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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: 'There are known related samples that are able to create such directories on removable drives , i.e . the sample with md5: 8cb08140ddb00ac373d29d37657a03cc .' [/INST] [There:O, are:O, known:O, related:O, samples:O, that:O, are:O, able:O, to:O, create:O, such:O, directories:O, on:O, removable:O, drives:O, ,:O, i.e:O, .:O, the:O, sample:O, with:O, md5::O, 8cb08140ddb00ac373d29d37657a03cc:S-MD5, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 configuration file is loaded from the same directory as the module and is expected to have a name “ NvCpld.dat “ .' [/INST] [The:O, configuration:O, file:O, is:O, loaded:O, from:O, the:O, same:O, directory:O, as:O, the:O, module:O, and:O, is:O, expected:O, to:O, have:O, a:O, name:O, “:O, NvCpld.dat:S-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: 'It is a text file that may contain the following configuration parameters :' [/INST] [It:O, is:O, a:O, text:O, file:O, that:O, may:O, contain:O, the:O, following:O, configuration:O, parameters: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: 'Path – location of the root “ stash ” directory Ext – search for files with one of these extensions only Date – search for files not earlier than this date Internal name : NvCpld.dll ( from export table ) , msdetltemp.dll ( from resources ) , IGFSRVC.dll ( from resources ) File format : PE32 DLL File size : 76,288 bytes MD5s : 8b238931a7f64fddcad3057a96855f6c , ce151285e8f0e7b2b90162ba171a4b90 Linker version : 11.0 , Microsoft Visual Studio Linker timestamps : 2015.05.29 11:20:32 ( GMT ) , 2006.11.25 04:39:15 ( GMT ) Exported functions :' [/INST] [Path:O, –:O, location:O, of:O, the:O, root:O, “:O, stash:O, ”:O, directory:O, Ext:O, –:O, search:O, for:O, files:O, with:O, one:O, of:O, these:O, extensions:O, only:O, Date:O, –:O, search:O, for:O, files:O, not:O, earlier:O, than:O, this:O, date:O, Internal:O, name:O, ::O, NvCpld.dll:S-FILE, (:O, from:O, export:O, table:O, ):O, ,:O, msdetltemp.dll:S-FILE, (:O, from:O, resources:O, ):O, ,:O, IGFSRVC.dll:S-FILE, (:O, from:O, resources:O, ):O, File:O, format:O, ::O, PE32:O, DLL:S-TOOL, File:O, size:O, ::O, 76,288:O, bytes:O, MD5s:O, ::O, 8b238931a7f64fddcad3057a96855f6c:S-MD5, ,:O, ce151285e8f0e7b2b90162ba171a4b90:S-MD5, Linker:O, version:O, ::O, 11.0:O, ,:O, Microsoft:S-IDTY, Visual:B-TOOL, Studio:E-TOOL, Linker:O, timestamps:O, ::O, 2015.05.29:B-TIME, 11:20:32:E-TIME, (:O, GMT:S-TOOL, ):O, ,:O, 2006.11.25:B-TIME, 04:39:15:E-TIME, (:O, GMT:S-TOOL, ):O, Exported:O, functions: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: '10002500: NvMswt 10002860: NvReg 10002880: NvStart 10002A80: NvStop This library is a newer version of the file collection module ( md5: 0369620eb139c3875a62e36bb7abdae8 ) wrapped in a DLL file .' [/INST] [10002500::O, NvMswt:O, 10002860::O, NvReg:O, 10002880::O, NvStart:O, 10002A80::O, NvStop:O, This:O, library:O, is:O, a:O, newer:O, version:O, of:O, the:O, file:O, collection:O, module:O, (:O, md5::O, 0369620eb139c3875a62e36bb7abdae8:S-MD5, ):O, wrapped:O, in:O, a:O, DLL:S-TOOL, 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: 'There are two known variants of this module ; they only differ in timestamp values and version information in the resource section .' [/INST] [There:O, are:O, two:O, known:O, variants:O, of:O, this:O, module:O, ;:O, they:O, only:O, differ:O, in:O, timestamp:O, values:O, and:O, version:O, information:O, in:O, the:O, resource:O, section: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 DllMain function only decrypts the data structures and initializes Windows API pointers .' [/INST] [The:O, DllMain:O, function:O, only:O, decrypts:O, the:O, data:O, structures:O, and:O, initializes:O, Windows:S-OS, API:O, pointers: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 function “ NvMswt ” is a wrapper for the API function MsgWaitForMultipleObjects .' [/INST] [The:O, function:O, “:O, NvMswt:O, ”:O, is:O, a:O, wrapper:O, for:O, the:O, API:O, function:O, MsgWaitForMultipleObjects: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 function “ NvReg ” is a wrapper for the API function RegisterClassW .' [/INST] [The:O, function:O, “:O, NvReg:O, ”:O, is:O, a:O, wrapper:O, for:O, the:O, API:O, function:O, RegisterClassW: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 function “ NvStart ” is similar to the main function of the older module ; it creates a window and enters the message loop waiting for device arrival notifications .' [/INST] [The:O, function:O, “:O, NvStart:O, ”:O, is:O, similar:O, to:O, the:O, main:O, function:O, of:O, the:O, older:O, module:O, ;:O, it:O, creates:O, a:O, window:O, and:O, enters:O, the:O, message:O, loop:O, waiting:O, for:O, device:O, arrival:O, notifications: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 only difference introduced is that an event named “ WerTyQ34C ” can be signalled by the function “ NvStop ” to terminate the message loop and stop processing .' [/INST] [The:O, only:O, difference:O, introduced:O, is:O, that:O, an:O, event:O, named:O, “:O, WerTyQ34C:O, ”:O, can:O, be:O, signalled:O, by:O, the:O, function:O, “:O, NvStop:O, ”:O, to:O, terminate:O, the:O, message:O, loop:O, and:O, stop:O, processing: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: 'How they did it : GRU hackers .' [/INST] [How:O, they:O, did:O, it:O, ::O, GRU:O, hackers: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: 'US elections .' [/INST] [US:O, elections: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 a press briefing just two weeks ago , Deputy Attorney General Rod Rosenstein announced that the grand jury assembled by Special Counsel Robert Mueller had returned an indictment against 12 officers of Russia 's Main Intelligence Directorate of the Russian General Staff ( better known as Glavnoye razvedyvatel'noye upravleniye , or GRU ) .' [/INST] [In:O, a:O, press:O, briefing:O, just:O, two:O, weeks:O, ago:O, ,:O, Deputy:O, Attorney:O, General:O, Rod:O, Rosenstein:O, announced:O, that:O, the:O, grand:O, jury:O, assembled:O, by:O, Special:O, Counsel:O, Robert:O, Mueller:O, had:O, returned:O, an:O, indictment:O, against:O, 12:O, officers:O, of:O, Russia:S-LOC, 's:O, Main:O, Intelligence:O, Directorate:O, of:O, the:O, Russian:O, General:O, Staff:O, (:O, better:O, known:O, as:O, Glavnoye:B-IDTY, razvedyvatel'noye:I-IDTY, upravleniye:E-IDTY, ,:O, or:O, GRU:S-IDTY, ):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 indictment was for conducting , active cyber operations with the intent of interfering in the 2016 presidential election . , The espionage operation was run by Unit 26165 , commanded by GRU Officer Viktor Borisovich Netykshko .' [/INST] [The:O, indictment:O, was:O, for:O, conducting:O, ,:O, active:O, cyber:O, operations:O, with:O, the:O, intent:O, of:O, interfering:O, in:O, the:O, 2016:S-TIME, presidential:O, election:O, .:O, ,:O, The:O, espionage:O, operation:O, was:O, run:O, by:O, Unit:B-APT, 26165:E-APT, ,:O, commanded:O, by:O, GRU:S-IDTY, Officer:O, Viktor:O, Borisovich:O, Netykshko: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: 'Unit 26165 appears to be the organization behind at least part of the "threat group" of tools , techniques , and procedures known as , Fancy Bear , , , Sofacy , , , APT28 , , and , Sednit , .' [/INST] [Unit:B-APT, 26165:E-APT, appears:O, to:O, be:O, the:O, organization:O, behind:O, at:O, least:O, part:O, of:O, the:O, "threat:O, group":O, of:O, tools:O, ,:O, techniques:O, ,:O, and:O, procedures:O, known:O, as:O, ,:O, Fancy:B-APT, Bear:E-APT, ,:O, ,:O, ,:O, Sofacy:S-APT, ,:O, ,:O, ,:O, APT28:S-APT, ,:O, ,:O, and:O, ,:O, Sednit:S-APT, ,: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: 'Within the unit , two divisions were involved in the breaches : one specializing in operations and the second in development and maintenance of hacking tools and infrastructure .' [/INST] [Within:O, the:O, unit:O, ,:O, two:O, divisions:O, were:O, involved:O, in:O, the:O, breaches:O, ::O, one:O, specializing:O, in:O, operations:O, and:O, the:O, second:O, in:O, development:O, and:O, maintenance:O, of:O, hacking:O, tools:O, and:O, infrastructure:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The operations division , supervised by Major Boris Alekseyevich Antonov , specialized in targeting organizations of intelligence interest through spear-phishing campaigns and the exploitation of stolen credentials .' [/INST] [The:O, operations:O, division:O, ,:O, supervised:O, by:O, Major:O, Boris:O, Alekseyevich:O, Antonov:O, ,:O, specialized:O, in:O, targeting:O, organizations:O, of:O, intelligence:O, interest:O, through:O, spear-phishing:S-ACT, campaigns:O, and:O, the:O, exploitation:O, of:O, stolen:O, credentials:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Antonov's group included Ivan Sergeyevich Yermakov and Senior Lieutenant Aleksey Viktorovich Lukashev , according to the indictment , and they were responsible for targeting the email accounts that were exposed on the , DCLeaks , site prior to the election operations .' [/INST] [Antonov's:O, group:O, included:O, Ivan:O, Sergeyevich:O, Yermakov:O, and:O, Senior:O, Lieutenant:O, Aleksey:O, Viktorovich:O, Lukashev:O, ,:O, according:O, to:O, the:O, indictment:O, ,:O, and:O, they:O, were:O, responsible:O, for:O, targeting:O, the:O, email:S-TOOL, accounts:O, that:O, were:O, exposed:O, on:O, the:O, ,:O, DCLeaks:S-APT, ,:O, site:O, prior:O, to:O, the:O, election: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: 'The second division , overseen by Lieutenant Colonel Sergey Aleksandrovich Morgachev , managed the development and maintenance of malware and hacking tools used by Unit 26165 , including the X-Agent , implant , .' [/INST] [The:O, second:O, division:O, ,:O, overseen:O, by:O, Lieutenant:O, Colonel:O, Sergey:O, Aleksandrovich:O, Morgachev:O, ,:O, managed:O, the:O, development:O, and:O, maintenance:O, of:O, malware:O, and:O, hacking:O, tools:O, used:O, by:O, Unit:B-APT, 26165:E-APT, ,:O, including:O, the:O, X-Agent:S-MAL, ,:O, implant:O, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'X-Agent is a signature tool of Fancy Bear operations—a cross-platform backdoor toolset with variants for Windows , MacOS , Android , and iOS .' [/INST] [X-Agent:S-MAL, is:O, a:O, signature:O, tool:O, of:O, Fancy:B-APT, Bear:E-APT, operations—a:O, cross-platform:O, backdoor:O, toolset:O, with:O, variants:O, for:O, Windows:S-OS, ,:O, MacOS:S-OS, ,:O, Android:S-OS, ,:O, and:O, iOS:S-OS, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Windows and MacOS versions of X-Agent are capable of recording keystrokes , taking screenshots , and exfiltrating files from infected systems back to a command and control server .' [/INST] [The:O, Windows:S-OS, and:O, MacOS:S-OS, versions:O, of:O, X-Agent:S-MAL, are:O, capable:O, of:O, recording:O, keystrokes:O, ,:O, taking:O, screenshots:O, ,:O, and:O, exfiltrating:O, files:O, from:O, infected:O, systems:O, back:O, to:O, a:O, command:O, and:O, control:O, server:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Lieutenant Captain Nikolay Kozacheck ( who used the hacker monikers , kazak , and , blablabla1234465 , ) was the primary developer and maintainer of X-Agent , according to the indictment , and he was assisted by another officer , Pavel Yershov , in preparing it for deployment .' [/INST] [Lieutenant:O, Captain:O, Nikolay:O, Kozacheck:O, (:O, who:O, used:O, the:O, hacker:O, monikers:O, ,:O, kazak:O, ,:O, and:O, ,:O, blablabla1234465:O, ,:O, ):O, was:O, the:O, primary:O, developer:O, and:O, maintainer:O, of:O, X-Agent:S-MAL, ,:O, according:O, to:O, the:O, indictment:O, ,:O, and:O, he:O, was:O, assisted:O, by:O, another:O, officer:O, ,:O, Pavel:O, Yershov:O, ,:O, in:O, preparing:O, it:O, for:O, deployment:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once X-Agent was implanted on the DNC and DCCC networks , Second Lieutenant Artem Malyshev ( AKA , djangomagicdev , and , realblatr , ) monitored the implants through the command and control network configured for the task .' [/INST] [Once:O, X-Agent:S-MAL, was:O, implanted:O, on:O, the:O, DNC:S-TOOL, and:O, DCCC:S-TOOL, networks:O, ,:O, Second:O, Lieutenant:O, Artem:O, Malyshev:O, (:O, AKA:O, ,:O, djangomagicdev:O, ,:O, and:O, ,:O, realblatr:O, ,:O, ):O, monitored:O, the:O, implants:O, through:O, the:O, command:O, and:O, control:O, network:O, configured:O, for:O, the:O, task:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The information operations unit , Unit 74455 , was commanded by Colonel Aleksandr Vladimirovich Osadchuk .' [/INST] [The:O, information:O, operations:O, unit:O, ,:O, Unit:B-APT, 74455:E-APT, ,:O, was:O, commanded:O, by:O, Colonel:O, Aleksandr:O, Vladimirovich:O, Osadchuk: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: 'Unit 74455 's members would be responsible for the distribution of some of the stolen data from the breaches through the , DCLeaks , and , Guccifer 2.0 , websites .' [/INST] [Unit:B-APT, 74455:E-APT, 's:O, members:O, would:O, be:O, responsible:O, for:O, the:O, distribution:O, of:O, some:O, of:O, the:O, stolen:O, data:O, from:O, the:O, breaches:O, through:O, the:O, ,:O, DCLeaks:S-APT, ,:O, and:O, ,:O, Guccifer:S-APT, 2.0:O, ,:O, websites:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This group famously also reached out to WikiLeaks ( referred to as , Organization 1 , in the indictment ) to amplify their information operation , and they promoted the leaks to journalists through GRU -controlled email and social media accounts .' [/INST] [This:O, group:O, famously:O, also:O, reached:O, out:O, to:O, WikiLeaks:S-TOOL, (:O, referred:O, to:O, as:O, ,:O, Organization:O, 1:O, ,:O, in:O, the:O, indictment:O, ):O, to:O, amplify:O, their:O, information:O, operation:O, ,:O, and:O, they:O, promoted:O, the:O, leaks:O, to:O, journalists:O, through:O, GRU:S-IDTY, -controlled:O, email:S-TOOL, and:O, social:O, media:O, accounts: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: 'Within Unit 74455 , Officer Aleksy Potemkin—a department supervisor—oversaw information operations infrastructure .' [/INST] [Within:O, Unit:B-APT, 74455:E-APT, ,:O, Officer:O, Aleksy:O, Potemkin—a:O, department:O, supervisor—oversaw:O, information:O, operations:O, infrastructure:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'His group configured the DCLeaks and Guccifer 2.0 blogs and social media accounts that would later be used to spread data stolen from the DNC , DCCC , and Clinton campaigns .' [/INST] [His:O, group:O, configured:O, the:O, DCLeaks:S-APT, and:O, Guccifer:S-APT, 2.0:O, blogs:O, and:O, social:O, media:O, accounts:O, that:O, would:O, later:O, be:O, used:O, to:O, spread:O, data:O, stolen:O, from:O, the:O, DNC:S-TOOL, ,:O, DCCC:S-TOOL, ,:O, and:O, Clinton:O, campaigns: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: 'Bears in the Midst : Intrusion Into the Democratic National Committee .' [/INST] [Bears:O, in:O, the:O, Midst:O, ::O, Intrusion:O, Into:O, the:O, Democratic:B-IDTY, National:I-IDTY, Committee:E-IDTY, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'There is rarely a dull day at CrowdStrike where we are not detecting or responding to a breach at a company somewhere around the globe .' [/INST] [There:O, is:O, rarely:O, a:O, dull:O, day:O, at:O, CrowdStrike:S-SECTEAM, where:O, we:O, are:O, not:O, detecting:O, or:O, responding:O, to:O, a:O, breach:O, at:O, a:O, company:O, somewhere:O, around:O, the:O, globe: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 of these cases , we operate under strict confidentiality rules with our customers and cannot reveal publicly any information about these attacks .' [/INST] [In:O, all:O, of:O, these:O, cases:O, ,:O, we:O, operate:O, under:O, strict:O, confidentiality:O, rules:O, with:O, our:O, customers:O, and:O, cannot:O, reveal:O, publicly:O, any:O, information:O, about:O, these: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: 'But on rare occasions , a customer decides to go public with information about their incident and give us permission to share our knowledge of the adversary tradecraft with the broader community and help protect even those who do not happen to be our customers .' [/INST] [But:O, on:O, rare:O, occasions:O, ,:O, a:O, customer:O, decides:O, to:O, go:O, public:O, with:O, information:O, about:O, their:O, incident:O, and:O, give:O, us:O, permission:O, to:O, share:O, our:O, knowledge:O, of:O, the:O, adversary:O, tradecraft:O, with:O, the:O, broader:O, community:O, and:O, help:O, protect:O, even:O, those:O, who:O, do:O, not:O, happen:O, to:O, be:O, our:O, customers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This story is about one of those cases .' [/INST] [This:O, story:O, is:O, about:O, one:O, of:O, those:O, cases: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: 'CrowdStrike Services Inc. , our Incident Response group , was called by the Democratic National Committee ( DNC ) , the formal governing body for the US Democratic Party , to respond to a suspected breach .' [/INST] [CrowdStrike:S-SECTEAM, Services:O, Inc.:O, ,:O, our:O, Incident:B-SECTEAM, Response:E-SECTEAM, group:O, ,:O, was:O, called:O, by:O, the:O, Democratic:B-IDTY, National:I-IDTY, Committee:E-IDTY, (:O, DNC:S-IDTY, ):O, ,:O, the:O, formal:O, governing:O, body:O, for:O, the:O, US:S-LOC, Democratic:O, Party:O, ,:O, to:O, respond:O, to:O, a:O, suspected:O, breach: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 deployed our IR team and technology and immediately identified two sophisticated adversaries on the network – COZY BEAR and FANCY BEAR .' [/INST] [We:O, deployed:O, our:O, IR:S-SECTEAM, team:O, and:O, technology:O, and:O, immediately:O, identified:O, two:O, sophisticated:O, adversaries:O, on:O, the:O, network:O, –:O, COZY:B-APT, BEAR:E-APT, and:O, FANCY:B-APT, BEAR:E-APT, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We ’ve had lots of experience with both of these actors attempting to target our customers in the past and know them well .' [/INST] [We:O, ’ve:O, had:O, lots:O, of:O, experience:O, with:O, both:O, of:O, these:O, actors:O, attempting:O, to:O, target:O, our:O, customers:O, in:O, the:O, past:O, and:O, know:O, them: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 fact , our team considers them some of the best threat actors out of all the numerous nation-state , criminal and hacktivist/terrorist groups we encounter on a daily basis .' [/INST] [In:O, fact:O, ,:O, our:O, team:O, considers:O, them:O, some:O, of:O, the:O, best:O, threat:O, actors:O, out:O, of:O, all:O, the:O, numerous:O, nation-state:O, ,:O, criminal:O, and:O, hacktivist/terrorist:O, groups:O, we:O, encounter:O, on:O, a:O, daily:O, basis:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Their tradecraft is superb , operational security second to none and the extensive usage of ‘ living-off-the-land ’ techniques enables them to easily bypass many security solutions they encounter .' [/INST] [Their:O, tradecraft:O, is:O, superb:O, ,:O, operational:O, security:O, second:O, to:O, none:O, and:O, the:O, extensive:O, usage:O, of:O, ‘:O, living-off-the-land:O, ’:O, techniques:O, enables:O, them:O, to:O, easily:O, bypass:O, many:O, security:O, solutions:O, they:O, encounter: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 particular , we identified advanced methods consistent with nation-state level capabilities including deliberate targeting and ‘ access management ’ tradecraft – both groups were constantly going back into the environment to change out their implants , modify persistent methods , move to new Command & Control channels and perform other tasks to try to stay ahead of being detected .' [/INST] [In:O, particular:O, ,:O, we:O, identified:O, advanced:O, methods:O, consistent:O, with:O, nation-state:O, level:O, capabilities:O, including:O, deliberate:O, targeting:O, and:O, ‘:O, access:O, management:O, ’:O, tradecraft:O, –:O, both:O, groups:O, were:O, constantly:O, going:O, back:O, into:O, the:O, environment:O, to:O, change:O, out:O, their:O, implants:O, ,:O, modify:O, persistent:O, methods:O, ,:O, move:O, to:O, new:O, Command:B-TOOL, &:I-TOOL, Control:E-TOOL, channels:O, and:O, perform:O, other:O, tasks:O, to:O, try:O, to:O, stay:O, ahead:O, of:O, being:O, detected:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Both adversaries engage in extensive political and economic espionage for the benefit of the government of the Russian Federation and are believed to be closely linked to the Russian government ’s powerful and highly capable intelligence services .' [/INST] [Both:O, adversaries:O, engage:O, in:O, extensive:O, political:O, and:O, economic:O, espionage:O, for:O, the:O, benefit:O, of:O, the:O, government:O, of:O, the:O, Russian:O, Federation:O, and:O, are:O, believed:O, to:O, be:O, closely:O, linked:O, to:O, the:O, Russian:O, government:O, ’s:O, powerful:O, and:O, highly:O, capable:O, intelligence:O, services: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: 'COZY BEAR ( also referred to in some industry reports as CozyDuke or APT 29 ) is the adversary group that last year successfully infiltrated the unclassified networks of the White House , State Department , and US Joint Chiefs of Staff .' [/INST] [COZY:B-APT, BEAR:E-APT, (:O, also:O, referred:O, to:O, in:O, some:O, industry:O, reports:O, as:O, CozyDuke:S-APT, or:O, APT:B-APT, 29:E-APT, ):O, is:O, the:O, adversary:O, group:O, that:O, last:O, year:O, successfully:O, infiltrated:O, the:O, unclassified:O, networks:O, of:O, the:O, White:B-IDTY, House:E-IDTY, ,:O, State:B-IDTY, Department:E-IDTY, ,:O, and:O, US:S-LOC, Joint:B-IDTY, Chiefs:I-IDTY, of:I-IDTY, Staff:E-IDTY, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 US government , they have targeted organizations across the Defense , Energy , Extractive , Financial , Insurance , Legal , Manufacturing Media , Think Tanks , Pharmaceutical , Research and Technology industries , along with Universities .' [/INST] [In:O, addition:O, to:O, the:O, US:S-LOC, government:O, ,:O, they:O, have:O, targeted:O, organizations:O, across:O, the:O, Defense:O, ,:O, Energy:O, ,:O, Extractive:O, ,:O, Financial:O, ,:O, Insurance:O, ,:O, Legal:O, ,:O, Manufacturing:O, Media:O, ,:O, Think:O, Tanks:O, ,:O, Pharmaceutical:O, ,:O, Research:O, and:O, Technology:O, industries:O, ,:O, along:O, with:O, Universities: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: 'Victims have also been observed in Western Europe , Brazil , China , Japan , Mexico , New Zealand , South Korea , Turkey and Central Asian countries .' [/INST] [Victims:O, have:O, also:O, been:O, observed:O, in:O, Western:B-LOC, Europe:E-LOC, ,:O, Brazil:S-LOC, ,:O, China:S-LOC, ,:O, Japan:S-LOC, ,:O, Mexico:S-LOC, ,:O, New:B-LOC, Zealand:E-LOC, ,:O, South:B-LOC, Korea:E-LOC, ,:O, Turkey:S-LOC, and:O, Central:O, Asian:O, countries:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'COZY BEAR ’s preferred intrusion method is a broadly targeted spearphish campaign that typically includes web links to a malicious dropper .' [/INST] [COZY:B-APT, BEAR:E-APT, ’s:O, preferred:O, intrusion:O, method:O, is:O, a:O, broadly:O, targeted:O, spearphish:O, campaign:O, that:O, typically:O, includes:O, web:O, links:O, to:O, a:O, malicious:O, dropper:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once executed on the machine , the code will deliver one of a number of sophisticated Remote Access Tools ( RATs ) , including AdobeARM , ATI-Agent , and MiniDionis .' [/INST] [Once:O, executed:O, on:O, the:O, machine:O, ,:O, the:O, code:O, will:O, deliver:O, one:O, of:O, a:O, number:O, of:O, sophisticated:O, Remote:B-TOOL, Access:I-TOOL, Tools:E-TOOL, (:O, RATs:S-TOOL, ):O, ,:O, including:O, AdobeARM:S-TOOL, ,:O, ATI-Agent:S-TOOL, ,:O, and:O, MiniDionis:S-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 many occasions , both the dropper and the payload will contain a range of techniques to ensure the sample is not being analyzed on a virtual machine , using a debugger , or located within a sandbox .' [/INST] [On:O, many:O, occasions:O, ,:O, both:O, the:O, dropper:O, and:O, the:O, payload:O, will:O, contain:O, a:O, range:O, of:O, techniques:O, to:O, ensure:O, the:O, sample:O, is:O, not:O, being:O, analyzed:O, on:O, a:O, virtual:O, machine:O, ,:O, using:O, a:O, debugger:O, ,:O, or:O, located:O, within:O, a:O, sandbox: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: 'They have extensive checks for the various security software that is installed on the system and their specific configurations .' [/INST] [They:O, have:O, extensive:O, checks:O, for:O, the:O, various:O, security:O, software:O, that:O, is:O, installed:O, on:O, the:O, system:O, and:O, their:O, specific:O, configurations: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: 'When specific versions are discovered that may cause issues for the RAT , it promptly exits .' [/INST] [When:O, specific:O, versions:O, are:O, discovered:O, that:O, may:O, cause:O, issues:O, for:O, the:O, RAT:S-TOOL, ,:O, it:O, promptly:O, exits: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 actions demonstrate a well-resourced adversary with a thorough implant-testing regime that is highly attuned to slight configuration issues that may result in their detection , and which would cause them to deploy a different tool instead .' [/INST] [These:O, actions:O, demonstrate:O, a:O, well-resourced:O, adversary:O, with:O, a:O, thorough:O, implant-testing:O, regime:O, that:O, is:O, highly:O, attuned:O, to:O, slight:O, configuration:O, issues:O, that:O, may:O, result:O, in:O, their:O, detection:O, ,:O, and:O, which:O, would:O, cause:O, them:O, to:O, deploy:O, a:O, different:O, tool:O, instead: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 implants are highly configurable via encrypted configuration files , which allow the adversary to customize various components , including C2 servers , the list of initial tasks to carry out , persistence mechanisms , encryption keys and others .' [/INST] [The:O, implants:O, are:O, highly:O, configurable:O, via:O, encrypted:O, configuration:O, files:O, ,:O, which:O, allow:O, the:O, adversary:O, to:O, customize:O, various:O, components:O, ,:O, including:O, C2:S-TOOL, servers:O, ,:O, the:O, list:O, of:O, initial:O, tasks:O, to:O, carry:O, out:O, ,:O, persistence:O, mechanisms:O, ,:O, encryption:O, keys:O, and:O, others:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'An HTTP protocol with encrypted payload is used for the Command & Control communication .' [/INST] [An:O, HTTP:S-PROT, protocol:O, with:O, encrypted:O, payload:O, is:O, used:O, for:O, the:O, Command:B-TOOL, &:I-TOOL, Control:E-TOOL, communication: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: 'FANCY BEAR ( also known as Sofacy or APT 28 ) is a separate Russian-based threat actor , which has been active since mid 2000s , and has been responsible for targeted intrusion campaigns against the Aerospace , Defense , Energy , Government and Media sectors .' [/INST] [FANCY:B-APT, BEAR:E-APT, (:O, also:O, known:O, as:O, Sofacy:S-APT, or:O, APT:B-APT, 28:E-APT, ):O, is:O, a:O, separate:O, Russian-based:O, threat:O, actor:O, ,:O, which:O, has:O, been:O, active:O, since:O, mid:B-TIME, 2000s:E-TIME, ,:O, and:O, has:O, been:O, responsible:O, for:O, targeted:O, intrusion:O, campaigns:O, against:O, the:O, Aerospace:O, ,:O, Defense:O, ,:O, Energy:O, ,:O, Government:O, and:O, Media:O, 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: 'Their victims have been identified in the United States , Western Europe , Brazil , Canada , China , Georgia , Iran , Japan , Malaysia and South Korea .' [/INST] [Their:O, victims:O, have:O, been:O, identified:O, in:O, the:O, United:B-LOC, States:E-LOC, ,:O, Western:B-LOC, Europe:E-LOC, ,:O, Brazil:S-LOC, ,:O, Canada:S-LOC, ,:O, China:S-LOC, ,:O, Georgia:S-LOC, ,:O, Iran:S-LOC, ,:O, Japan:S-LOC, ,:O, Malaysia:S-LOC, and:O, South:B-LOC, Korea:E-LOC, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Extensive targeting of defense ministries and other military victims has been observed , the profile of which closely mirrors the strategic interests of the Russian government , and may indicate affiliation with GRU , Russia ’s premier military intelligence service .' [/INST] [Extensive:O, targeting:O, of:O, defense:O, ministries:O, and:O, other:O, military:O, victims:O, has:O, been:O, observed:O, ,:O, the:O, profile:O, of:O, which:O, closely:O, mirrors:O, the:O, strategic:O, interests:O, of:O, the:O, Russian:O, government:O, ,:O, and:O, may:O, indicate:O, affiliation:O, with:O, GRU:S-IDTY, ,:O, Russia:S-LOC, ’s:O, premier:O, military:O, intelligence:O, service: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 adversary has a wide range of implants at their disposal , which have been developed over the course of many years and include Sofacy , X-Agent , X-Tunnel , WinIDS , Foozer and DownRage droppers , and even malware for Linux , OSX , IOS , Android and Windows Phones .' [/INST] [This:O, adversary:O, has:O, a:O, wide:O, range:O, of:O, implants:O, at:O, their:O, disposal:O, ,:O, which:O, have:O, been:O, developed:O, over:O, the:O, course:O, of:O, many:O, years:O, and:O, include:O, Sofacy:S-APT, ,:O, X-Agent:S-MAL, ,:O, X-Tunnel:S-TOOL, ,:O, WinIDS:S-MAL, ,:O, Foozer:S-MAL, and:O, DownRage:S-MAL, droppers:O, ,:O, and:O, even:O, malware:O, for:O, Linux:S-OS, ,:O, OSX:S-OS, ,:O, IOS:S-OS, ,:O, Android:S-OS, and:O, Windows:S-OS, Phones: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 group is known for its technique of registering domains that closely resemble domains of legitimate organizations they plan to target .' [/INST] [This:O, group:O, is:O, known:O, for:O, its:O, technique:O, of:O, registering:O, domains:O, that:O, closely:O, resemble:O, domains:O, of:O, legitimate:O, organizations:O, they:O, plan:O, to:O, target: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: 'Afterwards , they establish phishing sites on these domains that spoof the look and feel of the victim ’s web-based email services in order to steal their credentials .' [/INST] [Afterwards:O, ,:O, they:O, establish:O, phishing:E-ACT, sites:O, on:O, these:O, domains:O, that:O, spoof:O, the:O, look:O, and:O, feel:O, of:O, the:O, victim:O, ’s:O, web-based:O, email:S-TOOL, services:O, in:O, order:O, to:O, steal:O, their:O, credentials:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'FANCY BEAR has also been linked publicly to intrusions into the German Bundestag and France ’s TV5 Monde TV station in April 2015 .' [/INST] [FANCY:B-APT, BEAR:E-APT, has:O, also:O, been:O, linked:O, publicly:O, to:O, intrusions:O, into:O, the:O, German:S-LOC, Bundestag:S-IDTY, and:O, France:S-LOC, ’s:O, TV5:B-IDTY, Monde:E-IDTY, TV:O, station:O, in:O, April:B-TIME, 2015:E-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: 'At DNC , COZY BEAR intrusion has been identified going back to summer of 2015 , while FANCY BEAR separately breached the network in April 2016 .' [/INST] [At:O, DNC:S-IDTY, ,:O, COZY:B-APT, BEAR:E-APT, intrusion:O, has:O, been:O, identified:O, going:O, back:O, to:O, summer:B-TIME, of:I-TIME, 2015:E-TIME, ,:O, while:O, FANCY:B-APT, BEAR:E-APT, separately:O, breached:O, the:O, network:O, in:O, April:B-TIME, 2016:E-TIME, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We have identified no collaboration between the two actors , or even an awareness of one by the other .' [/INST] [We:O, have:O, identified:O, no:O, collaboration:O, between:O, the:O, two:O, actors:O, ,:O, or:O, even:O, an:O, awareness:O, of:O, one:O, by:O, the:O, other:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Instead , we observed the two Russian espionage groups compromise the same systems and engage separately in the theft of identical credentials .' [/INST] [Instead:O, ,:O, we:O, observed:O, the:O, two:O, Russian:O, espionage:O, groups:O, compromise:O, the:O, same:O, systems:O, and:O, engage:O, separately:O, in:O, the:O, theft:O, of:O, identical:O, credentials:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'While you would virtually never see Western intelligence agencies going after the same target without de-confliction for fear of compromising each other ’s operations , in Russia this is not an uncommon scenario . “ Putin ’s Hydra : Inside Russia ’s Intelligence Services ” , a recent paper from European Council on Foreign Relations , does an excellent job outlining the highly adversarial relationship between Russia ’s main intelligence services – FSB , the primary domestic intelligence agency but one with also significant external collection and ‘ active measures ’' [/INST] [While:O, you:O, would:O, virtually:O, never:O, see:O, Western:O, intelligence:O, agencies:O, going:O, after:O, the:O, same:O, target:O, without:O, de-confliction:O, for:O, fear:O, of:O, compromising:O, each:O, other:O, ’s:O, operations:O, ,:O, in:O, Russia:S-LOC, this:O, is:O, not:O, an:O, uncommon:O, scenario:O, .:O, “:O, Putin:O, ’s:O, Hydra:O, ::O, Inside:O, Russia:S-LOC, ’s:O, Intelligence:O, Services:O, ”:O, ,:O, a:O, recent:O, paper:O, from:O, European:O, Council:O, on:O, Foreign:O, Relations:O, ,:O, does:O, an:O, excellent:O, job:O, outlining:O, the:O, highly:O, adversarial:O, relationship:O, between:O, Russia:S-LOC, ’s:O, main:O, intelligence:O, services:O, –:O, FSB:S-IDTY, ,:O, the:O, primary:O, domestic:O, intelligence:O, agency:O, but:O, one:O, with:O, also:O, significant:O, external:O, collection:O, and:O, ‘:O, active:O, measures: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: 'remit , SVR , the primary foreign intelligence agency , and the aforementioned GRU .' [/INST] [remit:O, ,:O, SVR:O, ,:O, the:O, primary:O, foreign:O, intelligence:O, agency:O, ,:O, and:O, the:O, aforementioned:O, GRU:S-IDTY, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Not only do they have overlapping areas of responsibility , but also rarely share intelligence and even occasionally steal sources from each other and compromise operations .' [/INST] [Not:O, only:O, do:O, they:O, have:O, overlapping:O, areas:O, of:O, responsibility:O, ,:O, but:O, also:O, rarely:O, share:O, intelligence:O, and:O, even:O, occasionally:O, steal:O, sources:O, from:O, each:O, other:O, and:O, compromise: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: 'Thus , it is not surprising to see them engage in intrusions against the same victim , even when it may be a waste of resources and lead to the discovery and potential compromise of mutual operations .' [/INST] [Thus:O, ,:O, it:O, is:O, not:O, surprising:O, to:O, see:O, them:O, engage:O, in:O, intrusions:O, against:O, the:O, same:O, victim:O, ,:O, even:O, when:O, it:O, may:O, be:O, a:O, waste:O, of:O, resources:O, and:O, lead:O, to:O, the:O, discovery:O, and:O, potential:O, compromise:O, of:O, mutual: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: 'The COZY BEAR intrusion relied primarily on the SeaDaddy implant developed in Python and compiled with py2exe and another Powershell backdoor with persistence accomplished via Windows Management Instrumentation ( WMI ) system , which allowed the adversary to launch malicious code automatically after a specified period of system uptime or on a specific schedule .' [/INST] [The:O, COZY:B-APT, BEAR:E-APT, intrusion:O, relied:O, primarily:O, on:O, the:O, SeaDaddy:S-MAL, implant:O, developed:O, in:O, Python:S-TOOL, and:O, compiled:O, with:O, py2exe:S-TOOL, and:O, another:O, Powershell:S-TOOL, backdoor:O, with:O, persistence:O, accomplished:O, via:O, Windows:S-OS, Management:B-TOOL, Instrumentation:E-TOOL, (:O, WMI:S-TOOL, ):O, system:O, ,:O, which:O, allowed:O, the:O, adversary:O, to:O, launch:O, malicious:O, code:O, automatically:O, after:O, a:O, specified:O, period:O, of:O, system:O, uptime:O, or:O, on:O, a:O, specific:O, schedule: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 backdoor is ingenious in its simplicity and power .' [/INST] [The:O, Powershell:S-TOOL, backdoor:O, is:O, ingenious:O, in:O, its:O, simplicity:O, and:O, power: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 one-line powershell command , stored only in WMI database , establishes an encrypted connection to C2 and downloads additional powershell modules from it , executing them in memory .' [/INST] [This:O, one-line:O, powershell:S-TOOL, command:O, ,:O, stored:O, only:O, in:O, WMI:S-TOOL, database:O, ,:O, establishes:O, an:O, encrypted:O, connection:O, to:O, C2:S-TOOL, and:O, downloads:O, additional:O, powershell:S-TOOL, modules:O, from:O, it:O, ,:O, executing:O, them:O, in:O, memory: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 theory , the additional modules can do virtually anything on the victim system .' [/INST] [In:O, theory:O, ,:O, the:O, additional:O, modules:O, can:O, do:O, virtually:O, anything:O, on:O, the:O, victim:O, system:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The encryption keys in the script were different on every system .' [/INST] [The:O, encryption:O, keys:O, in:O, the:O, script:O, were:O, different:O, on:O, every:O, system:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Powershell version of credential theft tool MimiKatz was also used by the actors to facilitate credential acquisition for lateral movement purposes .' [/INST] [Powershell:S-TOOL, version:O, of:O, credential:O, theft:O, tool:O, MimiKatz:S-MAL, was:O, also:O, used:O, by:O, the:O, actors:O, to:O, facilitate:O, credential:O, acquisition:O, for:O, lateral:O, movement:O, purposes: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: 'FANCY BEAR adversary used different tradecraft , deploying X-Agent malware with capabilities to do remote command execution , file transmission and keylogging .' [/INST] [FANCY:B-APT, BEAR:E-APT, adversary:O, used:O, different:O, tradecraft:O, ,:O, deploying:O, X-Agent:S-MAL, malware:O, with:O, capabilities:O, to:O, do:O, remote:O, command:O, execution:O, ,:O, file:O, transmission:O, and:O, keylogging:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'It was executed via rundll32 commands such as : rundll32.exe “ C:\Windows\twain_64.dll ” .' [/INST] [It:O, was:O, executed:O, via:O, rundll32:O, commands:O, such:O, as:O, ::O, rundll32.exe:S-FILE, “:O, C:\Windows\twain_64.dll:S-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 addition , FANCY BEAR ’s X-Tunnel network tunneling tool , which facilitates connections to NAT-ed environments , was used to also execute remote commands .' [/INST] [In:O, addition:O, ,:O, FANCY:B-APT, BEAR:E-APT, ’s:O, X-Tunnel:S-TOOL, network:O, tunneling:O, tool:O, ,:O, which:O, facilitates:O, connections:O, to:O, NAT-ed:S-TOOL, environments:O, ,:O, was:O, used:O, to:O, also:O, execute:O, remote:O, commands:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Both tools were deployed via RemCOM , an open-source replacement for PsExec available from GitHub .' [/INST] [Both:O, tools:O, were:O, deployed:O, via:O, RemCOM:S-IDTY, ,:O, an:O, open-source:O, replacement:O, for:O, PsExec:S-TOOL, available:O, from:O, GitHub:S-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: 'Intelligence collection directed by nation state actors against US political targets provides invaluable insight into the requirements directed upon those actors .' [/INST] [Intelligence:O, collection:O, directed:O, by:O, nation:O, state:O, actors:O, against:O, US:S-LOC, political:O, targets:O, provides:O, invaluable:O, insight:O, into:O, the:O, requirements:O, directed:O, upon:O, those:O, actors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Regardless of the agency or unit tasked with this collection , the upcoming US election , and the associated candidates and parties are of critical interest to both hostile and friendly nation states .' [/INST] [Regardless:O, of:O, the:O, agency:O, or:O, unit:O, tasked:O, with:O, this:O, collection:O, ,:O, the:O, upcoming:O, US:S-LOC, election:O, ,:O, and:O, the:O, associated:O, candidates:O, and:O, parties:O, are:O, of:O, critical:O, interest:O, to:O, both:O, hostile:O, and:O, friendly:O, nation:O, states: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 2016 presidential election has the world ’s attention , and leaders of other states are anxiously watching and planning for possible outcomes .' [/INST] [The:O, 2016:S-TIME, presidential:O, election:O, has:O, the:O, world:O, ’s:O, attention:O, ,:O, and:O, leaders:O, of:O, other:O, states:O, are:O, anxiously:O, watching:O, and:O, planning:O, for:O, possible:O, outcomes: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: 'Corporate IoT – a path to intrusion .' [/INST] [Corporate:O, IoT:S-TOOL, –:O, a:O, path:O, to: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: 'Several sources estimate that by the year 2020 some 50 billion IoT devices will be deployed worldwide .' [/INST] [Several:O, sources:O, estimate:O, that:O, by:O, the:O, year:O, 2020:S-TIME, some:O, 50:O, billion:O, IoT:S-TOOL, devices:O, will:O, be:O, deployed:O, worldwide:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'IoT devices are purposefully designed to connect to a network and many are simply connected to the internet with little management or oversight.Some IoT devices may even communicate basic telemetry back to the device manufacturer or have means to receive software updates .' [/INST] [IoT:S-TOOL, devices:O, are:O, purposefully:O, designed:O, to:O, connect:O, to:O, a:O, network:O, and:O, many:O, are:O, simply:O, connected:O, to:O, the:O, internet:O, with:O, little:O, management:O, or:O, oversight.Some:O, IoT:S-TOOL, devices:O, may:O, even:O, communicate:O, basic:O, telemetry:O, back:O, to:O, the:O, device:O, manufacturer:O, or:O, have:O, means:O, to:O, receive:O, software:O, updates:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In 2016 , the Mirai botnet was discovered by the malware research group MalwareMustDie .' [/INST] [In:O, 2016:S-TIME, ,:O, the:O, Mirai:B-TOOL, botnet:E-TOOL, was:O, discovered:O, by:O, the:O, malware:O, research:O, group:O, MalwareMustDie:S-SECTEAM, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The botnet initially consisted of IP cameras and basic home routers , two types of IoT devices commonly found in the household .' [/INST] [The:O, botnet:O, initially:O, consisted:O, of:O, IP:O, cameras:O, and:O, basic:O, home:O, routers:O, ,:O, two:O, types:O, of:O, IoT:S-TOOL, devices:O, commonly:O, found:O, in:O, the:O, household: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 more variants of Mirai emerged , so did the list IoT devices it was targeting .' [/INST] [As:O, more:O, variants:O, of:O, Mirai:S-TOOL, emerged:O, ,:O, so:O, did:O, the:O, list:O, IoT:S-TOOL, devices:O, it:O, was:O, targeting: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 source code for the malware powering this botnet was eventually leaked online .' [/INST] [The:O, source:O, code:O, for:O, the:O, malware:O, powering:O, this:O, botnet:O, was:O, eventually:O, leaked:O, online: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 , hundreds of thousands of home and small business networking and storage devices were compromised and loaded with the so-called “ VPN Filter ” malware .' [/INST] [In:O, 2018:S-TIME, ,:O, hundreds:O, of:O, thousands:O, of:O, home:O, and:O, small:O, business:O, networking:O, and:O, storage:O, devices:O, were:O, compromised:O, and:O, loaded:O, with:O, the:O, so-called:O, “:O, VPN:B-MAL, Filter:E-MAL, ”:O, malware:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The FBI has publicly attributed this activity to a nation-state actor and took subsequent actions to disrupt this botnet , although the devices would remain vulnerable to re-infection unless proper firmware or security controls were put in place by the user .' [/INST] [The:O, FBI:S-IDTY, has:O, publicly:O, attributed:O, this:O, activity:O, to:O, a:O, nation-state:O, actor:O, and:O, took:O, subsequent:O, actions:O, to:O, disrupt:O, this:O, botnet:O, ,:O, although:O, the:O, devices:O, would:O, remain:O, vulnerable:O, to:O, re-infection:O, unless:O, proper:O, firmware:O, or:O, security:O, controls:O, were:O, put:O, in:O, place:O, by:O, the:O, user: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 , security researchers in the Microsoft Threat Intelligence Center discovered infrastructure of a known adversary communicating to several external devices .' [/INST] [In:O, April:S-TIME, ,:O, security:O, researchers:O, in:O, the:O, Microsoft:S-IDTY, Threat:B-TOOL, Intelligence:I-TOOL, Center:E-TOOL, discovered:O, infrastructure:O, of:O, a:O, known:O, adversary:O, communicating:O, to:O, several:O, external:O, devices: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: 'Further research uncovered attempts by the actor to compromise popular IoT devices ( a VOIP phone , an office printer , and a video decoder ) across multiple customer locations .' [/INST] [Further:O, research:O, uncovered:O, attempts:O, by:O, the:O, actor:O, to:O, compromise:O, popular:O, IoT:S-TOOL, devices:O, (:O, a:O, VOIP:B-TOOL, phone:E-TOOL, ,:O, an:O, office:B-TOOL, printer:E-TOOL, ,:O, and:O, a:O, video:B-TOOL, decoder:E-TOOL, ):O, across:O, multiple:O, customer:O, locations: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 investigation uncovered that an actor had used these devices to gain initial access to corporate networks .' [/INST] [The:O, investigation:O, uncovered:O, that:O, an:O, actor:O, had:O, used:O, these:O, devices:O, to:O, gain:O, initial:O, access:O, to:O, corporate:O, networks:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In two of the cases , the passwords for the devices were deployed without changing the default manufacturer ’s passwords and in the third instance the latest security update had not been applied to the device .' [/INST] [In:O, two:O, of:O, the:O, cases:O, ,:O, the:O, passwords:O, for:O, the:O, devices:O, were:O, deployed:O, without:O, changing:O, the:O, default:O, manufacturer:O, ’s:O, passwords:O, and:O, in:O, the:O, third:O, instance:O, the:O, latest:O, security:O, update:O, had:O, not:O, been:O, applied:O, to:O, the:O, device:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'These devices became points of ingress from which the actor established a presence on the network and continued looking for further access .' [/INST] [These:O, devices:O, became:O, points:O, of:O, ingress:O, from:O, which:O, the:O, actor:O, established:O, a:O, presence:O, on:O, the:O, network:O, and:O, continued:O, looking:O, for:O, further:O, access:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Once the actor had successfully established access to the network , a simple network scan to look for other insecure devices allowed them to discover and move across the network in search of higher-privileged accounts that would grant access to higher-value data .' [/INST] [Once:O, the:O, actor:O, had:O, successfully:O, established:O, access:O, to:O, the:O, network:O, ,:O, a:O, simple:O, network:O, scan:O, to:O, look:O, for:O, other:O, insecure:O, devices:O, allowed:O, them:O, to:O, discover:O, and:O, move:O, across:O, the:O, network:O, in:O, search:O, of:O, higher-privileged:O, accounts:O, that:O, would:O, grant:O, access:O, to:O, higher-value: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: 'After gaining access to each of the IoT devices , the actor ran tcpdump to sniff network traffic on local subnets .' [/INST] [After:O, gaining:O, access:O, to:O, each:O, of:O, the:O, IoT:S-TOOL, devices:O, ,:O, the:O, actor:O, ran:O, tcpdump:O, to:O, sniff:O, network:O, traffic:O, on:O, local:O, subnets: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: 'They were also seen enumerating administrative groups to attempt further exploitation .' [/INST] [They:O, were:O, also:O, seen:O, enumerating:O, administrative:O, groups:O, to:O, attempt:O, further:O, exploitation: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 the actor moved from one device to another , they would drop a simple shell script to establish persistence on the network which allowed extended access to continue hunting .' [/INST] [As:O, the:O, actor:O, moved:O, from:O, one:O, device:O, to:O, another:O, ,:O, they:O, would:O, drop:O, a:O, simple:O, shell:O, script:O, to:O, establish:O, persistence:O, on:O, the:O, network:O, which:O, allowed:O, extended:O, access:O, to:O, continue:O, hunting: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: 'Analysis of network traffic showed the devices were also communicating with an external command and control ( C2 ) server .' [/INST] [Analysis:O, of:O, network:O, traffic:O, showed:O, the:O, devices:O, were:O, also:O, communicating:O, with:O, an:O, external:O, command:B-TOOL, and:I-TOOL, control:E-TOOL, (:O, C2:S-TOOL, ):O, server:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The following IP addresses are believed to have been used by the actor for command and control ( C2 ) during these intrusions :' [/INST] [The:O, following:O, IP:O, addresses:O, are:O, believed:O, to:O, have:O, been:O, used:O, by:O, the:O, actor:O, for:O, command:B-TOOL, and:I-TOOL, control:E-TOOL, (:O, C2:S-TOOL, ):O, during:O, these:O, 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: '167.114.153.55 94.237.37.28 82.118.242.171 31.220.61.251 128.199.199.187 .' [/INST] [167.114.153.55:S-IP, 94.237.37.28:S-IP, 82.118.242.171:S-IP, 31.220.61.251:S-IP, 128.199.199.187:S-IP, .:O] </s> |
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