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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 documents attached to spear-phishing e-mails used in both attacks contain code that exploits CVE-2012-0158 , which despite its age remains one of the most common Microsoft Word vulnerabilities being exploited by multiple threat actors .' [/INST] [The:O, documents:B-SamFile, attached:O, to:O, spear-phishing:B-Way, e-mails:I-Way, used:O, in:O, both:O, attacks:B-OffAct, contain:O, code:O, that:O, exploits:O, CVE-2012-0158:B-Exp, ,:O, which:O, despite:O, its:O, age:O, remains:O, one:O, of:O, the:O, most:O, common:O, Microsoft:B-Exp, Word:I-Exp, vulnerabilities:I-Exp, being:O, exploited:O, by:O, multiple:O, threat:O, actors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'If the document was delivered with macros instead of exploits ( CVE-2012-0158 , CVE-2013-3906 or CVE-2014-1761 ) , then the document contained instructions for enabling macros .' [/INST] [If:O, the:O, document:B-SamFile, was:O, delivered:O, with:O, macros:O, instead:O, of:O, exploits:O, (:O, CVE-2012-0158:B-Exp, ,:O, CVE-2013-3906:B-Exp, or:O, CVE-2014-1761:B-Exp, ):O, ,:O, then:O, the:O, document:O, contained:O, instructions:O, for:O, enabling:O, macros:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Lately , Patchwork has been sending multiple RTF files exploiting CVE-2017-8570 .' [/INST] [Lately:O, ,:O, Patchwork:B-HackOrg, has:O, been:O, sending:O, multiple:O, RTF:B-SamFile, files:I-SamFile, exploiting:O, CVE-2017-8570: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: 'Kaspersky Lab 's products detect the Microsoft Office exploits used in the spear-phishing attacks , including Exploit.MSWord.CVE-2010-333 , Exploit.Win32.CVE-2012-0158 .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, products:O, detect:O, the:O, Microsoft:B-Exp, Office:I-Exp, exploits:I-Exp, used:O, in:O, the:O, spear-phishing:B-OffAct, attacks:I-OffAct, ,:O, including:O, Exploit.MSWord.CVE-2010-333:B-SamFile, ,:O, Exploit.Win32.CVE-2012-0158: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: 'The files exploit the well-known Microsoft Office vulnerability , CVE-2012-0158 , to execute malicious code in order to take control of the targeted systems .' [/INST] [The:O, files:B-SamFile, exploit:O, the:O, well-known:O, Microsoft:B-Exp, Office:I-Exp, vulnerability:I-Exp, ,:O, CVE-2012-0158:B-Exp, ,:O, to:O, execute:O, malicious:O, code:O, in:O, order:O, to:O, take:B-Features, control:I-Features, of:O, the:O, targeted: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: 'CVE-2017-0143 was also used by two other exploit tools—EternalRomance and EternalSynergy—that were released as part of the Shadow Brokers leak in April 2017 .' [/INST] [CVE-2017-0143:B-Exp, was:O, also:O, used:O, by:O, two:O, other:O, exploit:O, tools—EternalRomance:B-SamFile, and:O, EternalSynergy—that:B-SamFile, were:O, released:O, as:O, part:O, of:O, the:O, Shadow:O, Brokers:O, leak:O, in:O, April:B-Time, 2017: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: 'this RTF exploits again the CVE-2017_1882 on eqnedt32.exe .' [/INST] [this:O, RTF:B-SamFile, exploits:O, again:O, the:O, CVE-2017_1882:B-Exp, on:O, eqnedt32.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: 'The analyzed RTF files share the same object dimension (objw2180\objh300) used to track the RTF weaponizer in our previous report , however , the sample was not exploiting CVE-2017-11882 or CVE-2018-0802 .' [/INST] [The:O, analyzed:O, RTF:O, files:O, share:O, the:O, same:O, object:O, dimension:O, (objw2180\objh300):O, used:O, to:O, track:O, the:O, RTF:O, weaponizer:O, in:O, our:O, previous:O, report:O, ,:O, however:O, ,:O, the:O, sample:B-SamFile, was:O, not:O, exploiting:O, CVE-2017-11882:B-Exp, or:O, CVE-2018-0802: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: 'After further analysis , it was discovered that the RTF files were exploiting the CVE-2018-0798 vulnerability in Microsoft’s Equation Editor (EQNEDT32) .' [/INST] [After:O, further:O, analysis:O, ,:O, it:O, was:O, discovered:O, that:O, the:O, RTF:B-SamFile, files:I-SamFile, were:O, exploiting:O, the:O, CVE-2018-0798:B-Exp, vulnerability:O, in:O, Microsoft’s:O, Equation:O, Editor:O, (EQNEDT32):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Anomali Researchers were able to identify multiple samples of malicious RTF documents ITW using the same exploit for CVE-2018-0798 .' [/INST] [Anomali:B-SecTeam, Researchers:O, were:O, able:O, to:O, identify:O, multiple:O, samples:O, of:O, malicious:O, RTF:O, documents:O, ITW:B-SamFile, using:O, the:O, same:O, exploit:O, for:O, CVE-2018-0798: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: 'Upon opening of the MS Word document , our embedded file exploits CVE-2017-11882 to drop a malicious fake Norton Security Shell Extension module , 'NavShExt.dll' , which is then injected into iexplore.exe to install the backdoor , begin collection , and activate command and control .' [/INST] [Upon:O, opening:O, of:O, the:O, MS:O, Word:O, document:O, ,:O, our:O, embedded:O, file:O, exploits:O, CVE-2017-11882:B-Exp, to:O, drop:O, a:O, malicious:O, fake:O, Norton:O, Security:O, Shell:O, Extension:O, module:O, ,:O, 'NavShExt.dll':B-SamFile, ,:O, which:O, is:O, then:O, injected:O, into:O, iexplore.exe:B-SamFile, to:O, install:O, the:O, backdoor:O, ,:O, begin:O, collection:O, ,:O, and:O, activate:O, command:O, and:O, control:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Moving through the infection process , NetWitness Endpoint detects the initial exploit CVE-2017-1182 in action as the Microsoft Equation Editor , 'EQNEDT32.exe' , scores high for potentially malicious activity .' [/INST] [Moving:O, through:O, the:O, infection:O, process:O, ,:O, NetWitness:O, Endpoint:O, detects:O, the:O, initial:O, exploit:O, CVE-2017-1182:B-Exp, in:O, action:O, as:O, the:O, Microsoft:B-SamFile, Equation:I-SamFile, Editor:I-SamFile, ,:O, 'EQNEDT32.exe':B-SamFile, ,:O, scores:O, high:O, for:O, potentially: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: 'In some of the latest samples of BalkanDoor detected in 2019 , the malware is distributed as an ACE archive , disguised as a RAR archive (i.e , not an executable file) , specially crafted to exploit the WinRAR ACE vulnerability CVE-2018-20250 .' [/INST] [In:O, some:O, of:O, the:O, latest:O, samples:O, of:O, BalkanDoor:B-SamFile, detected:O, in:O, 2019:B-Time, ,:O, the:O, malware:O, is:O, distributed:O, as:O, an:O, ACE:O, archive:O, ,:O, disguised:O, as:O, a:O, RAR:O, archive:O, (i.e:O, ,:O, not:O, an:O, executable:O, file):O, ,:O, specially:O, crafted:O, to:O, exploit:O, the:O, WinRAR:O, ACE:O, vulnerability:O, CVE-2018-20250: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 China Chopper actor activity starts with the download and execution of two exploit files which attempt to exploit the Windows vulnerabilities CVE-2015-0062 , CVE-2015-1701 and CVE-2016-0099 to allow the attacker to modify other objects on the server .' [/INST] [The:O, China:B-SamFile, Chopper:I-SamFile, actor:O, activity:O, starts:O, with:O, the:O, download:O, and:O, execution:O, of:O, two:O, exploit:O, files:O, which:O, attempt:O, to:O, exploit:O, the:O, Windows:O, vulnerabilities:O, CVE-2015-0062:B-Exp, ,:O, CVE-2015-1701:B-Exp, and:O, CVE-2016-0099:B-Exp, to:O, allow:O, the:O, attacker:B-HackOrg, to:O, modify:O, other:O, objects:O, on:O, the: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 following archive caught our attention for exploiting a WinRAR unacev2 module vulnerability and for having interesting content .' [/INST] [The:O, following:O, archive:B-SamFile, caught:O, our:O, attention:O, for:O, exploiting:O, a:O, WinRAR:O, unacev2:O, module:O, vulnerability:B-Exp, and:O, for:O, having:O, interesting:O, content:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 all emails sent to these government officials , the actor used the same attachment : a malicious Microsoft Word document that exploited the CVE-2012-0158 vulnerability to drop a malicious payload .' [/INST] [In:O, all:O, emails:B-Way, sent:O, to:O, these:O, government:B-Org, officials:I-Org, ,:O, the:O, actor:O, used:O, the:O, same:O, attachment:O, ::O, a:O, malicious:B-SamFile, Microsoft:I-SamFile, Word:I-SamFile, document:I-SamFile, that:O, exploited:O, the:O, CVE-2012-0158:B-Exp, vulnerability:O, to:O, drop:O, a:O, malicious:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the security firm , this campaign targeted Indian military officials via spear-phishing emails , distributing spyware to its victims via an Adobe Reader vulnerability .' [/INST] [According:O, to:O, the:O, security:B-Org, firm:I-Org, ,:O, this:O, campaign:B-OffAct, targeted:O, Indian:O, military:B-Org, officials:I-Org, via:O, spear-phishing:B-Way, emails:I-Way, ,:O, distributing:O, spyware:O, to:O, its:O, victims:O, via:O, an:O, Adobe:B-Exp, Reader:I-Exp, vulnerability:I-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: 'PLATINUM 's persistent use of spear phishing tactics ( phishing attempts aimed at specific individuals ) and access to previously undiscovered zero-day exploits have made it a highly resilient threat .' [/INST] [PLATINUM:B-HackOrg, 's:O, persistent:O, use:O, of:O, spear:B-Way, phishing:I-Way, tactics:I-Way, (:O, phishing:B-Way, attempts:O, aimed:O, at:O, specific:B-Org, individuals:I-Org, ):O, and:O, access:O, to:O, previously:O, undiscovered:O, zero-day:B-Exp, exploits:I-Exp, have:O, made:O, it:O, a:O, highly:O, resilient:O, threat:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 group 's persistent use of spear phishing tactics ( phishing attempts aimed at specific individuals ) and access to previously undiscovered zero-day exploits have made it a highly resilient threat .' [/INST] [The:O, group:B-HackOrg, 's:O, persistent:O, use:O, of:O, spear:B-Way, phishing:I-Way, tactics:I-Way, (:O, phishing:B-Way, attempts:O, aimed:O, at:O, specific:B-Org, individuals:I-Org, ):O, and:O, access:O, to:O, previously:O, undiscovered:O, zero-day:B-Exp, exploits:I-Exp, have:O, made:O, it:O, a:O, highly:O, resilient:O, threat:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the Carbanak campaign is a clear indicator of a new era in cybercrime in which criminals use APT techniques directly against the financial industry instead of through its customers .' [/INST] [We:O, believe:O, that:O, the:O, Carbanak:B-Exp, campaign:B-OffAct, is:O, a:O, clear:O, indicator:O, of:O, a:O, new:O, era:O, in:O, cybercrime:O, in:O, which:O, criminals:B-HackOrg, use:O, APT:B-Way, techniques:I-Way, directly:O, against:O, the:O, financial:B-Idus, industry:I-Idus, instead:O, of:O, through:O, its:O, customers: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: 'Carbanak has its origin in more common financial fraud including theft from consumer and corporate bank accounts in Europe and Russia , using standard banking malware , mainly Carberp .' [/INST] [Carbanak:B-Exp, has:O, its:O, origin:O, in:O, more:O, common:O, financial:O, fraud:O, including:O, theft:O, from:O, consumer:B-Org, and:O, corporate:O, bank:O, accounts:O, in:O, Europe:B-Area, and:O, Russia:B-Area, ,:O, using:O, standard:O, banking:O, malware:O, ,:O, mainly:O, Carberp: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: 'However , in September last year , our friends at CSIS published a blog detailing a new Carbanak variant affecting one of its customers .' [/INST] [However:O, ,:O, in:O, September:B-Time, last:O, year:O, ,:O, our:O, friends:O, at:O, CSIS:B-SecTeam, published:O, a:O, blog:O, detailing:O, a:O, new:O, Carbanak:B-Exp, variant:O, affecting:O, one:O, of:O, its:O, customers: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: 'PIVY also played a key role in the 2011 campaign known as Nitro that targeted chemical makers , government agencies , defense contractors , and human rights groups.10,11 Still active a year later , the Nitro attackers used a zero-day vulnerability in Java to deploy PIVY in 2012 .' [/INST] [PIVY:B-Tool, also:O, played:O, a:O, key:O, role:O, in:O, the:O, 2011:B-OffAct, campaign:I-OffAct, known:O, as:O, Nitro:O, that:O, targeted:O, chemical:B-Org, makers:I-Org, ,:O, government:B-Org, agencies:I-Org, ,:O, defense:B-Org, contractors:I-Org, ,:O, and:O, human:O, rights:O, groups.10,11:O, Still:O, active:O, a:O, year:O, later:O, ,:O, the:O, Nitro:O, attackers:B-HackOrg, used:O, a:O, zero-day:B-Exp, vulnerability:I-Exp, in:O, Java:O, to:O, deploy:O, PIVY:B-Tool, 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: 'We believe that the Carbanak campaign is a clear indicator of a new era in cybercrime in which criminals use APT techniques directly against the financial industry instead of through its customers .' [/INST] [We:O, believe:O, that:O, the:O, Carbanak:B-Exp, campaign:B-OffAct, is:O, a:O, clear:O, indicator:O, of:O, a:O, new:O, era:O, in:O, cybercrime:O, in:O, which:O, criminals:B-HackOrg, use:O, APT:B-Way, techniques:I-Way, directly:O, against:O, the:O, financial:B-Idus, industry:I-Idus, instead:O, of:O, through:O, its:O, customers: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: 'Carbanak has its origin in more common financial fraud including theft from consumer and corporate bank accounts in Europe and Russia , using standard banking malware , mainly Carberp .' [/INST] [Carbanak:B-Exp, has:O, its:O, origin:O, in:O, more:O, common:O, financial:O, fraud:O, including:O, theft:O, from:O, consumer:B-Org, and:O, corporate:O, bank:O, accounts:O, in:O, Europe:B-Area, and:O, Russia:B-Area, ,:O, using:O, standard:O, banking:O, malware:O, ,:O, mainly:O, Carberp: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: 'However , in September last year , our friends at CSIS published a blog detailing a new Carbanak variant affecting one of its customers .' [/INST] [However:O, ,:O, in:O, September:B-Time, last:O, year:O, ,:O, our:O, friends:O, at:O, CSIS:B-SecTeam, published:O, a:O, blog:O, detailing:O, a:O, new:O, Carbanak:B-Exp, variant:O, affecting:O, one:O, of:O, its:O, customers: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: 'Alternatively , it is also possible that APT41 injected malicious code into the package prior to compilation , circumventing the need to steal the code-signing certificate and compile it on their own .' [/INST] [Alternatively:O, ,:O, it:O, is:O, also:O, possible:O, that:O, APT41:B-HackOrg, injected:B-Way, malicious:I-Way, code:I-Way, into:O, the:O, package:O, prior:O, to:O, compilation:O, ,:O, circumventing:B-Purp, the:O, need:O, to:O, steal:O, the:O, code-signing:O, certificate:O, and:O, compile:O, it:O, on:O, their:O, own:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 these instances , APT41 leveraged TeamViewer to transfer malware into the compromised environment , although we do not have direct evidence of APT41 compromising TeamViewer .' [/INST] [In:O, these:O, instances:O, ,:O, APT41:B-HackOrg, leveraged:O, TeamViewer:B-Tool, to:O, transfer:B-Purp, malware:I-Purp, into:O, the:O, compromised:O, environment:O, ,:O, although:O, we:O, do:O, not:O, have:O, direct:O, evidence:O, of:O, APT41:B-HackOrg, compromising:O, TeamViewer:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT41 has targeted payment services specializing in handling in-game transactions and real money transfer (RMT) purchases .' [/INST] [APT41:B-HackOrg, has:O, targeted:O, payment:B-Idus, services:I-Idus, specializing:O, in:O, handling:B-Purp, in-game:I-Purp, transactions:I-Purp, and:O, real:O, money:O, transfer:O, (RMT):O, purchases:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 instances , APT41 leveraged POISONPLUG as a first-stage backdoor to deploy the HIGHNOON backdoor in the targeted environment .' [/INST] [In:O, some:O, instances:O, ,:O, APT41:B-HackOrg, leveraged:O, POISONPLUG:B-Tool, as:O, a:O, first-stage:O, backdoor:O, to:O, deploy:B-Purp, the:O, HIGHNOON:B-Tool, backdoor:O, in:O, the:O, targeted:O, environment:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 another instance , APT41 targeted a hotel’s reservation systems ahead of Chinese officials staying there , suggesting the group was tasked to reconnoiter the facility for security reasons .' [/INST] [In:O, another:O, instance:O, ,:O, APT41:B-HackOrg, targeted:O, a:O, hotel’s:O, reservation:O, systems:O, ahead:O, of:O, Chinese:O, officials:O, staying:O, there:O, ,:O, suggesting:O, the:O, group:O, was:O, tasked:B-Purp, to:O, reconnoiter:O, the:O, facility:O, for:O, security:O, reasons:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 limited use of these tools by APT41 suggests the group reserves more advanced TTPs and malware only for high-value targets .' [/INST] [The:O, limited:O, use:O, of:O, these:O, tools:O, by:O, APT41:B-HackOrg, suggests:O, the:O, group:O, reserves:B-Purp, more:I-Purp, advanced:I-Purp, TTPs:I-Purp, and:O, malware:O, only:O, for:O, high-value:O, targets:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'At the time of analysis , the subdomains did not host a website; however , based on BITTER APT group’s targeting patterns , it is highly likely that they were created to host faux login phishing pages designed to steal user’s credentials .' [/INST] [At:O, the:O, time:O, of:O, analysis:O, ,:O, the:O, subdomains:O, did:O, not:O, host:O, a:O, website;:O, however:O, ,:O, based:O, on:O, BITTER:B-HackOrg, APT:I-HackOrg, group’s:O, targeting:O, patterns:O, ,:O, it:O, is:O, highly:O, likely:O, that:O, they:O, were:O, created:O, to:O, host:O, faux:O, login:O, phishing:O, pages:O, designed:O, to:O, steal:B-Purp, user’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: 'The group behind these attacks has stolen gigabytes of confidential documents , mostly from military organizations .' [/INST] [The:O, group:B-HackOrg, behind:O, these:O, attacks:O, has:O, stolen:B-Purp, gigabytes:I-Purp, of:O, confidential:O, documents:O, ,:O, mostly:O, from:O, military:B-Idus, organizations:B-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: 'They seem to have specialized knowledge about military operations , as they are focused on stealing specific files such as those that describe navigation routes .' [/INST] [They:B-HackOrg, seem:O, to:O, have:O, specialized:O, knowledge:O, about:O, military:B-Idus, operations:O, ,:O, as:O, they:O, are:O, focused:O, on:O, stealing:B-Purp, specific:I-Purp, files:I-Purp, such:O, as:O, those:O, that:O, describe:B-Purp, navigation:I-Purp, routes: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: 'SectorJ04 used the spear phishing email to spread malicious Excel or malicious Word files , and downloaded the MSI files from the attacker’s server when the malicious documents were run .' [/INST] [SectorJ04:B-HackOrg, used:O, the:O, spear:B-Way, phishing:I-Way, email:O, to:O, spread:B-Purp, malicious:I-Purp, Excel:O, or:O, malicious:O, Word:O, files:O, ,:O, and:O, downloaded:B-Purp, the:O, MSI:O, files:O, from:O, the:O, attacker’s:B-HackOrg, server:O, when:O, the:O, malicious:O, documents:O, were:O, run:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 have established that the aim of the attack was to deliver and launch the second stage of Silence’s Trojan , known as Silence.MainModule .' [/INST] [Group-IB:B-SecTeam, specialists:O, have:O, established:O, that:O, the:O, aim:O, of:O, the:O, attack:O, was:O, to:O, deliver:B-Purp, and:O, launch:B-Purp, the:O, second:O, stage:O, of:O, Silence’s:B-HackOrg, Trojan:O, ,:O, known:O, as:O, Silence.MainModule:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 hackers will map a company’s network and look for strategically favorable locations for placing their malware .' [/INST] [The:O, hackers:B-HackOrg, will:O, map:O, a:O, company’s:O, network:O, and:O, look:O, for:O, strategically:O, favorable:O, locations:O, for:O, placing:B-Purp, their:I-Purp, malware: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: 'Typically , APT10 tends to employ a namesquatting scheme in their domains that aims to confuse the observer by posing as a legitimate domain .' [/INST] [Typically:O, ,:O, APT10:B-HackOrg, tends:O, to:O, employ:B-Way, a:O, namesquatting:O, scheme:O, in:O, their:O, domains:O, that:O, aims:O, to:O, confuse:B-Purp, the:O, observer:O, by:O, posing:O, as:O, a:O, legitimate:O, domain:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'If the attack had succeeded , it would have given hackers control over the ATM network , while money mules would have been standing by the ATM machines at pre-set time intervals to cash them out .' [/INST] [If:O, the:O, attack:O, had:O, succeeded:O, ,:O, it:O, would:O, have:O, given:O, hackers:B-HackOrg, control:B-Purp, over:I-Purp, the:O, ATM:O, network:O, ,:O, while:O, money:O, mules:O, would:O, have:O, been:O, standing:O, by:O, the:O, ATM:O, machines:O, at:O, pre-set:O, time:O, intervals:O, to:O, cash:O, them:O, out:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the functionality of the various tools uploaded to the webshells , we believe the threat actors breach the SharePoint servers to use as a beachhead , then attempt to move laterally across the network via stolen credentials and exploiting vulnerabilities .' [/INST] [Based:O, on:O, the:O, functionality:O, of:O, the:O, various:O, tools:O, uploaded:O, to:O, the:O, webshells:O, ,:O, we:O, believe:O, the:O, threat:B-HackOrg, actors:I-HackOrg, breach:O, the:O, SharePoint:O, servers:O, to:O, use:O, as:O, a:O, beachhead:O, ,:O, then:O, attempt:O, to:O, move:B-Purp, laterally:O, across:O, the:O, network:O, via:O, stolen:B-Purp, credentials:I-Purp, and:O, exploiting:B-Purp, 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: 'The first of them is the well-known FIN7 , which specializes in attacking various companies to get access to financial data or PoS infrastructure .' [/INST] [The:O, first:O, of:O, them:O, is:O, the:O, well-known:O, FIN7:B-HackOrg, ,:O, which:O, specializes:O, in:O, attacking:O, various:B-Org, companies:I-Org, to:O, get:B-Purp, access:I-Purp, to:O, financial:B-Idus, data:O, or:O, PoS:O, infrastructure:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Alpha’s early role was fairly simple: engage with individuals , who he chose based on the goods they were selling , and then provide personal shipping addresses back to Omega .' [/INST] [Alpha’s:B-HackOrg, early:O, role:O, was:O, fairly:O, simple::O, engage:O, with:O, individuals:O, ,:O, who:O, he:O, chose:O, based:O, on:O, the:O, goods:O, they:O, were:O, selling:O, ,:O, and:O, then:O, provide:B-Purp, personal:I-Purp, shipping:I-Purp, addresses:O, back:O, to:O, Omega:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Instead of using fake Google Docs phishing pages to collect personal email login credentials , Scattered Canary began using phishing pages of commonly used business applications to compromise enterprise credentials .' [/INST] [Instead:O, of:O, using:O, fake:O, Google:O, Docs:O, phishing:B-Way, pages:O, to:O, collect:B-Purp, personal:O, email:O, login:O, credentials:O, ,:O, Scattered:B-HackOrg, Canary:I-HackOrg, began:O, using:O, phishing:B-Way, pages:O, of:O, commonly:O, used:O, business:O, applications:O, to:O, compromise:B-Purp, enterprise:I-Purp, credentials: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 some samples deployed since March 2019 , Turla developers modified their PowerShell scripts in order to bypass the Antimalware Scan Interface (AMSI) .' [/INST] [In:O, some:O, samples:O, deployed:O, since:O, March:B-Time, 2019:I-Time, ,:O, Turla:B-HackOrg, developers:O, modified:O, their:O, PowerShell:O, scripts:O, in:O, order:O, to:O, bypass:B-Purp, the:O, Antimalware:O, Scan:O, Interface:O, (AMSI):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Distinct changes to Azazel by the Winnti developers include the addition of a function named ‘Decrypt2’ , which is used to decode an embedded configuration similar to the core implant .' [/INST] [Distinct:O, changes:O, to:O, Azazel:B-Tool, by:O, the:O, Winnti:B-HackOrg, developers:I-HackOrg, include:O, the:O, addition:O, of:O, a:O, function:O, named:O, ‘Decrypt2’:O, ,:O, which:O, is:O, used:O, to:O, decode:B-Purp, an:O, embedded:B-Purp, configuration:O, similar:O, to:O, the:O, core:O, implant:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Early in Q2 , Kaspersky identified an interesting Lazarus attack targeting a mobile gaming company in South Korea that we believe was aimed at stealing application source code .' [/INST] [Early:O, in:O, Q2:O, ,:O, Kaspersky:B-SecTeam, identified:O, an:O, interesting:O, Lazarus:B-HackOrg, attack:O, targeting:O, a:O, mobile:B-Idus, gaming:I-Idus, company:O, in:O, South:B-Area, Korea:I-Area, that:O, we:O, believe:O, was:O, aimed:O, at:O, stealing:B-Purp, application:B-Purp, source: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: 'APT19 leveraged Rich Text Format (RTF) and macro-enabled Microsoft Excel files to deliver their initial exploits .' [/INST] [APT19:B-HackOrg, leveraged:O, Rich:O, Text:O, Format:O, (RTF):O, and:O, macro-enabled:O, Microsoft:B-SamFile, Excel:I-SamFile, files:I-SamFile, to:O, deliver:B-Purp, their:O, initial:O, exploits:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 of these data-stealing capabilities were present in the oldest variants of CARBANAK that we have seen and some were added over time .' [/INST] [Most:O, of:O, these:O, data-stealing:B-Purp, capabilities:O, were:O, present:O, in:O, the:O, oldest:O, variants:O, of:O, CARBANAK:B-SamFile, that:O, we:O, have:O, seen:O, and:O, some:O, were:O, added:O, over:O, 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: 'We have also observed them using virtual private network services that use IPs based in numerous countries to ensure anonymity and obfuscate criminal operations .' [/INST] [We:O, have:O, also:O, observed:O, them:B-SamFile, using:B-Features, virtual:I-Features, private:I-Features, network:I-Features, services:I-Features, that:O, use:O, IPs:O, based:O, in:O, numerous:O, countries:O, to:O, ensure:B-Purp, anonymity:I-Purp, and:O, obfuscate:B-Purp, criminal:I-Purp, operations: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: 'Once downloaded and executed , it drops an intermediate payload that further downloads a Pony DLL and Vawtrak executable , which perform data theft and connect to a command and control (C2) server .' [/INST] [Once:O, downloaded:O, and:O, executed:O, ,:O, it:O, drops:O, an:O, intermediate:O, payload:O, that:O, further:O, downloads:O, a:O, Pony:B-SamFile, DLL:I-SamFile, and:O, Vawtrak:B-SamFile, executable:O, ,:O, which:O, perform:O, data:B-Features, theft:I-Features, and:O, connect:B-Features, to:O, a:O, command:B-Purp, and:O, control:B-Purp, (C2):I-Purp, server: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 executable is executed , it downloads Pony and Vawtrak malware variants to steal data .' [/INST] [After:O, the:O, executable:O, is:O, executed:O, ,:O, it:O, downloads:O, Pony:B-SamFile, and:O, Vawtrak:B-SamFile, malware:O, variants:O, to:O, steal:B-Purp, data: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: 'Ploutus-D will load KXCashDispenserLib” library implemented by Kalignite Platform (K3A.Platform.dll) to interact with the XFS Manager and control the Dispenser (see Figure 13) .' [/INST] [Ploutus-D:B-SamFile, will:O, load:O, KXCashDispenserLib”:O, library:O, implemented:O, by:O, Kalignite:O, Platform:O, (K3A.Platform.dll):B-SamFile, to:O, interact:B-Purp, with:O, the:O, XFS:O, Manager:O, and:O, control:O, the:O, Dispenser:O, (see:O, Figure:O, 13):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'DarkPulsar is a very interesting administrative module for controlling a passive backdoor named ' sipauth32.tsp ' that provides remote control , belonging to this category .' [/INST] [DarkPulsar:B-Tool, is:O, a:O, very:O, interesting:O, administrative:O, module:O, for:O, controlling:O, a:O, passive:O, backdoor:B-Tool, named:O, ':O, sipauth32.tsp:B-SamFile, ':O, that:O, provides:B-Purp, remote:I-Purp, control:I-Purp, ,:O, belonging:O, to:O, this:O, category:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 a recent campaign , APT32 leveraged social engineering emails with Microsoft ActiveMime file attachments to deliver malicious macros .' [/INST] [During:O, a:O, recent:O, campaign:B-OffAct, ,:O, APT32:B-HackOrg, leveraged:O, social:B-Way, engineering:I-Way, emails:I-Way, with:O, Microsoft:B-SamFile, ActiveMime:I-SamFile, file:I-SamFile, attachments:O, to:O, deliver:B-Purp, malicious:I-Purp, macros: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: 'The group uses legitimate administration tools to fly under the radar in their post-exploitation phase , which makes detection of malicious activity , as well as attribution more complicated .' [/INST] [The:O, group:B-HackOrg, uses:O, legitimate:B-Tool, administration:I-Tool, tools:I-Tool, to:O, fly:B-Purp, under:I-Purp, the:I-Purp, radar:I-Purp, in:O, their:O, post-exploitation:O, phase:O, ,:O, which:O, makes:O, detection:O, of:O, malicious:B-OffAct, activity:I-OffAct, ,:O, as:O, well:O, as:O, attribution:O, more:O, complicated:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PittyTiger has also been seen using Heartbleed vulnerability in order to directly get valid credentials .' [/INST] [PittyTiger:B-HackOrg, has:O, also:O, been:O, seen:O, using:O, Heartbleed:B-Exp, vulnerability:I-Exp, in:O, order:O, to:O, directly:O, get:B-Purp, valid:I-Purp, credentials: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: 'They have also been seen using Heartbleed vulnerability in order to directly get valid credentials .' [/INST] [They:O, have:O, also:O, been:O, seen:O, using:O, Heartbleed:B-Exp, vulnerability:I-Exp, in:O, order:O, to:O, directly:O, get:B-Purp, valid:I-Purp, credentials: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: 'Tactic #1: Delivering the miner directly to a vulnerable serverSome tactics we've observed involve exploiting CVE-2017-10271 , leveraging PowerShell to download the miner directly onto the victim’s system (Figure 1) , and executing it using ShellExecute() .' [/INST] [Tactic:O, #1::O, Delivering:O, the:O, miner:O, directly:O, to:O, a:O, vulnerable:O, serverSome:O, tactics:O, we've:O, observed:O, involve:O, exploiting:O, CVE-2017-10271:B-Exp, ,:O, leveraging:O, PowerShell:B-Tool, to:O, download:B-Purp, the:O, miner:O, directly:O, onto:O, the:O, victim’s:O, system:O, (Figure:O, 1):O, ,:O, and:O, executing:B-Way, it:O, using:B-Way, ShellExecute():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: 'APT28 is using novel techniques involving the EternalBlue exploit and the open source tool Responder to spread laterally through networks and likely target travelers .' [/INST] [APT28:B-HackOrg, is:O, using:O, novel:O, techniques:O, involving:O, the:O, EternalBlue:B-Exp, exploit:I-Exp, and:O, the:O, open:B-Tool, source:I-Tool, tool:I-Tool, Responder:B-Tool, to:O, spread:B-Purp, laterally:I-Purp, through:I-Purp, networks:I-Purp, and:O, likely:O, target:O, travelers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Carbanak is a remote backdoor ( initially based on Carberp ) , designed for espionage , data exfiltration and to provide remote access to infected machines .' [/INST] [Carbanak:B-Exp, is:O, a:O, remote:O, backdoor:O, (:O, initially:O, based:O, on:O, Carberp:B-Tool, ):O, ,:O, designed:O, for:O, espionage:B-HackOrg, ,:O, data:B-Purp, exfiltration:I-Purp, and:O, to:O, provide:B-Purp, remote:I-Purp, access:I-Purp, to:O, infected:O, machines:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 found on the target system , Carbanak will try to exploit a known vulnerability in Windows XP , Windows Server 2003 , Windows Vista , Windows Server 2008 , Windows 7 , Windows 8 , and Windows Server 2012 , CVE-2013-3660 , for local privilege escalation .' [/INST] [If:O, found:O, on:O, the:O, target:O, system:O, ,:O, Carbanak:B-Exp, will:O, try:O, to:O, exploit:O, a:O, known:O, vulnerability:O, in:O, Windows:O, XP:O, ,:O, Windows:O, Server:O, 2003:O, ,:O, Windows:O, Vista:O, ,:O, Windows:O, Server:O, 2008:O, ,:O, Windows:O, 7:O, ,:O, Windows:O, 8:O, ,:O, and:O, Windows:O, Server:O, 2012:O, ,:O, CVE-2013-3660:B-Exp, ,:O, for:O, local:B-Purp, privilege:I-Purp, escalation: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: 'To enable connections to the infected computer using the Remote Desktop Protocol ( RDP ) , Carbanak sets Termservice service execution mode to Auto .' [/INST] [To:O, enable:O, connections:B-Purp, to:I-Purp, the:I-Purp, infected:I-Purp, computer:I-Purp, using:O, the:O, Remote:B-Tool, Desktop:I-Tool, Protocol:I-Tool, (:O, RDP:B-Tool, ):O, ,:O, Carbanak:B-Exp, sets:O, Termservice:O, service:O, execution:O, mode:O, to:O, Auto:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Just a few months later , in February 2015 , we announced the discovery of Carbanak , a cyber-criminal gang that used custom malware and APT techniques to steal millions of dollars while infecting hundreds of financial institutions in at least 30 countries .' [/INST] [Just:O, a:O, few:O, months:O, later:O, ,:O, in:O, February:B-Time, 2015:I-Time, ,:O, we:O, announced:O, the:O, discovery:O, of:O, Carbanak:B-Exp, ,:O, a:O, cyber-criminal:B-HackOrg, gang:I-HackOrg, that:O, used:O, custom:O, malware:O, and:O, APT:B-Way, techniques:I-Way, to:O, steal:B-Purp, millions:I-Purp, of:I-Purp, dollars:I-Purp, while:O, infecting:O, hundreds:O, of:O, financial:B-Org, institutions:I-Org, in:O, at:O, least:O, 30: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: 'Dubbed ‘Operation Sheep’ , this massive data stealing campaign is the first known campaign seen in the wild to exploit the Man-in-the-Disk vulnerability revealed by Check Point Research earlier last year .' [/INST] [Dubbed:O, ‘Operation:B-HackOrg, Sheep’:I-HackOrg, ,:O, this:O, massive:B-Purp, data:I-Purp, stealing:I-Purp, campaign:O, is:O, the:O, first:O, known:O, campaign:O, seen:O, in:O, the:O, wild:O, to:O, exploit:O, the:O, Man-in-the-Disk:B-Exp, vulnerability:O, revealed:O, by:O, Check:O, Point:O, Research:O, earlier:O, last:O, year:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 time , however , TA459 opportunistically used spear-phishing emails with a Microsoft Word attachment exploiting the recently patched CVE-2017-0199 to deploy the ZeroT Trojan , which in turn downloaded the PlugX Remote Access Trojan ( RAT ) .' [/INST] [This:O, time:O, ,:O, however:O, ,:O, TA459:O, opportunistically:O, used:O, spear-phishing:B-Way, emails:I-Way, with:O, a:O, Microsoft:B-SamFile, Word:I-SamFile, attachment:I-SamFile, exploiting:O, the:O, recently:O, patched:O, CVE-2017-0199:B-Exp, to:O, deploy:O, the:O, ZeroT:B-Tool, Trojan:I-Tool, ,:O, which:O, in:O, turn:O, downloaded:O, the:O, PlugX:B-Tool, Remote:I-Tool, Access:I-Tool, Trojan:I-Tool, (:O, RAT:B-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: 'This time , however , attackers opportunistically used spear-phishing emails with a Microsoft Word attachment exploiting the recently patched CVE-2017-0199 to deploy the ZeroT Trojan , which in turn downloaded the PlugX Remote Access Trojan ( RAT ) .' [/INST] [This:O, time:O, ,:O, however:O, ,:O, attackers:O, opportunistically:O, used:O, spear-phishing:B-Way, emails:I-Way, with:O, a:O, Microsoft:B-SamFile, Word:I-SamFile, attachment:I-SamFile, exploiting:O, the:O, recently:O, patched:O, CVE-2017-0199:B-Exp, to:O, deploy:O, the:O, ZeroT:B-Tool, Trojan:I-Tool, ,:O, which:O, in:O, turn:O, downloaded:O, the:O, PlugX:B-Tool, Remote:I-Tool, Access:I-Tool, Trojan:I-Tool, (:O, RAT:B-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: 'Data from the early part of this year shows that the Taidoor attackers rampantly used malicious.DOC files to exploit a Microsoft Common Controls vulnerability , CVE-2012-0158 .' [/INST] [Data:O, from:O, the:O, early:O, part:O, of:O, this:O, year:O, shows:O, that:O, the:O, Taidoor:O, attackers:O, rampantly:O, used:O, malicious.DOC:B-SamFile, files:O, to:O, exploit:O, a:O, Microsoft:B-Exp, Common:I-Exp, Controls:I-Exp, vulnerability:I-Exp, ,:O, CVE-2012-0158: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 attached to spear-phishing e-mails used in both attacks contain code that exploits CVE-2012-0158 , which despite its age remains one of the most common Microsoft Word vulnerabilities being exploited by multiple threat actors .' [/INST] [The:O, documents:B-SamFile, attached:O, to:O, spear-phishing:B-Way, e-mails:I-Way, used:O, in:O, both:O, attacks:B-OffAct, contain:O, code:O, that:O, exploits:O, CVE-2012-0158:B-Exp, ,:O, which:O, despite:O, its:O, age:O, remains:O, one:O, of:O, the:O, most:O, common:O, Microsoft:B-Exp, Word:I-Exp, vulnerabilities:I-Exp, being:O, exploited:O, by:O, multiple:O, threat:O, actors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'If the document was delivered with macros instead of exploits ( CVE-2012-0158 , CVE-2013-3906 or CVE-2014-1761 ) , then the document contained instructions for enabling macros .' [/INST] [If:O, the:O, document:B-SamFile, was:O, delivered:O, with:O, macros:O, instead:O, of:O, exploits:O, (:O, CVE-2012-0158:B-Exp, ,:O, CVE-2013-3906:B-Exp, or:O, CVE-2014-1761:B-Exp, ):O, ,:O, then:O, the:O, document:O, contained:O, instructions:O, for:O, enabling:O, macros:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Lately , Patchwork has been sending multiple RTF files exploiting CVE-2017-8570 .' [/INST] [Lately:O, ,:O, Patchwork:B-HackOrg, has:O, been:O, sending:O, multiple:O, RTF:B-SamFile, files:I-SamFile, exploiting:O, CVE-2017-8570: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: 'Kaspersky Lab 's products detect the Microsoft Office exploits used in the spear-phishing attacks , including Exploit.MSWord.CVE-2010-333 , Exploit.Win32.CVE-2012-0158 .' [/INST] [Kaspersky:B-SecTeam, Lab:I-SecTeam, 's:O, products:O, detect:O, the:O, Microsoft:B-Exp, Office:I-Exp, exploits:I-Exp, used:O, in:O, the:O, spear-phishing:B-OffAct, attacks:I-OffAct, ,:O, including:O, Exploit.MSWord.CVE-2010-333:B-SamFile, ,:O, Exploit.Win32.CVE-2012-0158: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: 'The files exploit the well-known Microsoft Office vulnerability , CVE-2012-0158 , to execute malicious code in order to take control of the targeted systems .' [/INST] [The:O, files:B-SamFile, exploit:O, the:O, well-known:O, Microsoft:B-Exp, Office:I-Exp, vulnerability:I-Exp, ,:O, CVE-2012-0158:B-Exp, ,:O, to:O, execute:O, malicious:O, code:O, in:O, order:O, to:O, take:B-Features, control:I-Features, of:O, the:O, targeted: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: 'CVE-2017-0143 was also used by two other exploit tools—EternalRomance and EternalSynergy—that were released as part of the Shadow Brokers leak in April 2017 .' [/INST] [CVE-2017-0143:B-Exp, was:O, also:O, used:O, by:O, two:O, other:O, exploit:O, tools—EternalRomance:B-SamFile, and:O, EternalSynergy—that:B-SamFile, were:O, released:O, as:O, part:O, of:O, the:O, Shadow:O, Brokers:O, leak:O, in:O, April:B-Time, 2017: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: 'this RTF exploits again the CVE-2017_1882 on eqnedt32.exe .' [/INST] [this:O, RTF:B-SamFile, exploits:O, again:O, the:O, CVE-2017_1882:B-Exp, on:O, eqnedt32.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: 'The analyzed RTF files share the same object dimension (objw2180\objh300) used to track the RTF weaponizer in our previous report , however , the sample was not exploiting CVE-2017-11882 or CVE-2018-0802 .' [/INST] [The:O, analyzed:O, RTF:O, files:O, share:O, the:O, same:O, object:O, dimension:O, (objw2180\objh300):O, used:O, to:O, track:O, the:O, RTF:O, weaponizer:O, in:O, our:O, previous:O, report:O, ,:O, however:O, ,:O, the:O, sample:B-SamFile, was:O, not:O, exploiting:O, CVE-2017-11882:B-Exp, or:O, CVE-2018-0802: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: 'After further analysis , it was discovered that the RTF files were exploiting the CVE-2018-0798 vulnerability in Microsoft’s Equation Editor (EQNEDT32) .' [/INST] [After:O, further:O, analysis:O, ,:O, it:O, was:O, discovered:O, that:O, the:O, RTF:B-SamFile, files:I-SamFile, were:O, exploiting:O, the:O, CVE-2018-0798:B-Exp, vulnerability:O, in:O, Microsoft’s:O, Equation:O, Editor:O, (EQNEDT32):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Anomali Researchers were able to identify multiple samples of malicious RTF documents ITW using the same exploit for CVE-2018-0798 .' [/INST] [Anomali:B-SecTeam, Researchers:O, were:O, able:O, to:O, identify:O, multiple:O, samples:O, of:O, malicious:O, RTF:O, documents:O, ITW:B-SamFile, using:O, the:O, same:O, exploit:O, for:O, CVE-2018-0798: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: 'Upon opening of the MS Word document , our embedded file exploits CVE-2017-11882 to drop a malicious fake Norton Security Shell Extension module , 'NavShExt.dll' , which is then injected into iexplore.exe to install the backdoor , begin collection , and activate command and control .' [/INST] [Upon:O, opening:O, of:O, the:O, MS:O, Word:O, document:O, ,:O, our:O, embedded:O, file:O, exploits:O, CVE-2017-11882:B-Exp, to:O, drop:O, a:O, malicious:O, fake:O, Norton:O, Security:O, Shell:O, Extension:O, module:O, ,:O, 'NavShExt.dll':B-SamFile, ,:O, which:O, is:O, then:O, injected:O, into:O, iexplore.exe:B-SamFile, to:O, install:O, the:O, backdoor:O, ,:O, begin:O, collection:O, ,:O, and:O, activate:O, command:O, and:O, control:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Moving through the infection process , NetWitness Endpoint detects the initial exploit CVE-2017-1182 in action as the Microsoft Equation Editor , 'EQNEDT32.exe' , scores high for potentially malicious activity .' [/INST] [Moving:O, through:O, the:O, infection:O, process:O, ,:O, NetWitness:O, Endpoint:O, detects:O, the:O, initial:O, exploit:O, CVE-2017-1182:B-Exp, in:O, action:O, as:O, the:O, Microsoft:B-SamFile, Equation:I-SamFile, Editor:I-SamFile, ,:O, 'EQNEDT32.exe':B-SamFile, ,:O, scores:O, high:O, for:O, potentially: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: 'In some of the latest samples of BalkanDoor detected in 2019 , the malware is distributed as an ACE archive , disguised as a RAR archive (i.e , not an executable file) , specially crafted to exploit the WinRAR ACE vulnerability CVE-2018-20250 .' [/INST] [In:O, some:O, of:O, the:O, latest:O, samples:O, of:O, BalkanDoor:B-SamFile, detected:O, in:O, 2019:B-Time, ,:O, the:O, malware:O, is:O, distributed:O, as:O, an:O, ACE:O, archive:O, ,:O, disguised:O, as:O, a:O, RAR:O, archive:O, (i.e:O, ,:O, not:O, an:O, executable:O, file):O, ,:O, specially:O, crafted:O, to:O, exploit:O, the:O, WinRAR:O, ACE:O, vulnerability:O, CVE-2018-20250: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 China Chopper actor activity starts with the download and execution of two exploit files which attempt to exploit the Windows vulnerabilities CVE-2015-0062 , CVE-2015-1701 and CVE-2016-0099 to allow the attacker to modify other objects on the server .' [/INST] [The:O, China:B-SamFile, Chopper:I-SamFile, actor:O, activity:O, starts:O, with:O, the:O, download:O, and:O, execution:O, of:O, two:O, exploit:O, files:O, which:O, attempt:O, to:O, exploit:O, the:O, Windows:O, vulnerabilities:O, CVE-2015-0062:B-Exp, ,:O, CVE-2015-1701:B-Exp, and:O, CVE-2016-0099:B-Exp, to:O, allow:O, the:O, attacker:B-HackOrg, to:O, modify:O, other:O, objects:O, on:O, the: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 following archive caught our attention for exploiting a WinRAR unacev2 module vulnerability and for having interesting content .' [/INST] [The:O, following:O, archive:B-SamFile, caught:O, our:O, attention:O, for:O, exploiting:O, a:O, WinRAR:O, unacev2:O, module:O, vulnerability:B-Exp, and:O, for:O, having:O, interesting:O, content:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 all emails sent to these government officials , the actor used the same attachment : a malicious Microsoft Word document that exploited the CVE-2012-0158 vulnerability to drop a malicious payload .' [/INST] [In:O, all:O, emails:B-Way, sent:O, to:O, these:O, government:O, officials:O, ,:O, the:O, actor:O, used:O, the:O, same:O, attachment:O, ::O, a:O, malicious:B-SamFile, Microsoft:I-SamFile, Word:I-SamFile, document:I-SamFile, that:O, exploited:O, the:O, CVE-2012-0158:B-Exp, vulnerability:O, to:O, drop:O, a:O, malicious:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the security firm , this campaign targeted Indian military officials via spear-phishing emails , distributing spyware to its victims via an Adobe Reader vulnerability .' [/INST] [According:O, to:O, the:O, security:B-Org, firm:I-Org, ,:O, this:O, campaign:B-OffAct, targeted:O, Indian:O, military:O, officials:O, via:O, spear-phishing:B-Way, emails:I-Way, ,:O, distributing:O, spyware:O, to:O, its:O, victims:O, via:O, an:O, Adobe:B-Exp, Reader:I-Exp, vulnerability:I-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: 'PLATINUM 's persistent use of spear phishing tactics ( phishing attempts aimed at specific individuals ) and access to previously undiscovered zero-day exploits have made it a highly resilient threat .' [/INST] [PLATINUM:B-HackOrg, 's:O, persistent:O, use:O, of:O, spear:B-Way, phishing:I-Way, tactics:I-Way, (:O, phishing:B-Way, attempts:O, aimed:O, at:O, specific:O, individuals:O, ):O, and:O, access:O, to:O, previously:O, undiscovered:O, zero-day:B-Exp, exploits:I-Exp, have:O, made:O, it:O, a:O, highly:O, resilient:O, threat:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 group 's persistent use of spear phishing tactics ( phishing attempts aimed at specific individuals ) and access to previously undiscovered zero-day exploits have made it a highly resilient threat .' [/INST] [The:O, group:B-HackOrg, 's:O, persistent:O, use:O, of:O, spear:B-Way, phishing:I-Way, tactics:I-Way, (:O, phishing:B-Way, attempts:O, aimed:O, at:O, specific:O, individuals:O, ):O, and:O, access:O, to:O, previously:O, undiscovered:O, zero-day:B-Exp, exploits:I-Exp, have:O, made:O, it:O, a:O, highly:O, resilient:O, threat:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the Carbanak campaign is a clear indicator of a new era in cybercrime in which criminals use APT techniques directly against the financial industry instead of through its customers .' [/INST] [We:O, believe:O, that:O, the:O, Carbanak:B-Exp, campaign:B-OffAct, is:O, a:O, clear:O, indicator:O, of:O, a:O, new:O, era:O, in:O, cybercrime:O, in:O, which:O, criminals:B-HackOrg, use:O, APT:B-Way, techniques:I-Way, directly:O, against:O, the:O, financial:B-Idus, industry:I-Idus, instead:O, of:O, through:O, its:O, customers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Carbanak has its origin in more common financial fraud including theft from consumer and corporate bank accounts in Europe and Russia , using standard banking malware , mainly Carberp .' [/INST] [Carbanak:B-Exp, has:O, its:O, origin:O, in:O, more:O, common:O, financial:O, fraud:O, including:O, theft:O, from:O, consumer:O, and:O, corporate:O, bank:O, accounts:O, in:O, Europe:B-Area, and:O, Russia:B-Area, ,:O, using:O, standard:O, banking:O, malware:O, ,:O, mainly:O, Carberp: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: 'However , in September last year , our friends at CSIS published a blog detailing a new Carbanak variant affecting one of its customers .' [/INST] [However:O, ,:O, in:O, September:B-Time, last:O, year:O, ,:O, our:O, friends:O, at:O, CSIS:B-SecTeam, published:O, a:O, blog:O, detailing:O, a:O, new:O, Carbanak:B-Exp, variant:O, affecting:O, one:O, of:O, its:O, customers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'PIVY also played a key role in the 2011 campaign known as Nitro that targeted chemical makers , government agencies , defense contractors , and human rights groups.10,11 Still active a year later , the Nitro attackers used a zero-day vulnerability in Java to deploy PIVY in 2012 .' [/INST] [PIVY:B-Tool, also:O, played:O, a:O, key:O, role:O, in:O, the:O, 2011:B-OffAct, campaign:I-OffAct, known:O, as:O, Nitro:O, that:O, targeted:O, chemical:O, makers:O, ,:O, government:B-Org, agencies:I-Org, ,:O, defense:B-Org, contractors:I-Org, ,:O, and:O, human:O, rights:O, groups.10,11:O, Still:O, active:O, a:O, year:O, later:O, ,:O, the:O, Nitro:O, attackers:B-HackOrg, used:O, a:O, zero-day:B-Exp, vulnerability:I-Exp, in:O, Java:O, to:O, deploy:O, PIVY:B-Tool, 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: 'We believe that the Carbanak campaign is a clear indicator of a new era in cybercrime in which criminals use APT techniques directly against the financial industry instead of through its customers .' [/INST] [We:O, believe:O, that:O, the:O, Carbanak:B-Exp, campaign:B-OffAct, is:O, a:O, clear:O, indicator:O, of:O, a:O, new:O, era:O, in:O, cybercrime:O, in:O, which:O, criminals:B-HackOrg, use:O, APT:B-Way, techniques:I-Way, directly:O, against:O, the:O, financial:B-Idus, industry:I-Idus, instead:O, of:O, through:O, its:O, customers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Carbanak has its origin in more common financial fraud including theft from consumer and corporate bank accounts in Europe and Russia , using standard banking malware , mainly Carberp .' [/INST] [Carbanak:B-Exp, has:O, its:O, origin:O, in:O, more:O, common:O, financial:O, fraud:O, including:O, theft:O, from:O, consumer:O, and:O, corporate:O, bank:O, accounts:O, in:O, Europe:B-Area, and:O, Russia:B-Area, ,:O, using:O, standard:O, banking:O, malware:O, ,:O, mainly:O, Carberp: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: 'However , in September last year , our friends at CSIS published a blog detailing a new Carbanak variant affecting one of its customers .' [/INST] [However:O, ,:O, in:O, September:B-Time, last:O, year:O, ,:O, our:O, friends:O, at:O, CSIS:B-SecTeam, published:O, a:O, blog:O, detailing:O, a:O, new:O, Carbanak:B-Exp, variant:O, affecting:O, one:O, of:O, its:O, customers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware was first seen packed with VMProtect; when unpacked the sample didn’t show any similarities with previously known malware .' [/INST] [The:O, malware:B-SamFile, was:O, first:O, seen:O, packed:O, with:O, VMProtect;:B-Features, when:O, unpacked:O, the:O, sample:O, didn’t:O, show:O, any:O, similarities:O, with:O, previously:O, known: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: 'The malware starts communicating with the C&C server by sending basic information about the infected machine .' [/INST] [The:O, malware:B-SamFile, starts:O, communicating:B-Features, with:I-Features, the:I-Features, C&C:I-Features, server:O, by:O, sending:O, basic:O, information:O, about:O, the:O, infected:O, machine:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 basically provides a remote CMD/PowerShell terminal for the attackers , enabling them to execute scripts/commands and receive the results via HTTP requests .' [/INST] [The:O, malware:B-SamFile, basically:O, provides:B-Features, a:O, remote:O, CMD/PowerShell:B-Tool, terminal:O, for:O, the:O, attackers:B-HackOrg, ,:O, enabling:O, them:O, to:O, execute:B-Purp, scripts/commands:I-Purp, and:O, receive:O, the:O, results:O, via:O, HTTP:O, requests:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 app installation , whenever SWAnalytics senses victims opening up infected applications or rebooting their phones , it silently uploads their entire contacts list to Hangzhou Shun Wang Technologies controlled servers .' [/INST] [After:O, app:O, installation:O, ,:O, whenever:O, SWAnalytics:B-SamFile, senses:O, victims:O, opening:O, up:O, infected:O, applications:O, or:O, rebooting:O, their:O, phones:O, ,:O, it:O, silently:O, uploads:B-Features, their:O, entire:O, contacts:O, list:O, to:O, Hangzhou:O, Shun:O, Wang:O, Technologies:O, controlled:O, servers:O, .:O] </s> |