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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This is a first for an APT group , and shows Sednit has access to very sophisticated tools to conduct its espionage operations .' [/INST] [This:O, is:O, a:O, first:O, for:O, an:O, APT:O, group:O, ,:O, and:O, shows:O, Sednit:B-HackOrg, has:O, access:O, to:O, very:O, sophisticated:B-Tool, tools:I-Tool, to:O, conduct:O, its:O, espionage:O, operations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Three years ago , the Sednit group unleashed new components targeting victims in various countries in the Middle East and Central Asia .' [/INST] [Three:B-Time, years:I-Time, ago:I-Time, ,:O, the:O, Sednit:B-HackOrg, group:O, unleashed:O, new:O, components:O, targeting:O, victims:O, in:O, various:O, countries:O, in:O, the:O, Middle:B-Area, East:I-Area, and:O, Central: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: 'In the past , Sednit used a similar technique for credential phishing .' [/INST] [In:O, the:O, past:O, ,:O, Sednit:B-HackOrg, used:O, a:O, similar:O, technique:O, for:O, credential:B-Way, phishing: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: 'At the end of August 2018 , the Sednit group launched a spearphishing email campaign where it distributed shortened URLs that delivered the first stage of Zebrocy components .' [/INST] [At:O, the:O, end:O, of:O, August:O, 2018:O, ,:O, the:O, Sednit:O, group:O, launched:O, a:O, spearphishing:O, email:O, campaign:O, where:O, it:O, distributed:O, shortened:O, URLs:O, that:O, delivered:O, the:O, first:O, stage:O, of:O, Zebrocy:O, components:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'As we explained in our most recent blogpost about Zebrocy , the configuration of the backdoor is stored in in the resource section and is split into four different hex-encoded , encrypted blobs .' [/INST] [As:O, we:B-SecTeam, explained:O, in:O, our:O, most:O, recent:O, blogpost:O, about:O, Zebrocy:B-HackOrg, ,:O, the:O, configuration:O, of:O, the:O, backdoor:B-Tool, is:O, stored:O, in:O, in:O, the:O, resource:O, section:O, and:O, is:O, split:O, into:O, four:O, different:O, hex-encoded:O, ,:O, encrypted:O, blobs:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 past iteration of SLUB spread from a unique watering hole website exploiting CVE-2018-8174 , a VBScript engine vulnerability .' [/INST] [The:O, past:O, iteration:O, of:O, SLUB:B-HackOrg, spread:O, from:O, a:O, unique:O, watering:B-Way, hole:I-Way, website:O, exploiting:O, CVE-2018-8174:B-Exp, ,:O, a:O, VBScript:O, engine:O, vulnerability:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 used GitHub and Slack as tools for communication between the malware and its controller .' [/INST] [It:B-HackOrg, used:O, GitHub:B-Tool, and:O, Slack:B-Tool, as:O, tools:O, for:O, communication:O, between:O, the:O, malware:O, and:O, its:O, controller:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 July 9 , we discovered a new version of SLUB delivered via another unique watering hole website .' [/INST] [On:O, July:B-Time, 9:I-Time, ,:O, we:B-SecTeam, discovered:O, a:O, new:O, version:O, of:O, SLUB:B-HackOrg, delivered:O, via:O, another:O, unique:O, watering:B-Way, hole:I-Way, website:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 malicious site used CVE-2019-0752 , an Internet Explorer vulnerability discovered by Trend Micro’s Zero Day Initiative (ZDI) that was just patched this April .' [/INST] [This:O, malicious:O, site:O, used:O, CVE-2019-0752:B-Exp, ,:O, an:O, Internet:O, Explorer:O, vulnerability:O, discovered:O, by:O, Trend:B-SecTeam, Micro’s:I-SecTeam, Zero:O, Day:O, Initiative:O, (ZDI):O, that:O, was:O, just:O, patched:O, this:O, April: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: 'Since we published out last report on SLUB , the backdoor has been updated and several improvements were implemented .' [/INST] [Since:O, we:B-SecTeam, published:O, out:O, last:O, report:O, on:O, SLUB:B-HackOrg, ,:O, the:O, backdoor:B-Tool, has:O, been:O, updated:O, and:O, several:O, improvements:O, were:O, implemented:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 SLUB malware was delivered through watering hole websites that were injected with exploits for CVE-2018-8174 or CVE-2019-0752 .' [/INST] [The:O, SLUB:B-HackOrg, malware:O, was:O, delivered:O, through:O, watering:O, hole:O, websites:O, that:O, were:O, injected:O, with:O, exploits:O, for:O, CVE-2018-8174:B-Exp, or:O, CVE-2019-0752: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: 'During this attack , we found that the SLUB malware used two Slack teams sales-yww9809” and marketing-pwx7789 .' [/INST] [During:O, this:O, attack:O, ,:O, we:O, found:O, that:O, the:O, SLUB:B-HackOrg, malware:O, used:B-Way, two:I-Way, Slack:I-Way, teams:O, sales-yww9809”:O, and:O, marketing-pwx7789:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'SWEED remains consistent across most of their campaigns in their use of spear-phishing emails with malicious attachments .' [/INST] [SWEED:B-HackOrg, remains:O, consistent:O, across:O, most:O, of:O, their:O, campaigns:O, in:O, their:O, use:O, of:O, spear-phishing:B-Way, emails:O, with:O, malicious: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: 'In April 2018 , SWEED began making use of a previously disclosed Office exploit .' [/INST] [In:O, April:B-Time, 2018:I-Time, ,:O, SWEED:B-HackOrg, began:O, making:O, use:O, of:O, a:O, previously:O, disclosed:O, Office:O, exploit:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 May 2018 , campaigns being conducted by SWEED began leveraging another vulnerability in Microsoft Office: CVE-2017-11882 , a remote code execution bug in Microsoft Office that is commonly observed being leveraged in malicious documents used in commodity malware distribution .' [/INST] [In:O, May:B-Time, 2018:I-Time, ,:O, campaigns:O, being:O, conducted:O, by:O, SWEED:B-HackOrg, began:O, leveraging:O, another:O, vulnerability:O, in:O, Microsoft:O, Office::O, CVE-2017-11882:B-Exp, ,:O, a:O, remote:O, code:O, execution:O, bug:O, in:O, Microsoft:O, Office:O, that:O, is:O, commonly:O, observed:O, being:O, leveraged:O, in:O, malicious:O, documents:O, used:O, in:O, commodity:O, malware:O, distribution:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 found them targeting countries in the Middle East such as United Arab Emirates and Saudi Arabia , as well as other countries such as India , Japan , Argentina , the Philippines , and South Korea .' [/INST] [We:O, found:O, them:B-HackOrg, targeting:O, countries:O, in:O, the:O, Middle:B-Area, East:I-Area, such:O, as:O, United:B-Area, Arab:I-Area, Emirates:I-Area, and:O, Saudi:B-Area, Arabia:I-Area, ,:O, as:O, well:O, as:O, other:O, countries:O, such:O, as:O, India:B-Area, ,:O, Japan:B-Area, ,:O, Argentina:B-Area, ,:O, the:B-Area, Philippines:I-Area, ,:O, and:O, South:B-Area, Korea: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: 'Similar to previous campaigns , the JAR was directly attached to emails and used file names such as Order_2018.jar .' [/INST] [Similar:O, to:O, previous:O, campaigns:O, ,:O, the:O, JAR:B-SamFile, was:O, directly:O, attached:O, to:O, emails:O, and:O, used:O, file:O, names:O, such:O, as:O, Order_2018.jar: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: 'Code contained inside one of the slides triggers an exploit for CVE-2017-8759 , a remote code execution vulnerability in Microsoft .NET framework .' [/INST] [Code:O, contained:O, inside:O, one:O, of:O, the:O, slides:B-SamFile, triggers:O, an:O, exploit:O, for:O, CVE-2017-8759:B-Exp, ,:O, a:O, remote:O, code:O, execution:O, vulnerability:O, in:O, Microsoft:B-Tool, .NET:I-Tool, framework: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: 'TA505 is also using FlowerPippi (Backdoor.Win32.FLOWERPIPPI.A) , a new backdoor that we found them using in their campaigns against targets in Japan , India , and Argentina .' [/INST] [TA505:B-HackOrg, is:O, also:O, using:O, FlowerPippi:B-Tool, (Backdoor.Win32.FLOWERPIPPI.A):O, ,:O, a:O, new:O, backdoor:B-Tool, that:O, we:O, found:O, them:O, using:O, in:O, their:O, campaigns:O, against:O, targets:O, in:O, Japan:B-Area, ,:O, India:B-Area, ,:O, and:O, Argentina: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: 'TA505 targeted Middle Eastern countries in a June 11 campaign that delivered more than 90% of the total spam emails to the UAE , Saudi Arabia , and Morroco .' [/INST] [TA505:B-HackOrg, targeted:O, Middle:B-Area, Eastern:I-Area, countries:O, in:O, a:O, June:B-Time, 11:I-Time, campaign:O, that:O, delivered:O, more:O, than:O, 90%:O, of:O, the:O, total:O, spam:O, emails:O, to:O, the:O, UAE:B-Area, ,:O, Saudi:B-Area, Arabia:I-Area, ,:O, and:O, Morroco: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: 'It fetches the same FlawedAmmyy downloader .msi file , then downloads the FlawedAmmyy payload .' [/INST] [It:B-HackOrg, fetches:O, the:O, same:O, FlawedAmmyy:B-Way, downloader:I-Way, .msi:O, file:O, ,:O, then:O, downloads:O, the:O, FlawedAmmyy:B-Tool, payload: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: 'TA505 used Wizard (.wiz) files in this campaign , with FlawedAmmyy RAT as the final payload .' [/INST] [TA505:B-HackOrg, used:O, Wizard:B-Tool, (.wiz):I-Tool, files:I-Tool, in:O, this:O, campaign:O, ,:O, with:O, FlawedAmmyy:B-Tool, RAT:I-Tool, as:O, the:O, final: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: 'On June 14 , we saw TA505’s campaign still targeting UAE with similar tactics and techniques , but this time , some of the spam emails were delivered via the Amadey botnet .' [/INST] [On:O, June:B-Time, 14:I-Time, ,:O, we:O, saw:O, TA505’s:B-HackOrg, campaign:O, still:O, targeting:O, UAE:B-Area, with:O, similar:O, tactics:O, and:O, techniques:O, ,:O, but:O, this:O, time:O, ,:O, some:O, of:O, the:O, spam:O, emails:O, were:O, delivered:O, via:O, the:O, Amadey:B-Tool, botnet: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: 'It later delivered an information stealer named EmailStealer , ” which stolesimple mail transfer protocol (SMTP) credentials and email addresses in the victim’s machine .' [/INST] [It:B-HackOrg, later:O, delivered:O, an:O, information:O, stealer:O, named:O, EmailStealer:B-Tool, ,:O, ”:O, which:O, stolesimple:O, mail:O, transfer:O, protocol:O, (SMTP):O, credentials:O, and:O, email:O, addresses:O, in:O, the:O, victim’s: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: 'On June 18 , the majority of the campaign’s spam emails were sent with the subject , Your RAKBANK Tax Invoice / Tax Credit Note” or Confirmation .' [/INST] [On:O, June:B-Time, 18:I-Time, ,:O, the:O, majority:O, of:O, the:O, campaign’s:B-OffAct, spam:O, emails:O, were:O, sent:O, with:O, the:O, subject:O, ,:O, Your:O, RAKBANK:O, Tax:O, Invoice:O, /:O, Tax:O, Credit:O, Note”:O, or:O, Confirmation:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 campaign used the abovementioned .html file , malicious Excel/Word document VBA macro , the FlawedAmmyy payload , and Amadey .' [/INST] [This:O, campaign:B-OffAct, used:O, the:O, abovementioned:O, .html:O, file:O, ,:O, malicious:O, Excel/Word:O, document:O, VBA:O, macro:B-Tool, ,:O, the:O, FlawedAmmyy:B-Tool, payload:I-Tool, ,:O, and:O, Amadey: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 June 24 , we found another campaign targeting Lebanon with the ServHelper malware .' [/INST] [On:O, June:B-Time, 24:I-Time, ,:O, we:O, found:O, another:O, campaign:O, targeting:O, Lebanon:B-Area, with:O, the:O, ServHelper:B-SamFile, 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: 'On June 17 , we observed the campaign’s spam emails delivering malware-embedded Excel files directly as an attachment .' [/INST] [On:O, June:B-Time, 17:I-Time, ,:O, we:O, observed:O, the:O, campaign’s:B-OffAct, spam:O, emails:O, delivering:O, malware-embedded:O, Excel:O, files:O, directly:O, as:O, an:O, attachment:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 June 20 , we spotted the campaign’s spam emails delivering .doc and .xls files .' [/INST] [On:O, June:B-Time, 20:I-Time, ,:O, we:B-SecTeam, spotted:O, the:O, campaign’s:O, spam:O, emails:O, delivering:O, .doc:O, and:O, .xls:O, files:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Nonetheless , these spam emails were not delivered to the UAE or Arabic-speaking users , but to banks in Asian countries such as India , Indonesia , and the Philippines .' [/INST] [Nonetheless:O, ,:O, these:O, spam:B-SamFile, emails:I-SamFile, were:O, not:O, delivered:O, to:O, the:O, UAE:B-Area, or:O, Arabic-speaking:B-Area, users:O, ,:O, but:O, to:O, banks:B-Idus, in:O, Asian:B-Area, countries:O, such:O, as:O, India:B-Area, ,:O, Indonesia:B-Area, ,:O, and:O, the:B-Area, Philippines: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: 'After our analysis , we found that Proofpoint reported this malware as AndroMut as well .' [/INST] [After:O, our:O, analysis:O, ,:O, we:B-SecTeam, found:O, that:O, Proofpoint:B-SecTeam, reported:O, this:O, malware:O, as:O, AndroMut:B-HackOrg, as:O, well:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the campaign that targeted Japan , Philippines , and Argentina on June 20 , we found what seems to be a new , undisclosed malware , which we named Gelup .' [/INST] [In:O, the:O, campaign:O, that:O, targeted:O, Japan:B-Area, ,:O, Philippines:B-Area, ,:O, and:O, Argentina:B-Area, on:O, June:B-Time, 20:I-Time, ,:O, we:O, found:O, what:O, seems:O, to:O, be:O, a:O, new:O, ,:O, undisclosed:O, malware:O, ,:O, which:O, we:O, named:O, Gelup: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: 'Another new malware we found that TA505 is using in their campaigns last June 20 against targets in Japan , the Philippines , and Argentina is FlowerPippi .' [/INST] [Another:O, new:O, malware:O, we:O, found:O, that:O, TA505:B-HackOrg, is:O, using:O, in:O, their:O, campaigns:O, last:O, June:B-Time, 20:I-Time, against:O, targets:O, in:O, Japan:B-Area, ,:O, the:O, Philippines:B-Area, ,:O, and:O, Argentina:B-Area, is:O, FlowerPippi: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 malicious email contains a highly suspicious sample which triggered the ZLAB team to investigate its capabilities and its possible attribution , discovering a potential expansion of the TA505 operation .' [/INST] [The:O, malicious:O, email:O, contains:O, a:O, highly:O, suspicious:O, sample:O, which:O, triggered:O, the:O, ZLAB:B-SecTeam, team:O, to:O, investigate:O, its:O, capabilities:O, and:O, its:O, possible:O, attribution:O, ,:O, discovering:O, a:O, potential:O, expansion:O, of:O, the:O, TA505:B-HackOrg, operation:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The attack , as stated by CyberInt , leveraged a command and control server located in Germany related to the TA505 actor: a very active group involved in cyber-criminal operation all around the world , threatening a wide range of high profile companies , active since 2014 .' [/INST] [The:O, attack:O, ,:O, as:O, stated:O, by:O, CyberInt:O, ,:O, leveraged:O, a:O, command:O, and:O, control:O, server:O, located:O, in:O, Germany:B-Area, related:O, to:O, the:O, TA505:B-HackOrg, actor::O, a:O, very:O, active:O, group:O, involved:O, in:O, cyber-criminal:O, operation:O, all:O, around:O, the:O, world:O, ,:O, threatening:O, a:O, wide:O, range:O, of:O, high:B-Org, profile:I-Org, companies:I-Org, ,:O, active: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: 'The comparison of the infection chains reveals in both cases TA505 used a couple of SFX stages to deploy the RMS” software: a legitimate remote administration tool produced by the Russian company TektonIT .' [/INST] [The:O, comparison:O, of:O, the:O, infection:O, chains:O, reveals:O, in:O, both:O, cases:O, TA505:B-HackOrg, used:O, a:O, couple:O, of:O, SFX:O, stages:O, to:O, deploy:B-Way, the:I-Way, RMS”:I-Way, software::O, a:O, legitimate:O, remote:O, administration:O, tool:O, produced:O, by:O, the:O, Russian:B-Area, company:O, TektonIT:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 TA505 group is one of the most active threat groups operating since 2014 , it has traditionally targeted Banking and Retail industries , as we recently documented during the analysis of the Stealthy Email Stealer” part of their arsenal .' [/INST] [The:O, TA505:B-HackOrg, group:O, is:O, one:O, of:O, the:O, most:O, active:O, threat:O, groups:O, operating:O, since:O, 2014:B-Time, ,:O, it:O, has:O, traditionally:O, targeted:O, Banking:B-Idus, and:O, Retail:B-Idus, industries:O, ,:O, as:O, we:O, recently:O, documented:O, during:O, the:O, analysis:O, of:O, the:O, Stealthy:O, Email:O, Stealer”:O, part:O, of:O, their:O, arsenal:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Also , some code pieces are directly re-used in the analyzed campaigns , such as the i.cmd” and exit.exe” files , and , at the same time , some new components have been introduced , for instance the rtegre.exe” and the veter1605_MAPS_10cr0.exe” file .' [/INST] [Also:O, ,:O, some:O, code:O, pieces:O, are:O, directly:O, re-used:O, in:O, the:O, analyzed:O, campaigns:O, ,:O, such:O, as:O, the:O, i.cmd”:B-SamFile, and:O, exit.exe”:B-SamFile, files:O, ,:O, and:O, ,:O, at:O, the:O, same:O, time:O, ,:O, some:O, new:O, components:O, have:O, been:O, introduced:O, ,:O, for:O, instance:O, the:O, rtegre.exe”:B-SamFile, and:O, the:O, veter1605_MAPS_10cr0.exe”:B-SamFile, file:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2018 , Kaspersky Labs published a report that analyzed a Turla PowerShell loader that was based on the open-source project Posh-SecMod .' [/INST] [In:O, 2018:B-Time, ,:O, Kaspersky:B-SecTeam, Labs:O, published:O, a:O, report:O, that:O, analyzed:O, a:O, Turla:B-HackOrg, PowerShell:B-Tool, loader:I-Tool, that:O, was:O, based:O, on:O, the:O, open-source:O, project:O, Posh-SecMod:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Turla is believed to have been operating since at least 2008 , when it successfully breached the US military .' [/INST] [Turla:B-HackOrg, is:O, believed:O, to:O, have:O, been:O, operating:O, since:O, at:O, least:O, 2008:B-Time, ,:O, when:O, it:O, successfully:O, breached:O, the:O, US:O, military: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: 'This is not the first time Turla has used PowerShell in-memory loaders to increase its chances of bypassing security products .' [/INST] [This:O, is:O, not:O, the:O, first:O, time:O, Turla:B-HackOrg, has:O, used:O, PowerShell:B-Tool, in-memory:O, loaders:O, to:O, increase:O, its:O, chances:O, of:O, bypassing:O, security:O, products:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 , it is likely the same scripts are used more globally against many traditional Turla targets in Western Europe and the Middle East .' [/INST] [However:O, ,:O, it:O, is:O, likely:O, the:O, same:O, scripts:O, are:O, used:O, more:O, globally:O, against:O, many:O, traditional:O, Turla:B-HackOrg, targets:O, in:O, Western:B-Area, Europe:I-Area, and:O, the:O, Middle:B-Area, East: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: '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: 'Based on our research , SWEED — which has been operating since at least 2017 — primarily targets their victims with stealers and remote access trojans .' [/INST] [Based:O, on:O, our:O, research:O, ,:O, SWEED:B-HackOrg, —:O, which:O, has:O, been:O, operating:O, since:O, at:O, least:O, 2017:B-Time, —:O, primarily:O, targets:O, their:O, victims:O, with:O, stealers:O, and:O, remote:O, access:O, trojans:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 interesting to note that Turla operators used the free email provider GMX again , as in the Outlook Backdoor and in LightNeuron .' [/INST] [It:O, is:O, interesting:O, to:O, note:O, that:O, Turla:B-HackOrg, operators:O, used:O, the:O, free:O, email:O, provider:O, GMX:O, again:O, ,:O, as:O, in:O, the:O, Outlook:B-Tool, Backdoor:I-Tool, and:O, in:O, LightNeuron: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: 'This new research confirms our forecast and shows that the Turla group does not hesitate to use open-source pen-testing frameworks to conduct intrusion .' [/INST] [This:O, new:O, research:O, confirms:O, our:O, forecast:O, and:O, shows:O, that:O, the:O, Turla:B-HackOrg, group:O, does:O, not:O, hesitate:O, to:O, use:O, open-source:O, pen-testing:O, frameworks:B-Tool, to:O, conduct:O, intrusion:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Neptun is installed on Microsoft Exchange servers and is designed to passively listen for commands from the attackers .' [/INST] [Neptun:B-SamFile, is:O, installed:O, on:O, Microsoft:O, Exchange:O, servers:O, and:O, is:O, designed:O, to:O, passively:O, listen:B-Features, for:I-Features, commands:I-Features, from:O, the:O, attackers:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 attack during this campaign involved the use of infrastructure belonging to another espionage group known as Crambus aka OilRig , APT34 .' [/INST] [One:O, attack:O, during:O, this:O, campaign:O, involved:O, the:O, use:O, of:O, infrastructure:O, belonging:O, to:O, another:O, espionage:O, group:O, known:O, as:O, Crambus:B-HackOrg, aka:O, OilRig:B-HackOrg, ,:O, APT34:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Waterbug has been using Meterpreter since at least early 2018 and , in this campaign , used a modified version of Meterpreter , which was encoded and given a .wav extension in order to disguise its true purpose .' [/INST] [Waterbug:B-HackOrg, has:O, been:O, using:O, Meterpreter:B-Tool, since:O, at:O, least:O, early:B-Time, 2018:I-Time, and:O, ,:O, in:O, this:O, campaign:O, ,:O, used:O, a:O, modified:O, version:O, of:O, Meterpreter:B-Tool, ,:O, which:O, was:O, encoded:O, and:O, given:O, a:O, .wav:O, extension:O, in:O, order:O, to:O, disguise:O, its:O, true:O, purpose:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 likelihood , Waterbug’s use of Crambus infrastructure appears to have been a hostile takeover .' [/INST] [In:O, all:O, likelihood:O, ,:O, Waterbug’s:B-HackOrg, use:O, of:O, Crambus:B-Tool, infrastructure:I-Tool, appears:O, to:O, have:O, been:O, a:O, hostile:O, takeover:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One of the most interesting things to occur during one of Waterbug’s recent campaigns was that during an attack against one target in the Middle East , Waterbug appeared to hijack infrastructure from the Crambus espionage group and used it to deliver malware on to the victim’s network .' [/INST] [One:O, of:O, the:O, most:O, interesting:O, things:O, to:O, occur:O, during:O, one:O, of:O, Waterbug’s:B-HackOrg, recent:O, campaigns:O, was:O, that:O, during:O, an:O, attack:O, against:O, one:O, target:O, in:O, the:O, Middle:B-Area, East:I-Area, ,:O, Waterbug:B-HackOrg, appeared:O, to:O, hijack:O, infrastructure:O, from:O, the:O, Crambus:O, espionage:O, group:B-HackOrg, and:O, used:O, it:O, to:O, deliver:O, malware:O, on:O, to:O, the:O, victim’s: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: 'These three recent Waterbug campaigns have seen the group compromise governments and international organizations across the globe in addition to targets in the IT and education sectors .' [/INST] [These:O, three:O, recent:O, Waterbug:B-HackOrg, campaigns:O, have:O, seen:O, the:O, group:B-HackOrg, compromise:B-Org, governments:I-Org, and:O, international:B-Org, organizations:I-Org, across:O, the:O, globe:O, in:O, addition:O, to:O, targets:O, in:O, the:O, IT:B-Idus, and:O, education:B-Idus, sectors: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: 'Curiously though , Waterbug also compromised other computers on the victim’s network using its own infrastructure .' [/INST] [Curiously:O, though:O, ,:O, Waterbug:B-HackOrg, also:O, compromised:O, other:O, computers:O, on:O, the:O, victim’s:O, network:O, using:O, its:O, own:O, infrastructure: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: 'Symantec believes that the variant of Mimikatz used in this attack is unique to Waterbug .' [/INST] [Symantec:B-SecTeam, believes:O, that:O, the:O, variant:O, of:O, Mimikatz:B-Tool, used:O, in:O, this:O, attack:O, is:O, unique:O, to:O, Waterbug:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Aside from the attack involving Crambus infrastructure , this sample of Mimikatz has only been seen used in one other attack , against an education target in the UK in 2017 .' [/INST] [Aside:O, from:O, the:O, attack:O, involving:O, Crambus:O, infrastructure:O, ,:O, this:O, sample:O, of:O, Mimikatz:B-Tool, has:O, only:O, been:O, seen:O, used:O, in:O, one:O, other:O, attack:O, ,:O, against:O, an:O, education:B-Idus, target:O, in:O, the:O, UK:B-Area, 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: 'The first observed evidence of Waterbug activity came on January 11 , 2018 , when a Waterbug-linked tool (a task scheduler named msfgi.exe) was dropped on to a computer on the victim’s network .' [/INST] [The:O, first:O, observed:O, evidence:O, of:O, Waterbug:B-HackOrg, activity:O, came:O, on:O, January:B-Time, 11:I-Time, ,:O, 2018:B-Time, ,:O, when:O, a:O, Waterbug-linked:O, tool:O, (a:O, task:O, scheduler:O, named:O, msfgi.exe):O, was:O, dropped:O, on:O, to:O, a:O, computer:O, on:O, the:O, victim’s: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 the case of the attack against the Middle Eastern target , Crambus was the first group to compromise the victim’s network , with the earliest evidence of activity dating to November 2017 .' [/INST] [In:O, the:O, case:O, of:O, the:O, attack:O, against:O, the:O, Middle:B-Area, Eastern:I-Area, target:O, ,:O, Crambus:B-HackOrg, was:O, the:O, first:O, group:O, to:O, compromise:O, the:O, victim’s:O, network:O, ,:O, with:O, the:O, earliest:O, evidence:O, of:O, activity:O, dating:O, to:O, November: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: 'Waterbug’s intrusions on the victim’s network continued for much of 2018 .' [/INST] [Waterbug’s:B-HackOrg, intrusions:O, on:O, the:O, victim’s:O, network:O, continued:O, for:O, much:O, of:O, 2018: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: 'Symantec did not observe the initial access point and the close timeframe between Waterbug observed activity on the victim’s network and its observed use of Crambus infrastructure suggests that Waterbug may have used the Crambus infrastructure as an initial access also reconfigures the Microsoft Sysinternals registry to prevent pop-ups when running the PsExec tool .' [/INST] [Symantec:B-SecTeam, did:O, not:O, observe:O, the:O, initial:O, access:O, point:O, and:O, the:O, close:O, timeframe:O, between:O, Waterbug:B-HackOrg, observed:O, activity:O, on:O, the:O, victim’s:O, network:O, and:O, its:O, observed:O, use:O, of:O, Crambus:O, infrastructure:O, suggests:O, that:O, Waterbug:B-HackOrg, may:O, have:O, used:O, the:O, Crambus:B-Org, infrastructure:I-Org, as:O, an:O, initial:O, access:O, also:O, reconfigures:O, the:O, Microsoft:O, Sysinternals:O, registry:O, to:O, prevent:O, pop-ups:O, when:O, running:O, the:O, PsExec:B-Tool, tool: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: 'Waterbug also used an older version of PowerShell , likely to avoid logging .' [/INST] [Waterbug:B-HackOrg, also:O, used:O, an:O, older:O, version:O, of:O, PowerShell:B-Tool, ,:O, likely:O, to:O, avoid:O, logging:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 one of these campaigns , Waterbug used a USB stealer that scans removable storage devices to identify and collect files of interest .' [/INST] [In:O, one:O, of:O, these:O, campaigns:O, ,:O, Waterbug:B-HackOrg, used:O, a:O, USB:B-Tool, stealer:I-Tool, that:O, scans:O, removable:O, storage:O, devices:O, to:O, identify:O, and:O, collect:O, files:O, of:O, interest:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 then uses WebDAV to upload the RAR archive to a Box account .' [/INST] [The:O, malware:B-SamFile, then:O, uses:O, WebDAV:B-Tool, to:O, upload:O, the:O, RAR:B-SamFile, archive:I-SamFile, to:O, a:O, Box:O, account:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 DeepSight Managed Adversary and Threat Intelligence (MATI) team co-authored this blog and its customers have received intelligence with additional details about these campaigns , the characteristics of the Waterbug (aka Turla) cyber espionage group , and methods of detecting and thwarting activities of this adversary .' [/INST] [The:O, DeepSight:B-SecTeam, Managed:I-SecTeam, Adversary:I-SecTeam, and:O, Threat:B-SecTeam, Intelligence:I-SecTeam, (MATI):O, team:I-SecTeam, co-authored:O, this:O, blog:O, and:O, its:O, customers:O, have:O, received:O, intelligence:O, with:O, additional:O, details:O, about:O, these:O, campaigns:O, ,:O, the:O, characteristics:O, of:O, the:O, Waterbug:B-HackOrg, (aka:O, Turla):O, cyber:O, espionage:O, group:B-SecTeam, ,:O, and:O, methods:O, of:O, detecting:O, and:O, thwarting:O, activities:O, of:O, this:O, adversary:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 DeepSight MATI team authored this blog and its customers have received intelligence with additional details about these campaigns , the characteristics of the Waterbug (aka Turla) cyber espionage group , and methods of detecting and thwarting activities of this adversary .' [/INST] [The:O, DeepSight:B-SecTeam, MATI:I-SecTeam, team:I-SecTeam, authored:O, this:O, blog:O, and:O, its:O, customers:O, have:O, received:O, intelligence:O, with:O, additional:O, details:O, about:O, these:O, campaigns:B-OffAct, ,:O, the:O, characteristics:O, of:O, the:O, Waterbug:B-HackOrg, (aka:O, Turla):O, cyber:O, espionage:O, group:B-HackOrg, ,:O, and:O, methods:O, of:O, detecting:B-Way, and:O, thwarting:B-Way, activities:I-Way, of:O, this:O, adversary:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While reviewing a 2015 report⁵ of a Winnti intrusion at a Vietnamese gaming company , we identified a small cluster of Winnti⁶ samples designed specifically for Linux⁷ .' [/INST] [While:O, reviewing:O, a:O, 2015:B-Time, report⁵:O, of:O, a:O, Winnti:B-HackOrg, intrusion:O, at:O, a:O, Vietnamese:B-Org, gaming:I-Org, company:I-Org, ,:O, we:O, identified:O, a:O, small:O, cluster:O, of:O, Winnti⁶:B-HackOrg, samples:O, designed:O, specifically:O, for:O, Linux⁷:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Following these reports , Chronicle researchers doubled down on efforts to try to unravel the various campaigns where Winnti was leveraged .' [/INST] [Following:O, these:O, reports:O, ,:O, Chronicle:B-SecTeam, researchers:O, doubled:O, down:O, on:O, efforts:O, to:O, try:O, to:O, unravel:O, the:O, various:O, campaigns:O, where:O, Winnti:B-HackOrg, was:O, leveraged:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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: 'Zebrocy activity initiates with spearphishing operations delivering various target profilers and downloaders without the use of any 0day exploits .' [/INST] [Zebrocy:B-HackOrg, activity:O, initiates:O, with:O, spearphishing:B-Way, operations:O, delivering:O, various:O, target:O, profilers:O, and:O, downloaders:O, without:O, the:O, use:O, of:O, any:O, 0day:B-Exp, exploits: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: 'We will see more from Zebrocy into 2019 on government and military related organizations .' [/INST] [We:O, will:O, see:O, more:O, from:O, Zebrocy:B-HackOrg, into:O, 2019:B-Time, on:O, government:B-Org, and:O, military:B-Idus, related:O, organizations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 PowerShell script will look at the architecture of the system to check which malicious DLL files should be downloaded .' [/INST] [The:O, PowerShell:B-Tool, script:I-Tool, will:O, look:O, at:O, the:O, architecture:O, of:O, the:O, system:O, to:O, check:O, which:O, malicious:B-SamFile, DLL:I-SamFile, files:I-SamFile, should:O, be:O, downloaded:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the same year , Silence conducted DDoS attacks using the Perl IRC bot and public IRC chats to control Trojans .' [/INST] [In:O, the:O, same:O, year:O, ,:O, Silence:B-HackOrg, conducted:O, DDoS:B-OffAct, attacks:I-OffAct, using:O, the:O, Perl:B-Tool, IRC:I-Tool, bot:I-Tool, and:O, public:B-Tool, IRC:I-Tool, chats:O, to:O, control:O, Trojans:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 FBI issued a rare bulletin admitting that a group named APT6 hacked into US government computer systems as far back as 2011 and for years stole sensitive data .' [/INST] [The:O, FBI:B-SecTeam, issued:O, a:O, rare:O, bulletin:O, admitting:O, that:O, a:O, group:B-HackOrg, named:O, APT6:B-HackOrg, hacked:O, into:O, US:B-Org, government:I-Org, computer:O, systems:O, as:O, far:O, back:O, as:O, 2011:B-Time, and:O, for:O, years:O, stole:O, sensitive:O, data:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye iSIGHT Intelligence believes that APT37 is aligned with the activity publicly reported as Scarcruft and Group123 .' [/INST] [FireEye:B-SecTeam, iSIGHT:I-SecTeam, Intelligence:O, believes:O, that:O, APT37:B-HackOrg, is:O, aligned:O, with:O, the:O, activity:O, publicly:O, reported:O, as:O, Scarcruft:B-HackOrg, and:O, Group123:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Trend Micro attributes this activity to MuddyWater , an Iran-nexus actor that has been active since at least May 2017 .' [/INST] [Trend:B-SecTeam, Micro:I-SecTeam, attributes:O, this:O, activity:O, to:O, MuddyWater:B-HackOrg, ,:O, an:O, Iran-nexus:O, actor:B-HackOrg, that:O, has:O, been:O, active:O, since:O, at:O, least:O, May: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: 'FireEye assess that the actors employing this latest Flash zero-day are a suspected North Korean group we track as TEMP.Reaper .' [/INST] [FireEye:B-SecTeam, assess:O, that:O, the:O, actors:B-HackOrg, employing:O, this:O, latest:O, Flash:O, zero-day:B-Way, are:O, a:O, suspected:O, North:B-Area, Korean:I-Area, group:O, we:O, track:O, as:O, TEMP.Reaper:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye has observed other suspected North Korean threat groups such as TEMP.Hermit employ wiper malware in disruptive attacks .' [/INST] [FireEye:B-SecTeam, has:O, observed:O, other:O, suspected:O, North:B-Area, Korean:I-Area, threat:O, groups:O, such:O, as:O, TEMP.Hermit:B-HackOrg, employ:O, wiper:O, malware:O, in:O, disruptive:O, attacks:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'On Nov14 , 2017 , FireEye observed APT34 using an exploit for the Microsoft Office vulnerability to target a government organization in the Middle East .' [/INST] [On:O, Nov14:B-Time, ,:O, 2017:B-Time, ,:O, FireEye:B-SecTeam, observed:O, APT34:B-HackOrg, using:O, an:O, exploit:O, for:O, the:O, Microsoft:O, Office:O, vulnerability:B-Exp, to:O, target:O, a:O, government:B-Org, organization:I-Org, in:O, the:O, Middle:B-Area, East: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: 'Kaspersky reveals that APT33 is a capable group that has carried out cyber espionage operations since at least 2013 .' [/INST] [Kaspersky:B-SecTeam, reveals:O, that:O, APT33:B-HackOrg, is:O, a:O, capable:O, group:B-HackOrg, that:O, has:O, carried:O, out:O, cyber:O, espionage:O, operations:O, since:O, at:O, least:O, 2013: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: 'APT33 is the only group that Kaspersky has observed use the DROPSHOT dropper .' [/INST] [APT33:B-HackOrg, is:O, the:O, only:O, group:O, that:O, Kaspersky:B-SecTeam, has:O, observed:O, use:O, the:O, DROPSHOT:B-Tool, dropper: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 cyber espionage group APT32 heavily obfuscates their backdoors and scripts , and Mandiant consultants observed APT32 implement additional command argument obfuscation in April 2017 .' [/INST] [The:O, cyber:O, espionage:O, group:O, APT32:B-HackOrg, heavily:O, obfuscates:O, their:O, backdoors:B-Tool, and:O, scripts:B-Tool, ,:O, and:O, Mandiant:O, consultants:O, observed:O, APT32:B-HackOrg, implement:O, additional:O, command:O, argument:O, obfuscation:O, in:O, April:B-Time, 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: 'In all Mandiant investigations to date where the CARBANAK backdoor has been discovered , the activity has been attributed to the FIN7 threat group .' [/INST] [In:O, all:O, Mandiant:B-SecTeam, investigations:O, to:O, date:O, where:O, the:O, CARBANAK:O, backdoor:O, has:O, been:O, discovered:O, ,:O, the:O, activity:O, has:O, been:O, attributed:O, to:O, the:O, FIN7:B-HackOrg, threat:O, group:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 released a similar report about the same group under the name Carbanak in February 2015 .' [/INST] [Kaspersky:B-SecTeam, released:O, a:O, similar:O, report:O, about:O, the:O, same:O, group:B-HackOrg, under:O, the:O, name:O, Carbanak:B-HackOrg, in:O, February:B-Time, 2015: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: 'FireEye assesses that APT32 leverages a unique suite of fully-featured malware .' [/INST] [FireEye:B-SecTeam, assesses:O, that:O, APT32:O, leverages:O, a:O, unique:O, suite:O, of:O, fully-featured: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: 'FireEye has observed APT32 targeting foreign corporations with a vested interest in Vietnam’s manufacturing , consumer products , and hospitality sectors .' [/INST] [FireEye:B-SecTeam, has:O, observed:O, APT32:B-HackOrg, targeting:O, foreign:O, corporations:O, with:O, a:O, vested:O, interest:O, in:O, Vietnam’s:B-Org, manufacturing:I-Org, ,:O, consumer:B-Idus, products:I-Idus, ,:O, and:O, hospitality:B-Idus, sectors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 FireEye iSIGHT Intelligence MySIGHT Portal contains additional information on these backdoor families based on Mandiant investigations of APT32 intrusions .' [/INST] [The:O, FireEye:B-SecTeam, iSIGHT:B-SecTeam, Intelligence:O, MySIGHT:O, Portal:O, contains:O, additional:O, information:O, on:O, these:O, backdoor:O, families:O, based:O, on:O, Mandiant:B-SecTeam, investigations:O, of:O, APT32:B-HackOrg, intrusions:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye assesses that APT32 is a cyber espionage group aligned with Vietnamese government interests .' [/INST] [FireEye:B-SecTeam, assesses:O, that:O, APT32:B-HackOrg, is:O, a:O, cyber:O, espionage:O, group:O, aligned:O, with:O, Vietnamese:B-Org, government:B-Org, interests:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 May and June 2017 , FireEye has associated this campaign with APT19 , a group that we assess is composed of freelancers , with some degree of sponsorship by the Chinese government .' [/INST] [In:O, May:B-Time, and:O, June:B-Time, 2017:I-Time, ,:O, FireEye:B-SecTeam, has:O, associated:O, this:O, campaign:O, with:O, APT19:B-HackOrg, ,:O, a:O, group:B-HackOrg, that:O, we:O, assess:O, is:O, composed:O, of:O, freelancers:O, ,:O, with:O, some:O, degree:O, of:O, sponsorship:O, by:O, the:O, Chinese:B-Org, government: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: 'APT10 is a Chinese cyber espionage group that FireEye has tracked since 2009 .' [/INST] [APT10:B-HackOrg, is:O, a:O, Chinese:O, cyber:O, espionage:O, group:O, that:O, FireEye:B-HackOrg, has:O, tracked:O, since:O, 2009: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: 'In addition to the spear phishes , FireEye ISIGHT Intelligence has observed APT10 accessing victims through global service providers .' [/INST] [In:O, addition:O, to:O, the:O, spear:B-Way, phishes:I-Way, ,:O, FireEye:B-SecTeam, ISIGHT:I-SecTeam, Intelligence:I-SecTeam, has:O, observed:O, APT10:B-HackOrg, accessing:O, victims:O, through:O, global:O, service:O, providers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye’s visibility into the operations of APT28 – a group we believe the Russian government sponsors – has given us insight into some of the government’s targets , as well as its objectives and the activities designed to further them .' [/INST] [FireEye’s:B-SecTeam, visibility:O, into:O, the:O, operations:O, of:O, APT28:B-HackOrg, –:O, a:O, group:O, we:O, believe:O, the:O, Russian:B-Org, government:I-Org, sponsors:O, –:O, has:O, given:O, us:O, insight:O, into:O, some:O, of:O, the:O, government’s:O, targets:O, ,:O, as:O, well:O, as:O, its:O, objectives:O, and:O, the:O, activities:O, designed:O, to:O, further:O, them:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye has tracked and profiled APT28 group through multiple investigations , endpoint and network detections , and continuous monitoring .' [/INST] [FireEye:B-SecTeam, has:O, tracked:O, and:O, profiled:O, APT28:B-HackOrg, group:O, through:O, multiple:O, investigations:O, ,:O, endpoint:O, and:O, network:O, detections:O, ,:O, and:O, continuous:O, monitoring:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 April 2015 , FireEye uncovered the malicious efforts of APT30 , a suspected China-based threat group .' [/INST] [In:O, April:B-Time, 2015:I-Time, ,:O, FireEye:B-SecTeam, uncovered:O, the:O, malicious:O, efforts:O, of:O, APT30:B-HackOrg, ,:O, a:O, suspected:O, China-based:B-Area, threat:O, group:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FireEye iSIGHT Intelligence has been tracking a pair of cybercriminals that we refer to as the Vendetta Brothers .' [/INST] [FireEye:B-SecTeam, iSIGHT:I-SecTeam, Intelligence:O, has:O, been:O, tracking:B-OffAct, a:O, pair:O, of:O, cybercriminals:O, that:O, we:O, refer:O, to:O, as:O, the:O, Vendetta:B-HackOrg, Brothers:I-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Google and Microsoft have already confirmed the Russian hacker group APT28 used a Flash vulnerability CVE-2016-7855 along with this kernel privilege escalation flaw to perform a targeted attack .' [/INST] [Google:B-SecTeam, and:O, Microsoft:B-SecTeam, have:O, already:O, confirmed:O, the:O, Russian:O, hacker:O, group:O, APT28:B-HackOrg, used:O, a:O, Flash:O, vulnerability:O, CVE-2016-7855:B-Exp, along:O, with:O, this:O, kernel:O, privilege:O, escalation:O, flaw:O, to:O, perform:O, a:O, targeted:O, attack:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'McAfee concludes that some groups—and especially the Poetry Group —have shifted tactics to use Citadel in ways other than what it was originally intended for .' [/INST] [McAfee:B-SecTeam, concludes:O, that:O, some:O, groups—and:O, especially:O, the:O, Poetry:O, Group:B-HackOrg, —have:O, shifted:O, tactics:O, to:O, use:O, Citadel:O, in:O, ways:O, other:O, than:O, what:O, it:O, was:O, originally:O, intended:O, for:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'McAfee Advanced Threat research determines with confidence that Lazarus is the threat group behind this attack for the following reasons:Contacts an IP address / domain that was used to host a malicious document from a Lazarus previous campaign in 2017 .' [/INST] [McAfee:B-SecTeam, Advanced:O, Threat:O, research:O, determines:O, with:O, confidence:O, that:O, Lazarus:B-HackOrg, is:O, the:O, threat:O, group:O, behind:O, this:O, attack:O, for:O, the:O, following:O, reasons:Contacts:O, an:O, IP:O, address:O, /:O, domain:O, that:O, was:O, used:O, to:O, host:O, a:O, malicious:B-SamFile, document:I-SamFile, from:O, a:O, Lazarus:B-HackOrg, previous:O, campaign: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: 'In November 2017 , Talos observed the Group123 , which included a new version of ROKRAT being used in the latest wave of attacks .' [/INST] [In:O, November:B-Time, 2017:I-Time, ,:O, Talos:B-SecTeam, observed:O, the:O, Group123:B-HackOrg, ,:O, which:O, included:O, a:O, new:O, version:O, of:O, ROKRAT:O, being:O, used:O, in:O, the:O, latest:O, wave:O, of: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 addition to TALOS investigation on KONNI , on July 18 2017 , BitDefender released a whitepaper on DarkHotel .' [/INST] [In:O, addition:O, to:O, TALOS:B-SecTeam, investigation:O, on:O, KONNI:O, ,:O, on:O, July:B-Time, 18:I-Time, 2017:I-Time, ,:O, BitDefender:O, released:O, a:O, whitepaper:O, on:O, DarkHotel:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 security 360 Threat Intelligence Center , Goldmouse was observed deploying the nebulous njRAT backdoor .' [/INST] [According:O, to:O, security: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-SamFile, backdoor: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: 'ESET has also reported PowerShell scripts being used by Turla to provide direct , in-memory loading and execution of malware .' [/INST] [ESET:B-SecTeam, has:O, also:O, reported:O, PowerShell:B-Tool, scripts:I-Tool, being:O, used:O, by:O, Turla:B-HackOrg, to:O, provide:O, direct:O, ,:O, in-memory:O, loading:O, and:O, execution:O, of:O, malware:O, .:O] </s> |
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