Skip to content

CheYenBzh/BTG

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

BTG

Not every IOC deserve to enter your internal MISP instance, for obvious quality reasons. But it may be usefull for you analyst to be able to do a broader research on IOC published online.

BTG with TOR IP

This tool allows you to qualify one or more potential malicious markers of different type (URL, MD5, SHA1, SHA256, SHA512, IPv4, IPv6, domain etc..). You can run this tool with a Gnu/Linux environement. The Windows compatibility is currently working in BETA version.

BTG was born from a need for Conix's collaborators. During their activities, SOC and DFIR analysts face off a lot of information and metadata of multiple nature that they must identify as malicious or not.

Many knowledge-bases of malicious known activity (aka IOC) are accessible online on various website like VirusTotal, ZeusTracker etc. SOC and CERT can also have their own internal database such as MISP.

Daily tasks for SOC and DFIR analysts is therefore marked out by the research of data like IP addresses, hashs, domains; on these private or public knowledge-bases; these are repetitive and time-consuming actions.

Thus CERT-Conix created a tool allowing analysts to qualify such elements searchling many sources.

asciicast

Module list:

DShield
Lehigh
Malekal
Malwaredomains
Malwaredomainlist
MalwareTeks
MISP (Malware Information Sharing Platform)
Tor exit nodes
OpenPhish
Palevo
VirusTotal
ZeusTracker

Installation

sudo pip install -r requirements
cp config.py.editme config.py
vim config.py 

Activate and fill licence key for modules you need to use.

Usage

python BTG.py http://mydomain.com 1a72dca1f6a961f528007ef04b6959d8 45.34.191.173

Authors

  • Lancelot Bogard
  • Robin Marsollier

About

BTG's purpose is to make fast and efficient search on IOC

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%