in:O, reducing:O, the:O, risk:O, of:O, infection:O, as:O, well: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: 'ViceLeaker Operation : mobile espionage targeting Middle East 26 JUN 2019 In May 2018 , we discovered a campaign targeting dozens of mobile Android devices belonging to Israeli citizens .' [/INST] [ViceLeaker:B-Malware, Operation:O, ::O, mobile:O, espionage:O, targeting:O, Middle:O, East:O, 26:O, JUN:O, 2019:O, In:O, May:O, 2018:O, ,:O, we:O, discovered:O, a:O, campaign:O, targeting:O, dozens:O, of:O, mobile:O, Android:B-System, devices:O, belonging:O, to:O, Israeli:O, citizens:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Kaspersky spyware sensors caught the signal of an attack from the device of one of the victims ; and a hash of the APK involved ( Android application ) was tagged in our sample feed for inspection .' [/INST] [Kaspersky:B-Organization, spyware:O, sensors:O, caught:O, the:O, signal:O, of:O, an:O, attack:O, from:O, the:O, device:O, of:O, one:O, of:O, the:O, victims:O, ;:O, and:O, a:O, hash:O, of:O, the:O, APK:O, involved:O, (:O, Android:B-System, application:O, ):O, was:O, tagged:O, in:O, our:O, sample:O, feed:O, for:O, inspection: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 we looked into the file , we quickly found out that the inner-workings of the APK included a malicious payload , embedded in the original code of the application .' [/INST] [Once:O, we:O, looked:O, into:O, the:O, file:O, ,:O, we:O, quickly:O, found:O, out:O, that:O, the:O, inner-workings:O, of:O, the:O, APK:O, included:O, a:O, malicious:O, payload:O, ,:O, embedded:O, in:O, the:O, original:O, code:O, of:O, the: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: 'This was an original spyware program , designed to exfiltrate almost all accessible information .' [/INST] [This:O, was:O, an:O, original:O, spyware:O, program:O, ,:O, designed:O, to:O, exfiltrate:O, almost:O, all:O, accessible:O, information:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'During the course of our research , we noticed that we were not the only ones to have found the operation .' [/INST] [During:O, the:O, course:O, of:O, our:O, research:O, ,:O, we:O, noticed:O, that:O, we:O, were:O, not:O, the:O, only:O, ones:O, to:O, have:O, found:O, the: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: 'Researchers from Bitdefender also released an analysis of one of the samples in a blogpost .' [/INST] [Researchers:O, from:O, Bitdefender:B-System, also:O, released:O, an:O, analysis:O, of:O, one:O, of:O, the:O, samples:O, in:O, a:O, blogpost: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: 'Although something had already been published , we decided to do something different with the data we acquired .' [/INST] [Although:O, something:O, had:O, already:O, been:O, published:O, ,:O, we:O, decided:O, to:O, do:O, something:O, different:O, with:O, the:O, data:O, we:O, acquired: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 month , we released a private report on our Threat Intelligence Portal to alert our clients about this newly discovered operation and began writing YARA rules in order to catch more samples .' [/INST] [The:O, following:O, month:O, ,:O, we:O, released:O, a:O, private:O, report:O, on:O, our:O, Threat:O, Intelligence:O, Portal:O, to:O, alert:O, our:O, clients:O, about:O, this:O, newly:O, discovered:O, operation:O, and:O, began:O, writing:O, YARA:O, rules:O, in:O, order:O, to:O, catch:O, more:O, samples: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 decided to call the operation “ ViceLeaker ” , because of strings and variables in its code .' [/INST] [We:O, decided:O, to:O, call:O, the:O, operation:O, “:O, ViceLeaker:B-Malware, ”:O, ,:O, because:O, of:O, strings:O, and:O, variables:O, in:O, its:O, code: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: 'Mobile ViceLeaker The following table shows meta information on the observed samples , including compiler timestamps : MD5 Package Compiler C2 51df2597faa3fce38a4c5ae024f97b1c com.xapps.SexGameForAdults dexlib 2.x 188.165.28 [ .' [/INST] [Mobile:O, ViceLeaker:B-Malware, The:O, following:O, table:O, shows:O, meta:O, information:O, on:O, the:O, observed:O, samples:O, ,:O, including:O, compiler:O, timestamps:O, ::O, MD5:O, Package:O, Compiler:O, C2:O, 51df2597faa3fce38a4c5ae024f97b1c:B-Indicator, com.xapps.SexGameForAdults:B-Indicator, dexlib:O, 2.x:O, 188.165.28: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: '] 251 2d108ff3a735dea1d1fdfa430f37fab2 com.psiphon3 dexlib 2.x 188.165.49 [ .' [/INST] []:I-Indicator, 251:I-Indicator, 2d108ff3a735dea1d1fdfa430f37fab2:B-Indicator, com.psiphon3:B-Indicator, dexlib:O, 2.x:O, 188.165.49: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: '] 205 7ed754a802f0b6a1740a99683173db73 com.psiphon3 dexlib 2.x 188.165.49 [ .' [/INST] []:I-Indicator, 205:I-Indicator, 7ed754a802f0b6a1740a99683173db73:B-Indicator, com.psiphon3:B-Indicator, dexlib:O, 2.x:O, 188.165.49: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: '] 205 3b89e5cd49c05ce6dc681589e6c368d9 ir.abed.dastan dexlib 2.x 185.141.60 [ .' [/INST] []:I-Indicator, 205:I-Indicator, 3b89e5cd49c05ce6dc681589e6c368d9:B-Indicator, ir.abed.dastan:B-Indicator, dexlib:O, 2.x:O, 185.141.60: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: '] 213 To backdoor legitimate applications , attackers used a Smali injection technique – a type of injection that allows attackers to disassemble the code of original app with the Baksmali tool , add their malicious code , and assemble it with Smali .' [/INST] []:I-Indicator, 213:I-Indicator, To:O, backdoor:O, legitimate:O, applications:O, ,:O, attackers:O, used:O, a:O, Smali:O, injection:O, technique:O, –:O, a:O, type:O, of:O, injection:O, that:O, allows:O, attackers:O, to:O, disassemble:O, the:O, code:O, of:O, original:O, app:O, with:O, the:O, Baksmali:O, tool:O, ,:O, add:O, their:O, malicious:O, code:O, ,:O, and:O, assemble:O, it:O, with:O, Smali: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 a result , due to such an unusual compilation process , there were signs in the dex file that point to dexlib , a library used by the Smali tool to assemble dex files .' [/INST] [As:O, a:O, result:O, ,:O, due:O, to:O, such:O, an:O, unusual:O, compilation:O, process:O, ,:O, there:O, were:O, signs:O, in:O, the:O, dex:O, file:O, that:O, point:O, to:O, dexlib:O, ,:O, a:O, library:O, used:O, by:O, the:O, Smali:O, tool:O, to:O, assemble:O, dex:O, files: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: 'Original code of the APK on the left , versus injected APK on the right The analysis of the APK was rather interesting , because some of the actions were very common spyware features , such as the exfiltration of SMS messages , call logs and other data .' [/INST] [Original:O, code:O, of:O, the:O, APK:O, on:O, the:O, left:O, ,:O, versus:O, injected:O, APK:O, on:O, the:O, right:O, The:O, analysis:O, of:O, the:O, APK:O, was:O, rather:O, interesting:O, ,:O, because:O, some:O, of:O, the:O, actions:O, were:O, very:O, common:O, spyware:O, features:O, ,:O, such:O, as:O, the:O, exfiltration:O, of:O, SMS:O, messages:O, ,:O, call:O, logs:O, and:O, other: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: 'However , in addition to the traditional functionality , there were also backdoor capabilities such as upload , download , delete files , camera takeover and record surrounding audio .' [/INST] [However:O, ,:O, in:O, addition:O, to:O, the:O, traditional:O, functionality:O, ,:O, there:O, were:O, also:O, backdoor:O, capabilities:O, such:O, as:O, upload:O, ,:O, download:O, ,:O, delete:O, files:O, ,:O, camera:O, takeover:O, and:O, record:O, surrounding:O, audio: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 uses HTTP for communication with the C2 server for command handling and data exfiltration .' [/INST] [The:O, malware:O, uses:O, HTTP:O, for:O, communication:O, with:O, the:O, C2:O, server:O, for:O, command:O, handling:O, and:O, data:O, exfiltration: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: 'Here is a command and control protocol fragment : Commands from C2 server parsing In total , the malicious APK handles 16 different commands : Command Endpoint Description 1 reqsmscal.php Send specified SMS message 2 reqsmscal.php Call specified number 3 reqsmscal.php Exfiltrate device info , such as phone model and OS version 4 reqsmscal.php Exfiltrate a list of all installed applications 5 reqsmscal.php Exfiltrate default browser history ( limited to a given date ) 6 reqsmscal.php' [/INST] [Here:O, is:O, a:O, command:O, and:O, control:O, protocol:O, fragment:O, ::O, Commands:O, from:O, C2:O, server:O, parsing:O, In:O, total:O, ,:O, the:O, malicious:O, APK:O, handles:O, 16:O, different:O, commands:O, ::O, Command:O, Endpoint:O, Description:O, 1:O, reqsmscal.php:B-Indicator, Send:O, specified:O, SMS:O, message:O, 2:O, reqsmscal.php:B-Indicator, Call:O, specified:O, number:O, 3:O, reqsmscal.php:B-Indicator, Exfiltrate:O, device:O, info:O, ,:O, such:O, as:O, phone:O, model:O, and:O, OS:O, version:O, 4:O, reqsmscal.php:B-Indicator, Exfiltrate:O, a:O, list:O, of:O, all:O, installed:O, applications:O, 5:O, reqsmscal.php:B-Indicator, Exfiltrate:O, default:O, browser:O, history:O, (:O, limited:O, to:O, a:O, given:O, date:O, ):O, 6:O, reqsmscal.php: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: 'Exfiltrate Chrome browser history ( limited to a given date ) 7 reqsmscal.php Exfiltrate memory card file structure 8 reqsmscal.php Record surrounding sound for 80 seconds 1 reqcalllog.php Exfiltrate all call logs 2 reqcalllog.php Exfiltrate all SMS messages 3 reqcalllog.php Upload specified file from the device to the C2 4 reqcalllog.php Download file from specified URL and save on device 5 reqcalllog.php Delete specified file 6,7,8 reqcalllog.php Commands not yet' [/INST] [Exfiltrate:O, Chrome:O, browser:O, history:O, (:O, limited:O, to:O, a:O, given:O, date:O, ):O, 7:O, reqsmscal.php:B-Indicator, Exfiltrate:O, memory:O, card:O, file:O, structure:O, 8:O, reqsmscal.php:B-Indicator, Record:O, surrounding:O, sound:O, for:O, 80:O, seconds:O, 1:O, reqcalllog.php:B-Indicator, Exfiltrate:O, all:O, call:O, logs:O, 2:O, reqcalllog.php:B-Indicator, Exfiltrate:O, all:O, SMS:O, messages:O, 3:O, reqcalllog.php:B-Indicator, Upload:O, specified:O, file:O, from:O, the:O, device:O, to:O, the:O, C2:O, 4:O, reqcalllog.php:B-Indicator, Download:O, file:O, from:O, specified:O, URL:O, and:O, save:O, on:O, device:O, 5:O, reqcalllog.php:B-Indicator, Delete:O, specified:O, file:O, 6,7,8:O, reqcalllog.php:B-Indicator, Commands:O, not:O, yet: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: 'implemented 9 reqcalllog.php Take photo ( muted audio ) with rear camera , send to C2 10 reqcalllog.php Take photo ( muted audio ) with front camera , send to C2 All observed samples with Smali injections were signed by the same debug certificate ( 0x936eacbe07f201df ) .' [/INST] [implemented:O, 9:O, reqcalllog.php:B-Indicator, Take:O, photo:O, (:O, muted:O, audio:O, ):O, with:O, rear:O, camera:O, ,:O, send:O, to:O, C2:O, 10:O, reqcalllog.php:B-Indicator, Take:O, photo:O, (:O, muted:O, audio:O, ):O, with:O, front:O, camera:O, ,:O, send:O, to:O, C2:O, All:O, observed:O, samples:O, with:O, Smali:O, injections:O, were:O, signed:O, by:O, the:O, same:O, debug:O, certificate:O, (:O, 0x936eacbe07f201df:O, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'As we know from our investigation , traces of the first development activities were found at the end of 2016 , but the main distribution campaign began in 2018 ( end of 2017 ) .' [/INST] [As:O, we:O, know:O, from:O, our:O, investigation:O, ,:O, traces:O, of:O, the:O, first:O, development:O, activities:O, were:O, found:O, at:O, the:O, end:O, of:O, 2016:O, ,:O, but:O, the:O, main:O, distribution:O, campaign:O, began:O, in:O, 2018:O, (:O, end:O, of:O, 2017:O, ):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Based on our detection statistics , the main infection vector is the spread of Trojanized applications directly to victims via Telegram and WhatsApp messengers .' [/INST] [Based:O, on:O, our:O, detection:O, statistics:O, ,:O, the:O, main:O, infection:O, vector:O, is:O, the:O, spread:O, of:O, Trojanized:O, applications:O, directly:O, to:O, victims:O, via:O, Telegram:O, and:O, WhatsApp:O, messengers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'There are the following relevant detection paths ( the last one is an alternative Telegram client – “ Telegram X “ ) : Name Detection path Sex Game For Adults 18.apk /storage/emulated/0/WhatsApp/Media/WhatsApp Documents/ 4_6032967490689041387.apk /storage/emulated/0/Telegram/Telegram Documents/ Psiphon-v91.apk /storage/emulated/0/Android/data/org.thunderdog.challegram/files/documents/ Backdoored Open Source During the course' [/INST] [There:O, are:O, the:O, following:O, relevant:O, detection:O, paths:O, (:O, the:O, last:O, one:O, is:O, an:O, alternative:O, Telegram:O, client:O, –:O, “:O, Telegram:O, X:O, “:O, ):O, ::O, Name:O, Detection:O, path:O, Sex:O, Game:O, For:O, Adults:O, 18.apk:B-Indicator, /storage/emulated/0/WhatsApp/Media/WhatsApp:B-Indicator, Documents/:I-Indicator, 4_6032967490689041387.apk:I-Indicator, /storage/emulated/0/Telegram/Telegram:I-Indicator, Documents/:I-Indicator, Psiphon-v91.apk:B-Indicator, /storage/emulated/0/Android/data/org.thunderdog.challegram/files/documents/:B-Indicator, Backdoored:O, Open:O, Source:O, During:O, the:O, course: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: 'of our analysis , we also found samples sharing code with the ViceLeaker malware , in particular they shared a delimiter that was used in both cases to parse commands from the C2 server .' [/INST] [of:O, our:O, analysis:O, ,:O, we:O, also:O, found:O, samples:O, sharing:O, code:O, with:O, the:O, ViceLeaker:B-Malware, malware:O, ,:O, in:O, particular:O, they:O, shared:O, a:O, delimiter:O, that:O, was:O, used:O, in:O, both:O, cases:O, to:O, parse:O, commands:O, from:O, the:O, C2: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: 'This would be a very unusual coincidence .' [/INST] [This:O, would:O, be:O, a:O, very:O, unusual:O, coincidence: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: 'Even when a false flag might also be a possibility , we consider this to be unlikely .' [/INST] [Even:O, when:O, a:O, false:O, flag:O, might:O, also:O, be:O, a:O, possibility:O, ,:O, we:O, consider:O, this:O, to:O, be:O, unlikely: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 samples sharing this overlap are modified versions of an open source Jabber/XMPP client called “ Conversations ” with some code additions .' [/INST] [The:O, samples:O, sharing:O, this:O, overlap:O, are:O, modified:O, versions:O, of:O, an:O, open:O, source:O, Jabber/XMPP:B-System, client:O, called:O, “:O, Conversations:O, ”:O, with:O, some:O, code:O, additions:O, .:O] </s> |
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