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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: 'Confucius' backdoors are delivered through Office documents exploiting memory corruption vulnerabilities CVE-2015-1641 and CVE-2017-11882 .' [/INST] [Confucius':B-Tool, backdoors:O, are:O, delivered:O, through:O, Office:O, documents:O, exploiting:O, memory:O, corruption:O, vulnerabilities:O, CVE-2015-1641:B-Exp, and:O, CVE-2017-11882:B-Exp, .: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 dove deeper into Confucius' operations—namely , the malware-ridden documents , backdoors , and file stealers they use in their campaigns .' [/INST] [We:O, dove:O, deeper:O, into:O, Confucius':O, operations—namely:O, ,:O, the:O, malware-ridden:O, documents:O, ,:O, backdoors:O, ,:O, and:O, file:O, stealers:O, they:O, use:O, in:O, their:O, campaigns:B-OffAct, .: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 sctrls backdoor we came across is delivered via RTF files exploiting CVE-2015-1641 .' [/INST] [The:O, sctrls:B-Tool, backdoor:I-Tool, we:O, came:O, across:O, is:O, delivered:O, via:O, RTF:B-Way, files:I-Way, exploiting:O, CVE-2015-1641:B-Exp, .: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 documents that exploit CVE2017-11882 download another payload — an HTML Application ( HTA ) file toting a malicious Visual Basic ( VBS ) script — from the server , which is executed accordingly by the command-line tool mshta.exe .' [/INST] [The:O, documents:O, that:O, exploit:O, CVE2017-11882:B-Exp, download:O, another:O, payload:O, —:O, an:O, HTML:B-Tool, Application:I-Tool, (:O, HTA:B-SamFile, ):O, file:O, toting:O, a:O, malicious:O, Visual:O, Basic:O, (:O, VBS:O, ):O, script:O, —:O, from:O, the:O, server:O, ,:O, which:O, is:O, executed:O, accordingly:O, by:O, the:O, command-line:O, tool:O, mshta.exe:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In August 2015 a new incident related to the Corkow ( Metel ) Trojan was detected .' [/INST] [In:O, August:B-Time, 2015:I-Time, a:O, new:O, incident:O, related:O, to:O, the:O, Corkow:B-Tool, (:O, Metel:B-HackOrg, ):O, Trojan:O, was:O, detected: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: 'Corkow provided remote access to the ITS-Broker system terminal by 《 Platforma soft 》 Ltd , which enabled the fraud to be committed .' [/INST] [Corkow:B-Tool, provided:O, remote:B-Way, access:I-Way, to:O, the:O, ITS-Broker:O, system:O, terminal:O, by:O, 《:O, Platforma:O, soft:O, 》:O, Ltd:O, ,:O, which:O, enabled:O, the:O, fraud:O, to:O, be:O, committed: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: 'According to our statistics , as of the beginning of 2015 this botnet encompassed over 250 000 infected devices worldwide including infecting more than 100 financial institutions with 80% of them from the top 20 list .' [/INST] [According:O, to:O, our:O, statistics:O, ,:O, as:O, of:O, the:O, beginning:O, of:O, 2015:B-Time, this:O, botnet:B-SamFile, encompassed:I-SamFile, over:O, 250:O, 000:O, infected:O, devices:O, worldwide:O, including:O, infecting:O, more:O, than:O, 100:O, financial:B-Org, institutions:I-Org, with:O, 80%:O, of:O, them:O, from:O, the:O, top:O, 20:O, list: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 interest among hackers in targeting trading systems is expected to grow .' [/INST] [The:O, interest:O, among:O, hackers:O, in:O, targeting:O, trading:O, systems:O, is:O, expected:O, to:O, grow: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: 'Russian-speaking hackers are believed to be responsible for these attacks and used the Corkow Trojan .' [/INST] [Russian-speaking:B-Area, hackers:O, are:O, believed:O, to:O, be:O, responsible:O, for:O, these:O, attacks:B-OffAct, and:O, used:O, the:O, Corkow:B-Tool, Trojan:I-Tool, .: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: 'Hackers target primarily companies in Russia and CIS countries , though it is noticed that the amount of attacks targeting the USA has increased 5 times since 2011 .' [/INST] [Hackers:O, target:O, primarily:B-Org, companies:I-Org, in:O, Russia:O, and:O, CIS:O, countries:O, ,:O, though:O, it:O, is:O, noticed:O, that:O, the:O, amount:O, of:O, attacks:B-OffAct, targeting:O, the:O, USA:O, has:O, increased:O, 5:O, times:O, since:O, 2011:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One of the first botnets specializing in targeting the trading software called Quik was , Ranbyus , , created in 2012 .' [/INST] [One:O, of:O, the:O, first:O, botnets:O, specializing:O, in:O, targeting:O, the:O, trading:O, software:O, called:O, Quik:B-Tool, was:O, ,:O, Ranbyus:B-Tool, ,:O, ,:O, created:O, in:O, 2012:B-Time, .: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 of the Group-IB investigation of this malware program in March 2015 , Corkow v.7.118.1.1 had not been detected by a single antivirus program .' [/INST] [As:O, of:O, the:O, Group-IB:B-SecTeam, investigation:O, of:O, this:O, malware:O, program:O, in:O, March:B-Time, 2015:I-Time, ,:O, Corkow:B-Tool, v.7.118.1.1:O, had:O, not:O, been:O, detected:O, by:O, a:O, single:O, antivirus:O, program: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: 'Hackers gained access to a computer in the trading system in September 2014 .' [/INST] [Hackers:O, gained:O, access:O, to:O, a:O, computer:O, in:O, the:O, trading:O, system:O, in:O, September:B-Time, 2014:I-Time, .: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: 'Starting in December 2014 , the criminal group began running keyloggers in the infected system .' [/INST] [Starting:O, in:O, December:O, 2014:O, ,:O, the:O, criminal:O, group:O, began:O, running:O, keyloggers:B-Tool, in:O, the:O, infected:O, system:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To spread the Corkow malware criminals use a drive-by downloads method , when victims are infected while visiting compromised legitimate websites .' [/INST] [To:O, spread:B-Purp, the:I-Purp, Corkow:I-Purp, malware:I-Purp, criminals:O, use:O, a:O, drive-by:O, downloads:O, method:O, ,:O, when:O, victims:O, are:O, infected:O, while:O, visiting:O, compromised:O, legitimate: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: 'Group-IB specialists detected various sites used by criminals to spread the Trojan : mail tracking websites , news portals , electronic books , computer graphics resources , music portals , etc .' [/INST] [Group-IB:B-SecTeam, specialists:O, detected:O, various:O, sites:O, used:O, by:O, criminals:O, to:O, spread:B-Purp, the:I-Purp, Trojan:I-Purp, ::O, mail:B-Tool, tracking:I-Tool, websites:I-Tool, ,:O, news:B-Tool, portals:I-Tool, ,:O, electronic:B-Tool, books:I-Tool, ,:O, computer:B-Tool, graphics:I-Tool, resources:I-Tool, ,:O, music:B-Tool, portals:I-Tool, ,: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: 'Hackers use the exploits , Nitris Exploit Kit , ( earlier known as CottonCastle ) , which is not available in open sources and sold only to trusted users .' [/INST] [Hackers:O, use:O, the:O, exploits:O, ,:O, Nitris:B-Exp, Exploit:I-Exp, Kit:I-Exp, ,:O, (:O, earlier:O, known:O, as:O, CottonCastle:B-Exp, ):O, ,:O, which:O, is:O, not:O, available:O, in:O, open:O, sources:O, and:O, sold:O, only:O, to:O, trusted: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: 'Group-IB Bot-trek TDS sensors are in place at a number of financial institutions and , unfortunately , we register that currently Corkow malware is present on 80% of protected corporate systems .' [/INST] [Group-IB:B-SecTeam, Bot-trek:O, TDS:O, sensors:O, are:O, in:O, place:O, at:O, a:O, number:O, of:O, financial:B-Org, institutions:I-Org, and:O, ,:O, unfortunately:O, ,:O, we:O, register:O, that:O, currently:O, Corkow:B-Tool, malware:I-Tool, is:O, present:O, on:O, 80%:O, of:O, protected:O, corporate:O, systems: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: 'Considering the Trojan delivery method and through our analysis of infections on banks' networks , we can confirm that all infections were conducted on a random basis .' [/INST] [Considering:O, the:O, Trojan:O, delivery:O, method:O, and:O, through:O, our:O, analysis:O, of:O, infections:O, on:O, banks':O, networks:O, ,:O, we:O, can:O, confirm:O, that:O, all:O, infections:O, were:O, conducted:O, on:O, a:O, random:O, basis: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: 'According to statistics , Corkow primarily targets users in Russia and the CIS , but it is worth noting that in 2014 the amount of attacks targeting the USA increased by 5 times , in comparison with 2011 .' [/INST] [According:O, to:O, statistics:O, ,:O, Corkow:B-Tool, primarily:O, targets:O, users:B-Org, in:O, Russia:O, and:O, the:O, CIS:O, ,:O, but:O, it:O, is:O, worth:O, noting:O, that:O, in:O, 2014:B-Time, the:O, amount:O, of:O, attacks:B-OffAct, targeting:O, the:O, USA:O, increased:O, by:O, 5:O, times:O, ,:O, in:O, comparison:O, with:O, 2011:B-Time, .: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: 'Moreover , the number of Corkow incidents detected in Q1 2015 in the United States exceeds the number of those in the CIS countries .' [/INST] [Moreover:O, ,:O, the:O, number:O, of:O, Corkow:B-Tool, incidents:O, detected:O, in:O, Q1:O, 2015:B-Time, in:O, the:O, United:O, States:O, exceeds:O, the:O, number:O, of:O, those:O, in:O, the:O, CIS: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: 'Moreover , the number of Corkow incidents detected in Q1 2015 in the United States exceeds the number of those in the CIS countries .' [/INST] [Moreover:O, ,:O, the:O, number:O, of:O, Corkow:B-Tool, incidents:O, detected:O, in:O, Q1:O, 2015:B-Time, in:O, the:O, United:B-Area, States:I-Area, exceeds:O, the:O, number:O, of:O, those:O, in:O, the:O, CIS: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: 'Hackers first actively spread bots using the Niteris exploit , and then search for infected devices at banks amongst their bots by analyzing IP addresses , cracked passwords and results of the modules performance .' [/INST] [Hackers:O, first:O, actively:O, spread:O, bots:O, using:O, the:O, Niteris:B-Exp, exploit:I-Exp, ,:O, and:O, then:O, search:O, for:O, infected:O, devices:O, at:O, banks:B-Idus, amongst:O, their:O, bots:O, by:O, analyzing:O, IP:O, addresses:O, ,:O, cracked:O, passwords:O, and:O, results:O, of:O, the:O, modules:O, performance:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to the legitimate AmmyAdmin tool , the hackers used Visconti Backdoor developed based on legitimate RMS ( remote manipulator system ) software .' [/INST] [In:O, addition:O, to:O, the:O, legitimate:O, AmmyAdmin:B-Tool, tool:I-Tool, ,:O, the:O, hackers:O, used:O, Visconti:B-Tool, Backdoor:I-Tool, developed:O, based:O, on:O, legitimate:O, RMS:B-Tool, (:O, remote:O, manipulator:O, system:O, ):O, software: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 a bot was installed on a network that was of interest to the hacking group , this bot was then used to upload one of the remote access programs .' [/INST] [If:O, a:O, bot:B-SamFile, was:O, installed:O, on:O, a:O, network:O, that:O, was:O, of:O, interest:O, to:O, the:O, hacking:O, group:O, ,:O, this:O, bot:O, was:O, then:O, used:O, to:O, upload:B-Features, one:I-Features, of:I-Features, the:I-Features, remote:I-Features, access:I-Features, programs:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To obtain logins and passwords they applied keyloggers built into Corkow , as well as a commonly used feature of Mimikatz , dumping clear text Windows credentials from LSA .' [/INST] [To:O, obtain:B-Features, logins:I-Features, and:I-Features, passwords:I-Features, they:O, applied:O, keyloggers:B-Tool, built:O, into:O, Corkow:B-Tool, ,:O, as:O, well:O, as:O, a:O, commonly:O, used:B-Features, feature:I-Features, of:I-Features, Mimikatz:I-Features, ,:O, dumping:B-Features, clear:I-Features, text:I-Features, Windows:I-Features, credentials:I-Features, from:O, LSA: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: 'Hackers used the remote access to detect servers of their interest in the internal network .' [/INST] [Hackers:O, used:O, the:O, remote:B-Way, access:I-Way, to:O, detect:O, servers:O, of:O, their:O, interest:O, in:O, the:O, internal:O, network:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2015 , the Metel gang began to target banks and financial institutions directly .' [/INST] [In:O, 2015:B-Time, ,:O, the:O, Metel:O, gang:O, began:O, to:O, target:O, banks:B-Idus, and:O, financial:B-Org, institutions:I-Org, directly: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: 'Metel is a banking Trojan ( also known as Corkow ) discovered in 2011 when it was used to attack users of online banking services .' [/INST] [Metel:B-Tool, is:O, a:O, banking:B-Tool, Trojan:I-Tool, (:O, also:O, known:O, as:O, Corkow:B-HackOrg, ):O, discovered:O, in:O, 2011:B-Time, when:O, it:O, was:O, used:O, to:O, attack:O, users:B-Purp, of:I-Purp, online:I-Purp, banking:I-Purp, services:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After the infection stage , criminals move laterally with the help of legitimate and pentesting tools , stealing passwords from their initial victims ( entry point ) to gain access to the computers within the organization that have access to money transactions .' [/INST] [After:O, the:O, infection:O, stage:O, ,:O, criminals:O, move:O, laterally:O, with:O, the:O, help:O, of:O, legitimate:O, and:O, pentesting:O, tools:O, ,:O, stealing:B-Purp, passwords:I-Purp, from:O, their:O, initial:O, victims:O, (:O, entry:O, point:O, ):O, to:O, gain:B-Purp, access:I-Purp, to:O, the:O, computers:O, within:O, the:O, organization:O, that:O, have:O, access:O, to:O, money:O, transactions: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 this level of access , the gang has been able to pull off a clever trick by automating the rollback of ATM transactions .' [/INST] [With:O, this:O, level:O, of:O, access:O, ,:O, the:O, gang:O, has:O, been:O, able:O, to:O, pull:O, off:O, a:O, clever:O, trick:O, by:O, automating:O, the:O, rollback:B-Way, of:I-Way, ATM:I-Way, transactions:I-Way, .: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: 'COVELLITE operates globally with targets primarily in Europe , East Asia , and North America .' [/INST] [COVELLITE:O, operates:O, globally:O, with:O, targets:O, primarily:O, in:O, Europe:B-Area, ,:O, East:B-Area, Asia:I-Area, ,:O, and:O, North:B-Area, America:I-Area, .: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: 'US targets emerged in September 2017 with a small , targeted phishing campaign directed at select U.S. electric companies .' [/INST] [US:B-Area, targets:O, emerged:O, in:O, September:B-Time, 2017:I-Time, with:O, a:O, small:O, ,:O, targeted:O, phishing:B-OffAct, campaign:I-OffAct, directed:O, at:O, select:O, U.S.:B-Area, electric:B-Org, companies:I-Org, .: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: 'LAZARUS GROUP is responsible for attacks ranging from the 2014 attack on Sony Pictures to a number of Bitcoin heists in 2017 .' [/INST] [LAZARUS:O, GROUP:O, is:O, responsible:O, for:O, attacks:B-OffAct, ranging:O, from:O, the:O, 2014:B-Time, attack:B-OffAct, on:O, Sony:B-Org, Pictures:I-Org, to:O, a:O, number:O, of:O, Bitcoin:O, heists:O, in:O, 2017:B-Time, .: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: 'Technical analysis of COVELLITE malware indicates an evolution from known LAZARUS toolkits .' [/INST] [Technical:O, analysis:O, of:O, COVELLITE:B-Tool, malware:I-Tool, indicates:O, an:O, evolution:O, from:O, known:O, LAZARUS:B-Tool, toolkits:I-Tool, .: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: 'COVELLITE remains active but appears to have abandoned North American targets , with indications of activity in Europe and East Asia .' [/INST] [COVELLITE:O, remains:O, active:O, but:O, appears:O, to:O, have:O, abandoned:O, North:O, American:O, targets:O, ,:O, with:O, indications:O, of:O, activity:B-OffAct, in:O, Europe:B-Area, and:O, East:B-Area, Asia:I-Area, .: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: 'Given the group 's specific interest in infrastructure operations , rapidly improving capabilities , and history of aggressive targeting , Dragos considers this group a primary threat to the ICS industry .' [/INST] [Given:O, the:O, group:O, 's:O, specific:O, interest:O, in:O, infrastructure:O, operations:O, ,:O, rapidly:O, improving:O, capabilities:O, ,:O, and:O, history:O, of:O, aggressive:O, targeting:O, ,:O, Dragos:B-SecTeam, considers:O, this:O, group:O, a:O, primary:O, threat:O, to:O, the:O, ICS:B-Idus, industry:I-Idus, .: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: 'Delivering a backdoor and spyware , this campaign was designed to steal information from infected systems using a malware client capable of filtering out , uninteresting , files , and spread primarily via a targeted phishing email usually promising a pornographic video .' [/INST] [Delivering:B-Purp, a:I-Purp, backdoor:I-Purp, and:I-Purp, spyware:I-Purp, ,:O, this:O, campaign:B-OffAct, was:O, designed:O, to:O, steal:B-Purp, information:I-Purp, from:O, infected:O, systems:O, using:O, a:O, malware:O, client:O, capable:O, of:O, filtering:O, out:O, ,:O, uninteresting:O, ,:O, files:O, ,:O, and:O, spread:O, primarily:O, via:O, a:O, targeted:O, phishing:B-Way, email:I-Way, usually:O, promising:O, a:O, pornographic:O, video: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: 'Lookout researchers have discovered a new mobile surveillanceware family , FrozenCell .' [/INST] [Lookout:B-SecTeam, researchers:O, have:O, discovered:O, a:O, new:O, mobile:O, surveillanceware:O, family:O, ,:O, FrozenCell:B-Tool, .: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 threat is likely targeting employees of various Palestinian government agencies , security services , Palestinian students , and those affiliated with the Fatah political party .' [/INST] [The:O, threat:O, is:O, likely:O, targeting:O, employees:B-Org, of:O, various:O, Palestinian:B-Area, government:B-Org, agencies:I-Org, ,:O, security:B-Idus, services:I-Idus, ,:O, Palestinian:O, students:B-Org, ,:O, and:O, those:O, affiliated:O, with:O, the:O, Fatah:B-Org, political:I-Org, party:I-Org, .: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: 'Delivering a backdoor and spyware , Desert Falcons 's campaign was designed to steal information from infected systems using a malware client capable of filtering out , uninteresting , files , and spread primarily via a targeted phishing email usually promising a pornographic video .' [/INST] [Delivering:B-Purp, a:I-Purp, backdoor:I-Purp, and:I-Purp, spyware:I-Purp, ,:O, Desert:O, Falcons:O, 's:O, campaign:B-OffAct, was:O, designed:O, to:O, steal:B-Purp, information:I-Purp, from:O, infected:O, systems:O, using:O, a:O, malware:O, client:O, capable:O, of:O, filtering:O, out:O, ,:O, uninteresting:O, ,:O, files:O, ,:O, and:O, spread:O, primarily:O, via:O, a:O, targeted:O, phishing:B-Way, email:I-Way, usually:O, promising:O, a:O, pornographic:O, video: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: 'FrozenCell is the mobile component of a multi-platform attack we've seen a threat actor known as , Two-tailed Scorpion/APT-C-23 , , use to spy on victims through compromised mobile devices and desktops .' [/INST] [FrozenCell:B-Tool, is:O, the:O, mobile:O, component:O, of:O, a:O, multi-platform:B-OffAct, attack:I-OffAct, we've:O, seen:O, a:O, threat:O, actor:O, known:O, as:O, ,:O, Two-tailed:O, Scorpion/APT-C-23:B-HackOrg, ,:O, ,:O, use:O, to:O, spy:O, on:O, victims:O, through:O, compromised:O, mobile:O, devices:O, and:O, desktops: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 threat is another proof point that attackers are clearly incorporating the mobile device into their surveillance campaigns as a primary attack vector .' [/INST] [This:O, threat:O, is:O, another:O, proof:O, point:O, that:O, attackers:O, are:O, clearly:O, incorporating:O, the:O, mobile:B-Tool, device:I-Tool, into:O, their:O, surveillance:B-OffAct, campaigns:I-OffAct, as:O, a:O, primary:O, attack:B-OffAct, vector: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: 'Desert Falcons is keenly aware of the information they can derive from these devices and are using multi-stage ( phishing + an executable ) , multi-platform ( Android + desktop ) attacks to accomplish their spying .' [/INST] [Desert:B-HackOrg, Falcons:I-HackOrg, is:O, keenly:O, aware:O, of:O, the:O, information:O, they:O, can:O, derive:O, from:O, these:O, devices:O, and:O, are:O, using:O, multi-stage:O, (:O, phishing:B-Way, +:O, an:O, executable:O, ):O, ,:O, multi-platform:O, (:O, Android:O, +:O, desktop:O, ):O, attacks:B-OffAct, to:O, accomplish:O, their:O, spying: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: 'FrozenCell masquerades as fake updates to chat applications like Facebook , WhatsApp , Messenger , LINE , and LoveChat .' [/INST] [FrozenCell:B-Tool, masquerades:I-Tool, as:O, fake:O, updates:O, to:O, chat:O, applications:O, like:O, Facebook:B-Org, ,:O, WhatsApp:B-Org, ,:O, Messenger:B-Org, ,:O, LINE:B-Org, ,:O, and:O, LoveChat:B-Org, .: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 actors behind FrozenCell used a spoofed app called Tawjihi 2016 , which Jordanian or Palestinian students would ordinarily use during their general secondary examination .' [/INST] [For:O, example:O, ,:O, the:O, actors:O, behind:O, FrozenCell:B-Tool, used:O, a:O, spoofed:O, app:O, called:O, Tawjihi:B-Tool, 2016:I-Tool, ,:O, which:O, Jordanian:B-Area, or:O, Palestinian:B-Area, students:B-Org, would:O, ordinarily:O, use:O, during:O, their:O, general:O, secondary:O, examination: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 appears the Desert Falcons sent malicious executables though phishing campaigns impersonating individuals associated with the Palestinian Security Services , the General Directorate of Civil Defence - Ministry of the Interior , and the 7th Fateh Conference of the Palestinian National Liberation Front ( held in late 2016 ) .' [/INST] [It:O, appears:O, the:O, Desert:B-HackOrg, Falcons:I-HackOrg, sent:O, malicious:O, executables:O, though:O, phishing:B-OffAct, campaigns:I-OffAct, impersonating:O, individuals:O, associated:O, with:O, the:O, Palestinian:B-Area, Security:O, Services:O, ,:O, the:O, General:O, Directorate:O, of:O, Civil:O, Defence:O, -:O, Ministry:O, of:O, the:O, Interior:O, ,:O, and:O, the:O, 7th:O, Fateh:O, Conference:O, of:O, the:O, Palestinian:B-Area, National:B-Org, Liberation:I-Org, Front:I-Org, (:O, held:O, in:O, late:O, 2016:B-Time, ):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 titles and contents of these files suggest that the actor targeted individuals affiliated with these government agencies and the Fatah political party .' [/INST] [The:O, titles:O, and:O, contents:O, of:O, these:O, files:O, suggest:O, that:O, the:O, actor:O, targeted:O, individuals:O, affiliated:O, with:O, these:O, government:B-Org, agencies:I-Org, and:O, the:O, Fatah:B-Org, political:I-Org, party:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We believe that this is a new variant of VAMP , indicating that the threat actors behind APT-C-23 are still active and continuously improving their product .' [/INST] [We:O, believe:O, that:O, this:O, is:O, a:O, new:O, variant:O, of:O, VAMP:B-Tool, ,:O, indicating:O, that:O, the:O, threat:O, actors:O, behind:O, APT-C-23:B-HackOrg, are:O, still:O, active:O, and:O, continuously:O, improving:O, their:O, product: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: 'VAMP targeted various types of data from the phones of victims : images , text messages , contacts , and call history , among others .' [/INST] [VAMP:B-Tool, targeted:O, various:O, types:O, of:O, data:O, from:O, the:O, phones:O, of:O, victims:O, ::O, images:O, ,:O, text:O, messages:O, ,:O, contacts:O, ,:O, and:O, call:O, history:O, ,:O, among:O, others: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: 'Recently , Trend Micro researchers came across a new mobile malware family which we have called GnatSpy .' [/INST] [Recently:O, ,:O, Trend:B-SecTeam, Micro:I-SecTeam, researchers:O, came:O, across:O, a:O, new:O, mobile:O, malware:O, family:O, which:O, we:O, have:O, called:O, GnatSpy:B-Tool, .: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: 'On Nov. 27 , 2018 , Cisco 's Talos research division published a write-up outlining the contours of a sophisticated cyber espionage campaign it dubbed DNSpionage .' [/INST] [On:O, Nov.:B-Time, 27:I-Time, ,:O, 2018:B-Time, ,:O, Cisco:B-SecTeam, 's:I-SecTeam, Talos:I-SecTeam, research:O, division:O, published:O, a:O, write-up:O, outlining:O, the:O, contours:O, of:O, a:O, sophisticated:O, cyber:B-OffAct, espionage:I-OffAct, campaign:I-OffAct, it:O, dubbed:O, DNSpionage:B-OffAct, .: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: 'Talos said the perpetrators of DNSpionage were able to steal email and other login credentials from a number of government and private sector entities in Lebanon and the United Arab Emirates by hijacking the DNS servers for these targets , so that all email and virtual private networking ( VPN ) traffic was redirected to an Internet address controlled by the attackers .' [/INST] [Talos:B-SecTeam, said:O, the:O, perpetrators:O, of:O, DNSpionage:B-OffAct, were:O, able:O, to:O, steal:B-Purp, email:I-Purp, and:O, other:O, login:B-Purp, credentials:I-Purp, from:O, a:O, number:O, of:O, government:B-Idus, and:O, private:O, sector:O, entities:O, in:O, Lebanon:O, and:O, the:O, United:O, Arab:O, Emirates:O, by:O, hijacking:O, the:O, DNS:O, servers:O, for:O, these:O, targets:O, ,:O, so:O, that:O, all:O, email:B-Way, and:O, virtual:O, private:O, networking:O, (:O, VPN:B-Tool, ):O, traffic:O, was:O, redirected:O, to:O, an:O, Internet:O, address:O, controlled:O, by:O, the:O, attackers: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: 'Talos reported that these DNS hijacks also paved the way for the attackers to obtain SSL encryption certificates for the targeted domains ( e.g.webmail.finance.gov.lb ) , which allowed them to decrypt the intercepted email and VPN credentials and view them in plain text .' [/INST] [Talos:B-SecTeam, reported:O, that:O, these:O, DNS:B-Way, hijacks:I-Way, also:O, paved:O, the:O, way:O, for:O, the:O, attackers:O, to:O, obtain:B-Purp, SSL:I-Purp, encryption:I-Purp, certificates:I-Purp, for:O, the:O, targeted:O, domains:O, (:O, e.g.webmail.finance.gov.lb:O, ):O, ,:O, which:O, allowed:O, them:O, to:O, decrypt:O, the:O, intercepted:B-Purp, email:I-Purp, and:O, VPN:B-Purp, credentials:I-Purp, and:O, view:O, them:O, in:O, plain:O, text: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: 'That changed on Jan. 25 , 2019 , when security firm CrowdStrike published a blog post listing virtually every Internet address known to be ( ab )used by the espionage campaign to date .' [/INST] [That:O, changed:O, on:O, Jan.:B-Time, 25:I-Time, ,:O, 2019:B-Time, ,:O, when:O, security:B-Org, firm:I-Org, CrowdStrike:B-SecTeam, published:O, a:O, blog:O, post:O, listing:O, virtually:O, every:O, Internet:O, address:O, known:O, to:O, be:O, (:O, ab:O, )used:O, by:O, the:O, espionage:B-OffAct, campaign:I-OffAct, to:O, date: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: 'Working backwards from each Internet address , I was able to see that in the last few months of 2018 the hackers behind DNSpionage succeeded in compromising key components of DNS infrastructure for more than 50 Middle Eastern companies and government agencies , including targets in Albania , Cyprus , Egypt , Iraq , Jordan , Kuwait , Lebanon , Libya , Saudi Arabia and the United Arab Emirates .' [/INST] [Working:O, backwards:O, from:O, each:O, Internet:O, address:O, ,:O, I:O, was:O, able:O, to:O, see:O, that:O, in:O, the:O, last:O, few:O, months:O, of:O, 2018:B-Time, the:O, hackers:O, behind:O, DNSpionage:B-OffAct, succeeded:O, in:O, compromising:O, key:O, components:O, of:O, DNS:O, infrastructure:O, for:O, more:O, than:O, 50:O, Middle:B-Area, Eastern:I-Area, companies:B-Org, and:O, government:B-Org, agencies:I-Org, ,:O, including:O, targets:O, in:O, Albania:B-Area, ,:O, Cyprus:B-Area, ,:O, Egypt:B-Area, ,:O, Iraq:B-Area, ,:O, Jordan:B-Area, ,:O, Kuwait:B-Area, ,:O, Lebanon:B-Area, ,:O, Libya:B-Area, ,:O, Saudi:B-Area, Arabia:B-Area, and:O, the:O, United:B-Area, Arab:I-Area, Emirates:I-Area, .: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: 'PCH is a nonprofit entity based in northern California that also manages significant amounts of the world 's DNS infrastructure , particularly the DNS for more than 500 top-level domains and a number of the Middle East top-level domains targeted by DNSpionage .' [/INST] [PCH:O, is:O, a:O, nonprofit:O, entity:O, based:O, in:O, northern:O, California:O, that:O, also:O, manages:O, significant:O, amounts:O, of:O, the:O, world:O, 's:O, DNS:O, infrastructure:O, ,:O, particularly:O, the:O, DNS:O, for:O, more:O, than:O, 500:O, top-level:O, domains:O, and:O, a:O, number:O, of:O, the:O, Middle:B-Area, East:I-Area, top-level:O, domains:O, targeted:O, by:O, DNSpionage:B-OffAct, .: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 APT group usually carries out target attacks against government agencies to steal sensitive information .' [/INST] [This:O, APT:O, group:O, usually:O, carries:O, out:O, target:B-OffAct, attacks:I-OffAct, against:O, government:B-Org, agencies:I-Org, to:O, steal:B-Purp, sensitive:I-Purp, information:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to spreading malware via spear fishing email with Office attachment containing either vulnerability or malicious macro , this group is particularly good at leveraging malicious Android APKs in the target attacks .' [/INST] [In:O, addition:O, to:O, spreading:O, malware:O, via:O, spear:B-Way, fishing:I-Way, email:I-Way, with:O, Office:B-Way, attachment:I-Way, containing:O, either:O, vulnerability:O, or:O, malicious:O, macro:O, ,:O, this:O, group:O, is:O, particularly:O, good:O, at:O, leveraging:O, malicious:O, Android:B-Tool, APKs:I-Tool, in:O, the:O, target:B-OffAct, attacks:I-OffAct, .: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 named the actor DustSquad and have provided private intelligence reports to our customers on four of their campaigns involving custom Android and Windows malware .' [/INST] [We:O, named:O, the:O, actor:O, DustSquad:B-HackOrg, and:O, have:O, provided:O, private:O, intelligence:O, reports:O, to:O, our:O, customers:O, on:O, four:O, of:O, their:O, campaigns:B-OffAct, involving:O, custom:O, Android:O, and:O, Windows:B-Tool, malware:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this blogpost we cover a malicious program for Windows called Octopus that mostly targets diplomatic entities .' [/INST] [In:O, this:O, blogpost:O, we:O, cover:O, a:O, malicious:O, program:O, for:O, Windows:O, called:O, Octopus:B-Tool, that:O, mostly:O, targets:O, diplomatic:B-Org, entities:I-Org, .: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 also started monitoring the malware and , using Kaspersky Attribution Engine based on similarity algorithms , discovered that Octopus is related to DustSquad , something we reported in April 2018 .' [/INST] [We:O, also:O, started:O, monitoring:O, the:O, malware:O, and:O, ,:O, using:O, Kaspersky:B-SecTeam, Attribution:O, Engine:O, based:O, on:O, similarity:O, algorithms:O, ,:O, discovered:O, that:O, Octopus:B-Tool, is:O, related:O, to:O, DustSquad:O, ,:O, something:O, we:O, reported:O, in:O, April:B-Time, 2018:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'From early 2014 until December 2018 , ns0.idm.net.lb pointed to 194.126.10.18 , which appropriately enough is an Internet address based in Lebanon .' [/INST] [From:O, early:O, 2014:B-Time, until:O, December:B-Time, 2018:I-Time, ,:O, ns0.idm.net.lb:O, pointed:O, to:O, 194.126.10.18:O, ,:O, which:O, appropriately:O, enough:O, is:O, an:O, Internet:O, address:O, based:O, in:O, Lebanon: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 Lab products detect the Octopus Trojan as Trojan.Win32.Octopus.gen .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, products:O, detect:O, the:O, Octopus:B-Tool, Trojan:I-Tool, as:O, Trojan.Win32.Octopus.gen:I-Tool, .: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: 'Political entities in Central Asia have been targeted throughout 2018 by different actors , including IndigoZebra , Sofacy ( with Zebrocy malware ) and most recently by DustSquad ( with Octopus malware ) .' [/INST] [Political:B-Org, entities:I-Org, in:O, Central:O, Asia:O, have:O, been:O, targeted:O, throughout:O, 2018:B-Time, by:O, different:O, actors:O, ,:O, including:O, IndigoZebra:B-HackOrg, ,:O, Sofacy:B-HackOrg, (:O, with:O, Zebrocy:B-Tool, malware:I-Tool, ):O, and:O, most:O, recently:O, by:O, DustSquad:O, (:O, with:O, Octopus:B-Tool, malware:I-Tool, ):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: 'El Machete is one of these threats that was first publicly disclosed and named by Kaspersky here .' [/INST] [El:O, Machete:O, is:O, one:O, of:O, these:O, threats:O, that:O, was:O, first:O, publicly:O, disclosed:O, and:O, named:O, by:O, Kaspersky:B-SecTeam, here: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've found that this group has continued to operate successfully , predominantly in Latin America , since 2014 .' [/INST] [We've:O, found:O, that:O, this:O, group:O, has:O, continued:O, to:O, operate:O, successfully:O, ,:O, predominantly:O, in:O, Latin:B-Area, America:I-Area, ,:O, since:O, 2014:B-Time, .: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 attackers simply moved to new C2 infrastructure , based largely around dynamic DNS domains , in addition to making minimal changes to the malware in order to evade signature-based detection .' [/INST] [All:O, attackers:O, simply:O, moved:O, to:O, new:O, C2:O, infrastructure:O, ,:O, based:O, largely:O, around:O, dynamic:B-Way, DNS:I-Way, domains:I-Way, ,:O, in:O, addition:O, to:O, making:O, minimal:O, changes:O, to:O, the:O, malware:O, in:O, order:O, to:O, evade:B-Purp, signature-based:I-Purp, detection:I-Purp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the case of Octopus , DustSquad used Delphi as their programming language of choice , which is unusual for such an actor .' [/INST] [In:O, the:O, case:O, of:O, Octopus:B-Tool, ,:O, DustSquad:O, used:O, Delphi:O, as:O, their:O, programming:O, language:O, of:O, choice:O, ,:O, which:O, is:O, unusual:O, for:O, such:O, an:O, actor: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: 'Targets included a wide array of high-profile entities , including intelligence services , military , utility providers ( telecommunications and power ) , embassies , and government institutions .' [/INST] [Targets:O, included:O, a:O, wide:O, array:O, of:O, high-profile:O, entities:O, ,:O, including:O, intelligence:B-Idus, services:I-Idus, ,:O, military:B-Idus, ,:O, utility:B-Org, providers:I-Org, (:O, telecommunications:B-Idus, and:O, power:B-Idus, ):O, ,:O, embassies:B-Org, ,:O, and:O, government:B-Org, institutions:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Some time ago , a Kaspersky Lab customer in Latin America contacted us to say he had visited China and suspected his machine was infected with an unknown , undetected malware .' [/INST] [Some:O, time:O, ago:O, ,:O, a:O, Kaspersky:B-SecTeam, Lab:I-SecTeam, customer:O, in:O, Latin:B-Area, America:I-Area, contacted:O, us:O, to:O, say:O, he:O, had:O, visited:O, China:B-Area, and:O, suspected:O, his:O, machine:O, was:O, infected:O, with:O, an:O, unknown:O, ,:O, undetected: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: 'It was a targeted attack we are calling , Machete , .' [/INST] [It:O, was:O, a:O, targeted:B-OffAct, attack:I-OffAct, we:O, are:O, calling:O, ,:O, Machete: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: 'At first look , it pretends to be a Java related application but after a quick analysis , it was obvious this was something more than just a simple Java file .' [/INST] [At:O, first:O, look:O, ,:O, it:O, pretends:O, to:O, be:O, a:O, Java:B-Tool, related:I-Tool, application:I-Tool, but:O, after:O, a:O, quick:O, analysis:O, ,:O, it:O, was:O, obvious:O, this:O, was:O, something:O, more:O, than:O, just:O, a:O, simple:O, Java:B-SamFile, file:I-SamFile, .: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: ', Machete , is a targeted attack campaign with Spanish speaking roots .' [/INST] [,:O, Machete:O, ,:O, is:O, a:O, targeted:B-OffAct, attack:I-OffAct, campaign:I-OffAct, with:O, Spanish:B-Area, speaking:O, roots: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 decoy slideshows all contain photos from very meaningful events to individuals in Thailand , suggesting that the actors continually look for impactful events to use to disguise their attacks .' [/INST] [The:O, decoy:B-Tool, slideshows:I-Tool, all:O, contain:O, photos:O, from:O, very:O, meaningful:O, events:O, to:O, individuals:O, in:O, Thailand:B-Area, ,:O, suggesting:O, that:O, the:O, actors:O, continually:O, look:O, for:O, impactful:O, events:O, to:O, use:O, to:O, disguise:O, their:O, attacks:B-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In some cases , such as Russia , the target appears to be an embassy from one of the countries of this list .' [/INST] [In:O, some:O, cases:O, ,:O, such:O, as:O, Russia:B-Area, ,:O, the:O, target:O, appears:O, to:O, be:O, an:O, embassy:B-Org, from:O, one:O, of:O, the:O, countries:O, of:O, this:O, list: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: 'Both attackers and victims speak Spanish natively , as we see it consistently in the source code of the client side and in the Python code .' [/INST] [Both:O, attackers:O, and:O, victims:O, speak:O, Spanish:B-Area, natively:O, ,:O, as:O, we:O, see:O, it:O, consistently:O, in:O, the:O, source:O, code:O, of:O, the:O, client:O, side:O, and:O, in:O, the:O, Python: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: 'We are also grateful to the Private Office of his Holiness the Dalai Lama , the Tibetan Government-in-Exile , the missions of Tibet in London , Brussels , and New York , and Drewla ( a Tibetan NGO ) .' [/INST] [We:O, are:O, also:O, grateful:O, to:O, the:O, Private:O, Office:O, of:O, his:O, Holiness:O, the:O, Dalai:O, Lama:O, ,:O, the:O, Tibetan:O, Government-in-Exile:O, ,:O, the:O, missions:O, of:O, Tibet:B-Org, in:O, London:O, ,:O, Brussels:B-Org, ,:O, and:O, New:O, York:O, ,:O, and:O, Drewla:B-Org, (:O, a:O, Tibetan:B-Org, NGO:B-Idus, ):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: 'Between June 2008 and March 2009 the Information Warfare Monitor conducted an extensive and exhaustive two-phase investigation focused on allegations of Chinese cyber espionage against the Tibetan community .' [/INST] [Between:O, June:B-Time, 2008:I-Time, and:O, March:B-Time, 2009:I-Time, the:O, Information:O, Warfare:O, Monitor:O, conducted:O, an:O, extensive:O, and:O, exhaustive:O, two-phase:O, investigation:O, focused:O, on:O, allegations:O, of:O, Chinese:B-Area, cyber:I-Area, espionage:O, against:O, the:O, Tibetan:B-Org, community:I-Org, .: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: 'These instances of Gh0st RAT are consistently controlled from commercial Internet access accounts located on the island of Hainan , People's Republic of China .' [/INST] [These:O, instances:O, of:O, Gh0st:B-Tool, RAT:I-Tool, are:O, consistently:O, controlled:O, from:O, commercial:O, Internet:O, access:O, accounts:O, located:O, on:O, the:O, island:B-Area, of:I-Area, Hainan:I-Area, ,:O, People's:B-Area, Republic:I-Area, of:I-Area, China:I-Area, .: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 fieldwork generated extensive data that allowed us to examine Tibetan information security practices , as well as capture real-time evidence of malware that had penetrated Tibetan computer systems .' [/INST] [The:O, fieldwork:O, generated:O, extensive:O, data:O, that:O, allowed:O, us:O, to:O, examine:O, Tibetan:B-Org, information:I-Org, security:I-Org, practices:I-Org, ,:O, as:O, well:O, as:O, capture:O, real-time:O, evidence:O, of:O, malware:O, that:O, had:O, penetrated:O, Tibetan:B-Org, computer:O, systems: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 is therefore possible that the large percentage of high value targets identified in our analysis of the GhostNet are coincidental , spread by contact between individuals who previously communicated through e-mail .' [/INST] [It:O, is:O, therefore:O, possible:O, that:O, the:O, large:O, percentage:O, of:O, high:O, value:O, targets:O, identified:O, in:O, our:O, analysis:O, of:O, the:O, GhostNet:B-OffAct, are:O, coincidental:O, ,:O, spread:O, by:O, contact:O, between:O, individuals:O, who:O, previously:O, communicated:O, through:O, e-mail:B-Way, .: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: 'Where they exist , they often use grey market or pirated software .' [/INST] [Where:O, they:O, exist:O, ,:O, they:O, often:O, use:O, grey:B-Tool, market:I-Tool, or:O, pirated:B-Tool, software:I-Tool, .: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: 'Contextually relevant emails are sent to specific targets with attached documents that are packed with exploit code and Trojan horse programmes designed to take advantage of vulnerabilities in software installed on the target 's computer .' [/INST] [Contextually:O, relevant:O, emails:B-Way, are:O, sent:O, to:O, specific:O, targets:O, with:O, attached:O, documents:B-SamFile, that:O, are:O, packed:O, with:O, exploit:O, code:O, and:O, Trojan:O, horse:O, programmes:O, designed:O, to:O, take:O, advantage:O, of:O, vulnerabilities:O, in:O, software:O, installed:O, on:O, the:O, target:O, 's:O, computer: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: 'GhostNet represents a network of compromised computers resident in high-value political , economic , and media locations spread across numerous countries worldwide .' [/INST] [GhostNet:B-OffAct, represents:O, a:O, network:O, of:O, compromised:O, computers:O, resident:O, in:O, high-value:O, political:B-Idus, ,:O, economic:B-Idus, ,:O, and:O, media:B-Idus, locations:O, spread:O, across:O, numerous:O, countries:O, worldwide:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After that , the attacker is capable to control the compromised device .' [/INST] [After:O, that:O, ,:O, the:O, attacker:O, is:O, capable:O, to:O, control:O, the:O, compromised:B-Way, device:I-Way, .: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 computers of diplomats , military attachés , private assistants , secretaries to Prime Ministers , journalists and others are under the concealed control of unknown assailant (s ) .' [/INST] [The:O, computers:O, of:O, diplomats:B-Org, ,:O, military:B-Org, attachés:I-Org, ,:O, private:B-Org, assistants:I-Org, ,:O, secretaries:B-Org, to:O, Prime:B-Org, Ministers:I-Org, ,:O, journalists:B-Org, and:O, others:O, are:O, under:O, the:O, concealed:O, control:O, of:O, unknown:O, assailant:O, (s: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 C&C server ( 82.137.255.56 ) used by the above backdoors was used by APT-C-27 ( Goldmouse ) many times since 2017 .' [/INST] [The:O, C&C:O, server:O, (:O, 82.137.255.56:O, ):O, used:O, by:O, the:O, above:O, backdoors:O, was:O, used:O, by:O, APT-C-27:O, (:O, Goldmouse:B-HackOrg, ):O, many:O, times:O, since:O, 2017: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: 'According to 360 Threat Intelligence Center , Goldmouse was observed deploying the nebulous njRAT backdoor .' [/INST] [According:O, to:O, 360:B-SecTeam, Threat:I-SecTeam, Intelligence:I-SecTeam, Center:I-SecTeam, ,:O, Goldmouse:O, was:O, observed:O, deploying:O, the:O, nebulous:O, njRAT:B-Tool, backdoor:I-Tool, .: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 banking malware GozNym has legs ; only a few weeks after the hybrid Trojan was discovered , it has reportedly spread into Europe and begun plaguing banking customers in Poland with redirection attacks .' [/INST] [The:O, banking:O, malware:O, GozNym:B-Tool, has:O, legs:O, ;:O, only:O, a:O, few:O, weeks:O, after:O, the:O, hybrid:O, Trojan:O, was:O, discovered:O, ,:O, it:O, has:O, reportedly:O, spread:O, into:O, Europe:O, and:O, begun:O, plaguing:O, banking:B-Org, customers:I-Org, in:O, Poland:O, with:O, redirection:B-OffAct, attacks:I-OffAct, .: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 APT group is reportedly targeting the Middle East region .' [/INST] [The:O, APT:O, group:O, is:O, reportedly:O, targeting:O, the:O, Middle:B-Area, East:I-Area, region:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware has started targeting corporate , SMB , investment banking and consumer accounts at banks , including some in Portugal and the U.S. , in addition to Poland , according to researchers at IBM 's X-Force team .' [/INST] [The:O, malware:O, has:O, started:O, targeting:O, corporate:O, ,:O, SMB:B-Tool, ,:O, investment:B-Idus, banking:I-Idus, and:O, consumer:O, accounts:O, at:O, banks:B-Idus, ,:O, including:O, some:O, in:O, Portugal:O, and:O, the:O, U.S.:B-Area, ,:O, in:O, addition:O, to:O, Poland:B-Area, ,:O, according:O, to:O, researchers:O, at:O, IBM:B-SecTeam, 's:I-SecTeam, X-Force:I-SecTeam, team: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: 'According to Kessem the malware has redirection instructions for 17 banks , and features an additional 230 URLs to assist attackers in targeting community banks and email service providers in Poland .' [/INST] [According:O, to:O, Kessem:B-SecTeam, the:O, malware:O, has:O, redirection:O, instructions:O, for:O, 17:O, banks:B-Idus, ,:O, and:O, features:O, an:O, additional:O, 230:O, URLs:O, to:O, assist:O, attackers:O, in:O, targeting:O, community:B-Idus, banks:I-Idus, and:O, email:B-Org, service:I-Org, providers:I-Org, in:O, Poland:B-Area, .: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 GozNym , attackers dupe users by showing them the actual bank 's URL and SSL certificate .' [/INST] [With:O, GozNym:B-Tool, ,:O, attackers:O, dupe:B-Purp, users:I-Purp, by:O, showing:O, them:O, the:O, actual:O, bank:B-Idus, 's:O, URL:B-Tool, and:O, SSL:B-Tool, certificate:I-Tool, .: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: 'Fresh from targeting banks in Poland , the banking Trojan GozNym has begun taking aim at banks in Germany .' [/INST] [Fresh:O, from:O, targeting:O, banks:B-Idus, in:O, Poland:B-Area, ,:O, the:O, banking:B-Tool, Trojan:I-Tool, GozNym:B-Tool, has:O, begun:O, taking:O, aim:O, at:O, banks:B-Idus, in:O, Germany:B-Area, .: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: 'Attackers went on to use the Trojan to steal $4 million from 24 banks , including 22 in the United States and two in Canada , in just two weeks .' [/INST] [Attackers:O, went:O, on:O, to:O, use:O, the:O, Trojan:O, to:O, steal:O, $4:O, million:O, from:O, 24:O, banks:B-Idus, ,:O, including:O, 22:O, in:O, the:O, United:B-Area, States:I-Area, and:O, two:O, in:O, Canada:B-Area, ,:O, in:O, just:O, two:O, weeks: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: 'Recreating and maintaining fake bank sites can be an arduous task , but Kessem claims the GozNym group appears up to the task .' [/INST] [Recreating:O, and:O, maintaining:O, fake:O, bank:B-Idus, sites:O, can:O, be:O, an:O, arduous:O, task:O, ,:O, but:O, Kessem:B-SecTeam, claims:O, the:O, GozNym:O, group:O, appears:O, up:O, to:O, the:O, task: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 is distributed primarily through laced spam emails that lure recipients into opening attachments .' [/INST] [The:O, malware:O, is:O, distributed:O, primarily:O, through:O, laced:B-Way, spam:I-Way, emails:I-Way, that:O, lure:O, recipients:O, into:O, opening:O, attachments: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: 'Kessem .' [/INST] [Kessem:B-SecTeam, .: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: 'Fresh from targeting banks in Poland , the banking Trojan has reportedly begun taking aim at banks in Germany .' [/INST] [Fresh:O, from:O, targeting:O, banks:B-Idus, in:O, Poland:B-Area, ,:O, the:O, banking:B-Tool, Trojan:I-Tool, has:O, reportedly:O, begun:O, taking:O, aim:O, at:O, banks:B-Idus, in:O, Germany:B-Area, .:O] </s> |
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