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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: 'Therefore , the Stuxnet MOF file creation tool that the Shadow Brokers dropped on Friday is possibly the earliest technical evidence that NSA hackers and developers coded Stuxnet , as many suspect .' [/INST] [Therefore:O, ,:O, the:O, Stuxnet:B-Tool, MOF:I-Tool, file:O, creation:O, tool:O, that:O, the:O, Shadow:O, Brokers:O, dropped:O, on:O, Friday:O, is:O, possibly:O, the:O, earliest:O, technical:O, evidence:O, that:O, NSA:B-Org, hackers:O, and:O, developers:O, coded:O, Stuxnet:B-Tool, ,:O, as:O, many:O, suspect:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Of course , it 's also possible that whatever group The Shadow Brokers have exposed simply gained access to the Stuxnet tools secondhand , and reused them .' [/INST] [Of:O, course:O, ,:O, it:O, 's:O, also:O, possible:O, that:O, whatever:O, group:O, The:O, Shadow:O, Brokers:O, have:O, exposed:O, simply:O, gained:O, access:O, to:O, the:O, Stuxnet:B-Tool, tools:I-Tool, secondhand:O, ,:O, and:O, reused:O, them:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'That post included download links for a slew of NSA hacking tools and exploits , many of which could be used to break into hardware firewall appliances , and in turn , corporate or government networks .' [/INST] [That:O, post:O, included:O, download:O, links:O, for:O, a:O, slew:O, of:O, NSA:B-Org, hacking:O, tools:O, and:O, exploits:O, ,:O, many:O, of:O, which:O, could:O, be:O, used:O, to:O, break:B-Features, into:I-Features, hardware:I-Features, firewall:I-Features, appliances:I-Features, ,:O, and:O, in:O, turn:O, ,:O, corporate:B-Features, or:I-Features, government:I-Features, networks:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Some hackers even went onto use the Cisco exploits in the wild .' [/INST] [Some:O, hackers:O, even:O, went:O, onto:O, use:O, the:O, Cisco:B-Exp, exploits:I-Exp, in:O, the:O, wild:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'DanderSpritz consists entirely of plugins to gather intelligence , use exploits and examine already controlled machines .' [/INST] [DanderSpritz:B-Tool, consists:O, entirely:O, of:O, plugins:O, to:O, gather:B-Features, intelligence:I-Features, ,:O, use:B-Features, exploits:I-Features, and:O, examine:B-Features, already:I-Features, controlled:I-Features, machines:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'DanderSpritz consists entirely of plugins to gather intelligence , use exploits and examine already controlled machines .' [/INST] [DanderSpritz:B-Tool, consists:O, entirely:O, of:O, plugins:O, to:O, gather:B-Features, intelligence:I-Features, ,:O, use:B-Features, exploits:I-Features, and:O, examine:B-Features, already:I-Features, controlled:I-Features, machines:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'DarkPulsar is a very interesting administrative module for controlling a passive backdoor named ' sipauth32.tsp ' that provides remote control , belonging to this category .' [/INST] [DarkPulsar:B-Tool, is:O, a:O, very:O, interesting:O, administrative:O, module:O, for:O, controlling:O, a:O, passive:O, backdoor:B-Tool, named:O, ':O, sipauth32.tsp:B-SamFile, ':O, that:O, provides:B-Purp, remote:I-Purp, control:I-Purp, ,:O, belonging:O, to:O, this:O, category:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'DanderSpritz is the framework for controlling infected machines , different from FuZZbuNch as the latter provides a limited toolkit for the post-exploitation stage with specific functions such as DisableSecurity and EnableSecurity for DarkPulsar .' [/INST] [DanderSpritz:B-Tool, is:O, the:O, framework:O, for:O, controlling:O, infected:O, machines:O, ,:O, different:O, from:O, FuZZbuNch:B-Tool, as:O, the:O, latter:O, provides:O, a:O, limited:O, toolkit:O, for:O, the:O, post-exploitation:O, stage:O, with:O, specific:O, functions:O, such:O, as:O, DisableSecurity:B-Tool, and:O, EnableSecurity:B-Tool, for:O, DarkPulsar: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: 'PeddleCheap is a plugin of DanderSpritz which can be used to configure implants and connect to infected machines .' [/INST] [PeddleCheap:B-Tool, is:O, a:O, plugin:O, of:O, DanderSpritz:B-Tool, which:O, can:O, be:O, used:O, to:O, configure:B-Features, implants:I-Features, and:O, connect:B-Features, to:I-Features, infected:I-Features, machines:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 FuzzBunch and DanderSpritz frameworks are designed to be flexible and to extend functionality and compatibility with other tools .' [/INST] [The:O, FuzzBunch:B-Tool, and:O, DanderSpritz:B-Tool, frameworks:O, are:O, designed:O, to:O, be:O, flexible:O, and:O, to:O, extend:O, functionality:O, and:O, compatibility:O, with:O, other:O, tools:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Each of them consists of a set of plugins designed for different tasks : while FuzzBunch plugins are responsible for reconnaissance and attacking a victim , plugins in the DanderSpritz framework are developed for managing already infected victims .' [/INST] [Each:O, of:O, them:O, consists:O, of:O, a:O, set:O, of:O, plugins:O, designed:O, for:O, different:O, tasks:O, ::O, while:O, FuzzBunch:B-Tool, plugins:I-Tool, are:O, responsible:O, for:O, reconnaissance:B-Features, and:I-Features, attacking:I-Features, a:I-Features, victim:O, ,:O, plugins:O, in:O, the:O, DanderSpritz:B-Tool, framework:O, are:O, developed:O, for:O, managing:B-Features, already:I-Features, infected:I-Features, victims:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 leaked NSA documents and tools published in recent months by the mysterious Shadow Brokers group have provided rare insight into the clandestine digital espionage operations pursued by the spy agency over the past few years , including information on operations aimed at Iran and Russia .' [/INST] [The:O, leaked:O, NSA:B-Org, documents:O, and:O, tools:O, published:O, in:O, recent:O, months:O, by:O, the:O, mysterious:O, Shadow:O, Brokers:O, group:O, have:O, provided:O, rare:O, insight:O, into:O, the:O, clandestine:O, digital:O, espionage:B-OffAct, operations:I-OffAct, pursued:O, by:O, the:O, spy:B-Org, agency:I-Org, over:O, the:O, past:O, few:O, years:O, ,:O, including:O, information:O, on:O, operations:O, aimed:O, at:O, Iran:B-Area, and:O, Russia: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: 'Yet the document cache published April 8 provides evidence that the NSA had once launched a series of successful computer-based intrusions against multiple high-profile foreign targets , including the Office of the President of Iran and the Russian Federal Nuclear Center .' [/INST] [Yet:O, the:O, document:O, cache:O, published:O, April:O, 8:O, provides:O, evidence:O, that:O, the:O, NSA:B-Org, had:O, once:O, launched:O, a:O, series:O, of:O, successful:O, computer-based:O, intrusions:O, against:O, multiple:O, high-profile:O, foreign:O, targets:O, ,:O, including:O, the:O, Office:O, of:O, the:O, President:O, of:O, Iran:O, and:O, the:O, Russian:B-Area, Federal:I-Idus, Nuclear:I-Idus, Center:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The ShadowBrokers' latest dump of Equation Group hacks focuses on UNIX systems and GSM networks , and was accompanied by an open letter to President Trump .' [/INST] [The:O, ShadowBrokers':O, latest:O, dump:O, of:O, Equation:O, Group:O, hacks:O, focuses:O, on:O, UNIX:O, systems:O, and:O, GSM:O, networks:O, ,:O, and:O, was:O, accompanied:O, by:O, an:O, open:O, letter:O, to:O, President:O, Trump:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Numerous Windows hacking tools are also among the new batch of files the Shadow Brokers dumped Friday .' [/INST] [Numerous:O, Windows:B-Tool, hacking:I-Tool, tools:I-Tool, are:O, also:O, among:O, the:O, new:O, batch:O, of:O, files:O, the:O, Shadow:O, Brokers:O, dumped:O, Friday:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 leaked files show the NSA was allegedly targeting EastNets in Dubai , Belgium , and Egypt .' [/INST] [The:O, leaked:O, files:O, show:O, the:O, NSA:B-Org, was:O, allegedly:O, targeting:O, EastNets:B-Org, in:O, Dubai:O, ,:O, Belgium:O, ,:O, and:O, Egypt:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The files appear to include logs from 2013 that show the NSA was also targeting oil and investment companies across the Middle East .' [/INST] [The:O, files:O, appear:O, to:O, include:O, logs:O, from:O, 2013:B-Time, that:O, show:O, the:O, NSA:B-Org, was:O, also:O, targeting:O, oil:B-Idus, and:O, investment:B-Org, companies:I-Org, across:O, the:O, Middle:B-Area, East:I-Area, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to Kaspersky , the Equation Group has more than 60 members and has been operating since at least 2001 .' [/INST] [According:O, to:O, Kaspersky:B-SecTeam, ,:O, the:O, Equation:O, Group:O, has:O, more:O, than:O, 60:O, members:O, and:O, has:O, been:O, operating:O, since:O, at:O, least:O, 2001: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 existence of the Equation Group was first posited in Feb. 2015 by researchers at Russian security firm Kaspersky Lab , which described it as one of the most sophisticated cyber attack teams in the world .' [/INST] [The:O, existence:O, of:O, the:O, Equation:O, Group:O, was:O, first:O, posited:O, in:O, Feb.:B-Time, 2015:I-Time, by:O, researchers:O, at:O, Russian:B-Area, security:B-Org, firm:I-Org, Kaspersky:B-SecTeam, Lab:I-SecTeam, ,:O, which:O, described:O, it:O, as:O, one:O, of:O, the:O, most:O, sophisticated:O, cyber:B-OffAct, attack:I-OffAct, teams:O, in: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: 'Most of the Equation Group 's targets have been in Iran , Russia , Pakistan , Afghanistan , India , Syria , and Mali .' [/INST] [Most:O, of:O, the:O, Equation:B-HackOrg, Group:I-HackOrg, 's:O, targets:O, have:O, been:O, in:O, Iran:B-Area, ,:O, Russia:B-Area, ,:O, Pakistan:B-Area, ,:O, Afghanistan:B-Area, ,:O, India:B-Area, ,:O, Syria:B-Area, ,:O, and:O, Mali: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: 'According to Wikipedia , the CSS was formed in 1972 to integrate the NSA and the Service Cryptologic Elements ( SCE ) of the U.S armed forces .' [/INST] [According:O, to:O, Wikipedia:O, ,:O, the:O, CSS:O, was:O, formed:O, in:O, 1972:B-Time, to:O, integrate:B-Purp, the:I-Purp, NSA:I-Purp, and:O, the:O, Service:B-Purp, Cryptologic:I-Purp, Elements:I-Purp, (:O, SCE:B-Purp, ):O, of:O, the:O, U.S:O, armed:O, forces:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'KrebsOnSecurity was first made aware of the metadata in the Shadow Brokers leak by Mike Poor , Rob Curtinseufert , and Larry Pesce .' [/INST] [KrebsOnSecurity:B-SecTeam, was:O, first:O, made:O, aware:O, of:O, the:O, metadata:O, in:O, the:O, Shadow:B-HackOrg, Brokers:I-HackOrg, leak:O, by:O, Mike:O, Poor:O, ,:O, Rob:O, Curtinseufert:O, ,:O, and:O, Larry:O, Pesce:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 their latest leak , they have released the UNITEDRAKE NSA exploit , which is a remote access and control tool that can remotely target Windows-based systems to capture desired information and transfer it to a server .' [/INST] [In:O, their:O, latest:O, leak:O, ,:O, they:O, have:O, released:O, the:O, UNITEDRAKE:B-Exp, NSA:I-Exp, exploit:I-Exp, ,:O, which:O, is:O, a:O, remote:O, access:O, and:O, control:O, tool:O, that:O, can:O, remotely:O, target:O, Windows-based:O, systems:O, to:O, capture:B-Features, desired:I-Features, information:I-Features, and:O, transfer:B-Features, it:O, to:O, a: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 ShadowBrokers is a group of hackers known for leaking exclusive information about the National Security Agency – NSA 's hacking tools and tactics .' [/INST] [The:O, ShadowBrokers:B-HackOrg, is:O, a:O, group:O, of:O, hackers:O, known:O, for:O, leaking:O, exclusive:O, information:O, about:O, the:O, National:O, Security:O, Agency:O, –:O, NSA:B-Org, 's:O, hacking:O, tools:O, and:O, tactics:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 captures information using plugins to compromise webcam and microphone output along with documenting log keystrokes , carrying out surveillance and access external drives .' [/INST] [It:O, captures:B-Features, information:I-Features, using:O, plugins:O, to:O, compromise:O, webcam:O, and:O, microphone:O, output:O, along:O, with:O, documenting:O, log:O, keystrokes:O, ,:O, carrying:B-Features, out:I-Features, surveillance:I-Features, and:O, access:B-Features, external:I-Features, drives:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'UNITEDRAKE is described as a , fully extensible , data collection tool that is specifically developed for Windows machines to allow operators the chance of controlling a device completely .' [/INST] [UNITEDRAKE:B-Tool, is:O, described:O, as:O, a:O, ,:O, fully:O, extensible:O, ,:O, data:O, collection:O, tool:O, that:O, is:O, specifically:O, developed:O, for:O, Windows:O, machines:O, to:O, allow:O, operators:O, the:O, chance:O, of:O, controlling:O, a:O, device:O, completely:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the other hand , ShadowBrokers group made headlines in 2016 when it claimed to have robbed various exploitation tools used by the NSA including the notorious ETERNALBLUE that was a vital component in the WannaCry ransomware campaign causing damages to systems worldwide .' [/INST] [On:O, the:O, other:O, hand:O, ,:O, ShadowBrokers:O, group:O, made:O, headlines:O, in:O, 2016:B-Time, when:O, it:O, claimed:O, to:O, have:O, robbed:O, various:O, exploitation:O, tools:O, used:O, by:O, the:O, NSA:B-Org, including:O, the:O, notorious:O, ETERNALBLUE:B-Exp, that:O, was:O, a:O, vital:O, component:O, in:O, the:O, WannaCry:B-OffAct, ransomware:I-OffAct, campaign:I-OffAct, causing:O, damages:O, to:O, systems: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: 'This turned out to be a malicious loader internally named ' Slingshot ' , part of a new , and highly sophisticated attack platform that rivals Project Sauron and Regin in complexity .' [/INST] [This:O, turned:O, out:O, to:O, be:O, a:O, malicious:O, loader:O, internally:O, named:O, ':O, Slingshot:B-Tool, ':O, ,:O, part:O, of:O, a:O, new:O, ,:O, and:O, highly:O, sophisticated:O, attack:B-OffAct, platform:O, that:O, rivals:O, Project:B-Tool, Sauron:I-Tool, and:O, Regin:B-Tool, in:O, complexity:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'One of them – ipv4.dll – has been placed by the APT with what is , in fact , a downloader for other malicious components .' [/INST] [One:O, of:O, them:O, –:O, ipv4.dll:B-SamFile, –:O, has:O, been:O, placed:O, by:O, the:O, APT:O, with:O, what:O, is:O, ,:O, in:O, fact:O, ,:O, a:O, downloader:B-Tool, for:O, other:O, malicious:O, components:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To run its code in kernel mode in the most recent versions of operating systems , that have Driver Signature Enforcement , Slingshot loads signed vulnerable drivers and runs its own code through their vulnerabilities .' [/INST] [To:O, run:O, its:O, code:O, in:O, kernel:O, mode:O, in:O, the:O, most:O, recent:O, versions:O, of:O, operating:O, systems:O, ,:O, that:O, have:O, Driver:O, Signature:O, Enforcement:O, ,:O, Slingshot:B-Tool, loads:O, signed:O, vulnerable:B-Way, drivers:I-Way, and:O, runs:O, its:O, own:O, code:O, through:O, their:O, vulnerabilities:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'During our research we also found a component called KPWS that turned out to be another downloader for Slingshot components .' [/INST] [During:O, our:O, research:O, we:O, also:O, found:O, a:O, component:O, called:O, KPWS:B-Tool, that:O, turned:O, out:O, to:O, be:O, another:O, downloader:O, for:O, Slingshot:B-Tool, components:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Written in pure C language , Canhadr/Ndriver provides full access to the hard drive and operating memory despite device security restrictions , and carries out integrity control of various system components to avoid debugging and security detection .' [/INST] [Written:O, in:O, pure:O, C:O, language:O, ,:O, Canhadr/Ndriver:B-SamFile, provides:B-Features, full:I-Features, access:I-Features, to:O, the:O, hard:O, drive:O, and:O, operating:O, memory:O, despite:O, device:O, security:O, restrictions:O, ,:O, and:O, carries:B-Features, out:I-Features, integrity:I-Features, control:I-Features, of:O, various:O, system:O, components:O, to:O, avoid:O, debugging:O, and:O, security:O, detection:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 toolset includes reams of documentation explaining how the cyber weapons work , as well as details about their use in highly classified intelligence operations abroad .' [/INST] [The:O, toolset:O, includes:O, reams:O, of:O, documentation:O, explaining:B-Features, how:I-Features, the:I-Features, cyber:I-Features, weapons:I-Features, work:O, ,:O, as:O, well:O, as:O, details:O, about:O, their:O, use:O, in:O, highly:B-Purp, classified:I-Purp, intelligence:I-Purp, operations:O, abroad:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'So far , researchers have seen around 100 victims of Slingshot and its related modules , located in Kenya , Yemen , Afghanistan , Libya , Congo , Jordan , Turkey , Iraq , Sudan , Somalia and Tanzania .' [/INST] [So:O, far:O, ,:O, researchers:O, have:O, seen:O, around:O, 100:O, victims:O, of:O, Slingshot:B-Tool, and:O, its:O, related:O, modules:O, ,:O, located:O, in:O, Kenya:B-Area, ,:O, Yemen:B-Area, ,:O, Afghanistan:B-Area, ,:O, Libya:B-Area, ,:O, Congo:B-Area, ,:O, Jordan:B-Area, ,:O, Turkey:B-Area, ,:O, Iraq:B-Area, ,:O, Sudan:B-Area, ,:O, Somalia:B-Area, and:O, Tanzania: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: 'Some of the techniques used by Slingshot , such as the exploitation of legitimate , yet vulnerable drivers has been seen before in other malware , such as White and Grey Lambert .' [/INST] [Some:O, of:O, the:O, techniques:O, used:O, by:O, Slingshot:B-Tool, ,:O, such:O, as:O, the:O, exploitation:O, of:O, legitimate:O, ,:O, yet:O, vulnerable:O, drivers:O, has:O, been:O, seen:O, before:O, in:O, other:O, malware:O, ,:O, such:O, as:O, White:B-Tool, and:O, Grey:B-Tool, Lambert: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: 'Cylance tracks this threat group internally as ' Snake Wine ' .' [/INST] [Cylance:B-SecTeam, tracks:O, this:O, threat:O, group:O, internally:O, as:O, ':O, Snake:B-HackOrg, Wine:I-HackOrg, ':O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'To date , all observed Snake Wine 's attacks were the result of spear phishing attempts against the victim organizations .' [/INST] [To:O, date:O, ,:O, all:O, observed:O, Snake:B-HackOrg, Wine:I-HackOrg, 's:O, attacks:B-OffAct, were:O, the:O, result:O, of:O, spear:B-Way, phishing:I-Way, attempts:O, against:O, the:O, victim:O, organizations:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The Ham Backdoor functions primarily as a modular platform , which provides the attacker with the ability to directly download additional modules and execute them in memory from the command and control ( C2 ) server .' [/INST] [The:O, Ham:B-Tool, Backdoor:I-Tool, functions:O, primarily:O, as:O, a:O, modular:O, platform:O, ,:O, which:O, provides:O, the:O, attacker:O, with:O, the:O, ability:O, to:O, directly:O, download:B-Features, additional:I-Features, modules:I-Features, and:O, execute:O, them:O, in:O, memory:O, from:O, the:O, command:O, and:O, control:O, (:O, C2:O, ):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: 'Based upon Cylance 's observations , the Tofu Backdoor was deployed in far fewer instances than the Ham Backdoor .' [/INST] [Based:O, upon:O, Cylance:B-SecTeam, 's:O, observations:O, ,:O, the:O, Tofu:B-Tool, Backdoor:I-Tool, was:O, deployed:O, in:O, far:O, fewer:O, instances:O, than:O, the:O, Ham: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: 'This suggests that the Snake Wine group will likely continue to escalate their activity and persistently target both private and government entities within Japan .' [/INST] [This:O, suggests:O, that:O, the:O, Snake:O, Wine:O, group:O, will:O, likely:O, continue:O, to:O, escalate:O, their:O, activity:B-OffAct, and:O, persistently:O, target:O, both:O, private:O, and:O, government:B-Org, entities:I-Org, within:O, Japan:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 publicly disclosed by FireEye in this report .' [/INST] [The:O, group:O, was:O, first:O, publicly:O, disclosed:O, by:O, FireEye:B-SecTeam, in:O, this:O, report:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'MenuPass is a well-documented CN-APT group , whose roots go back to 2009 .' [/INST] [MenuPass:B-HackOrg, is:O, a:O, well-documented:O, CN-APT:O, group:O, ,:O, whose:O, roots:O, go:O, back:O, to:O, 2009:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Snake Wine was first publicly disclosed by FireEye in this report .' [/INST] [Snake:O, Wine:O, was:O, first:O, publicly:O, disclosed:O, by:O, FireEye:B-SecTeam, in:O, this:O, report:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the MenuPass Group used mostly publicly available RATs , they were successful in penetrating a number of high value targets , so it is entirely possible this is indeed a continuation of past activity .' [/INST] [Although:O, the:O, MenuPass:O, Group:O, used:O, mostly:O, publicly:B-Tool, available:I-Tool, RATs:I-Tool, ,:O, they:O, were:O, successful:O, in:O, penetrating:O, a:O, number:O, of:O, high:O, value:O, targets:O, ,:O, so:O, it:O, is:O, entirely:O, possible:O, this:O, is:O, indeed:O, a:O, continuation:O, of:O, past:O, activity:B-OffAct, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Also of particular interest was the use of a domain hosting company that accepts BTC and was previously heavily leveraged by the well-known Russian group APT28 .' [/INST] [Also:O, of:O, particular:O, interest:O, was:O, the:O, use:O, of:O, a:O, domain:B-Org, hosting:I-Org, company:I-Org, that:O, accepts:O, BTC:O, and:O, was:O, previously:O, heavily:O, leveraged:O, by:O, the:O, well-known:O, Russian:B-Area, group:O, APT28: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: 'Germany 's Der Spiegel re-published the slide set with far less deletions recently , in January 2015 , and therefore gave a deeper insight about what CSEC actually says they have tracked down .' [/INST] [Germany:B-Area, 's:O, Der:B-SecTeam, Spiegel:I-SecTeam, re-published:O, the:O, slide:O, set:O, with:O, far:O, less:O, deletions:O, recently:O, ,:O, in:O, January:B-Time, 2015:I-Time, ,:O, and:O, therefore:O, gave:O, a:O, deeper:O, insight:O, about:O, what:O, CSEC:O, actually:O, says:O, they:O, have:O, tracked:O, down:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'According to slide 22 , , CSEC assesses , with moderate certainty , SNOWGLOBE to be a state-sponsored Cyber Network Operation effort , put forth by a French intelligence agency , .' [/INST] [According:O, to:O, slide:O, 22:O, ,:O, ,:O, CSEC:O, assesses:O, ,:O, with:O, moderate:O, certainty:O, ,:O, SNOWGLOBE:O, to:O, be:O, a:O, state-sponsored:O, Cyber:B-OffAct, Network:I-OffAct, Operation:I-OffAct, effort:O, ,:O, put:O, forth:O, by:O, a:O, French:B-Area, intelligence:I-Area, agency:I-Area, ,:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 given dates back to 2011 and nothing else has been published since .' [/INST] [The:O, information:O, given:O, dates:O, back:O, to:O, 2011:B-Time, and:O, nothing:O, else:O, has:O, been:O, published:O, since:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Now that specific Babar samples have been identified and analyzed , there might be new information , also with regards to similarities or differences between the two Remote Administration Tools ( RATs ) EvilBunny and Babar .' [/INST] [Now:O, that:O, specific:O, Babar:B-Tool, samples:I-Tool, have:O, been:O, identified:O, and:O, analyzed:O, ,:O, there:O, might:O, be:O, new:O, information:O, ,:O, also:O, with:O, regards:O, to:O, similarities:O, or:O, differences:O, between:O, the:O, two:O, Remote:B-Tool, Administration:I-Tool, Tools:I-Tool, (:O, RATs:B-Tool, ):O, EvilBunny:B-Tool, and:O, Babar: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: 'We recommend reading Marion 's report , Shooting Elephants , , a complementary piece of work regarding the Babar malware .' [/INST] [We:O, recommend:O, reading:O, Marion:O, 's:O, report:O, ,:O, Shooting:O, Elephants:O, ,:O, ,:O, a:O, complementary:O, piece:O, of:O, work:O, regarding:O, the:O, Babar:B-Tool, malware: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: 'And finally , as every elephant , Babar has big ears and the malware is able to listen to conversations and log them by using the dsound and winmm libraries .' [/INST] [And:O, finally:O, ,:O, as:O, every:O, elephant:O, ,:O, Babar:B-Tool, has:O, big:O, ears:O, and:O, the:O, malware:O, is:O, able:O, to:O, listen:O, to:O, conversations:O, and:O, log:O, them:O, by:O, using:O, the:O, dsound:B-Tool, and:O, winmm:B-Tool, libraries: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 G DATA SecurityLabs are convinced that the number of similarities identified between EvilBunny and Babar show that both malware families originate from the same developers .' [/INST] [The:O, G:B-SecTeam, DATA:I-SecTeam, SecurityLabs:I-SecTeam, are:O, convinced:O, that:O, the:O, number:O, of:O, similarities:O, identified:O, between:O, EvilBunny:B-Tool, and:O, Babar:B-Tool, show:O, that:O, both:O, malware:O, families:O, originate:O, from:O, the:O, same:O, developers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'TA542 , the primary actor behind Emotet , is known for the development of lures and malicious mail specific to given regions .' [/INST] [TA542:B-HackOrg, ,:O, the:O, primary:O, actor:O, behind:O, Emotet:B-Tool, ,:O, is:O, known:O, for:O, the:O, development:O, of:O, lures:O, and:O, malicious:O, mail:O, specific:O, to:O, given:O, regions:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 discussions of threats in this region often focus on , North America , generally or just the United States , nearly 100 campaigns during this period were either specifically targeted at Canadian organizations or were customized for Canadian audiences .' [/INST] [While:O, discussions:O, of:O, threats:O, in:O, this:O, region:O, often:O, focus:O, on:O, ,:O, North:O, America:O, ,:O, generally:O, or:O, just:O, the:O, United:O, States:O, ,:O, nearly:O, 100:O, campaigns:B-OffAct, during:O, this:O, period:O, were:O, either:O, specifically:O, targeted:O, at:O, Canadian:O, organizations:O, or:O, were:O, customized:O, for:O, Canadian:B-Area, audiences:B-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Emotet is a type of general-purpose malware that evolved from a well-known banking Trojan , , Cridex , , which was first discovered in 2014 .' [/INST] [Emotet:B-Tool, is:O, a:O, type:O, of:O, general-purpose:O, malware:O, that:O, evolved:O, from:O, a:O, well-known:O, banking:B-Tool, Trojan:I-Tool, ,:O, ,:O, Cridex:B-Tool, ,:O, ,:O, which:O, was:O, first:O, discovered:O, in:O, 2014:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 discussions of threats in this region often focus on , North America , generally or just the United States , nearly 100 campaigns during this period were either specifically targeted at Canadian organizations or were customized for Canadian audiences .' [/INST] [While:O, discussions:O, of:O, threats:O, in:O, this:O, region:O, often:O, focus:O, on:O, ,:O, North:O, America:O, ,:O, generally:O, or:O, just:O, the:O, United:B-Area, States:I-Area, ,:O, nearly:O, 100:O, campaigns:B-OffAct, during:O, this:O, period:O, were:O, either:O, specifically:O, targeted:O, at:O, Canadian:B-Area, organizations:O, or:O, were:O, customized:O, for:O, Canadian:B-Area, audiences:B-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Emotet activity in 2019 included several high-volume campaigns that collectively distributed tens of millions of messages primarily targeting the manufacturing and healthcare industries .' [/INST] [Emotet:B-OffAct, activity:I-OffAct, in:O, 2019:O, included:O, several:O, high-volume:O, campaigns:B-OffAct, that:O, collectively:O, distributed:O, tens:O, of:O, millions:O, of:O, messages:O, primarily:O, targeting:O, the:O, manufacturing:B-Idus, and:O, healthcare:B-Idus, industries:I-Idus, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Originally targeting Western European banks , Emotet has since been developed into a robust global botnet that is comprised of several modules , each of which equips Emotet with different spamming , email logging , information stealing , bank fraud , downloading , and DDoS , among others .' [/INST] [Originally:O, targeting:O, Western:B-Area, European:I-Area, banks:B-Idus, ,:O, Emotet:B-Tool, has:O, since:O, been:O, developed:O, into:O, a:O, robust:O, global:O, botnet:O, that:O, is:O, comprised:O, of:O, several:O, modules:O, ,:O, each:O, of:O, which:O, equips:O, Emotet:B-Tool, with:O, different:O, spamming:O, ,:O, email:B-Features, logging:I-Features, ,:O, information:B-Features, stealing:I-Features, ,:O, bank:B-Features, fraud:I-Features, ,:O, downloading:B-Features, ,:O, and:O, DDoS:B-Features, ,:O, among: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: 'Originally targeting Western European banks , it has since been developed into a robust global botnet that is comprised of several modules , each of which equips Emotet with different spamming , email logging , information stealing , bank fraud , downloading , and DDoS , among others .' [/INST] [Originally:O, targeting:O, Western:B-Area, European:I-Area, banks:B-Idus, ,:O, it:O, has:O, since:O, been:O, developed:O, into:O, a:O, robust:O, global:O, botnet:O, that:O, is:O, comprised:O, of:O, several:O, modules:O, ,:O, each:O, of:O, which:O, equips:O, Emotet:B-Tool, with:O, different:O, spamming:O, ,:O, email:B-Features, logging:I-Features, ,:O, information:B-Features, stealing:I-Features, ,:O, bank:B-Features, fraud:I-Features, ,:O, downloading:B-Features, ,:O, and:O, DDoS:B-Features, ,:O, among: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: 'Beginning in mid-January 2019 , TA542 distributed millions of Emotet-laden emails in both English and German .' [/INST] [Beginning:O, in:O, mid-January:B-Time, 2019:I-Time, ,:O, TA542:O, distributed:O, millions:O, of:O, Emotet-laden:B-Way, emails:I-Way, in:O, both:O, English:O, and:O, German:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'DanaBot is a Trojan that includes banking site web injections and stealer functions .' [/INST] [DanaBot:B-Tool, is:O, a:O, Trojan:B-Tool, that:O, includes:O, banking:B-Features, site:I-Features, web:I-Features, injections:I-Features, and:O, stealer:B-Features, functions:I-Features, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Proofpoint researchers observed one DanaBot affiliate ( Affid 11 ) specifically targeting Canada with , Canada Post , themed lures between January 1 and May 1 , 2019 .' [/INST] [Proofpoint:B-SecTeam, researchers:O, observed:O, one:O, DanaBot:B-Tool, affiliate:O, (:O, Affid:O, 11:O, ):O, specifically:O, targeting:O, Canada:B-Area, with:O, ,:O, Canada:B-Org, Post:I-Org, ,:O, themed:B-Way, lures:I-Way, between:O, January:O, 1:O, and:O, May:B-Time, 1:I-Time, ,:O, 2019: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: 'FormBook is a browser form stealer/keylogger that is under active development .' [/INST] [FormBook:B-Tool, is:O, a:O, browser:O, form:O, stealer/keylogger:B-Tool, that:O, is:O, under:O, active:O, development:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 Canada-targeted threats are not new , Emotet in particular , with its frequent region-specific email campaigns , is bringing new attention to geo-targeting in Canada and beyond .' [/INST] [While:O, Canada-targeted:O, threats:O, are:O, not:O, new:O, ,:O, Emotet:B-Tool, in:O, particular:O, ,:O, with:O, its:O, frequent:O, region-specific:O, email:B-OffAct, campaigns:I-OffAct, ,:O, is:O, bringing:O, new:O, attention:O, to:O, geo-targeting:O, in:O, Canada:B-Area, and:O, beyond:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 observed in mid-2014 , this malware shared code with the Bugat ( aka Feodo ) banking Trojan .' [/INST] [First:O, observed:O, in:O, mid-2014:B-Time, ,:O, this:O, malware:O, shared:O, code:O, with:O, the:O, Bugat:B-SamFile, (:O, aka:O, Feodo:O, ):O, banking:B-Tool, Trojan: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: 'MUMMY SPIDER is a criminal entity linked to the core development of the malware most commonly known as Emotet or Geodo .' [/INST] [MUMMY:B-HackOrg, SPIDER:I-HackOrg, is:O, a:O, criminal:O, entity:O, linked:O, to:O, the:O, core:O, development:O, of:O, the:O, malware:O, most:O, commonly:O, known:O, as:O, Emotet:B-Tool, or:O, Geodo: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: 'After a 10 month hiatus , MUMMY SPIDER returned Emotet to operation in December 2016 but the latest variant is not deploying a banking Trojan module with web injects , it is currently acting as a ' loader ' delivering other malware packages .' [/INST] [After:O, a:O, 10:O, month:O, hiatus:O, ,:O, MUMMY:B-HackOrg, SPIDER:I-HackOrg, returned:O, Emotet:B-Tool, to:O, operation:O, in:O, December:B-Time, 2016:I-Time, but:O, the:O, latest:O, variant:O, is:O, not:O, deploying:O, a:O, banking:B-Tool, Trojan:I-Tool, module:O, with:O, web:O, injects:O, ,:O, it:O, is:O, currently:O, acting:O, as:O, a:O, ':O, loader:O, ':O, delivering:O, other:O, malware:O, packages:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The malware is also issuing commands to download and execute other malware families such as the banking Trojans Dridex and Qakbot .' [/INST] [The:O, malware:O, is:O, also:O, issuing:O, commands:O, to:O, download:O, and:O, execute:O, other:O, malware:O, families:O, such:O, as:O, the:O, banking:B-Tool, Trojans:I-Tool, Dridex:I-Tool, and:O, Qakbot: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: 'It seems that the main objective of the attackers was information gathering from the infected computers .' [/INST] [It:O, seems:O, that:O, the:O, main:O, objective:O, of:O, the:O, attackers:O, was:O, information:B-Purp, gathering:I-Purp, from:O, the:O, infected:O, computers:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 the TeamViewer-based activities , we have traces in the past until September 2012 .' [/INST] [For:O, the:O, TeamViewer-based:B-OffAct, activities:I-OffAct, ,:O, we:O, have:O, traces:O, in:O, the:O, past:O, until:O, September:B-Time, 2012: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 the actual targeted attack detected by the Hungarian National Security Agency , TeamSpy used components of the TeamViewer tool combined with other malware modules .' [/INST] [In:O, the:O, actual:O, targeted:B-OffAct, attack:I-OffAct, detected:O, by:O, the:O, Hungarian:O, National:O, Security:O, Agency:O, ,:O, TeamSpy:B-OffAct, used:O, components:O, of:O, the:O, TeamViewer:B-Tool, tool:I-Tool, combined:O, with:O, other:O, malware:B-Tool, modules: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: 'In the actual targeted attack detected by the Hungarian National Security Agency , they used components of the TeamViewer tool combined with other malware modules .' [/INST] [In:O, the:O, actual:O, targeted:B-OffAct, attack:I-OffAct, detected:O, by:O, the:O, Hungarian:O, National:O, Security:O, Agency:O, ,:O, they:O, used:O, components:O, of:O, the:O, TeamViewer:B-Tool, tool:I-Tool, combined:O, with:O, other:O, malware:B-Tool, modules: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: 'TeamViewer has also been used in the , Sheldor , attack campaign , which was detected between 2010 and 2011 , and which resulted in assets stolen at the value of $600k and $832k .' [/INST] [TeamViewer:B-Tool, has:O, also:O, been:O, used:O, in:O, the:O, ,:O, Sheldor:B-OffAct, ,:O, attack:B-OffAct, campaign:I-OffAct, ,:O, which:O, was:O, detected:O, between:O, 2010:B-Time, and:O, 2011:B-Time, ,:O, and:O, which:O, resulted:O, in:O, assets:O, stolen:O, at:O, the:O, value:O, of:O, $600k:O, and:O, $832k:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 match shows a direct relationship between Sheldor and TeamSpy , although we do not known if the connection is only at the tool level or at the operation level too .' [/INST] [This:O, match:O, shows:O, a:O, direct:O, relationship:O, between:O, Sheldor:B-OffAct, and:O, TeamSpy:B-OffAct, ,:O, although:O, we:O, do:O, not:O, known:O, if:O, the:O, connection:O, is:O, only:O, at:O, the:O, tool:O, level:O, or:O, at:O, the:O, operation:O, level:O, too:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Microsoft Threat Intelligence refers to the activity group behind these attacks as TERBIUM , following our internal practice of assigning rogue actors chemical element names .' [/INST] [Microsoft:B-Org, Threat:I-Org, Intelligence:I-Org, refers:O, to:O, the:O, activity:O, group:O, behind:O, these:O, attacks:B-OffAct, as:O, TERBIUM:B-HackOrg, ,:O, following:O, our:O, internal:O, practice:O, of:O, assigning:O, rogue:O, actors:O, chemical:O, element:O, names:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'From the samples we collected , we can conclude that the same threat actor produced many individual malware modules during the last ten years .' [/INST] [From:O, the:O, samples:O, we:O, collected:O, ,:O, we:O, can:O, conclude:O, that:O, the:O, same:O, threat:O, actor:O, produced:O, many:O, individual:O, malware:B-Tool, modules:I-Tool, during:O, the:O, last:O, ten:O, years:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 TERBIUM has a foothold in the organization , its infection chain starts by writing an executable file to disk that contains all the components required to carry out the data-wiping operation .' [/INST] [Once:O, TERBIUM:B-HackOrg, has:O, a:O, foothold:O, in:O, the:O, organization:O, ,:O, its:O, infection:O, chain:O, starts:O, by:O, writing:O, an:O, executable:O, file:O, to:O, disk:O, that:O, contains:O, all:O, the:O, components:O, required:O, to:O, carry:O, out:O, the:O, data-wiping:O, operation:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Microsoft Threat Intelligence has observed that the malware used by TERBIUM , dubbed , Depriz , by Microsoft , reuses several components and techniques seen in the 2012 attacks , and has been highly customized for each targeted organization .' [/INST] [Microsoft:B-Org, Threat:I-Org, Intelligence:I-Org, has:O, observed:O, that:O, the:O, malware:O, used:O, by:O, TERBIUM:B-HackOrg, ,:O, dubbed:O, ,:O, Depriz:B-HackOrg, ,:O, by:O, Microsoft:B-Org, ,:O, reuses:O, several:O, components:O, and:O, techniques:O, seen:O, in:O, the:O, 2012:B-OffAct, attacks:I-OffAct, ,:O, and:O, has:O, been:O, highly:O, customized:O, for:O, each:O, targeted:O, organization:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Note : TERBIUM establishes a foothold throughout the organization and does not proceed with the destructive wiping operation until a specific date/time : November 17 , 2016 at 8:45 p.m .' [/INST] [Note:O, ::O, TERBIUM:B-HackOrg, establishes:O, a:O, foothold:O, throughout:O, the:O, organization:O, and:O, does:O, not:O, proceed:O, with:O, the:O, destructive:O, wiping:O, operation:O, until:O, a:O, specific:O, date/time:O, ::O, November:B-Time, 17:I-Time, ,:O, 2016:B-Time, at:O, 8:45:O, p.m:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Transparent Tribe has been active for several years and conducting suspected intelligence collection operations against South Asian political and military targets .' [/INST] [Transparent:O, Tribe:O, has:O, been:O, active:O, for:O, several:O, years:O, and:O, conducting:O, suspected:O, intelligence:B-Purp, collection:I-Purp, operations:O, against:O, South:O, Asian:O, political:B-Idus, and:O, military:B-Idus, 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: 'We initially reported on this threat group and their UPDATESEE malware in our FireEye Intelligence Center in February 2016 .' [/INST] [We:O, initially:O, reported:O, on:O, this:O, threat:O, group:O, and:O, their:O, UPDATESEE:B-Tool, malware:I-Tool, in:O, our:O, FireEye:B-SecTeam, Intelligence:I-SecTeam, Center:O, in:O, February:B-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: 'We initially reported on Transparent Tribe and their UPDATESEE malware in our FireEye Intelligence Center in February 2016 .' [/INST] [We:O, initially:O, reported:O, on:O, Transparent:O, Tribe:O, and:O, their:O, UPDATESEE:B-Tool, malware:I-Tool, in:O, our:O, FireEye:B-SecTeam, Intelligence:I-SecTeam, Center:O, in:O, February:B-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: 'In all emails sent to these government officials , the actor used the same attachment : a malicious Microsoft Word document that exploited the CVE-2012-0158 vulnerability to drop a malicious payload .' [/INST] [In:O, all:O, emails:B-Way, sent:O, to:O, these:O, government:B-Org, officials:I-Org, ,:O, the:O, actor:O, used:O, the:O, same:O, attachment:O, ::O, a:O, malicious:B-SamFile, Microsoft:I-SamFile, Word:I-SamFile, document:I-SamFile, that:O, exploited:O, the:O, CVE-2012-0158:B-Exp, vulnerability:O, to:O, drop:O, a:O, malicious:O, payload:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this latest incident , the group registered a fake news domain , timesofindiaa.in , on May 18 , 2016 , and then used it to send spear phishing emails to Indian government officials on the same day .' [/INST] [In:O, this:O, latest:O, incident:O, ,:O, the:O, group:O, registered:O, a:O, fake:O, news:O, domain:O, ,:O, timesofindiaa.in:O, ,:O, on:O, May:B-Time, 18:I-Time, ,:O, 2016:B-Time, ,:O, and:O, then:O, used:O, it:O, to:O, send:O, spear:B-Way, phishing:I-Way, emails:I-Way, to:O, Indian:B-Area, government:B-Org, officials:I-Org, on:O, the:O, same:O, day:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 being an older vulnerability , many threat actors continue to leverage CVE-2012-0158 to exploit Microsoft Word .' [/INST] [Despite:O, being:O, an:O, older:O, vulnerability:O, ,:O, many:O, threat:O, actors:O, continue:O, to:O, leverage:O, CVE-2012-0158:B-Exp, to:O, exploit:O, Microsoft:B-SamFile, Word: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: 'In previous incidents involving this threat actor , we observed them using malicious documents hosted on websites about the Indian Army , instead of sending these documents directly as an email attachment .' [/INST] [In:O, previous:O, incidents:O, involving:O, this:O, threat:O, actor:O, ,:O, we:O, observed:O, them:O, using:O, malicious:O, documents:O, hosted:O, on:O, websites:O, about:O, the:O, Indian:B-Idus, Army:I-Idus, ,:O, instead:O, of:O, sending:O, these:O, documents:O, directly:O, as:O, an:O, email:B-Way, attachment:I-Way, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'In this latest incident , Transparent Tribe registered a fake news domain , timesofindiaa.in , on May 18 , 2016 , and then used it to send spear phishing emails to Indian government officials on the same day .' [/INST] [In:O, this:O, latest:O, incident:O, ,:O, Transparent:O, Tribe:O, registered:O, a:O, fake:O, news:O, domain:O, ,:O, timesofindiaa.in:O, ,:O, on:O, May:B-Time, 18:I-Time, ,:O, 2016:B-Time, ,:O, and:O, then:O, used:O, it:O, to:O, send:O, spear:B-Way, phishing:I-Way, emails:I-Way, to:O, Indian:O, government:B-Org, officials:I-Org, on:O, the:O, same:O, day:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide 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 exploit file made use of the same shellcode that we have observed Transparent Tribe use across a number of spear phishing incidents .' [/INST] [This:O, exploit:O, file:O, made:O, use:O, of:O, the:O, same:O, shellcode:O, that:O, we:O, have:O, observed:O, Transparent:O, Tribe:O, use:O, across:O, a:O, number:O, of:O, spear:B-Way, phishing:I-Way, incidents:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The first time this happened was at the beginning of the month , when Proofpoint researchers blew the lid off a cyber-espionage campaign named Operation Transparent Tribe , which targeted the Indian embassies in Saudi Arabia and Kazakhstan .' [/INST] [The:O, first:O, time:O, this:O, happened:O, was:O, at:O, the:O, beginning:O, of:O, the:O, month:O, ,:O, when:O, Proofpoint:B-SecTeam, researchers:O, blew:O, the:O, lid:O, off:O, a:O, cyber-espionage:B-OffAct, campaign:I-OffAct, named:O, Operation:B-OffAct, Transparent:I-OffAct, Tribe:I-OffAct, ,:O, which:O, targeted:O, the:O, Indian:O, embassies:B-Org, in:O, Saudi:B-Area, Arabia:I-Area, and:O, Kazakhstan: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: 'Back in February 2016 , Indian army officials issued a warning against the usage of three apps , WeChat , SmeshApp , and Line , fearing that these apps collected too much information if installed on smartphones used by Indian army personnel .' [/INST] [Back:O, in:O, February:B-Time, 2016:I-Time, ,:O, Indian:O, army:B-Org, officials:I-Org, issued:O, a:O, warning:O, against:O, the:O, usage:O, of:O, three:O, apps:O, ,:O, WeChat:B-Tool, ,:O, SmeshApp:B-Tool, ,:O, and:O, Line:B-Tool, ,:O, fearing:O, that:O, these:O, apps:O, collected:O, too:O, much:O, information:O, if:O, installed:O, on:O, smartphones:O, used:O, by:O, Indian:O, army:B-Org, personnel:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The May 2018 adversary spotlight is on MYTHIC LEOPARD , a Pakistan-based adversary with operations likely located in Karachi .' [/INST] [The:O, May:B-Time, 2018:I-Time, adversary:O, spotlight:O, is:O, on:O, MYTHIC:B-HackOrg, LEOPARD:I-HackOrg, ,:O, a:O, Pakistan-based:B-Area, adversary:O, with:O, operations:O, likely:O, located:O, in:O, Karachi: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: 'According to the security firm , this campaign targeted Indian military officials via spear-phishing emails , distributing spyware to its victims via an Adobe Reader vulnerability .' [/INST] [According:O, to:O, the:O, security:B-Org, firm:I-Org, ,:O, this:O, campaign:B-OffAct, targeted:O, Indian:O, military:B-Org, officials:I-Org, via:O, spear-phishing:B-Way, emails:I-Way, ,:O, distributing:O, spyware:O, to:O, its:O, victims:O, via:O, an:O, Adobe:B-Exp, Reader:I-Exp, vulnerability:I-Exp, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'The CrowdStrike Falcon Intelligence™ team 's tracking of MYTHIC LEOPARD began in late 2016 , when evidence of an attack surfaced against a victim based in India and working in the hospitality sector .' [/INST] [The:O, CrowdStrike:B-SecTeam, Falcon:I-SecTeam, Intelligence™:I-SecTeam, team:O, 's:O, tracking:O, of:O, MYTHIC:O, LEOPARD:O, began:O, in:O, late:O, 2016:B-Time, ,:O, when:O, evidence:O, of:O, an:O, attack:B-OffAct, surfaced:O, against:O, a:O, victim:O, based:O, in:O, India:O, and:O, working:O, in:O, the:O, hospitality:B-Org, sector:I-Org, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Two binder tools — used to disguise custom executables as legitimate Microsoft implants — were discovered by Falcon Intelligence and linked to MYTHIC LEOPARD in July 2017 .' [/INST] [Two:O, binder:O, tools:O, —:O, used:O, to:O, disguise:B-Features, custom:I-Features, executables:I-Features, as:O, legitimate:O, Microsoft:B-Org, implants:O, —:O, were:O, discovered:O, by:O, Falcon:B-SecTeam, Intelligence:I-SecTeam, and:O, linked:O, to:O, MYTHIC:B-HackOrg, LEOPARD:I-HackOrg, in:O, July:B-Time, 2017:I-Time, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Falcon Intelligence has observed MYTHIC LEOPARD using this technique for several years to install multiple first-stage implants and downloaders , including the isqlmanager and Waizsar RAT malware families .' [/INST] [Falcon:B-SecTeam, Intelligence:I-SecTeam, has:O, observed:O, MYTHIC:B-HackOrg, LEOPARD:I-HackOrg, using:O, this:O, technique:O, for:O, several:O, years:O, to:O, install:O, multiple:O, first-stage:O, implants:O, and:O, downloaders:O, ,:O, including:O, the:O, isqlmanager:B-Tool, and:O, Waizsar:B-Tool, RAT:I-Tool, malware:I-Tool, families: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: 'Patchwork also uses the Delphi file stealer as a similarity with Urpage , which suggests the three groups are somehow related .' [/INST] [Patchwork:B-HackOrg, also:O, uses:O, the:O, Delphi:O, file:O, stealer:O, as:O, a:O, similarity:O, with:O, Urpage:O, ,:O, which:O, suggests:O, the:O, three:O, groups:O, are:O, somehow:O, related:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Patchwork has also recently employed Android malware in its attacks , with its use of a customized version of AndroRAT .' [/INST] [Patchwork:B-HackOrg, has:O, also:O, recently:O, employed:O, Android:B-Tool, malware:I-Tool, in:O, its:O, attacks:B-OffAct, ,:O, with:O, its:O, use:O, of:O, a:O, customized:O, version:O, of:O, AndroRAT: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: 'Trend Micro 's Mobile App Reputation Service ( MARS ) covers Android and iOS threats using leading sandbox and machine learning technologies .' [/INST] [Trend:B-SecTeam, Micro:I-SecTeam, 's:O, Mobile:O, App:O, Reputation:O, Service:O, (:O, MARS:O, ):O, covers:O, Android:O, and:O, iOS:O, threats:O, using:O, leading:B-Tool, sandbox:I-Tool, and:O, machine:B-Tool, learning:I-Tool, technologies: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: 'Symantec researchers have discovered that this attack group , which we call Whitefly , has been operating since at least 2017 , has targeted organizations based mostly in Singapore across a wide variety of sectors , and is primarily interested in stealing large amounts of sensitive information .' [/INST] [Symantec:B-SecTeam, researchers:O, have:O, discovered:O, that:O, this:O, attack:B-OffAct, group:O, ,:O, which:O, we:O, call:O, Whitefly:B-HackOrg, ,:O, has:O, been:O, operating:O, since:O, at:O, least:O, 2017:B-Time, ,:O, has:O, targeted:O, organizations:O, based:O, mostly:O, in:O, Singapore:O, across:O, a:O, wide:O, variety:O, of:O, sectors:O, ,:O, and:O, is:O, primarily:O, interested:O, in:O, stealing:O, large:O, amounts:O, of:O, sensitive:O, information:O, .:O] </s> |
<s>[INST] You are a cybersecurity and NLP expert tasked with named entity extraction. You need to provide the named entities for each token in the given sentence. You will be penalized for incorrect predictions. Identify the entities for the following sentence: 'Whitefly compromises its victims using custom malware alongside open-source hacking tools and living off the land tactics , such as malicious PowerShell scripts .' [/INST] [Whitefly:B-HackOrg, compromises:O, its:O, victims:O, using:O, custom:O, malware:O, alongside:O, open-source:O, hacking:O, tools:O, and:O, living:O, off:O, the:O, land:B-Way, tactics:I-Way, ,:O, such:O, as:O, malicious:O, PowerShell:B-Tool, scripts:I-Tool, .:O] </s> |