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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: 'They also used WinRAR and cURL for Windows , both often renamed , to compress and upload the exfiltrated files from the Visma network to the Dropbox API .' [/INST] [They:O, also:O, used:O, WinRAR:O, and:O, cURL:O, for:O, Windows:O, ,:O, both:O, often:O, renamed:O, ,:O, to:O, compress:O, and:O, upload:B-Purp, the:O, exfiltrated:O, files:O, from:O, the:O, Visma:B-Tool, network:O, to:O, the:O, Dropbox:B-Tool, API:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Our research partner Rapid7 investigated the Dropbox use and found that the attackers had used the same account to store exfiltrated data from a global apparel company .' [/INST] [Our:O, research:O, partner:O, Rapid7:B-SecTeam, investigated:O, the:O, Dropbox:B-Tool, use:O, and:O, found:O, that:O, the:O, attackers:B-HackOrg, had:O, used:O, the:O, same:O, account:O, to:O, store:O, exfiltrated:O, data:O, from:O, a:O, global:O, apparel:O, company: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 also identified broadly similar TTPs being used in the attack against a U.S law firm specializing in intellectual property law .' [/INST] [They:B-SecTeam, also:O, identified:O, broadly:O, similar:O, TTPs:O, being:O, used:O, in:O, the:O, attack:B-OffAct, against:I-OffAct, a:O, U.S:O, law:O, firm:O, specializing:O, in:O, intellectual:O, property:O, law: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: 'Rapid7’s investigation revealed the law firm was first targeted in late 2017 , followed by the apparel company a few months later , and finally , the Visma attack in August 2018 .' [/INST] [Rapid7’s:B-SecTeam, investigation:O, revealed:O, the:O, law:B-Org, firm:I-Org, was:O, first:O, targeted:O, in:O, late:O, 2017:B-Time, ,:O, followed:O, by:O, the:O, apparel:O, company:O, a:O, few:O, months:O, later:O, ,:O, and:O, finally:O, ,:O, the:O, Visma:B-OffAct, attack:I-OffAct, in:O, August:B-Time, 2018:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In one of the attacks , Rapid7 identified the attackers escaping a Citrix application in order to run the payload script on the victim desktop .' [/INST] [In:O, one:O, of:O, the:O, attacks:O, ,:O, Rapid7:B-SecTeam, identified:O, the:O, attackers:B-HackOrg, escaping:O, a:O, Citrix:B-Tool, application:O, in:O, order:O, to:O, run:O, the:O, payload:O, script:O, on:O, the:O, victim:O, desktop: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: 'Additionally , the same DLL sideloading technique observed in the Visma attack was used , and many of the tools deployed by the APT10 shared naming similarities as well 1.bat , cu.exe , ss.rar , r.exe , pd.exe .' [/INST] [Additionally:O, ,:O, the:O, same:O, DLL:O, sideloading:O, technique:O, observed:O, in:O, the:O, Visma:B-Tool, attack:O, was:O, used:O, ,:O, and:O, many:O, of:O, the:O, tools:O, deployed:O, by:O, the:O, APT10:B-HackOrg, shared:O, naming:O, similarities:O, as:O, well:O, 1.bat:B-Tool, ,:O, cu.exe:B-Tool, ,:O, ss.rar:B-Tool, ,:O, r.exe:B-Tool, ,:O, pd.exe:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Most interestingly , Rapid7 observed the use of the Notepad++ updater gup.exe as a legitimate executable to sideload a malicious DLL (libcurl.dll) in order to deploy a variant of the UPPERCUT backdoor also known as ANEL .' [/INST] [Most:O, interestingly:O, ,:O, Rapid7:B-SecTeam, observed:O, the:O, use:O, of:O, the:O, Notepad++:O, updater:O, gup.exe:B-SamFile, as:O, a:O, legitimate:O, executable:O, to:O, sideload:O, a:O, malicious:O, DLL:O, (libcurl.dll):O, in:O, order:O, to:O, deploy:O, a:O, variant:O, of:O, the:O, UPPERCUT:O, backdoor:O, also:O, known:O, as:O, ANEL:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 used this approach to deploy UPPERCUT when targeting Japanese corporations in July 2018 .' [/INST] [APT10:B-HackOrg, used:O, this:O, approach:O, to:O, deploy:O, UPPERCUT:B-Tool, when:O, targeting:O, Japanese:B-Idus, corporations:I-Idus, in:O, July:B-Time, 2018:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'APT10 actors gained initial access to the Visma network around August 17 , 2018 .' [/INST] [APT10:B-HackOrg, actors:O, gained:O, initial:O, access:O, to:O, the:O, Visma:B-Tool, network:I-Tool, around:O, August:B-Time, 17:I-Time, ,:O, 2018: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 we are confident that APT10 actors gained access to the Visma network in August using stolen employee Citrix remote desktop credentials , it is not clear how or when these credentials were initially compromised .' [/INST] [While:O, we:O, are:O, confident:O, that:O, APT10:B-HackOrg, actors:O, gained:O, access:O, to:O, the:O, Visma:B-Org, network:O, in:O, August:O, using:O, stolen:O, employee:O, Citrix:B-Tool, remote:I-Tool, desktop:I-Tool, credentials:O, ,:O, it:O, is:O, not:O, clear:O, how:O, or:O, when:O, these:O, credentials:O, were:O, initially:O, compromised: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: 'Insikt Group analysis of network metadata to and from the VPN endpoint IPs revealed consistent connectivity to Citrix-hosted infrastructure from all eight VPN endpoint IPs starting on August 17 , 2018 — the same date the first authenticated login to Visma’s network was made using stolen credentials .' [/INST] [Insikt:B-HackOrg, Group:I-HackOrg, analysis:O, of:O, network:O, metadata:O, to:O, and:O, from:O, the:O, VPN:O, endpoint:O, IPs:O, revealed:O, consistent:O, connectivity:O, to:O, Citrix-hosted:B-SamFile, infrastructure:O, from:O, all:O, eight:O, VPN:B-Features, endpoint:I-Features, IPs:O, starting:O, on:O, August:B-Time, 17:I-Time, ,:O, 2018:O, —:O, the:O, same:O, date:O, the:O, first:O, authenticated:O, login:O, to:O, Visma’s:O, network:O, was:O, made:O, using: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: 'After almost two weeks , on August 30 , 2018 , APT10 attackers used their access to the network to move laterally and made their first deployment of an RC4- and Salsa20-encrypted variant of the Trochilus malware using a previously associated DLL sideloading techniquE .' [/INST] [After:O, almost:O, two:O, weeks:O, ,:O, on:O, August:B-Time, 30:I-Time, ,:O, 2018:O, ,:O, APT10:B-HackOrg, attackers:O, used:O, their:O, access:O, to:O, the:O, network:O, to:O, move:O, laterally:O, and:O, made:O, their:O, first:O, deployment:O, of:O, an:O, RC4-:O, and:O, Salsa20-encrypted:O, variant:O, of:O, the:O, Trochilus:B-Tool, malware:O, using:O, a:O, previously:O, associated:O, DLL:O, sideloading:O, techniquE: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 means that APT10 actors had two separate access points into the Visma network .' [/INST] [This:O, means:O, that:O, APT10:B-HackOrg, actors:O, had:O, two:O, separate:O, access:O, points:O, into:O, the:O, Visma:B-Tool, network:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This slight delay may point to the handing over of active exploitation duties to other operator(s) in a multi-team APT10 effort within the Ministry of State Security for the attack .' [/INST] [This:O, slight:O, delay:O, may:O, point:O, to:O, the:O, handing:O, over:O, of:O, active:O, exploitation:O, duties:O, to:O, other:O, operator(s):O, in:O, a:O, multi-team:O, APT10:B-HackOrg, effort:O, within:O, the:O, Ministry:B-Area, of:O, State:O, Security:O, for:O, the:O, attack:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Other examples of malicious infrastructure registered with internet.bs include domains for APT28’s VPNFilter malware campaign and the registration of the cyber-berkut .' [/INST] [Other:O, examples:O, of:O, malicious:O, infrastructure:O, registered:O, with:O, internet.bs:O, include:O, domains:O, for:O, APT28’s:B-HackOrg, VPNFilter:B-Tool, malware:O, campaign:O, and:O, the:O, registration:O, of:O, the:O, cyber-berkut:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'org domain that was affiliated with the pro-Russian and potentially Russian state-linked threat actor CyberBerkut .' [/INST] [org:O, domain:O, that:O, was:O, affiliated:O, with:O, the:O, pro-Russian:B-Area, and:O, potentially:O, Russian:O, state-linked:O, threat:O, actor:O, CyberBerkut:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'KHRAT is a backdoor trojan purported to be used with the China-linked cyberespionage group DragonOK .' [/INST] [KHRAT:B-SamFile, is:O, a:O, backdoor:B-Tool, trojan:I-Tool, purported:O, to:O, be:O, used:O, with:O, the:O, China-linked:B-Area, cyberespionage:O, group:O, DragonOK:B-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In early 2018 , Rapid7 identified that APT10 compromised an apparel company , based upon detections and intelligence gathered from the U.S.-based law firm breach .' [/INST] [In:O, early:B-Time, 2018:I-Time, ,:O, Rapid7:B-SecTeam, identified:O, that:O, APT10:B-HackOrg, compromised:O, an:O, apparel:B-Idus, company:I-Idus, ,:O, based:O, upon:O, detections:O, and:O, intelligence:O, gathered:O, from:O, the:O, U.S.-based:O, law:B-Idus, firm:I-Idus, 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: 'The attacker gained access to the victim’s internet-accessible Citrix systems and authenticated to them from networks associated with low-cost VPN providers owned by VPN Consumer Network .' [/INST] [The:O, attacker:B-HackOrg, gained:B-Purp, access:I-Purp, to:O, the:O, victim’s:O, internet-accessible:O, Citrix:B-Tool, systems:O, and:O, authenticated:O, to:O, them:O, from:O, networks:O, associated:O, with:O, low-cost:O, VPN:O, providers:O, owned:O, by:O, VPN:O, Consumer:O, Network:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Rapid7 again observed APT10 dropping payloads named ccSEUPDT.exe.” The attackers used identical TTPs for executing malware and Mimikatz as observed before , by using DLL sideloading with known good binaries that had DLL search order path issues .' [/INST] [Rapid7:B-SecTeam, again:O, observed:O, APT10:B-HackOrg, dropping:O, payloads:O, named:O, ccSEUPDT.exe.”:O, The:O, attackers:O, used:O, identical:O, TTPs:O, for:O, executing:O, malware:O, and:O, Mimikatz:B-Tool, as:O, observed:O, before:O, ,:O, by:O, using:O, DLL:O, sideloading:O, with:O, known:O, good:O, binaries:O, that:O, had:O, DLL:O, search:O, order:O, path:O, issues: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: 'Rapid7 reviewed malware discovered in the victim’s environment and found implants that used Dropbox as the C2 .' [/INST] [Rapid7:B-SecTeam, reviewed:O, malware:O, discovered:O, in:O, the:O, victim’s:O, environment:O, and:O, found:O, implants:O, that:O, used:O, Dropbox:B-SamFile, as:O, the:O, C2: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 attackers used the same method of lateral movement by mounting the remote drive on a system , copying 1.bat to it , using task scheduler to execute the batch script , and finally , deleting the batch script .' [/INST] [The:O, attackers:B-HackOrg, used:O, the:O, same:O, method:O, of:O, lateral:O, movement:O, by:O, mounting:O, the:O, remote:B-Purp, drive:I-Purp, on:O, a:O, system:O, ,:O, copying:O, 1.bat:B-Tool, to:O, it:O, ,:O, using:O, task:O, scheduler:O, to:O, execute:O, the:O, batch:O, script:O, ,:O, and:O, finally:O, ,:O, deleting:O, the:O, batch:O, script: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: 'APT10 used the same method of lateral movement by mounting the remote drive on a system , copying 1.bat to it , using task scheduler to execute the batch script , and finally , deleting the batch script .' [/INST] [APT10:B-HackOrg, used:O, the:O, same:O, method:O, of:O, lateral:O, movement:O, by:O, mounting:B-Way, the:O, remote:O, drive:O, on:O, a:O, system:O, ,:O, copying:O, 1.bat:O, to:O, it:O, ,:O, using:O, task:B-Way, scheduler:I-Way, to:O, execute:O, the:O, batch:O, script:O, ,:O, and:O, finally:O, ,:O, deleting:O, the:O, batch:O, script: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: 'For exfiltration of stolen data , APT10 used WinRAR and renamed rar.exe” to r.exe” to create archives , upload them with curl.exe” (renamed to c.exe”) , and again , use the cloud storage provider Dropbox .' [/INST] [For:O, exfiltration:O, of:O, stolen:O, data:O, ,:O, APT10:B-HackOrg, used:O, WinRAR:B-Tool, and:O, renamed:O, rar.exe”:B-Tool, to:O, r.exe”:B-Tool, to:O, create:O, archives:O, ,:O, upload:O, them:O, with:O, curl.exe”:O, (renamed:O, to:O, c.exe”):O, ,:O, and:O, again:O, ,:O, use:O, the:O, cloud:O, storage:O, provider:O, Dropbox:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Rapid7 discovered that additional data was placed into the Dropbox accounts under control of the attacker during the compromise and was able to attribute data that was placed into it as being owned by Visma .' [/INST] [Rapid7:B-SecTeam, discovered:O, that:O, additional:O, data:O, was:O, placed:O, into:O, the:O, Dropbox:O, accounts:O, under:O, control:O, of:O, the:O, attacker:B-HackOrg, during:O, the:O, compromise:O, and:O, was:O, able:O, to:O, attribute:B-Way, data:I-Way, that:O, was:O, placed:O, into:O, it:O, as:O, being:O, owned:O, by:O, Visma: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 on the Visma network , APT10 attackers used the Microsoft BITSAdmin CLI tool to copy malicious tools from a suspected attacker-controlled C2 hosted on 173.254.236[.]158 to the \ProgramData\temp\ directory on the infected host .' [/INST] [Once:O, on:O, the:O, Visma:B-Tool, network:I-Tool, ,:O, APT10:B-HackOrg, attackers:O, used:O, the:O, Microsoft:O, BITSAdmin:B-Tool, CLI:O, tool:O, to:O, copy:O, malicious:O, tools:O, from:O, a:O, suspected:O, attacker-controlled:O, C2:O, hosted:O, on:O, 173.254.236[.]158:O, to:O, the:O, \ProgramData\temp\:O, directory:O, on:O, the:O, infected:O, host: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: 'Rapid7 then provided a breach notification to Visma to alert them to this compromise in September 2018 .' [/INST] [Rapid7:B-SecTeam, then:O, provided:O, a:O, breach:O, notification:O, to:O, Visma:O, to:O, alert:O, them:O, to:O, this:O, compromise:O, in:O, September:B-Time, 2018:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We believe APT10 is the most significant known Chinese state-sponsored cyber threat to global corporations .' [/INST] [We:O, believe:O, APT10:B-HackOrg, is:O, the:O, most:O, significant:O, known:O, Chinese:B-Area, state-sponsored:O, cyber:O, threat:O, to:O, global:O, corporations: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: 'APT10's unprecedented campaign against MSPs , alleged to have included some of the largest MSPs in the world , in order to conduct secondary attacks against their clients , grants the Chinese state the ability to potentially access the networks of hundreds (if not thousands) of corporations around the world .' [/INST] [APT10's:B-HackOrg, unprecedented:O, campaign:O, against:O, MSPs:B-Org, ,:O, alleged:O, to:O, have:O, included:O, some:O, of:O, the:O, largest:O, MSPs:O, in:O, the:O, world:O, ,:O, in:O, order:O, to:O, conduct:B-Purp, secondary:O, attacks:O, against:O, their:O, clients:O, ,:O, grants:B-Purp, the:O, Chinese:O, state:O, the:O, ability:O, to:O, potentially:O, access:O, the:O, networks:O, of:O, hundreds:O, (if:O, not:O, thousands):O, of:O, corporations:O, around:O, the:O, world:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This campaign brings to light further evidence supporting the assertions made by the Five Eyes nations , led by the U.S Department of Justice indictment against APT10 actors outlining the unprecedented scale of economic cyberespionage being conducted by the Chinese Ministry of State Security .' [/INST] [This:O, campaign:O, brings:O, to:O, light:O, further:O, evidence:O, supporting:O, the:O, assertions:O, made:O, by:O, the:O, Five:O, Eyes:O, nations:O, ,:O, led:O, by:O, the:O, U.S:O, Department:O, of:O, Justice:O, indictment:O, against:O, APT10:B-HackOrg, actors:O, outlining:O, the:O, unprecedented:O, scale:O, of:O, economic:B-Idus, cyberespionage:O, being:O, conducted:O, by:O, the:O, Chinese:O, Ministry:O, of:O, State:O, Security: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 report , alongside the plethora of other reporting on APT10 operations , acutely highlights the vulnerability of organizational supply chains .' [/INST] [This:O, report:O, ,:O, alongside:O, the:O, plethora:O, of:O, other:O, reporting:O, on:O, APT10:B-HackOrg, operations:O, ,:O, acutely:O, highlights:B-Way, the:O, vulnerability:O, of:O, organizational:O, supply:O, chains:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We believe the groups moved to use CVE-2018-0798 instead of the other Microsoft Equation Editor Remote Code Execution (RCE) vulnerabilities because the former is more reliable as it works on all known versions of Equation Editor .' [/INST] [We:O, believe:O, the:O, groups:B-HackOrg, moved:O, to:O, use:O, CVE-2018-0798:B-Exp, instead:O, of:O, the:O, other:O, Microsoft:O, Equation:O, Editor:O, Remote:O, Code:O, Execution:O, (RCE):O, vulnerabilities:O, because:O, the:O, former:O, is:O, more:O, reliable:O, as:O, it:O, works:O, on:O, all:O, known:O, versions:O, of:O, Equation:O, Editor: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 analyzed RTF files share the same object dimension (objw2180\objh300) used to track the RTF weaponizer in our previous report , however , the sample was not exploiting CVE-2017-11882 or CVE-2018-0802 .' [/INST] [The:O, analyzed:O, RTF:O, files:O, share:O, the:O, same:O, object:O, dimension:O, (objw2180\objh300):O, used:O, to:O, track:O, the:O, RTF:O, weaponizer:O, in:O, our:O, previous:O, report:O, ,:O, however:O, ,:O, the:O, sample:B-SamFile, was:O, not:O, exploiting:O, CVE-2017-11882:B-Exp, or:O, CVE-2018-0802:B-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'After further analysis , it was discovered that the RTF files were exploiting the CVE-2018-0798 vulnerability in Microsoft’s Equation Editor (EQNEDT32) .' [/INST] [After:O, further:O, analysis:O, ,:O, it:O, was:O, discovered:O, that:O, the:O, RTF:B-SamFile, files:I-SamFile, were:O, exploiting:O, the:O, CVE-2018-0798:B-Exp, vulnerability:O, in:O, Microsoft’s:O, Equation:O, Editor:O, (EQNEDT32):O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Anomali Researchers were able to identify multiple samples of malicious RTF documents ITW using the same exploit for CVE-2018-0798 .' [/INST] [Anomali:B-SecTeam, Researchers:O, were:O, able:O, to:O, identify:O, multiple:O, samples:O, of:O, malicious:O, RTF:O, documents:O, ITW:B-SamFile, using:O, the:O, same:O, exploit:O, for:O, CVE-2018-0798:B-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The earliest use of the exploit ITW we were able to identify and confirm is a sample (e228045ef57fb8cc1226b62ada7eee9b) dating back to October 2018 (VirusTotal submission of 2018-10-29) with the RTF creation time 2018-10-23 .' [/INST] [The:O, earliest:O, use:O, of:O, the:O, exploit:O, ITW:B-SamFile, we:O, were:O, able:O, to:O, identify:O, and:O, confirm:O, is:O, a:O, sample:O, (e228045ef57fb8cc1226b62ada7eee9b):O, dating:O, back:O, to:O, October:B-Time, 2018:I-Time, (VirusTotal:O, submission:O, of:O, 2018-10-29):O, with:O, the:O, RTF:B-SamFile, creation:O, time:O, 2018-10-23:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'CVE-2018-0798 is an RCE vulnerability , a stack buffer overflow that can be exploited by a threat actor to perform stack corruption .' [/INST] [CVE-2018-0798:B-Exp, is:O, an:O, RCE:O, vulnerability:O, ,:O, a:O, stack:O, buffer:O, overflow:O, that:O, can:O, be:O, exploited:O, by:O, a:O, threat:B-HackOrg, actor:I-HackOrg, to:O, perform:O, stack:O, corruption: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 observed previously with CVE-2017-11882 and CVE-2018-0802 , the weaponizer was used exclusively by Chinese cyber espionage actors for approximately one year December 2017 through December 2018 , after which cybercrime actors began to incorporate it in their malicious activity .' [/INST] [As:O, observed:O, previously:O, with:O, CVE-2017-11882:B-Exp, and:O, CVE-2018-0802:B-Exp, ,:O, the:O, weaponizer:B-Tool, was:O, used:O, exclusively:O, by:O, Chinese:O, cyber:O, espionage:O, actors:B-HackOrg, for:O, approximately:O, one:O, year:O, December:B-Time, 2017:I-Time, through:O, December:B-Time, 2018:I-Time, ,:O, after:O, which:O, cybercrime:O, actors:O, began:O, to:O, incorporate:O, it:O, in:O, their:O, malicious:O, activity:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Upon decrypting and executing , it drops two additional files wsc_proxy.exe” (legitimate Avast executable) and a malicious DLL wsc.dll” in the %TEMP% folder .' [/INST] [Upon:O, decrypting:O, and:O, executing:O, ,:O, it:O, drops:O, two:O, additional:O, files:O, wsc_proxy.exe”:B-SamFile, (legitimate:O, Avast:O, executable):O, and:O, a:O, malicious:O, DLL:O, wsc.dll”:B-SamFile, in:O, the:O, %TEMP%:O, folder:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , Beginning on 25 June 2019 , we started observing multiple commodity campaigns Mostly dropping AsyncRAT using the updated RTF weaponizer with the same exploit (CVE-2018-0798) .' [/INST] [However:O, ,:O, Beginning:O, on:O, 25:O, June:O, 2019:O, ,:O, we:B-SecTeam, started:O, observing:O, multiple:O, commodity:O, campaigns:O, Mostly:O, dropping:O, AsyncRAT:B-SamFile, using:O, the:O, updated:O, RTF:O, weaponizer:O, with:O, the:O, same:O, exploit:O, (CVE-2018-0798):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 the Royal Road weaponizer has resulted in the discovery that multiple Chinese threat groups started utilizing CVE-2018-0798 in their RTF weaponizer .' [/INST] [Analysis:O, of:O, the:O, Royal:O, Road:O, weaponizer:O, has:O, resulted:O, in:O, the:O, discovery:O, that:O, multiple:O, Chinese:O, threat:B-HackOrg, groups:I-HackOrg, started:O, utilizing:O, CVE-2018-0798:B-Exp, in:O, their:O, RTF:B-Tool, weaponizer:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'These findings also suggest that the threat groups have robust exploit developing capabilities because CVE-2018-0798 is not widely reported on and it is typically not incorporated into publicly available weaponizers .' [/INST] [These:O, findings:O, also:O, suggest:O, that:O, the:O, threat:B-HackOrg, groups:I-HackOrg, have:O, robust:O, exploit:O, developing:O, capabilities:O, because:O, CVE-2018-0798:B-Exp, is:O, not:O, widely:O, reported:O, on:O, and:O, it:O, is:O, typically:O, not:O, incorporated:O, into:O, publicly:O, available:O, weaponizers: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 , a current ANY.RUN playback of our observed Elise infection is also available .' [/INST] [In:O, addition:O, ,:O, a:O, current:O, ANY.RUN:B-SamFile, playback:O, of:O, our:O, observed:O, Elise:B-SamFile, infection:O, is:O, also:O, available: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: 'Upon opening of the MS Word document , our embedded file exploits CVE-2017-11882 to drop a malicious fake Norton Security Shell Extension module , 'NavShExt.dll' , which is then injected into iexplore.exe to install the backdoor , begin collection , and activate command and control .' [/INST] [Upon:O, opening:O, of:O, the:O, MS:O, Word:O, document:O, ,:O, our:O, embedded:O, file:O, exploits:O, CVE-2017-11882:B-Exp, to:O, drop:O, a:O, malicious:O, fake:O, Norton:O, Security:O, Shell:O, Extension:O, module:O, ,:O, 'NavShExt.dll':B-SamFile, ,:O, which:O, is:O, then:O, injected:O, into:O, iexplore.exe:B-SamFile, to:O, install:O, the:O, backdoor:O, ,:O, begin:O, collection:O, ,:O, and:O, activate:O, command:O, and:O, control:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Moving through the infection process , NetWitness Endpoint detects the initial exploit CVE-2017-1182 in action as the Microsoft Equation Editor , 'EQNEDT32.exe' , scores high for potentially malicious activity .' [/INST] [Moving:O, through:O, the:O, infection:O, process:O, ,:O, NetWitness:O, Endpoint:O, detects:O, the:O, initial:O, exploit:O, CVE-2017-1182:B-Exp, in:O, action:O, as:O, the:O, Microsoft:B-SamFile, Equation:I-SamFile, Editor:I-SamFile, ,:O, 'EQNEDT32.exe':B-SamFile, ,:O, scores:O, high:O, for:O, potentially:O, malicious:O, activity:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Most recently though , a new campaign , targeting Belarus , Turkey and Ukraine , has emerged that caught the attention of Check Point researchers .' [/INST] [Most:O, recently:O, though:O, ,:O, a:O, new:O, campaign:B-OffAct, ,:O, targeting:O, Belarus:B-Area, ,:O, Turkey:B-Area, and:O, Ukraine:B-Area, ,:O, has:O, emerged:O, that:O, caught:O, the:O, attention:O, of:O, Check:B-SecTeam, Point:I-SecTeam, researchers: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 well-crafted and socially engineered malicious documents then become the first stage of a long and mainly fileless infection chain that eventually delivers POWERSTATS , a signature PowerShell backdoor of this threat group .' [/INST] [The:O, well-crafted:O, and:O, socially:O, engineered:O, malicious:O, documents:O, then:O, become:O, the:O, first:O, stage:O, of:O, a:O, long:O, and:O, mainly:O, fileless:O, infection:O, chain:O, that:O, eventually:O, delivers:O, POWERSTATS:B-SamFile, ,:O, a:O, signature:O, PowerShell:B-SamFile, backdoor:I-SamFile, of:O, this:O, threat:B-HackOrg, group:I-HackOrg, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This powerful backdoor can receive commands from the attackers , enabling it to exfiltrate files from the system it is running on , execute additional scripts , delete files , and more .' [/INST] [This:O, powerful:O, backdoor:B-SamFile, can:O, receive:O, commands:O, from:O, the:O, attackers:O, ,:O, enabling:O, it:O, to:O, exfiltrate:B-Features, files:I-Features, from:O, the:O, system:O, it:O, is:O, running:O, on:O, ,:O, execute:B-Features, additional:I-Features, scripts:I-Features, ,:O, delete:B-Features, files:I-Features, ,:O, and:O, more:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'If the macros in SPK KANUN DEĞİŞİKLİĞİ GİB GÖRÜŞÜ.doc” are enabled , an embedded payload is decoded and saved in the %APPDATA% directory with the name CiscoAny.exe” .' [/INST] [If:O, the:O, macros:O, in:O, SPK:B-SamFile, KANUN:I-SamFile, DEĞİŞİKLİĞİ:O, GİB:O, GÖRÜŞÜ.doc”:O, are:O, enabled:O, ,:O, an:O, embedded:O, payload:O, is:O, decoded:O, and:O, saved:O, in:O, the:O, %APPDATA%:O, directory:O, with:O, the:O, name:O, CiscoAny.exe”:B-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'INF files have been used in the past by MuddyWater , although they were launched using Advpack.dll and not IEAdvpack.dll .' [/INST] [INF:B-Tool, files:I-Tool, have:O, been:O, used:O, in:O, the:O, past:O, by:O, MuddyWater:B-HackOrg, ,:O, although:O, they:O, were:O, launched:O, using:O, Advpack.dll:B-Tool, and:O, not:O, IEAdvpack.dll:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In addition , by using VBA2Graph , we were able to visualize the VBA call graph in the macros of each document .' [/INST] [In:O, addition:O, ,:O, by:O, using:O, VBA2Graph:B-SamFile, ,:O, we:O, were:O, able:O, to:O, visualize:O, the:O, VBA:O, call:B-Features, graph:I-Features, in:O, the:O, macros:O, of:O, each:O, document: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: 'Although it has focused most of its efforts on the Middle East region , the political affiliations , motives and purposes behind MuddyWater’s attacks are not very well- defined , thus earning it its name .' [/INST] [Although:O, it:O, has:O, focused:O, most:O, of:O, its:O, efforts:O, on:O, the:O, Middle:B-Area, East:I-Area, region:O, ,:O, the:O, political:O, affiliations:O, ,:O, motives:O, and:O, purposes:O, behind:O, MuddyWater’s:B-HackOrg, attacks:O, are:O, not:O, very:O, well-:O, defined:O, ,:O, thus:O, earning:O, it:O, its:O, name:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In the past , countries such as Saudi Arabia , the UAE and Turkey have been a MuddyWater's main target , but the campaigns have also reached a much wider audience , making their way to victims in countries such as Belarus and Ukraine .' [/INST] [In:O, the:O, past:O, ,:O, countries:O, such:O, as:O, Saudi:B-Area, Arabia:I-Area, ,:O, the:O, UAE:B-Area, and:O, Turkey:B-Area, have:O, been:O, a:O, MuddyWater's:B-HackOrg, main:O, target:O, ,:O, but:O, the:O, campaigns:O, have:O, also:O, reached:O, a:O, much:O, wider:O, audience:O, ,:O, making:O, their:O, way:O, to:O, victims:O, in:O, countries:O, such:O, as:O, Belarus:B-Area, and:O, Ukraine:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'MuddyWater target groups across Middle East and Central Asia , primarily using spear phishing emails with malicious attachments .' [/INST] [MuddyWater:B-HackOrg, target:O, groups:O, across:O, Middle:B-Area, East:I-Area, and:O, Central:B-Area, Asia:I-Area, ,:O, primarily:O, using:O, spear:B-Way, phishing:I-Way, emails:O, with:O, malicious:O, attachments:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Most recently MuddyWater were connected to a campaign in March that targeted organizations in Turkey , Pakistan , and Tajikistan .' [/INST] [Most:O, recently:O, MuddyWater:B-HackOrg, were:O, connected:O, to:O, a:O, campaign:O, in:O, March:O, that:O, targeted:O, organizations:O, in:O, Turkey:B-Area, ,:O, Pakistan:B-Area, ,:O, and:O, Tajikistan:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The group has been quite visible since the initial 2017 Malwarebytes report on their elaborate espionage attack against the Saudi Arabian government .' [/INST] [The:O, group:B-HackOrg, has:O, been:O, quite:O, visible:O, since:O, the:O, initial:O, 2017:B-Time, Malwarebytes:O, report:O, on:O, their:O, elaborate:O, espionage:O, attack:O, against:O, the:O, Saudi:B-Area, Arabian:I-Area, government: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: 'Our analysis revealed that they drop a new backdoor , which is written in PowerShell as MuddyWater’s known POWERSTATS backdoor .' [/INST] [Our:O, analysis:O, revealed:O, that:O, they:O, drop:O, a:O, new:O, backdoor:O, ,:O, which:O, is:O, written:O, in:O, PowerShell:O, as:O, MuddyWater’s:B-HackOrg, known:O, POWERSTATS:B-Tool, backdoor:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We assume that RunPow stands for run PowerShell , ” and triggers the PowerShell code embedded inside the .dll file .' [/INST] [We:O, assume:O, that:O, RunPow:O, stands:O, for:O, run:O, PowerShell:B-SamFile, ,:O, ”:O, and:O, triggers:O, the:O, PowerShell:O, code:O, embedded:O, inside:O, the:O, .dll:B-SamFile, file:I-SamFile, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This backdoor has some features similar to a previously discovered version of the Muddywater backdoor .' [/INST] [This:O, backdoor:B-Tool, has:O, some:O, features:O, similar:O, to:O, a:O, previously:O, discovered:O, version:O, of:O, the:O, Muddywater:B-HackOrg, backdoor:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Based on our analysis , we can confirm that MuddyWater target Turkish government organizations related to the finance and energy sectors .' [/INST] [Based:O, on:O, our:O, analysis:O, ,:O, we:O, can:O, confirm:O, that:O, MuddyWater:B-HackOrg, target:O, Turkish:B-Idus, government:I-Idus, organizations:I-Idus, related:O, to:O, the:O, finance:B-Idus, and:O, energy:B-Idus, sectors:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This is yet another similarity with previous MuddyWater campaigns , which were known to have targeted multiple Turkish government entities .' [/INST] [This:O, is:O, yet:O, another:O, similarity:O, with:O, previous:O, MuddyWater:B-HackOrg, campaigns:O, ,:O, which:O, were:O, known:O, to:O, have:O, targeted:O, multiple:O, Turkish:B-Area, government:O, entities: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 main delivery method of this type of backdoor is spear phishing emails or spam that uses social engineering to manipulate targets into enabling malicious documents .' [/INST] [The:O, main:O, delivery:O, method:O, of:O, this:O, type:O, of:O, backdoor:B-SamFile, is:O, spear:B-Way, phishing:B-Way, emails:O, or:O, spam:B-Way, that:O, uses:O, social:O, engineering:O, to:O, manipulate:O, targets:O, into:O, enabling:O, malicious:O, documents: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: 'Trend Micro™ Deep Discovery™ provides detection , in-depth analysis , and proactive response to today’s stealthy malware , and targeted attacks in real time .' [/INST] [Trend:B-SecTeam, Micro™:I-SecTeam, Deep:O, Discovery™:O, provides:O, detection:O, ,:O, in-depth:O, analysis:O, ,:O, and:O, proactive:O, response:O, to:O, today’s:O, stealthy:O, malware:O, ,:O, and:O, targeted:O, attacks:B-HackOrg, in:O, real:O, time:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'MuddyWater first surfaced in 2017 .' [/INST] [MuddyWater:B-HackOrg, first:O, surfaced:O, in:O, 2017:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'First stage infections and graphical decoys have been described by multiple sources , including in our previous research MuddyWater expands operations .' [/INST] [First:O, stage:O, infections:O, and:O, graphical:O, decoys:O, have:O, been:O, described:O, by:O, multiple:O, sources:O, ,:O, including:O, in:O, our:O, previous:O, research:O, MuddyWater:B-HackOrg, expands:B-OffAct, operations:I-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'MuddyWater compiles various offensive Python scripts .' [/INST] [MuddyWater:B-HackOrg, compiles:O, various:O, offensive:O, Python:B-Tool, scripts:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'This includes Python scripts .' [/INST] [This:O, includes:O, Python:O, scripts: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: 'Usually , the Stageless Meterpreter has the Ext_server_stdapi.x64.dll” , Ext_server_extapi.x64.dll” , and Ext_server_espia.x64.dll” extensions .' [/INST] [Usually:O, ,:O, the:O, Stageless:B-SamFile, Meterpreter:I-SamFile, has:O, the:O, Ext_server_stdapi.x64.dll”:B-SamFile, ,:O, Ext_server_extapi.x64.dll”:B-SamFile, ,:O, and:O, Ext_server_espia.x64.dll”:B-SamFile, extensions: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 January 2017 report followed up on other private reports published on the group’s BeEF-related activity in 2015 and 2016 .' [/INST] [The:O, January:B-Time, 2017:I-Time, report:O, followed:O, up:O, on:O, other:O, private:O, reports:O, published:O, on:O, the:O, group’s:O, BeEF-related:B-HackOrg, activity:O, in:O, 2015:B-Time, and:O, 2016:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Previous analysis of the NewsBeef APT indicates that the group focuses on Saudi Arabian (SA) and Western targets , and lacks advanced offensive technology development capabilities .' [/INST] [Previous:O, analysis:O, of:O, the:O, NewsBeef:B-HackOrg, APT:O, indicates:O, that:O, the:O, group:O, focuses:O, on:O, Saudi:B-Area, Arabian:I-Area, (SA):O, and:O, Western:B-Area, targets:O, ,:O, and:O, lacks:O, advanced:O, offensive:O, technology:O, development:O, capabilities:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , in the summer of 2016 , NewsBeef deployed a new toolset that includes macro-enabled Office documents , PowerSploit , and the Pupy backdoor .' [/INST] [However:O, ,:O, in:O, the:O, summer:O, of:O, 2016:B-Time, ,:O, NewsBeef:B-HackOrg, deployed:O, a:O, new:O, toolset:O, that:O, includes:O, macro-enabled:B-Tool, Office:I-Tool, documents:I-Tool, ,:O, PowerSploit:B-Tool, ,:O, and:O, the:O, Pupy:B-Tool, backdoor:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The most recent NewsBeef campaign uses this toolset in conjunction with spearphishing emails , links sent over social media/standalone private messaging applications , and watering hole attacks that leverage compromised high-profile websites some belonging to the SA government .' [/INST] [The:O, most:O, recent:O, NewsBeef:B-HackOrg, campaign:O, uses:O, this:O, toolset:O, in:O, conjunction:O, with:O, spearphishing:B-Way, emails:O, ,:O, links:O, sent:O, over:O, social:B-Way, media/standalone:I-Way, private:B-Way, messaging:I-Way, applications:I-Way, ,:O, and:O, watering:B-Way, hole:I-Way, attacks:O, that:O, leverage:O, compromised:O, high-profile:O, websites:O, some:O, belonging:O, to:O, the:O, SA:O, government: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 NewsBeef actor deployed a new toolset in a campaign that focused primarily on Saudi Arabian targets .' [/INST] [The:O, NewsBeef:B-HackOrg, actor:O, deployed:O, a:O, new:O, toolset:O, in:O, a:O, campaign:O, that:O, focused:O, primarily:O, on:O, Saudi:B-Area, Arabian:I-Area, targets:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'NewsBeef continues to deploy malicious macro-enabled Office documents , poisoned legitimate Flash and Chrome installers , PowerSploit , and Pupy tools .' [/INST] [NewsBeef:B-HackOrg, continues:O, to:O, deploy:O, malicious:O, macro-enabled:O, Office:O, documents:O, ,:O, poisoned:O, legitimate:O, Flash:B-Tool, and:O, Chrome:B-Tool, installers:I-Tool, ,:O, PowerSploit:B-Tool, ,:O, and:O, Pupy:B-Tool, tools:I-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The NewsBeef campaign is divided into two main attack vectors , spearphishing and strategic web compromise watering hole attacks .' [/INST] [The:O, NewsBeef:B-HackOrg, campaign:O, is:O, divided:O, into:O, two:O, main:O, attack:O, vectors:O, ,:O, spearphishing:B-Way, and:O, strategic:B-Way, web:I-Way, compromise:I-Way, watering:B-Way, hole:I-Way, attacks:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'On December 25 , 2016 , the NewsBeef APT stood up a server to host a new set of Microsoft Office documents (maintaining malicious macros and PowerShell scripts) to support its spear-phishing operations .' [/INST] [On:O, December:B-Time, 25:B-Time, ,:O, 2016:B-Time, ,:O, the:O, NewsBeef:B-HackOrg, APT:O, stood:O, up:O, a:O, server:O, to:O, host:O, a:O, new:O, set:O, of:O, Microsoft:O, Office:O, documents:O, (maintaining:O, malicious:O, macros:O, and:O, PowerShell:O, scripts):O, to:O, support:O, its:O, spear-phishing:B-Way, 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: 'These compromised servers include Saudi Arabian government servers and other high-value organizational identities relevant to NewsBeef's targets .' [/INST] [These:O, compromised:O, servers:O, include:O, Saudi:B-Area, Arabian:I-Area, government:O, servers:O, and:O, other:O, high-value:O, organizational:O, identities:O, relevant:O, to:O, NewsBeef's:B-HackOrg, targets:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , Kaspersky Security Network (KSN) records also contain links that victims clicked from the Outlook web client outlook.live.com” as well as attachments arriving through the Outlook desktop application .' [/INST] [However:O, ,:O, Kaspersky:B-SecTeam, Security:O, Network:O, (KSN):O, records:O, also:O, contain:O, links:O, that:O, victims:O, clicked:O, from:O, the:O, Outlook:O, web:O, client:O, outlook.live.com”:B-SamFile, as:O, well:O, as:O, attachments:O, arriving:O, through:O, the:O, Outlook:O, desktop:O, application: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: 'Interestingly , NewsBeef set up its server using the hosting provider Choopa , LLC , US” , the same hosting provider that the group used in attacks over the summer of 2016 .' [/INST] [Interestingly:O, ,:O, NewsBeef:B-HackOrg, set:O, up:O, its:O, server:O, using:O, the:O, hosting:O, provider:O, Choopa:B-Tool, ,:O, LLC:B-Tool, ,:O, US”:B-Tool, ,:O, the:O, same:O, hosting:O, provider:O, that:O, the:O, group:O, used:O, in:O, attacks:O, over:O, the:O, summer:B-Time, of:I-Time, 2016:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'NTG’s IT focus and client list likely aided NewsBeef’s delivery of malicious PowerShell-enabled Office documents and poisoned installers .' [/INST] [NTG’s:B-Org, IT:O, focus:O, and:O, client:O, list:O, likely:O, aided:O, NewsBeef’s:B-HackOrg, delivery:O, of:O, malicious:O, PowerShell-enabled:O, Office:O, documents:O, and:O, poisoned:O, installers: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 other schemes , NewsBeef sent macro-enabled Office attachments from spoofed law firm identities or other relevant service providers to targets in SA .' [/INST] [In:O, other:O, schemes:O, ,:O, NewsBeef:B-HackOrg, sent:O, macro-enabled:O, Office:O, attachments:O, from:O, spoofed:O, law:O, firm:O, identities:O, or:O, other:O, relevant:O, service:O, providers:O, to:O, targets:O, in:O, SA:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The law firm in this scheme is based in the United Kingdom and is the sole location for targets outside of SA for this campaign .' [/INST] [The:O, law:O, firm:O, in:O, this:O, scheme:O, is:O, based:O, in:O, the:O, United:B-Area, Kingdom:I-Area, and:O, is:O, the:O, sole:O, location:O, for:O, targets:B-HackOrg, outside:O, of:O, SA:B-Area, for:O, this:O, campaign: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: 'Starting in October 2016 , NewsBeef compromised a set of legitimate servers (shown below) , and injected JavaScript to redirect visitors to http://analytics-google.org:69/Check.aspx .' [/INST] [Starting:O, in:O, October:B-Time, 2016:I-Time, ,:O, NewsBeef:B-HackOrg, compromised:O, a:O, set:O, of:O, legitimate:O, servers:O, (shown:O, below):O, ,:O, and:O, injected:O, JavaScript:O, to:O, redirect:O, visitors:O, to:O, http://analytics-google.org:69/Check.aspx: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: 'For example , on a Saudi government website , the NewsBeef APT delivered packed JavaScript into the bottom of a referenced script that is included in every page served from the site the packed and unpacked JavaScript is shown below .' [/INST] [For:O, example:O, ,:O, on:O, a:O, Saudi:B-Area, government:O, website:O, ,:O, the:O, NewsBeef:B-HackOrg, APT:O, delivered:O, packed:O, JavaScript:O, into:O, the:O, bottom:O, of:O, a:O, referenced:O, script:O, that:O, is:O, included:O, in:O, every:O, page:O, served:O, from:O, the:O, site:O, the:O, packed:O, and:O, unpacked:O, JavaScript:B-Tool, is:O, shown:O, below: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 JavaScript forces visiting web browsers to collect and send (via a POST request) web browser , browser version , country of origin , and IP address data to the attacker controlled server jquerycodedownload.live/check.aspx” .' [/INST] [The:O, JavaScript:B-SamFile, forces:B-Features, visiting:O, web:O, browsers:O, to:O, collect:B-Features, and:O, send:O, (via:O, a:O, POST:O, request):O, web:O, browser:O, ,:O, browser:O, version:O, ,:O, country:O, of:O, origin:O, ,:O, and:O, IP:O, address:O, data:O, to:O, the:O, attacker:O, controlled:O, server:O, jquerycodedownload.live/check.aspx”: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: 'A high volume of redirections from the compromised site continues into mid-January 2017 .' [/INST] [A:O, high:O, volume:O, of:O, redirections:B-HackOrg, from:O, the:O, compromised:O, site:O, continues:O, into:O, mid-January:B-Time, 2017:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'However , as this recent campaign indicates , the NewsBeef APT appears to have shifted its intrusion toolset away from BeEF and towards macro-enabled malicious Office documents , PowerSploit , and Pupy .' [/INST] [However:O, ,:O, as:O, this:O, recent:O, campaign:O, indicates:O, ,:O, the:O, NewsBeef:B-HackOrg, APT:O, appears:O, to:O, have:O, shifted:O, its:O, intrusion:O, toolset:O, away:O, from:O, BeEF:O, and:O, towards:O, macro-enabled:O, malicious:O, Office:B-Tool, documents:I-Tool, ,:O, PowerSploit:B-Tool, ,:O, and:O, Pupy:B-Tool, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Despite this shift in toolset , the group still relies on old infrastructure as evidenced by their reuse of servers hosted by the service providers Choopa and Atlantic.net .' [/INST] [Despite:O, this:O, shift:O, in:O, toolset:O, ,:O, the:O, group:O, still:O, relies:O, on:O, old:O, infrastructure:O, as:O, evidenced:O, by:O, their:O, reuse:O, of:O, servers:O, hosted:O, by:O, the:O, service:O, providers:O, Choopa:O, and:O, Atlantic.net: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: 'Its attack activities can be traced back to April 2012 .' [/INST] [Its:O, attack:B-OffAct, activities:I-OffAct, can:O, be:O, traced:O, back:O, to:O, April:B-Time, 2012:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The OceanLotus reflects a very strong confrontational ability and willing to attack by keep evolving their techniques .' [/INST] [The:O, OceanLotus:B-HackOrg, reflects:B-Way, a:O, very:O, strong:O, confrontational:O, ability:O, and:O, willing:O, to:O, attack:O, by:O, keep:O, evolving:O, their:O, techniques: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 APT attacks and adopting confrontation measures will exist for a long time .' [/INST] [These:O, APT:B-HackOrg, attacks:O, and:O, adopting:B-Org, confrontation:I-Org, measures:I-Org, will:O, exist:O, for:O, a:O, long:O, time:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'OceanLotus’ targets are global .' [/INST] [OceanLotus’:B-HackOrg, targets:O, are:O, global:B-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'OceanLotus have been actively using since at least early 2018 .' [/INST] [OceanLotus:B-HackOrg, have:O, been:O, actively:O, using:O, since:O, at:O, least:O, early:B-Time, 2018:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'OceanLotus malware family samples used no earlier than 2017 .' [/INST] [OceanLotus:B-HackOrg, malware:O, family:O, samples:O, used:O, no:O, earlier:O, than:O, 2017:B-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'We identified two methods to deliver the KerrDown downloader to targets .' [/INST] [We:B-SecTeam, identified:O, two:O, methods:O, to:O, deliver:O, the:O, KerrDown:B-SamFile, downloader:O, to:O, targets:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The link to the final payload of KerrDown was still active during the time of analysis and hence we were able to download a copy which turned out to be a variant of Cobalt Strike Beacon .' [/INST] [The:O, link:O, to:O, the:O, final:O, payload:O, of:O, KerrDown:B-SamFile, was:O, still:O, active:O, during:O, the:O, time:O, of:O, analysis:O, and:O, hence:O, we:B-SecTeam, were:O, able:O, to:O, download:O, a:O, copy:O, which:O, turned:O, out:O, to:O, be:O, a:O, variant:O, of:O, Cobalt:O, Strike:O, Beacon: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 investigating KerrDown we found multiple RAR files containing a variant of the malware .' [/INST] [While:O, investigating:O, KerrDown:B-SamFile, we:B-SecTeam, found:O, multiple:O, RAR:O, files:O, containing:O, a:O, variant:O, of:O, the: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: 'Therefore , it is clear that the OceanLotus group works during weekdays and takes a break during the weekends .' [/INST] [Therefore:O, ,:O, it:O, is:O, clear:O, that:O, the:O, OceanLotus:B-HackOrg, group:O, works:O, during:O, weekdays:B-Time, and:O, takes:O, a:O, break:O, during:O, the:O, weekends:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The group was first revealed and named by SkyEye Team in May 2015 .' [/INST] [The:O, group:B-HackOrg, was:O, first:O, revealed:O, and:O, named:O, by:O, SkyEye:O, Team:O, in:O, May:B-Time, 2015:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'OceanLotus's targets include China's maritime institutions , maritime construction , scientific research institutes and shipping enterprises .' [/INST] [OceanLotus's:B-HackOrg, targets:O, include:O, China's:O, maritime:B-Org, institutions:I-Org, ,:O, maritime:B-Org, construction:I-Org, ,:O, scientific:B-Org, research:I-Org, institutes:I-Org, and:O, shipping:B-Org, enterprises:I-Org, .:O] </s> |
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