NETRESEC Network Security Blog - Tag : Umbrella


CapLoader 1.6 Released

CapLoader 1.6

CapLoader is designed to simplify complex tasks, such as digging through gigabytes of PCAP data looking for traffic that sticks out or shouldn’t be there. Improved usability has therefore been the primary goal, when developing CapLoader 1.6, in order to help our users do their work even more efficiently than before.

Some of the new features in CapLoader 1.6 are:

  • Context aware selection and filter suggestions when right-clicking a flow, session or host.
  • Support for IPv6 addresses in the BPF syntax for Input Filter as well as Display Filter.
  • Flows that are inactive for more than 60 minutes are considered closed. This timeout is configurable in Tools > Settings.


Latency Measurements

CapLoader 1.6 also introduces a new column in the Flows tab labeled “Initial_RTT”, which shows the Round Trip Time (RTT) measured during the start of a session. The RTT is defined as “the time it takes for a signal to be sent plus the time it takes for an acknowledgment of that signal to be received”. RTT is often called “ping time” because the ping utility computes the RTT by sending ICMP echo requests and measuring the delay until a reply is received.

Initial RTT in CapLoader Flows Tab
Image: CapLoader 1.6 showing ICMP and TCP round trip times.

But using a PCAP file to measure the RTT between two hosts isn’t as straight forward as one might think. One complicating factor is that the PCAP might be generated by the client, server or by any device in between. If we know that the sniffing point is at the client then things are simple, because we can then use the delta-time between an ICMP echo request and the returning ICMP echo response as RTT. In lack of ping traffic the same thing can be achieved with TCP by measuring the time between a SYN and the returning SYN+ACK packet. However, consider the situation when the sniffer is located somewhere between the client and server. The previously mentioned method would then ignore the latency between the client and sniffer, the delta-time will therefore only show the RTT between the sniffer and the server.

This problem is best solved by calculating the Initial RTT (iRTT) as the delta-time between the SYN packet and the final ACK packet in a TCP three-way handshake, as shown here:

Initial Round Trip Time in PCAP Explained
Image: Initial RTT is the total time of the black/bold packet traversal paths.

Jasper Bongertz does a great job of explaining why and how to use the iRTT in his blog post “Determining TCP Initial Round Trip Time”, so I will not cover it in any more detail here. However, keep in mind that iRTT can only be calculated this way for TCP sessions. CapLoader therefore falls back on measuring the delta time between the first packet in each direction when it comes to transport protocols like UDP and ICMP.


Exclusive Features Not Available in the Free Trail

The new features mentioned so far are all available in the free 30 day CapLoader trial, which can be downloaded from our CapLoader product page (no registration required). But we’ve also added features that are only available in the commercial/professional edition of CapLoader. One such exclusive feature is the matching of hostnames against the Cisco Umbrella top 1 million domain list. CapLoader already had a feature for matching domain names against the Alexa top 1 million list, so the addition of the Umbrella list might seem redundant. But it’s actually not, the two lists are compiled using different data sources and therefore complement each other (see our blog post “Domain Whitelist Benchmark: Alexa vs Umbrella” for more details). Also, the Umbrella list contains subdomains (such as www.google.com, safebrowsing.google.com and accounts.google.com) while the Alexa list only contains main domains (like “google.com”). CapLoader can therefore do more fine-granular domain matching with the Umbrella list (requiring a full match of the Umbrella domain), while the Alexa list enables a more rough “catch ‘em all” approach (allowing *.google.com to be matched).

CapLoader Hosts tab with ASN, Alexa and Umbrella details

CapLoader 1.6 also comes with an ASN lookup feature, which presents the autonomous system number (ASN) and organization name for IPv4 and IPv6 addresses in a PCAP file (see image above). The ASN lookup is built using the GeoLite database created by MaxMind. The information gained from the MaxMind ASN database is also used to provide intelligent display filter CIDR suggestions in the context menu that pops up when right-clicking a flow, service or host.

CapLoader Flows tab with context menu for Apply as Display Filter
Image: Context menu suggests Display Filter BPF “net 104.84.152.0/17” based on the server IP in the right-clicked flow.

Users who have previously purchased a license for CapLoader can download a free update to version 1.6 from our customer portal.


Credits and T-shirts

We’d like to thank Christian Reusch for suggesting the Initial RTT feature and Daan from the Dutch Ministry of Defence for suggesting the ASN lookup feature. We’d also like to thank David Billa, Ran Tohar Braun and Stephen Bell for discovering and reporting bugs in CapLoader which now have been fixed. These three guys have received a “PCAP or it didn’t happen” t-shirt as promised in our Bug Bounty Program.

Got a t-shirt for crashing CapLoader

If you too wanna express your view of outlandish cyber attack claims without evidence, then please feel free to send us your bug reports and get rewarded with a “PCAP or it didn’t happen” t-shirt!

Posted by Erik Hjelmvik on Monday, 09 October 2017 08:12:00 (UTC/GMT)

Tags: #CapLoader #free #IPv6 #BPF #CIDR #PCAP #Umbrella #Alexa

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Domain Whitelist Benchmark: Alexa vs Umbrella

Alexa vs Umbrella

In November last year Alexa admitted in a tweet that they had stopped releasing their CSV file with the one million most popular domains.

Yes, the top 1m sites file has been retired

Members of the Internet measurement and infosec research communities were outraged, surprised and disappointed since this domain list had become the de-facto tool for evaluating the popularity of a domain. As a result of this Cisco Umbrella (previously OpenDNS) released a free top 1 million list of their own in December the same year. However, by then Alexa had already announced that their “top-1m.csv” file was back up again.

The file is back for now. We'll post an update before it changes again.

The Alexa list was unavailable for just about a week but this was enough for many researchers, developers and security professionals to make the move to alternative lists, such as the one from Umbrella. This move was perhaps fueled by Alexa saying that the “file is back for now”, which hints that they might decide to remove it again later on.

We’ve been leveraging the Alexa list for quite some time in NetworkMiner and CapLoader in order to do DNS whitelisting, for example when doing threat hunting with Rinse-Repeat. But we haven’t made the move from Alexa to Umbrella, at least not yet.


Malware Domains in the Top 1 Million Lists

Threat hunting expert Veronica Valeros recently pointed out that there are a great deal of malicious domains in the Alexa top one million list.

Researchers using Alexa top 1M as legit, you may want to think twice about that. You'd be surprised how many malicious domains end there.

I often recommend analysts to use the Alexa list as a whitelist to remove “normal” web surfing from their PCAP dataset when doing threat hunting or network forensics. And, as previously mentioned, both NetworkMiner and CapLoader make use of the Alexa list in order to simplify domain whitelisting. I therefore decided to evaluate just how many malicious domains there are in the Alexa and Umbrella lists.

hpHosts EMD (by Malwarebytes)

Alexa Umbrella
Whitelisted malicious domains: 1365 1458
Percent of malicious domains whitelisted: 0.89% 0.95%

Malware Domain Blocklist

Alexa Umbrella
Whitelisted malicious domains: 84 63
Percent of malicious domains whitelisted: 0.46% 0.34%

CyberCrime Tracker

Alexa Umbrella
Whitelisted malicious domains: 15 10
Percent of malicious domains whitelisted: 0.19% 0.13%

The results presented above indicate that Alexa and Umbrella both contain roughly the same number of malicious domains. The percentages also reveal that using Alexa or Umbrella as a whitelist, i.e. ignore all traffic to the top one million domains, might result in ignoring up to 1% of the traffic going to malicious domains. I guess this is an acceptable number of false negatives since techniques like Rinse-Repeat Intrusion Detection isn’t intended to replace traditional intrusion detection systems, instead it is meant to be use as a complement in order to hunt down the intrusions that your IDS failed to detect. Working on a reduced dataset containing 99% of the malicious traffic is an acceptable price to pay for having removed all the “normal” traffic going to the one million most popular domains.


Sub Domains

One significat difference between the two lists is that the Umbrella list contains subdomains (such as www.google.com, safebrowsing.google.com and accounts.google.com) while the Alexa list only contains main domains (like “google.com”). In fact, the Umbrella list contains over 1800 subdomains for google.com alone! This means that the Umbrella list in practice contains fewer main domains compared to the one million main domains in the Alexa list. We estimate that roughly half of the domains in the Umbrella list are redundant if you only are interested in main domains. However, having sub domains can be an asset if you need to match the full domain name rather than just the main domain name.


Data Sources used to Compile the Lists

The Alexa Extension for Firefox
Image: The Alexa Extension for Firefox

The two lists are compiled in different ways, which can be important to be aware of depending on what type of traffic you are analyzing. Alexa primarily receives web browsing data from users who have installed one of Alexa’s many browser extensions (such as the Alexa browser toolbar shown above). They also gather additional data from users visiting web sites that include Alexa’s tracker script.

Cisco Umbrella, on the other hand, compile their data from “the actual world-wide usage of domains by Umbrella global network users”. We’re guessing this means building statistics from DNS queries sent through the OpenDNS service that was recently acquired by Cisco.

This means that the Alexa list might be better suited if you are only analyzing HTTP traffic from web browsers, while the Umbrella list probably is the best choice if you are analyzing non-HTTP traffic or HTTP traffic that isn’t generated by browsers (for example HTTP API communication).


Other Quirks

As noted by Greg Ferro, the Umbrella list contains test domains like “www.example.com”. These domains are not present in the Alexa list.

We have also noticed that the Umbrella list contains several domains with non-authorized gTLDs, such as “.home”, “.mail” and “.corp”. The Alexa list, on the other hand, only seem to contain real domain names.


Resources and Raw Data

Both the Alexa and Cisco Umbrella top one million lists are CSV files named “top-1m.csv”. The CSV files can be downloaded from these URL’s:

The analysis results presented in this blog post are based on top-1m.csv files downloaded from Alexa and Umbrella on March 31, 2017. The malware domain lists were also downloaded from the three respective sources on that same day.

We have decided to share the “false negatives” (malware domains that were present in the Alexa and Umbrella lists) for transparency. You can download the lists with all false negatives from here:
https://www.netresec.com/files/alexa-umbrella-malware-domains_170331.zip


Hands-on Practice and Training

If you wanna learn more about how a list of common domains can be used to hunt down intrusions in your network, then please register for one of our network forensic trainings. The next training will be a pre-conference training at 44CON in London.

Posted by Erik Hjelmvik on Monday, 03 April 2017 14:47:00 (UTC/GMT)

Tags: #Alexa #Umbrella #domain #DNS #malware

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Recommended Books

» The Practice of Network Security Monitoring, Richard Bejtlich (2013)

» Applied Network Security Monitoring, Chris Sanders and Jason Smith (2013)

» Network Forensics, Sherri Davidoff and Jonathan Ham (2012)

» The Tao of Network Security Monitoring, Richard Bejtlich (2004)

» Practical Packet Analysis, Chris Sanders (2017)

» Windows Forensic Analysis, Harlan Carvey (2009)

» TCP/IP Illustrated, Volume 1, Kevin Fall and Richard Stevens (2011)

» Industrial Network Security, Eric D. Knapp and Joel Langill (2014)