An introduction to honeyclient technologies

Christian Seifert

Angelo Dell'Aera

Speakers

Christian Seifert

• Full Member of the Honeynet Project since 2007

• PhD from Victoria University of Wellington, NZ

• Research Software Engineer @ Microsoft Bing

Angelo Dell'Aera

• Full Member of the Honeynet Project since 2009

• Senior Threat Analyst @ Security Reply (7 years)

• Information Security Independent Researcher @ Antifork Research (13 years)

Agenda

Introduction Honeyclient technologies Low-Interaction (PhoneyC) High-Interaction (Capture-HPC) Malware Distribution Networks Challenges and Future Work

New trends, new tools

In the last years more and more attacks against client systems

The end user as the weakest link of the security chain

New tools are required to learn more about such client-side attacks

New trends, new tools

The browser is the most popular client system deployed on every user system

A lot of vulnerabilities are daily identified and (almost always) reported in the most used browsers

The browser is currently the preferred way to own an host

Honeyclients

What we need is something which seems like a real browser the same way as a classical honeypot system seems like a real vulnerable server

A real system (high-interaction)

Or an emulated one (low-interaction)?

Queuer

Visitor

Analysis Engine

Low-interaction strengths and weaknesses

+ Different browser versions (“personalities”)

+ Different ActiveX and plugins modules (even different versions)

+ Much more safer

+ More scalable

- Easy to detect

PhoneyC - Brief History

A pure Python low-interaction honeyclient First version developed by Jose Nazario Great improvements during GSoC 2009 And the history continues...

PhoneyC – DOM Emulation

“The Document Object Model is a platform- and language-neutral interface that will allow programs and scripts to dynamically access and update the content, structure and style of documents. The document can be further processed and the results of that processing can be incorporated back into the presented page.” (W3C definition)

• Huge improvements during GSoC 2009 Python object __getattr__ and __setattr__ methods

PhoneyC - Browser Personalities

Currently supported personalities: Internet Explorer 6.0 (Windows XP) Internet Explorer 6.1 (Windows XP) Internet Explorer 7.0 (Windows XP) Internet Explorer 8.0 (Windows XP) Internet Explorer 6.0 (Windows 2000) Internet Explorer 8.0 (Windows 2000)

Easy to add new personalities

PhoneyC - Javascript Engine

Based on SpiderMonkey, the Mozilla implementation of the Javascript engine HoneyJS: a bridge between Python and SpiderMonkey which wraps a subset of its APIs HoneyJS based on python-spidermonkey

PhoneyC - Vulnerability Modules

Python-based vulnerability modules Core browser functionalities Browser plugins (Mock) ActiveX controls

PhoneyC - Shellcode detection and emulation

HoneyJS“The shellcode manipulation and the spraying of the fillblock involve assignments.The shellcode will be detected immediately on its assignment if we are able to interrupt spidermonkey at the interpretion of certain bytecodes related to an assignment and check its arguments and values for shellcodes”

Libemu integration (shellcode detection, execution and profiling)

PhoneyC - Future Improvements

A new and more reliable DOM (Document Object Model) emulation

Replacing Spidermonkey with Google V8 Mixed static/dynamic analysis for detecting

potential attacks

High-interaction Client Honeypot

• Real system• Observe effects of attack

Request

Response

Request

Attack MaliciousServer

BenignServer

No state changesdetectedNew file appearedin start up folder

Client Honeypots

High-interaction strengths and weaknesses

+ No emulation necessary

+ Accurate classification (extremely low false positive rate)

+ Ability to detect zero-day attacks

+ More difficult to evade

- Miss attacks

- “Dangerous”

- More computationally expensive

Capture-HPC (v2.5) - Functionality

• Platform Independence *

• Flexibility around client application

• Forensically ready• Records information at kernel level• Collects modified files (e.g. malware)• Collects network traffic (pcap)

• Maintained by the New Zealand Honeynet Project Chapter

Malware Distribution Networks

Malware Distribution NetworksOverview

• Set of web servers (network) controlled by a group of cyber criminals to distribute malware efficiently

• Specialized structures that support specialized roles of the cyber criminal

• Malware distribution networks allow for campaigns and temp renting out components of the distribution network

Malware Distribution Networks

Source: Microsoft Security Intelligence Threat Report (http://www.microsoft.com/sir)

Malware Distribution Network

Exploit Servers12.8% of exploit servers responsible for 84.1% of drive-by-download pages

Source: Microsoft Security Intelligence Threat Report (http://www.microsoft.com/sir)

Challenges and Future Work

Malware Distribution Network

Malware Distribution NetworksFast-Flux

LP1 LP2

R1

ES1 ES2

R2

• LP infected with script that contacts twitter to obtain popular topics (e.g. japan)

• From popular query from last week, script constructs host name (e.g. “j” + date)

• Next day, the same LP will contact twitter to obtain popular topics (e.g. tunesia)

• Now, it will construct different host name (e.g. “t” + date)

• Attacker registers hostname a few days in advance twitter.com h1 h2 h3 h4 h5 h6 h7 h8 h9 h10

3/19/2011 1 13/20/2011 1 13/21/2011 1 1 13/22/2011 1 1 13/23/2011 1 1 13/24/2011 1 1 13/25/2011 1 1 13/26/2011 1 1 13/27/2011 1 1 13/28/2011 1 1 13/29/2011 1 1

Evasion Techniques

• Technology Differences (Browser vs Honeyclient)

• Human vs Machine Interaction

• Decrease visibility

The Threats

IntegrityAvailability

Confidentiality

Drive-by-Downloads

Cookie, history, file, and clipboard stealing

Network scanners

Phishing

Crashes

Popup floods

Network floods/ Puppetnets

Web spam/ junk pages

Cross-X attacksHosting of malware

Drive-by-pharming

Social Engineering

References

• Jose Nazario, “PhoneyC: A virtual client honeypot”, LEET 2009

The Honeynet Project, KYE: Malicious Web Servers, http://www.honeynet.org/papers

Junjie Zhang, Jack Stokes, Christian Seifert and Wenke Lee, ARROW: Generating Signatures to Detect Drive-By Downloads, in proceedings of www conference, Hyderabad, India, 2011

Microsoft, Security Intelligence Threat Report, http://www.microsoft.com/sir

Thanks for the attention

Questions?Christian Seifert <christian.seifert@honeynet.org>Angelo Dell'Aera <angelo.dellaera@honeynet.org>

http://code.google.com/p/phoneyc/https://projects.honeynet.org/capture-hpc