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MALTEGO
ONE OF THE BEST “OSINT” TOOL
WHAT IS MALTEGO?
• Open Source Intelligence (OSINT) gathering tools
• Used fot reconnaissance (Information gathering) and data-mining
• Maltego is a unique platform developed to deliver a clear threat picture to the
environment that an organization owns and operates.
• Maltego’s unique advantage is to demonstrate the complexity of single points of
failure as well as trust relationships that exist currently within the scope of your
infrastructure.
• Reconnaissance on any person, by scraping up data from all publicly available
areas of the Internets.
TERMS: ENTITIES
• The type of entity (e.g. Website) defines what transforms can be run against
• Any Building block of graphs
• Eg:
• Website
• Phrase
• E-mail address
• Social Network
TERMS: TRANSFORMS
• Take starting entities and run code on it
• It result the data in other entity
• In other word the transforms means the processing on the data according to the
our requirement.
• Two type:
• Local Transforms
• Remote Transforms
TERMS: MACHINE
• Set of transforms and action to be
performed on the entities
• Machine and run the predefined task
on the entity and fetch the result in
graphical form
• We can create our own machine by
using some programming language
such as python
DISCLAIMER
• Crawl “Damage”: Unclear what “damage” may occur from transforms (but
some crawls may be working correctly)
• Sample of a Disclaimer: “Please note this transform is being run on the
Paterva Transform Distribution Server and has been written by the user
'Andrew MacPherson'. This transform will be run on * and Paterva cannot be
held responsible for any damage caused by this transform, you run this AT
YOUR OWN RISK. For more information on this transform feel free to
contact…”
WHY USE MALTEGO?
• People’s online relationships can identify an unknown node based on the
connections, power relationships, intercommunications, and the external
identities
• People have used their realworld identities in their virtual world
• Used for the analysis of the footprint
• All online actions can be linked to geographical locations, and those locations
may be revealing
• Results are well represented in a variety of easy to understand views
• Maltego identifies key relationships between data sets and identifies previously
unknown relationships between them
BASIC FEATURES OF MALTEGO
• Shows links between people; groups of people (social networks); companies;
organizations; web sites; internet infrastructure (domain, DNS names, netblocks,
IP addresses); phrases; affiliations; documents and files
• Based on open-source (publicly available) information or “open-source intelligence”
(OSINT)
• Does not involve the breaking of network controls to access information
• Assumes benign information in isolation may be turned malicious in combination and
/ or relationship to other data (as in “big data” analytics)
• Is a “dual use” technology with a range of applied “data harvesting” / structure-
mining / datamining and analytical uses
TYPE OF MACHINE ON MALTEGO
• Company Stalker: Email addresses at a company’s domain(s)
• Footprint L1: “Fast” and limited footprint of a domain
• Footprint L2: “Mild” and semi-limited footprint of a domain
• Footprint L3: “Intense” and fairly in-depth and internal footprint of a domain
• Person- Email Address: Identifies a person’s email addresses (but needs a
disambiguated or fairly uncommon name…or the data is noisy)
• Prune Leaf Entities: Prunes all leaves (entities with no outgoing links and just
one incoming link—aka pendant nodes) to clear the screen for re-crawls (and to
de-noise the data
TYPE OF MACHINE
• Twitter Digger: Phrase as a Twitter search
• Twitter Geo(graphical) Location: Finding a person’s location based on multiple
information streams
• Twitter Monitor: Monitors Twitter for hashtags (#) and named entities
mentioned (@)
• URL to Network and Domain Information: From URL to network and domain
information
NODE LEVEL TRANSFORM
• Devices
• A phone, mobile device, or other
used by the individual or
connected to various accounts or
a network
• Infrastructure
• AS – Autonomous System
Number (as assigned by IANA to
RIRs)
• DNS Name – Domain Name
System (identification string)
• Domain – Internet Domain
• IPv4 Address – IP version 4
address
• MX Record – DNS mail exchanger
record (indicator of mail server
accepting email messages and how
email should be routed through
SMTP)
• NS Record – A DNS name server
record (with indicators of
subdomains)
• Netblock – An internet autonomous
system
• URL – An internet Uniform Resource
Locator (web address as a character
sting)
• Website – An internet website
(related web pages served from a
single domain)
NODE LEVEL TRANSFORM
• Locations
• A location on Earth (to find
domains and other such
information)
• Penetration (“Pen”) Testing
• Company
• Social Network
• Facebook Object
• Twit entity
• Affiliation – Facebook
• Affiliation – Twitter
• Personal
• Alias
• Document
• Email Address
• Image (EXIF or “Exchangeable Image
File” data extraction: geotagged
data, GPS, and general image
conditions information like digital
camera settings)
• Person
• Phone Number
• Phrase
DEMO
THANK YOU

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Basics of Maltego

  • 1. MALTEGO ONE OF THE BEST “OSINT” TOOL
  • 2. WHAT IS MALTEGO? • Open Source Intelligence (OSINT) gathering tools • Used fot reconnaissance (Information gathering) and data-mining • Maltego is a unique platform developed to deliver a clear threat picture to the environment that an organization owns and operates. • Maltego’s unique advantage is to demonstrate the complexity of single points of failure as well as trust relationships that exist currently within the scope of your infrastructure. • Reconnaissance on any person, by scraping up data from all publicly available areas of the Internets.
  • 3. TERMS: ENTITIES • The type of entity (e.g. Website) defines what transforms can be run against • Any Building block of graphs • Eg: • Website • Phrase • E-mail address • Social Network
  • 4. TERMS: TRANSFORMS • Take starting entities and run code on it • It result the data in other entity • In other word the transforms means the processing on the data according to the our requirement. • Two type: • Local Transforms • Remote Transforms
  • 5. TERMS: MACHINE • Set of transforms and action to be performed on the entities • Machine and run the predefined task on the entity and fetch the result in graphical form • We can create our own machine by using some programming language such as python
  • 6. DISCLAIMER • Crawl “Damage”: Unclear what “damage” may occur from transforms (but some crawls may be working correctly) • Sample of a Disclaimer: “Please note this transform is being run on the Paterva Transform Distribution Server and has been written by the user 'Andrew MacPherson'. This transform will be run on * and Paterva cannot be held responsible for any damage caused by this transform, you run this AT YOUR OWN RISK. For more information on this transform feel free to contact…”
  • 7. WHY USE MALTEGO? • People’s online relationships can identify an unknown node based on the connections, power relationships, intercommunications, and the external identities • People have used their realworld identities in their virtual world • Used for the analysis of the footprint • All online actions can be linked to geographical locations, and those locations may be revealing • Results are well represented in a variety of easy to understand views • Maltego identifies key relationships between data sets and identifies previously unknown relationships between them
  • 8. BASIC FEATURES OF MALTEGO • Shows links between people; groups of people (social networks); companies; organizations; web sites; internet infrastructure (domain, DNS names, netblocks, IP addresses); phrases; affiliations; documents and files • Based on open-source (publicly available) information or “open-source intelligence” (OSINT) • Does not involve the breaking of network controls to access information • Assumes benign information in isolation may be turned malicious in combination and / or relationship to other data (as in “big data” analytics) • Is a “dual use” technology with a range of applied “data harvesting” / structure- mining / datamining and analytical uses
  • 9.
  • 10. TYPE OF MACHINE ON MALTEGO • Company Stalker: Email addresses at a company’s domain(s) • Footprint L1: “Fast” and limited footprint of a domain • Footprint L2: “Mild” and semi-limited footprint of a domain • Footprint L3: “Intense” and fairly in-depth and internal footprint of a domain • Person- Email Address: Identifies a person’s email addresses (but needs a disambiguated or fairly uncommon name…or the data is noisy) • Prune Leaf Entities: Prunes all leaves (entities with no outgoing links and just one incoming link—aka pendant nodes) to clear the screen for re-crawls (and to de-noise the data
  • 11. TYPE OF MACHINE • Twitter Digger: Phrase as a Twitter search • Twitter Geo(graphical) Location: Finding a person’s location based on multiple information streams • Twitter Monitor: Monitors Twitter for hashtags (#) and named entities mentioned (@) • URL to Network and Domain Information: From URL to network and domain information
  • 12. NODE LEVEL TRANSFORM • Devices • A phone, mobile device, or other used by the individual or connected to various accounts or a network • Infrastructure • AS – Autonomous System Number (as assigned by IANA to RIRs) • DNS Name – Domain Name System (identification string) • Domain – Internet Domain • IPv4 Address – IP version 4 address • MX Record – DNS mail exchanger record (indicator of mail server accepting email messages and how email should be routed through SMTP) • NS Record – A DNS name server record (with indicators of subdomains) • Netblock – An internet autonomous system • URL – An internet Uniform Resource Locator (web address as a character sting) • Website – An internet website (related web pages served from a single domain)
  • 13. NODE LEVEL TRANSFORM • Locations • A location on Earth (to find domains and other such information) • Penetration (“Pen”) Testing • Company • Social Network • Facebook Object • Twit entity • Affiliation – Facebook • Affiliation – Twitter • Personal • Alias • Document • Email Address • Image (EXIF or “Exchangeable Image File” data extraction: geotagged data, GPS, and general image conditions information like digital camera settings) • Person • Phone Number • Phrase
  • 14. DEMO