(My) Brucon 2017 notes (1)

Here are my quick notes from the BruCON 2017 conference. All the slides can be found here.

Detecting malware when it is encrypted – machine learning for network https analysis

The goal is to find a way to detect malware using htps without decrypting the traffic.

Context:

  • 1/2 of the world wide Internet traffic is encrypted
  • 10%-40% of all malware traffic is encrypted
  • the encryption interferes with the efficacy of classical detection techniques

Some solutions to the problems:

  • TLS inspection; basically is the reverse proxy which is in the middle between the server and the client
    • advantage – can use the classical detection method
    • drawback – proxy server is expensive.
    • drawback – computationally demanding
  • try to find with no HTTPS decryption

Detect malware with no HTTPS decryption

Dataset used:

Used the pro ids product to capture different logs:

  • connection.log/s
  • ssl.log/s
  • x509.log/s

All this logs will be aggregated in order to create ssl aggregations and then generate a ssl-connect-units (each ssl-connect-unit represents a SSL connection). Each ssl-connect-unit have a source IP, destination IP, destination port, protocol and other 40 features (properties) like number of packages, number of bytes, number of different certificates, ratio of established and not established states .

A data set was created from all this ssl-connection-units and machine learning algorithms have been used against this dataset.

(ML) Algorithms used

  • XGBoost (Extreme Gradient Boosting)
  • Random forest
  • Neural network
  • svm

After using all this ML algorithms the features that have been identified as the most important ones to detect malware traffic:

  • certificate length of validity
  • inbound and outbound packets
  • number of domains in certificate
  • ssl/tls version
  •  periodicity

 

Knock Knock… Who’s there? admin admin and get in! An overview of the CMS brute-forcing malware landscape.

The talk was about malware brute force attacks of WordPress web sites which is the most used CMS product.

historical overview of the brute-force malware

2009 – first distributed brute force attack against WordPress
2013 – firstDisco also isntalled backdoors in the system
2014 – Mayhem
2015 – Aetra
2015 – CMS Catcher
2015- Troldeshkey
2017 – Stantinko

deep dive of SATHURBOT malware

modular botnet , 4 modules:

  • backdoor module
  • crawling module
  •  brute force module

Evading Microsoft ATA for Active Directory Domination

Microsoft ATA

  • Microsoft Advanced Threat Analytics
  • a product that detects attacks by reading traffic
  • how is deployed; an ATA gateway that intercepts the traffic

Threats detected by ATA:

  • recon
  • compromised credentials
  • lateral movement
  • domain dominance

Evading ATA :

  •  not poking the DC (Domain Controller) is the key
  • If you can’t bypass it then ovoid it by minimal talk with the DC

Atacking ATA deployment:

  • ATA console can be identified with basic banner grabbing.

Secure channels: Building real world crypto systems

What are secure channels – goal is to guarantee the confidentiality and integrity of data travelling over untrusted network.

objectives of a secure channel:

  • confidentiality
  • integrity establishment
  • authenticity

Constructing a secure channel:

  • need a way to exchange keys; keys establishment protocol
  • need a key derivation phase

Secure channel protocol design phases :

  • channel establishment
  • key establishment
  • secure data transfer
  • finish the protocol

How to build efficient security awareness programs

Some quotes from the talk:

  • Security problems are arising where more than one security technology are overlapping.
  • Stop trying to fix human behavior with tech only;maybe that are other ways to fix that.
  • Security isn’t always a business problem, but it’s always a human problem.
  • Tools to fix the human factor in security:
    • Fear
    • Incentives
    • Habits
      • trigger
      • routine
      • reward
      • repeat

Open Source Security Orchestration

Context:

  • multiple cloud severs, all using same Fail2ban jail.
  • How can make the different servers communicate.

In security operations most of the workflows are manual despite of multitude of solutions.
Different scenarios on which the automation could help a lot:

  • firewall role propagation scenario
  • drop propagation scenario
  • prevent known threats scenario
  • capture threat activity scenario

How to do the orchestration: using Adaptive Network Protocol (ANP)

  • developed so that nodes can share event information with each other
  • needed an ANP agent installed on each node.
Shlomi Zeltsinger

Blockchain made simple