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Cybercrime and Attacks in the
Dark Side of the Web
Dr. Marco Balduzzi*
Senior Researcher at Trend Micro
http://www.madlab.it @embyte
*With the cooperation of Mayra
Rosario and Vincenzo Ciancaglini
Marco Balduzzi - Cyber-crime and attacks in the dark side of the web - Codemotion Milan 2017
The Dark Ecosystem
Dark Nets
• TOR
• I2P
• Freenet
Custom DNS
• Namecoin
• Emercoin
Rogue TLDs
• Cesidian Root
• OpenNIC
• NewNations
• …
A perfect platform for Cybercrime
Our Investigative System: DEMO
timestamp:[2015-01-01 TO 2015-12-31] AND title:marketplace
Our Gateway to the Dark Internet
Privoxy +
TOR
anonymizer
Squid transparent proxy
Polipo +
TOR 64
instances
I2P Freenet Custom DNS resolver (DNSMASQ)
Namecoin
DNS
rogueTLD DNS
Cesidian
root
Opennic NameSpace …
Data Exploration
Headless
browser
HAR Log
Page
DOM
Screen
Shot
Title
Text
Metadata
Raw
HTML
Links
Email
Bitcoin
Wallets
Headless Browser
Scrapinghub's Splash
• QTWebkit browser, Dockerized, LUA scriptable
• Full HTTP traces
Crawler based on Python's Scrapy +
multiprocess + Splash access
• Headers rewrite
• Shared queue support
• Har log -> HTTP redirection chain
Extract links, emails, bitcoin wallets
Data Analysis
Embedded links
classification (WRS)
• Surface Web links
• Classification and
categorization
Page translation
•Language detection
•Non-English to English
Significant wordcloud
• Semantic clustering
• Custom algorithm
Significant Wordcloud
Page text
Tokenization
Filtering
Semantic
distance matrix
Hierarchical
clustering
Cluster label
and popularity
Word cloud
Scrap text from HTML, clean up, strip spaces, etc
Create list of (word, frequency) pairs
Keep only substantives
How “far” are words from one another?
Group similar words
Label clusters, sum frequencies
Draw using summed frequencies
lxml
NLTK.wordnet
Wordcloud
(pillow)
The Dark Portal
Examples
Guns
Identities and Passports
Credit Cards
Accounts, e.g. Israeli Paypal
Cashout services
Bulletproof Hosting Providers
Impact on organizations
Dark Web traffic is difficult to be detected by
traditional systems (IDS)
Resilient and stealth malware
Persistence and monitoring (APT)
TorrentLocker, i.e. variant of CryptoLocker
Payment page hosted in TOR
◎wzaxcyqroduouk5n.onion/axdf84v.php/user_code=qz1n2i&user_pass=9019
◎wzaxcyqroduouk5n.onion/o2xd3x.php/user_code=8llak0&user_pass=6775
Cashout via BITCOINS
Ransomware
Keylogger
Organized Attacks
We simulated a
cybercriminal
installation in the
Dark Web
Honeypot
I. Black Market
II. Hosting Provider
III. Underground Forum
IV. Misconfigured Server
(FTP/SSH/IRC)
Technology
I. Wordpress + Shells
II. OsCommerce
III. Custom Web App
IV. Custom OS (Linux)
Marco Balduzzi - Cyber-crime and attacks in the dark side of the web - Codemotion Milan 2017
Registration-Only Forum
Exposes a Local File Inclusion
A 7-months experiment
Month 1: Different advertisement strategies to honeypot #1
#DailyPOSTRequests
Average of 1.4 malicious
uploads per day
Manual VS Automated Attacks
Pre-installed web shells attracted the most of “visitors”
CMS #1-2 reached via Google Dorks (on Tor2Web), CMS #3 no because custom
CMS #2 reached via TOR’s search engine’s query “Index of /files/images/”
(http://hss3uro2hsxfogfq.onion)
# Attacks
# Days with Attacks
Traditional Web Attacks
Password-protected Shells
Smart use of Obfuscation
Abuse of Tor for Anonymized Attacks
(Anonymized) Phishing Campaign
Rival Gangs
• Cyber-criminal gangs
compromising opponents
• Self-promoting their
“business”
(TOR Keys)
Used to compute the hidden service descriptor
Instruction
Points
Public
Key
Private Key
Instruction
Points
Public
Key
XYZ.onion
Signing
Keypair
Generation
HS’ Private Key theft
400+ attacks
MiTM, hijack and decryption
Dark Web as “corner case” of the Internet… NO!
Active and Dynamic Underground Market
Motivated and Knowledgeable Attackers
Manual and Targeted Attacks
Modern and Sophisticated Threats
Lessons Learned
Thank You!
Dr. Marco Balduzzi*
Senior Researcher at Trend Micro
http://www.madlab.it @embyte
*With the cooperation of Mayra
Rosario and Vincenzo Ciancaglini

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