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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: 'Additionally , the apparent timezone of the timestamps in all of the GeminiDuke samples compiled during the winter is UTC+3 , while for samples compiled during the summer , it is UTC+4 .' [/INST] [Additionally:O, ,:O, the:O, apparent:O, timezone:O, of:O, the:O, timestamps:O, in:O, all:O, of:O, the:O, GeminiDuke:S-MAL, samples:O, compiled:O, during:O, the:O, winter:O, is:O, UTC+3:O, ,:O, while:O, for:O, samples:O, compiled:O, during:O, the:O, summer:O, ,:O, it:O, is:O, UTC+4:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The observed timezones correspond to the pre-2011 definition of Moscow Standard Time ( MSK ) , which was UTC+3 during the winter and UTC+4 during the summer .' [/INST] [The:O, observed:O, timezones:O, correspond:O, to:O, the:O, pre-2011:O, definition:O, of:O, Moscow:S-LOC, Standard:O, Time:O, (:O, MSK:O, ):O, ,:O, which:O, was:O, UTC+3:O, during:O, the:O, winter:O, and:O, UTC+4:O, during:O, the:O, summer:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2011 MSK stopped following Daylight Saving Time ( DST ) and was set to UTC+4 year-round , then reset to UTC +3 yearround in 2014 .' [/INST] [In:O, 2011:S-TIME, MSK:O, stopped:O, following:O, Daylight:O, Saving:O, Time:O, (:O, DST:O, ):O, and:O, was:O, set:O, to:O, UTC+4:O, year-round:O, ,:O, then:O, reset:O, to:O, UTC:O, +3:O, yearround:O, in:O, 2014:S-TIME, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Some of the observed GeminiDuke samples that used timestamps as mutex names were compiled while MSK still respected DST and for these samples , the timestamps perfectly align with MSK as it was defined at the time .' [/INST] [Some:O, of:O, the:O, observed:O, GeminiDuke:S-MAL, samples:O, that:O, used:O, timestamps:O, as:O, mutex:O, names:O, were:O, compiled:O, while:O, MSK:O, still:O, respected:O, DST:O, and:O, for:O, these:O, samples:O, ,:O, the:O, timestamps:O, perfectly:O, align:O, with:O, MSK:O, as:O, it:O, was:O, defined:O, at:O, the:O, time:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , GeminiDuke samples compiled after MSK was altered still vary the timezone between UTC+3 in the winter and UTC+4 during the summer .' [/INST] [However:O, ,:O, GeminiDuke:S-MAL, samples:O, compiled:O, after:O, MSK:O, was:O, altered:O, still:O, vary:O, the:O, timezone:O, between:O, UTC+3:O, in:O, the:O, winter:O, and:O, UTC+4:O, during:O, the:O, summer:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While computers using Microsoft Windows automatically adjust for DST , changes in timezone definitions require that an update to Windows be installed .' [/INST] [While:O, computers:O, using:O, Microsoft:S-IDTY, Windows:S-OS, automatically:O, adjust:O, for:O, DST:O, ,:O, changes:O, in:O, timezone:O, definitions:O, require:O, that:O, an:O, update:O, to:O, Windows:S-OS, be:O, installed:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We therefore believe that the Dukes group simply failed to update the computer they were using to compile GeminiDuke samples , so that the timestamps seen in later samples still appear to follow the old definition of Moscow Standard Time .' [/INST] [We:O, therefore:O, believe:O, that:O, the:O, Dukes:S-APT, group:O, simply:O, failed:O, to:O, update:O, the:O, computer:O, they:O, were:O, using:O, to:O, compile:O, GeminiDuke:S-MAL, samples:O, ,:O, so:O, that:O, the:O, timestamps:O, seen:O, in:O, later:O, samples:O, still:O, appear:O, to:O, follow:O, the:O, old:O, definition:O, of:O, Moscow:S-LOC, Standard:O, Time:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The GeminiDuke infostealer has occasionally been wrapped with a loader that appears to be unique to GeminiDuke and has never been observed being used with any of the other Duke toolsets .' [/INST] [The:O, GeminiDuke:S-MAL, infostealer:O, has:O, occasionally:O, been:O, wrapped:O, with:O, a:O, loader:O, that:O, appears:O, to:O, be:O, unique:O, to:O, GeminiDuke:S-MAL, and:O, has:O, never:O, been:O, observed:O, being:O, used:O, with:O, any:O, of:O, the:O, other:O, Duke:S-APT, toolsets:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'GeminiDuke also occasionally embeds additional executables that attempt to achieve persistence on the victim computer .' [/INST] [GeminiDuke:S-MAL, also:O, occasionally:O, embeds:O, additional:O, executables:O, that:O, attempt:O, to:O, achieve:O, persistence:O, on:O, the:O, victim:O, computer:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'These persistence components appear to be uniquely customized for use with GeminiDuke , but they use many of the same techniques as CosmicDuke persistence components .' [/INST] [These:O, persistence:O, components:O, appear:O, to:O, be:O, uniquely:O, customized:O, for:O, use:O, with:O, GeminiDuke:S-MAL, ,:O, but:O, they:O, use:O, many:O, of:O, the:O, same:O, techniques:O, as:O, CosmicDuke:S-MAL, persistence:O, components:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'COSMICDUKE : First known activity January 2010 , Most recent known activity Summer 2015 , Other names Tinybaron , BotgenStudios , NemesisGemina , C&C communication methods HTTP(S) , FTP , WebDav , Known toolset components Information stealer , Multiple loaders , Privilege escalation component , Multiple persistence components .' [/INST] [COSMICDUKE:S-MAL, ::O, First:O, known:O, activity:O, January:B-TIME, 2010:E-TIME, ,:O, Most:O, recent:O, known:O, activity:O, Summer:B-TIME, 2015:E-TIME, ,:O, Other:O, names:O, Tinybaron:S-MAL, ,:O, BotgenStudios:S-MAL, ,:O, NemesisGemina:S-MAL, ,:O, C&C:S-TOOL, communication:O, methods:O, HTTP(S):S-PROT, ,:O, FTP:S-PROT, ,:O, WebDav:S-PROT, ,:O, Known:O, toolset:O, components:O, Information:B-TOOL, stealer:E-TOOL, ,:O, Multiple:O, loaders:S-TOOL, ,:O, Privilege:O, escalation:O, component:O, ,:O, Multiple:O, persistence:O, components:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The CosmicDuke toolset is designed around a main information stealer component .' [/INST] [The:O, CosmicDuke:S-MAL, toolset:O, is:O, designed:O, around:O, a:O, main:O, information:B-TOOL, stealer:E-TOOL, component:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This information stealer is augmented by a variety of components that the toolset operators may selectively include with the main component to provide additional functionalities , such as multiple methods of establishing persistence , as well as modules that attempt to exploit privilege escalation vulnerabilities in order to execute CosmicDuke with higher privileges .' [/INST] [This:O, information:B-TOOL, stealer:E-TOOL, is:O, augmented:O, by:O, a:O, variety:O, of:O, components:O, that:O, the:O, toolset:O, operators:O, may:O, selectively:O, include:O, with:O, the:O, main:O, component:O, to:O, provide:O, additional:O, functionalities:O, ,:O, such:O, as:O, multiple:O, methods:O, of:O, establishing:O, persistence:O, ,:O, as:O, well:O, as:O, modules:O, that:O, attempt:O, to:O, exploit:O, privilege:O, escalation:O, vulnerabilities:O, in:O, order:O, to:O, execute:O, CosmicDuke:S-MAL, with:O, higher:O, privileges:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CosmicDuke ’s information stealing functionality includes : Keylogging , Taking screenshots , Stealing clipboard contents , Stealing user files with file extensions that match a predefined list , Exporting the users cryptographic certificates including private keys , Collecting user credentials , including passwords , for a variety of popular chat and email programs as well as from web browsers CosmicDuke may use HTTP , HTTPS , FTP or WebDav to exfiltrate the collected data to a hardcoded C&C server .' [/INST] [CosmicDuke:S-MAL, ’s:O, information:O, stealing:O, functionality:O, includes:O, ::O, Keylogging:O, ,:O, Taking:O, screenshots:O, ,:O, Stealing:O, clipboard:O, contents:O, ,:O, Stealing:O, user:O, files:O, with:O, file:O, extensions:O, that:O, match:O, a:O, predefined:O, list:O, ,:O, Exporting:O, the:O, users:O, cryptographic:O, certificates:O, including:O, private:O, keys:O, ,:O, Collecting:O, user:O, credentials:O, ,:O, including:O, passwords:O, ,:O, for:O, a:O, variety:O, of:O, popular:O, chat:O, and:O, email:S-TOOL, programs:O, as:O, well:O, as:O, from:O, web:O, browsers:O, CosmicDuke:S-MAL, may:O, use:O, HTTP:S-PROT, ,:O, HTTPS:S-PROT, ,:O, FTP:S-PROT, or:O, WebDav:S-PROT, to:O, exfiltrate:O, the:O, collected:O, data:O, to:O, a:O, hardcoded:O, C&C:S-TOOL, server:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While we believe CosmicDuke to be an entirely custom- written toolset with no direct sharing of code with other Duke toolsets , the high-level ways in which many of its features have been implemented appear to be shared with other members of the Duke arsenal .' [/INST] [While:O, we:O, believe:O, CosmicDuke:S-MAL, to:O, be:O, an:O, entirely:O, custom-:O, written:O, toolset:O, with:O, no:O, direct:O, sharing:O, of:O, code:O, with:O, other:O, Duke:S-APT, toolsets:O, ,:O, the:O, high-level:O, ways:O, in:O, which:O, many:O, of:O, its:O, features:O, have:O, been:O, implemented:O, appear:O, to:O, be:O, shared:O, with:O, other:O, members:O, of:O, the:O, Duke:S-APT, arsenal:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Specifically , the techniques CosmicDuke uses to extract user credentials from targeted software and to detect the presence of analysis tools appear to be based on the techniques used by PinchDuke .' [/INST] [Specifically:O, ,:O, the:O, techniques:O, CosmicDuke:S-MAL, uses:O, to:O, extract:O, user:O, credentials:O, from:O, targeted:O, software:O, and:O, to:O, detect:O, the:O, presence:O, of:O, analysis:O, tools:O, appear:O, to:O, be:O, based:O, on:O, the:O, techniques:O, used:O, by:O, PinchDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Likewise , many of CosmicDuke ’s persistence components use techniques also used by components associated with GeminiDuke and CozyDuke .' [/INST] [Likewise:O, ,:O, many:O, of:O, CosmicDuke:S-MAL, ’s:O, persistence:O, components:O, use:O, techniques:O, also:O, used:O, by:O, components:O, associated:O, with:O, GeminiDuke:S-MAL, and:O, CozyDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In all of these cases , the techniques are the same , but the code itself has been altered to work with the toolset in question , leading to small differences in the final implementation .' [/INST] [In:O, all:O, of:O, these:O, cases:O, ,:O, the:O, techniques:O, are:O, the:O, same:O, ,:O, but:O, the:O, code:O, itself:O, has:O, been:O, altered:O, to:O, work:O, with:O, the:O, toolset:O, in:O, question:O, ,:O, leading:O, to:O, small:O, differences:O, in:O, the:O, final:O, implementation:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the case of CVE-2010-0232 , the exploit appears to be based directly on the proof of concept code published by security researcher Tavis Ormandy when he disclosed the vulnerability .' [/INST] [In:O, the:O, case:O, of:O, CVE-2010-0232:S-VULID, ,:O, the:O, exploit:O, appears:O, to:O, be:O, based:O, directly:O, on:O, the:O, proof:O, of:O, concept:O, code:O, published:O, by:O, security:O, researcher:O, Tavis:O, Ormandy:O, when:O, he:O, disclosed:O, the:O, vulnerability:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to often embedding persistence or privilege escalation components , CosmicDuke has occasionally embedded PinchDuke , GeminiDuke , or MiniDuke components .' [/INST] [In:O, addition:O, to:O, often:O, embedding:O, persistence:O, or:O, privilege:O, escalation:O, components:O, ,:O, CosmicDuke:S-MAL, has:O, occasionally:O, embedded:O, PinchDuke:S-MAL, ,:O, GeminiDuke:S-MAL, ,:O, or:O, MiniDuke:S-MAL, components:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'It should be noted that CosmicDuke does not interoperate with the second , embedded malware in any way other than by writing the malware to disk and executing it .' [/INST] [It:O, should:O, be:O, noted:O, that:O, CosmicDuke:S-MAL, does:O, not:O, interoperate:O, with:O, the:O, second:O, ,:O, embedded:O, malware:O, in:O, any:O, way:O, other:O, than:O, by:O, writing:O, the:O, malware:O, to:O, disk:O, and:O, executing:O, it:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After that , CosmicDuke and the second malware operate entirely independently of each other , including separately contacting their C&C servers .' [/INST] [After:O, that:O, ,:O, CosmicDuke:S-MAL, and:O, the:O, second:O, malware:O, operate:O, entirely:O, independently:O, of:O, each:O, other:O, ,:O, including:O, separately:O, contacting:O, their:O, C&C:S-TOOL, servers:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Sometimes , both malware have used the same C&C server , but in other cases , even the servers have been different .' [/INST] [Sometimes:O, ,:O, both:O, malware:O, have:O, used:O, the:O, same:O, C&C:S-TOOL, server:O, ,:O, but:O, in:O, other:O, cases:O, ,:O, even:O, the:O, servers:O, have:O, been:O, different:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Finally , it is worth noting that while most of the compilation timestamps for CosmicDuke samples appear to be authentic , we are aware of a few cases of them being forged .' [/INST] [Finally:O, ,:O, it:O, is:O, worth:O, noting:O, that:O, while:O, most:O, of:O, the:O, compilation:O, timestamps:O, for:O, CosmicDuke:S-MAL, samples:O, appear:O, to:O, be:O, authentic:O, ,:O, we:O, are:O, aware:O, of:O, a:O, few:O, cases:O, of:O, them:O, being:O, forged:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One such case was detailed on page 10 as an apparent evasion attempt .' [/INST] [One:O, such:O, case:O, was:O, detailed:O, on:O, page:O, 10:O, as:O, an:O, apparent:O, evasion:O, attempt:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Another is a loader variant seen during the spring of 2010 in conjunction with both CosmicDuke and PinchDuke .' [/INST] [Another:O, is:O, a:O, loader:S-TOOL, variant:O, seen:O, during:O, the:O, spring:B-TIME, of:I-TIME, 2010:E-TIME, in:O, conjunction:O, with:O, both:O, CosmicDuke:S-MAL, and:O, PinchDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'These loader samples all had compilation timestamps purporting to be from the 24th or the 25th of September , 2001 .' [/INST] [These:O, loader:S-TOOL, samples:O, all:O, had:O, compilation:O, timestamps:O, purporting:O, to:O, be:O, from:O, the:O, 24th:B-TIME, or:I-TIME, the:I-TIME, 25th:I-TIME, of:I-TIME, September:I-TIME, ,:I-TIME, 2001:E-TIME, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'MINIDUKE : First known activity Loader July 2010 , Backdoor May 2011 Most recent known activity Loader : Spring 2015 , Backdoor : Summer 2014 C&C communication methods HTTP(S) , Twitter , Known toolset components Downloader , Backdoor , Loader .' [/INST] [MINIDUKE:S-MAL, ::O, First:O, known:O, activity:O, Loader:O, July:B-TIME, 2010:E-TIME, ,:O, Backdoor:O, May:B-TIME, 2011:E-TIME, Most:O, recent:O, known:O, activity:O, Loader:O, ::O, Spring:B-TIME, 2015:E-TIME, ,:O, Backdoor:O, ::O, Summer:B-TIME, 2014:E-TIME, C&C:S-TOOL, communication:O, methods:O, HTTP(S):S-PROT, ,:O, Twitter:S-TOOL, ,:O, Known:O, toolset:O, components:O, Downloader:S-TOOL, ,:O, Backdoor:S-TOOL, ,:O, Loader:S-TOOL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The MiniDuke toolset consists of multiple downloader and backdoor components , which are commonly referred to as the MiniDuke “ stage 1 ” , “ stage 2 ” , and “ stage 3 ” components as per Kaspersky ’s original MiniDuke whitepaper .' [/INST] [The:O, MiniDuke:S-MAL, toolset:O, consists:O, of:O, multiple:O, downloader:O, and:O, backdoor:O, components:O, ,:O, which:O, are:O, commonly:O, referred:O, to:O, as:O, the:O, MiniDuke:S-MAL, “:O, stage:O, 1:O, ”:O, ,:O, “:O, stage:O, 2:O, ”:O, ,:O, and:O, “:O, stage:O, 3:O, ”:O, components:O, as:O, per:O, Kaspersky:O, ’s:O, original:O, MiniDuke:S-MAL, whitepaper:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Additionally , a specific loader is often associated with the MiniDuke toolset and is referred to as the “ MiniDuke loader ” .' [/INST] [Additionally:O, ,:O, a:O, specific:O, loader:S-TOOL, is:O, often:O, associated:O, with:O, the:O, MiniDuke:S-MAL, toolset:O, and:O, is:O, referred:O, to:O, as:O, the:O, “:O, MiniDuke:S-MAL, loader:S-TOOL, ”:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While the loader has often been used together with other MiniDuke components , it has also commonly been used in conjunction with CosmicDuke and PinchDuke .' [/INST] [While:O, the:O, loader:S-TOOL, has:O, often:O, been:O, used:O, together:O, with:O, other:O, MiniDuke:S-MAL, components:O, ,:O, it:O, has:O, also:O, commonly:O, been:O, used:O, in:O, conjunction:O, with:O, CosmicDuke:S-MAL, and:O, PinchDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In fact , the oldest samples of the loader that we have found were used with PinchDuke .' [/INST] [In:O, fact:O, ,:O, the:O, oldest:O, samples:O, of:O, the:O, loader:S-TOOL, that:O, we:O, have:O, found:O, were:O, used:O, with:O, PinchDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To avoid confusion however , we have decided to continue referring to the loader as the “ MiniDuke loader ” .' [/INST] [To:O, avoid:O, confusion:O, however:O, ,:O, we:O, have:O, decided:O, to:O, continue:O, referring:O, to:O, the:O, loader:S-TOOL, as:O, the:O, “:O, MiniDuke:S-MAL, loader:S-TOOL, ”:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Two details about MiniDuke components are worth noting .' [/INST] [Two:O, details:O, about:O, MiniDuke:S-MAL, components:O, are:O, worth:O, noting:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Firstly , some of the MiniDuke components were written in Assembly language .' [/INST] [Firstly:O, ,:O, some:O, of:O, the:O, MiniDuke:S-MAL, components:O, were:O, written:O, in:O, Assembly:S-TOOL, language:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While many malware were written in Assembly during the ‘ old days ‘ of curiosity-driven virus writing , it has since become a rarity .' [/INST] [While:O, many:O, malware:O, were:O, written:O, in:O, Assembly:S-TOOL, during:O, the:O, ‘:O, old:O, days:O, ‘:O, of:O, curiosity-driven:O, virus:O, writing:O, ,:O, it:O, has:O, since:O, become:O, a:O, rarity:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Secondly , some of the MiniDuke components do not contain a hardcoded C&C server address , but instead obtain the address of a current C&C server via Twitter .' [/INST] [Secondly:O, ,:O, some:O, of:O, the:O, MiniDuke:S-MAL, components:O, do:O, not:O, contain:O, a:O, hardcoded:O, C&C:S-TOOL, server:O, address:O, ,:O, but:O, instead:O, obtain:O, the:O, address:O, of:O, a:O, current:O, C&C:S-TOOL, server:O, via:O, Twitter:S-TOOL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The use of Twitter either to initially obtain the address of a C&C server ( or as a backup if no hardcoded primary C&C server responds ) is a feature also found in OnionDuke , CozyDuke , and HammerDuke .' [/INST] [The:O, use:O, of:O, Twitter:S-TOOL, either:O, to:O, initially:O, obtain:O, the:O, address:O, of:O, a:O, C&C:S-TOOL, server:O, (:O, or:O, as:O, a:O, backup:O, if:O, no:O, hardcoded:O, primary:O, C&C:S-TOOL, server:O, responds:O, ):O, is:O, a:O, feature:O, also:O, found:O, in:O, OnionDuke:S-MAL, ,:O, CozyDuke:S-MAL, ,:O, and:O, HammerDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'COZYDUKE : First known activity January 2010 , Most recent known activity : Spring 2015 , Other names CozyBear , CozyCar , Cozer , EuroAPT , C&C communication methods HTTP(S) , Twitter ( backup ) , Known toolset components Dropper , Modular backdoor , Multiple persistence components , Information gathering module , Screenshot module , Password stealing module , Password hash stealing module .' [/INST] [COZYDUKE:S-MAL, ::O, First:O, known:O, activity:O, January:B-TIME, 2010:E-TIME, ,:O, Most:O, recent:O, known:O, activity:O, ::O, Spring:B-TIME, 2015:E-TIME, ,:O, Other:O, names:O, CozyBear:S-MAL, ,:O, CozyCar:S-MAL, ,:O, Cozer:S-MAL, ,:O, EuroAPT:S-MAL, ,:O, C&C:S-TOOL, communication:O, methods:O, HTTP(S):S-PROT, ,:O, Twitter:S-TOOL, (:O, backup:O, ):O, ,:O, Known:O, toolset:O, components:O, Dropper:S-TOOL, ,:O, Modular:S-TOOL, backdoor:O, ,:O, Multiple:O, persistence:O, components:O, ,:O, Information:O, gathering:O, module:O, ,:O, Screenshot:O, module:O, ,:O, Password:O, stealing:O, module:O, ,:O, Password:O, hash:O, stealing:O, module:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CozyDuke is not simply a malware toolset ; rather , it is a modular malware platform formed around a core backdoor component .' [/INST] [CozyDuke:S-MAL, is:O, not:O, simply:O, a:O, malware:O, toolset:O, ;:O, rather:O, ,:O, it:O, is:O, a:O, modular:O, malware:O, platform:O, formed:O, around:O, a:O, core:O, backdoor:S-TOOL, component:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This component can be instructed by the C&C server to download and execute arbitrary modules , and it is these modules that provide CozyDuke with its vast array of functionality .' [/INST] [This:O, component:O, can:O, be:O, instructed:O, by:O, the:O, C&C:S-TOOL, server:O, to:O, download:O, and:O, execute:O, arbitrary:O, modules:O, ,:O, and:O, it:O, is:O, these:O, modules:O, that:O, provide:O, CozyDuke:S-MAL, with:O, its:O, vast:O, array:O, of:O, functionality:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Known CozyDuke modules include : Command execution module for executing arbitrary Windows Command Prompt commands , Password stealer module , NT LAN Manager ( NTLM ) hash stealer module , System information gathering module , Screenshot module .' [/INST] [Known:O, CozyDuke:S-MAL, modules:O, include:O, ::O, Command:O, execution:O, module:O, for:O, executing:O, arbitrary:O, Windows:S-OS, Command:B-TOOL, Prompt:E-TOOL, commands:O, ,:O, Password:B-TOOL, stealer:E-TOOL, module:O, ,:O, NT:B-TOOL, LAN:I-TOOL, Manager:E-TOOL, (:O, NTLM:S-TOOL, ):O, hash:B-TOOL, stealer:E-TOOL, module:O, ,:O, System:O, information:O, gathering:O, module:O, ,:O, Screenshot:O, module:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition to modules , CozyDuke can also be instructed to download and execute other , independent executables .' [/INST] [In:O, addition:O, to:O, modules:O, ,:O, CozyDuke:S-MAL, can:O, also:O, be:O, instructed:O, to:O, download:O, and:O, execute:O, other:O, ,:O, independent:O, executables:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In some observed cases , these executables were self-extracting archive files containing common hacking tools , such as PSExec and Mimikatz , combined with script files that execute these tools .' [/INST] [In:O, some:O, observed:O, cases:O, ,:O, these:O, executables:O, were:O, self-extracting:O, archive:O, files:O, containing:O, common:O, hacking:O, tools:O, ,:O, such:O, as:O, PSExec:S-TOOL, and:O, Mimikatz:S-TOOL, ,:O, combined:O, with:O, script:O, files:O, that:O, execute:O, these:O, tools:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In other cases , CozyDuke has been observed downloading and executing tools from other toolsets used by the Dukes such as OnionDuke , SeaDuke , and HammerDuke .' [/INST] [In:O, other:O, cases:O, ,:O, CozyDuke:S-MAL, has:O, been:O, observed:O, downloading:O, and:O, executing:O, tools:O, from:O, other:O, toolsets:O, used:O, by:O, the:O, Dukes:S-APT, such:O, as:O, OnionDuke:S-MAL, ,:O, SeaDuke:S-MAL, ,:O, and:O, HammerDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'ONIONDUKE : First known activity February 2013 , Most recent known activity Spring 2015 , C&C communication methods HTTP(S) , Twitter ( backup ) , Known toolset components Dropper , Loader , Multiple modular core components , Information stealer , Distributed Denial of Service ( DDoS ) module , Password stealing module , Information gathering module , Social network spamming module .' [/INST] [ONIONDUKE:S-MAL, ::O, First:O, known:O, activity:O, February:B-TIME, 2013:E-TIME, ,:O, Most:O, recent:O, known:O, activity:O, Spring:B-TIME, 2015:E-TIME, ,:O, C&C:S-TOOL, communication:O, methods:O, HTTP(S):S-PROT, ,:O, Twitter:S-TOOL, (:O, backup:O, ):O, ,:O, Known:O, toolset:O, components:O, Dropper:S-TOOL, ,:O, Loader:S-TOOL, ,:O, Multiple:B-TOOL, modular:E-TOOL, core:O, components:O, ,:O, Information:B-TOOL, stealer:E-TOOL, ,:O, Distributed:B-TOOL, Denial:I-TOOL, of:I-TOOL, Service:E-TOOL, (:O, DDoS:S-TOOL, ):O, module:O, ,:O, Password:O, stealing:O, module:O, ,:O, Information:O, gathering:O, module:O, ,:O, Social:O, network:O, spamming:O, module:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The OnionDuke toolset includes at least a dropper , a loader , an information stealer Trojan and multiple modular variants with associated modules .' [/INST] [The:O, OnionDuke:S-MAL, toolset:O, includes:O, at:O, least:O, a:O, dropper:S-TOOL, ,:O, a:O, loader:S-TOOL, ,:O, an:O, information:B-TOOL, stealer:E-TOOL, Trojan:S-MAL, and:O, multiple:B-TOOL, modular:E-TOOL, variants:O, with:O, associated:O, modules:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'OnionDuke first caught our attention because it was being spread via a malicious Tor exit node .' [/INST] [OnionDuke:S-MAL, first:O, caught:O, our:O, attention:O, because:O, it:O, was:O, being:O, spread:O, via:O, a:O, malicious:O, Tor:S-TOOL, exit:O, node:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Tor node would intercept any unencrypted executable files being downloaded and modify those executables by adding a malicious wrapper contained an embedded OnionDuke .' [/INST] [The:O, Tor:S-TOOL, node:O, would:O, intercept:O, any:O, unencrypted:O, executable:O, files:O, being:O, downloaded:O, and:O, modify:O, those:O, executables:O, by:O, adding:O, a:O, malicious:O, wrapper:O, contained:O, an:O, embedded:O, OnionDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once the victim finished downloading the file and executed it , the wrapper would infect the victim ’s computer with OnionDuke before executing the original legitimate executable .' [/INST] [Once:O, the:O, victim:O, finished:O, downloading:O, the:O, file:O, and:O, executed:O, it:O, ,:O, the:O, wrapper:O, would:O, infect:O, the:O, victim:O, ’s:O, computer:O, with:O, OnionDuke:S-MAL, before:O, executing:O, the:O, original:O, legitimate:O, executable:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The same wrapper has also been used to wrap legitimate executable files , which were then made available for users to download from torrent sites .' [/INST] [The:O, same:O, wrapper:O, has:O, also:O, been:O, used:O, to:O, wrap:O, legitimate:O, executable:O, files:O, ,:O, which:O, were:O, then:O, made:O, available:O, for:O, users:O, to:O, download:O, from:O, torrent:O, sites:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Again , if a victim downloaded a torrent containing a wrapped executable , they would get infected with OnionDuke .' [/INST] [Again:O, ,:O, if:O, a:O, victim:O, downloaded:O, a:O, torrent:O, containing:O, a:O, wrapped:O, executable:O, ,:O, they:O, would:O, get:O, infected:O, with:O, OnionDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Finally , we have also observed victims being infected with OnionDuke after they were already infected with CozyDuke .' [/INST] [Finally:O, ,:O, we:O, have:O, also:O, observed:O, victims:O, being:O, infected:O, with:O, OnionDuke:S-MAL, after:O, they:O, were:O, already:O, infected:O, with:O, CozyDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In these cases , CozyDuke was instructed by its C&C server to download and execute OnionDuke toolset .' [/INST] [In:O, these:O, cases:O, ,:O, CozyDuke:S-MAL, was:O, instructed:O, by:O, its:O, C&C:S-TOOL, server:O, to:O, download:O, and:O, execute:O, OnionDuke:S-MAL, toolset:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'SEADUKE : First known activity October 2014 , Most recent known activity Spring 2015 , Other names SeaDaddy , SeaDask , C&C communication methods HTTP(S) , Known toolset components Backdoor .' [/INST] [SEADUKE:S-MAL, ::O, First:O, known:O, activity:O, October:B-TIME, 2014:E-TIME, ,:O, Most:O, recent:O, known:O, activity:O, Spring:B-TIME, 2015:E-TIME, ,:O, Other:O, names:O, SeaDaddy:S-MAL, ,:O, SeaDask:S-MAL, ,:O, C&C:S-MAL, communication:O, methods:O, HTTP(S):S-PROT, ,:O, Known:O, toolset:O, components:O, Backdoor:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'SeaDuke is a simple backdoor that focuses on executing commands retrieved from its C&C server , such as uploading and downloading files , executing system commands and evaluating additional Python code .' [/INST] [SeaDuke:S-MAL, is:O, a:O, simple:O, backdoor:O, that:O, focuses:O, on:O, executing:O, commands:O, retrieved:O, from:O, its:O, C&C:S-TOOL, server:O, ,:O, such:O, as:O, uploading:O, and:O, downloading:O, files:O, ,:O, executing:O, system:O, commands:O, and:O, evaluating:O, additional:O, Python:S-TOOL, code:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'SeaDuke is made interesting by the fact that it is written in Python and designed to be cross-platform so that it works on both Windows and Linux .' [/INST] [SeaDuke:S-MAL, is:O, made:O, interesting:O, by:O, the:O, fact:O, that:O, it:O, is:O, written:O, in:O, Python:S-TOOL, and:O, designed:O, to:O, be:O, cross-platform:O, so:O, that:O, it:O, works:O, on:O, both:O, Windows:S-OS, and:O, Linux:S-OS, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The only known infection vector for SeaDuke is via an existing CozyDuke infection , wherein CozyDuke downloads and executes the SeaDuke toolset .' [/INST] [The:O, only:O, known:O, infection:O, vector:O, for:O, SeaDuke:S-MAL, is:O, via:O, an:O, existing:O, CozyDuke:S-MAL, infection:O, ,:O, wherein:O, CozyDuke:S-MAL, downloads:O, and:O, executes:O, the:O, SeaDuke:S-MAL, toolset:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Like HammerDuke , SeaDuke appears to be used by the Dukes group primarily as a secondary backdoor left on CozyDuke victims after that toolset has completed the initial infection and stolen any readily available information from them .' [/INST] [Like:O, HammerDuke:S-MAL, ,:O, SeaDuke:S-MAL, appears:O, to:O, be:O, used:O, by:O, the:O, Dukes:S-APT, group:O, primarily:O, as:O, a:O, secondary:O, backdoor:O, left:O, on:O, CozyDuke:S-MAL, victims:O, after:O, that:O, toolset:O, has:O, completed:O, the:O, initial:O, infection:O, and:O, stolen:O, any:O, readily:O, available:O, information:O, from:O, them:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'HAMMERDUKE : First known activity January 2015 , Most recent known activity Summer 2015 , Other names HAMMERTOSS , Netduke , C&C communication methods HTTP(S) , Twitter , Known toolset components Backdoor .' [/INST] [HAMMERDUKE:S-MAL, ::O, First:O, known:O, activity:O, January:B-TIME, 2015:E-TIME, ,:O, Most:O, recent:O, known:O, activity:O, Summer:B-TIME, 2015:E-TIME, ,:O, Other:O, names:O, HAMMERTOSS:S-MAL, ,:O, Netduke:S-MAL, ,:O, C&C:S-TOOL, communication:O, methods:O, HTTP(S):S-PROT, ,:O, Twitter:S-TOOL, ,:O, Known:O, toolset:O, components:O, Backdoor:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'HammerDuke is a simple backdoor that is apparently designed for similar use cases as SeaDuke .' [/INST] [HammerDuke:S-MAL, is:O, a:O, simple:O, backdoor:O, that:O, is:O, apparently:O, designed:O, for:O, similar:O, use:O, cases:O, as:O, SeaDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Specifically , the only known infection vector for HammerDuke is to be downloaded and executed by CozyDuke onto a victim that has already been compromised by that toolset .' [/INST] [Specifically:O, ,:O, the:O, only:O, known:O, infection:O, vector:O, for:O, HammerDuke:S-MAL, is:O, to:O, be:O, downloaded:O, and:O, executed:O, by:O, CozyDuke:S-MAL, onto:O, a:O, victim:O, that:O, has:O, already:O, been:O, compromised:O, by:O, that:O, toolset:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This , together with HammerDuke ’s simplistic backdoor functionality , suggests that it is primarily used by the Dukes group as a secondary backdoor left on CozyDuke victims after CozyDuke performed the initial infection and stole any readily available information from them .' [/INST] [This:O, ,:O, together:O, with:O, HammerDuke:S-MAL, ’s:O, simplistic:O, backdoor:O, functionality:O, ,:O, suggests:O, that:O, it:O, is:O, primarily:O, used:O, by:O, the:O, Dukes:S-APT, group:O, as:O, a:O, secondary:O, backdoor:O, left:O, on:O, CozyDuke:S-MAL, victims:O, after:O, CozyDuke:S-MAL, performed:O, the:O, initial:O, infection:O, and:O, stole:O, any:O, readily:O, available:O, information:O, from:O, them:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'HammerDuke is however interesting because it is written in .NET , and even more so because of its occasional use of Twitter as a C&C communication channel .' [/INST] [HammerDuke:S-MAL, is:O, however:O, interesting:O, because:O, it:O, is:O, written:O, in:O, .NET:S-TOOL, ,:O, and:O, even:O, more:O, so:O, because:O, of:O, its:O, occasional:O, use:O, of:O, Twitter:S-TOOL, as:O, a:O, C&C:S-APT, communication:O, channel:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Some HammerDuke variants only contain a hardcoded C&C server address from which they will retrieve commands , but other HammerDuke variants will first use a custom algorithm to generate a Twitter account name based on the current date .' [/INST] [Some:O, HammerDuke:S-MAL, variants:O, only:O, contain:O, a:O, hardcoded:O, C&C:S-TOOL, server:O, address:O, from:O, which:O, they:O, will:O, retrieve:O, commands:O, ,:O, but:O, other:O, HammerDuke:S-MAL, variants:O, will:O, first:O, use:O, a:O, custom:O, algorithm:O, to:O, generate:O, a:O, Twitter:S-TOOL, account:O, name:O, based:O, on:O, the:O, current:O, date:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'If the account exists , HammerDuke will then search for tweets from that account with links to image files that contain embedded commands for the toolset to execute .' [/INST] [If:O, the:O, account:O, exists:O, ,:O, HammerDuke:S-MAL, will:O, then:O, search:O, for:O, tweets:O, from:O, that:O, account:O, with:O, links:O, to:O, image:O, files:O, that:O, contain:O, embedded:O, commands:O, for:O, the:O, toolset:O, to:O, execute:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'HammerDuke ’s use of Twitter and crafted image files is reminiscent of other Duke toolsets .' [/INST] [HammerDuke:S-MAL, ’s:O, use:O, of:O, Twitter:S-TOOL, and:O, crafted:O, image:O, files:O, is:O, reminiscent:O, of:O, other:O, Duke:S-APT, toolsets:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Both OnionDuke and MiniDuke also use date-based algorithms to generate Twitter account names and then searched for any tweets from those accounts that linked to image files .' [/INST] [Both:O, OnionDuke:S-MAL, and:O, MiniDuke:S-MAL, also:O, use:O, date-based:O, algorithms:O, to:O, generate:O, Twitter:S-TOOL, account:O, names:O, and:O, then:O, searched:O, for:O, any:O, tweets:O, from:O, those:O, accounts:O, that:O, linked:O, to:O, image:O, files:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In contrast however , for OnionDuke and MiniDuke the linked image files contain embedded malware to be downloaded and executed , rather than instructions .' [/INST] [In:O, contrast:O, however:O, ,:O, for:O, OnionDuke:S-MAL, and:O, MiniDuke:S-MAL, the:O, linked:O, image:O, files:O, contain:O, embedded:O, malware:O, to:O, be:O, downloaded:O, and:O, executed:O, ,:O, rather:O, than:O, instructions:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Similarly , GeminiDuke may also download image files , but these would contain embedded additional configuration information for the toolset itself .' [/INST] [Similarly:O, ,:O, GeminiDuke:S-MAL, may:O, also:O, download:O, image:O, files:O, ,:O, but:O, these:O, would:O, contain:O, embedded:O, additional:O, configuration:O, information:O, for:O, the:O, toolset:O, itself:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Unlike HammerDuke however , the URLs for the images downloaded by GeminiDuke are hardcoded in its initial configuration , rather than retrieved from Twitter .' [/INST] [Unlike:O, HammerDuke:S-MAL, however:O, ,:O, the:O, URLs:O, for:O, the:O, images:O, downloaded:O, by:O, GeminiDuke:S-MAL, are:O, hardcoded:O, in:O, its:O, initial:O, configuration:O, ,:O, rather:O, than:O, retrieved:O, from:O, Twitter:S-TOOL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CLOUDDUKE : First known activity June 2015 , Most recent known activity Summer 2015 , Other names MiniDionis , CloudLook , C&C communication methods HTTP(S) , Microsoft OneDrive , Known toolset components Downloader , Loader , Two backdoor variants .' [/INST] [CLOUDDUKE:S-MAL, ::O, First:O, known:O, activity:O, June:B-TIME, 2015:E-TIME, ,:O, Most:O, recent:O, known:O, activity:O, Summer:B-TIME, 2015:E-TIME, ,:O, Other:O, names:O, MiniDionis:S-MAL, ,:O, CloudLook:S-MAL, ,:O, C&C:S-TOOL, communication:O, methods:O, HTTP(S):S-PROT, ,:O, Microsoft:S-IDTY, OneDrive:S-TOOL, ,:O, Known:O, toolset:O, components:O, Downloader:S-TOOL, ,:O, Loader:S-TOOL, ,:O, Two:O, backdoor:O, variants:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CloudDuke is a malware toolset known to consist of , at least , a downloader , a loader and two backdoor variants .' [/INST] [CloudDuke:S-MAL, is:O, a:O, malware:O, toolset:O, known:O, to:O, consist:O, of:O, ,:O, at:O, least:O, ,:O, a:O, downloader:S-TOOL, ,:O, a:O, loader:S-TOOL, and:O, two:O, backdoor:O, variants:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The CloudDuke downloader will download and execute additional malware from a preconfigured location .' [/INST] [The:O, CloudDuke:S-MAL, downloader:S-TOOL, will:O, download:O, and:O, execute:O, additional:O, malware:O, from:O, a:O, preconfigured:O, location:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Interestingly , that location may be either a web address or a Microsoft OneDrive account .' [/INST] [Interestingly:O, ,:O, that:O, location:O, may:O, be:O, either:O, a:O, web:O, address:O, or:O, a:O, Microsoft:S-IDTY, OneDrive:S-TOOL, account:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Both CloudDuke backdoor variants support simple backdoor functionality , similar to SeaDuke .' [/INST] [Both:O, CloudDuke:B-MAL, backdoor:E-MAL, variants:O, support:O, simple:O, backdoor:O, functionality:O, ,:O, similar:O, to:O, SeaDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While one variant will use a preconfigured C&C server over HTTP or HTTPS , the other variant will use a Microsoft OneDrive account to exchange commands and stolen data with its operators .' [/INST] [While:O, one:O, variant:O, will:O, use:O, a:O, preconfigured:O, C&C:S-TOOL, server:O, over:O, HTTP:S-PROT, or:O, HTTPS:S-PROT, ,:O, the:O, other:O, variant:O, will:O, use:O, a:O, Microsoft:S-IDTY, OneDrive:S-TOOL, account:O, to:O, exchange:O, commands:O, and:O, stolen:O, data:O, with:O, its:O, operators:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'THE DUKES 7 YEARS OF RUSSIAN CYBER ESPIONAGE .' [/INST] [THE:O, DUKES:S-APT, 7:O, YEARS:O, OF:O, RUSSIAN:O, CYBER:O, ESPIONAGE:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Dukes primarily use spear-phishing emails when attempting to infect victims with their malware .' [/INST] [The:O, Dukes:S-APT, primarily:O, use:O, spear-phishing:S-ACT, emails:S-TOOL, when:O, attempting:O, to:O, infect:O, victims:O, with:O, their:O, malware:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'These spear-phishing emails range from ones purposely designed to look like spam messages used to spread common crimeware and addressed to large numbers of people , to highly targeted emails addressed to only a few recipients ( or even just one person ) and with content that is highly relevant for the intended recipient .' [/INST] [These:O, spear-phishing:S-ACT, emails:S-TOOL, range:O, from:O, ones:O, purposely:O, designed:O, to:O, look:O, like:O, spam:O, messages:O, used:O, to:O, spread:O, common:O, crimeware:O, and:O, addressed:O, to:O, large:O, numbers:O, of:O, people:O, ,:O, to:O, highly:O, targeted:O, emails:S-TOOL, addressed:O, to:O, only:O, a:O, few:O, recipients:O, (:O, or:O, even:O, just:O, one:O, person:O, ):O, and:O, with:O, content:O, that:O, is:O, highly:O, relevant:O, for:O, the:O, intended:O, recipient:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In some cases , the Dukes appear to have used previously compromised victims to send new spear-phishing emails to other targets .' [/INST] [In:O, some:O, cases:O, ,:O, the:O, Dukes:S-APT, appear:O, to:O, have:O, used:O, previously:O, compromised:O, victims:O, to:O, send:O, new:O, spear-phishing:S-ACT, emails:S-TOOL, to:O, other:O, targets:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The spear-phishing emails used by the Dukes may contain either specially-crafted malicious attachments or links to URLs hosting the malware .' [/INST] [The:O, spear-phishing:S-ACT, emails:S-TOOL, used:O, by:O, the:O, Dukes:S-APT, may:O, contain:O, either:O, specially-crafted:O, malicious:O, attachments:O, or:O, links:O, to:O, URLs:O, hosting:O, the:O, malware:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'When malicious attachments are used , they may either be designed to exploit a vulnerability in a popular software assumed to be installed on the victim ’s machine , such as Microsoft Word or Adobe Reader , or the attachment itself may have its icon and filename obfuscated in such a way that the file does not appear to be an executable .' [/INST] [When:O, malicious:O, attachments:O, are:O, used:O, ,:O, they:O, may:O, either:O, be:O, designed:O, to:O, exploit:O, a:O, vulnerability:O, in:O, a:O, popular:O, software:O, assumed:O, to:O, be:O, installed:O, on:O, the:O, victim:O, ’s:O, machine:O, ,:O, such:O, as:O, Microsoft:S-IDTY, Word:S-TOOL, or:O, Adobe:B-TOOL, Reader:E-TOOL, ,:O, or:O, the:O, attachment:O, itself:O, may:O, have:O, its:O, icon:O, and:O, filename:O, obfuscated:O, in:O, such:O, a:O, way:O, that:O, the:O, file:O, does:O, not:O, appear:O, to:O, be:O, an:O, executable:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The only instances which we are aware of where the Dukes did not use spear-phishing as the initial infection vector is with certain OnionDuke variants .' [/INST] [The:O, only:O, instances:O, which:O, we:O, are:O, aware:O, of:O, where:O, the:O, Dukes:S-APT, did:O, not:O, use:O, spear-phishing:S-ACT, as:O, the:O, initial:O, infection:O, vector:O, is:O, with:O, certain:O, OnionDuke:S-MAL, variants:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'These were instead spread using either a malicious Tor node that would trojanize legitimate applications on-the-fly with the OnionDuke toolset , or via torrent files containing previously trojanized versions of legitimate applications .' [/INST] [These:O, were:O, instead:O, spread:O, using:O, either:O, a:O, malicious:O, Tor:S-TOOL, node:O, that:O, would:O, trojanize:O, legitimate:O, applications:O, on-the-fly:O, with:O, the:O, OnionDuke:S-MAL, toolset:O, ,:O, or:O, via:O, torrent:O, files:O, containing:O, previously:O, trojanized:O, versions:O, of:O, legitimate:O, applications:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Finally , it is worth noting that the Dukes are known to sometimes re-infect a victim of one of their malware tools with another one of their tools .' [/INST] [Finally:O, ,:O, it:O, is:O, worth:O, noting:O, that:O, the:O, Dukes:S-APT, are:O, known:O, to:O, sometimes:O, re-infect:O, a:O, victim:O, of:O, one:O, of:O, their:O, malware:O, tools:O, with:O, another:O, one:O, of:O, their:O, tools:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Examples include CozyDuke infecting its victims with SeaDuke , HammerDuke ,or OnionDuke ; and CosmicDuke infecting its victims with PinchDuke ,GeminiDuke or MiniDuke .' [/INST] [Examples:O, include:O, CozyDuke:S-MAL, infecting:O, its:O, victims:O, with:O, SeaDuke:S-MAL, ,:O, HammerDuke:S-MAL, ,or:O, OnionDuke:S-MAL, ;:O, and:O, CosmicDuke:S-MAL, infecting:O, its:O, victims:O, with:O, PinchDuke:S-MAL, ,GeminiDuke:S-MAL, or:O, MiniDuke:S-MAL, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Dukes have employed exploits both in their infection vectors as well as in their malware .' [/INST] [The:O, Dukes:S-APT, have:O, employed:O, exploits:O, both:O, in:O, their:O, infection:O, vectors:O, as:O, well:O, as:O, in:O, their:O, malware:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We are however only aware of one instance - the exploitation of CVE-2013-0640 to deploy MiniDuke - where we believe the exploited vulnerability was a zero-day at the time that the group acquired the exploit .' [/INST] [We:O, are:O, however:O, only:O, aware:O, of:O, one:O, instance:O, -:O, the:O, exploitation:O, of:O, CVE-2013-0640:S-VULID, to:O, deploy:O, MiniDuke:S-MAL, -:O, where:O, we:O, believe:O, the:O, exploited:O, vulnerability:O, was:O, a:O, zero-day:S-VULNAME, at:O, the:O, time:O, that:O, the:O, group:O, acquired:O, the:O, exploit:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In all known cases where exploits were employed , we believe the Dukes did not themselves discover the vulnerabilities or design the original exploits ; for the exploited zero-day , we believe the Dukes purchased the exploit .' [/INST] [In:O, all:O, known:O, cases:O, where:O, exploits:O, were:O, employed:O, ,:O, we:O, believe:O, the:O, Dukes:S-APT, did:O, not:O, themselves:O, discover:O, the:O, vulnerabilities:O, or:O, design:O, the:O, original:O, exploits:O, ;:O, for:O, the:O, exploited:O, zero-day:S-VULNAME, ,:O, we:O, believe:O, the:O, Dukes:S-APT, purchased:O, the:O, exploit:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In all other cases , we believe the group simply repurposed publicly available exploits or proofs of concept .' [/INST] [In:O, all:O, other:O, cases:O, ,:O, we:O, believe:O, the:O, group:O, simply:O, repurposed:O, publicly:O, available:O, exploits:O, or:O, proofs:O, of:O, concept:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Attribution is always a difficult question , but attempting to answer it is important in understanding these types of threats and how to defend against them .' [/INST] [Attribution:O, is:O, always:O, a:O, difficult:O, question:O, ,:O, but:O, attempting:O, to:O, answer:O, it:O, is:O, important:O, in:O, understanding:O, these:O, types:O, of:O, threats:O, and:O, how:O, to:O, defend:O, against:O, them:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This paper has already stated that we believe the Dukes to be a Russian state-sponsored cyberespionage operation .' [/INST] [This:O, paper:O, has:O, already:O, stated:O, that:O, we:O, believe:O, the:O, Dukes:S-APT, to:O, be:O, a:O, Russian:O, state-sponsored:O, cyberespionage:B-ACT, operation:E-ACT, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To reach this conclusion , we began by analyzing the apparent objectives and motivations of the group .' [/INST] [To:O, reach:O, this:O, conclusion:O, ,:O, we:O, began:O, by:O, analyzing:O, the:O, apparent:O, objectives:O, and:O, motivations:O, of:O, the:O, group:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Based on what we currently know about the targets chosen by the Dukes over the past 7 years , they appear to have consistently targeted entities that deal with foreign policy and security policy matters .' [/INST] [Based:O, on:O, what:O, we:O, currently:O, know:O, about:O, the:O, targets:O, chosen:O, by:O, the:O, Dukes:S-APT, over:O, the:O, past:O, 7:O, years:O, ,:O, they:O, appear:O, to:O, have:O, consistently:O, targeted:O, entities:O, that:O, deal:O, with:O, foreign:O, policy:O, and:O, security:O, policy:O, matters:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'These targets have included organizations such as ministries of foreign affairs , embassies , senates , parliaments , ministries of defense , defense contractors , and think tanks .' [/INST] [These:O, targets:O, have:O, included:O, organizations:O, such:O, as:O, ministries:O, of:O, foreign:O, affairs:O, ,:O, embassies:O, ,:O, senates:O, ,:O, parliaments:O, ,:O, ministries:O, of:O, defense:O, ,:O, defense:O, contractors:O, ,:O, and:O, think:O, tanks:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In one of their more intriguing cases , the Dukes have appeared to also target entities involved in the trafficking of illegal drugs .' [/INST] [In:O, one:O, of:O, their:O, more:O, intriguing:O, cases:O, ,:O, the:O, Dukes:S-APT, have:O, appeared:O, to:O, also:O, target:O, entities:O, involved:O, in:O, the:O, trafficking:O, of:O, illegal:O, drugs:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Even such targets however appear to be consistent with the overarching theme , given the drug trade ’s relevance to security policy .' [/INST] [Even:O, such:O, targets:O, however:O, appear:O, to:O, be:O, consistent:O, with:O, the:O, overarching:O, theme:O, ,:O, given:O, the:O, drug:O, trade:O, ’s:O, relevance:O, to:O, security:O, policy:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Based on this , we are confident in our conclusion that the Dukes ’ primary mission is the collection of intelligence to support foreign and security policy decision-making .' [/INST] [Based:O, on:O, this:O, ,:O, we:O, are:O, confident:O, in:O, our:O, conclusion:O, that:O, the:O, Dukes:S-APT, ’:O, primary:O, mission:O, is:O, the:O, collection:O, of:O, intelligence:O, to:O, support:O, foreign:O, and:O, security:O, policy:O, decision-making:O, .:O] </s>
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<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Based on the length of the Dukes ’ activity , our estimate of the amount of resources invested in the operation and the fact that their activity only appears to be increasing , we believe the group to have significant and most critically , stable financial backing .' [/INST] [Based:O, on:O, the:O, length:O, of:O, the:O, Dukes:S-APT, ’:O, activity:O, ,:O, our:O, estimate:O, of:O, the:O, amount:O, of:O, resources:O, invested:O, in:O, the:O, operation:O, and:O, the:O, fact:O, that:O, their:O, activity:O, only:O, appears:O, to:O, be:O, increasing:O, ,:O, we:O, believe:O, the:O, group:O, to:O, have:O, significant:O, and:O, most:O, critically:O, ,:O, stable:O, financial:O, backing:O, .:O] </s>
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