nDPI

Cybersecurity

How to Detect Domain Hiding (a.k.a. as Domain Fronting)
Domain fronting is a technique that was used in 2010s by mobile apps to attempt to bypass censorship. The technique relies on a “front” legitimate domain that basically acts as a pivot for the forbidden domain. In essence an attacker performs a HTTPS connection where in the DNS (used to resolve the domain name) and TLS SNI the legitimate domain name is used, whereas inside the HTTP connection in the “Host” HTTP header it specifies the forbidden domain Recently at DEF CON 28 a new tool named Noctilucent has been …
nDPI

Introducing nDPI Risk Analysis for (Cybersecurity) Network Traffic Analysis (was Ripple20)
Earlier last month Ripple20 became popular as it has listed some vulnerabilities found in a custom IP stack used by many IoT devices. Despite the hype on Ripple20, in essence the tool used to fingerprint vulnerable devices sends either malformed or valid (with some values in the allowed range albeit with values deprecated or obsolete) packets that are easy to catch (see Suricata and Zeek rules for detection). In essence IDS rules/scripts are checking whether packets sent on the wire are valid or if they contain unexpected values used by …
nDPI

Howto Identify and Block Telegram-based Botnets
Botnets are a popular way to run malware on a network using the command and control paradigm. Popular protocols used by botnets include IRC and HTTP. Most IDSs can detect bots as long as they can inspect the network traffic. This makes networks administrators blind when bots move to encrypted and cloud-based (i.e. that you cannot block with a simple IP-based ACL) protocols. The popular Telegram messaging system allows people to create a bot in minutes as shown in the code excerpt below.   bot = Bot(token) def run(): """ …
nDPI

Why Traffic Behaviour Analysis is Good (was Encrypting TLS 1.3 Traffic)
In the latest nDPI meetup, we have discussed future directions, including extending the current encrypted traffic analysis features. Currently nDPI supports both fingerprint and behaviour encrypted traffic analysis techniques to provide TLS traffic visibility. At ntop we have never liked too much fingerprinting techniques such as JA3 that are used by many popular IDSs and security tools, simply because they often lead to false positives making them a “nice to have” features but nothing more than that. Recently the IETF is designing a new TLS 1.3 extension named ECHO (Encrypted …
nDPI

How Lockdown Changed Corporate Internet Connectivity
Global lockdown has forced many people to work from remote: empty offices, all remote working until the emergency is over.   In essence during the lockdown remote workers used very few corporate services via VPN, with relatively light traffic (e.g. accounting) and the heavy videoconferencing traffic not propagating in the company networks: this as moderns videoconferencing solutions are all cloud based. So in essence moving to remote working has not put too much pressure on corporate networks beside the creation of VPN accounts or other limited changes. As you can …
nDPI

You’re invited to the future of nDPI: Python, Cybersecurity and Behaviour. May 15th, 4PM CET
Hi all, this is to invite you to an open discussion about nDPI, its future. In particular Python bindings, cybersecurity extensions and behaviour analysis. We will meet at 4PM CET (10AM EST) live on the Internet. For those who have not been able to join, this is the video of the session. Links: https://github.com/aouinizied/nfstream https://notebooks.gesis.org/binder/jupyter/user/aouinizied-nfstream-tutorials-mg04vt7x/tree Enjoy! …
nDPI

Trickbot Malware Analysis Using nDPI and ntopng
Trickbot is a malware distributed via malspam, spam emails containing links for downloading malicious files that infect computers.  A pcap file of a trickbot infection named 2019-09-25-Trickbot-gtag-ono19-infection-traffic.pcap can be downloaded at this URL. You can analyse the file using nDPI as follows ndpiReader -i 2019-09-25-Trickbot-gtag-ono19-infection-traffic.pcap -v 2 -J > /tmp/trickbot.txt Let’s now open the trickbot.txt file and search for “Risk”. This is a tag added to nDPI analysed flows when there is a non-zero security risk associated with the analysed traffic. Most problems include: Obsolete TLS protocol with self-signed certificate …
nDPI

Towards Traffic Behaviour Analysis: Introducing nDPI 3.2
This is to announce the new stable release of nDPI 3.2. The main trend of nDPI is to move from “simple” application protocol detection towards behavioral traffic interpretation. This has been implemented with the integration of modules for detecting attacks (e.g. SQL injections and XSS in HTTP) and behavioral indications on packet length/time/entropy as well indicators used for creating simple indicators typical of IDS systems. In essence nDPI is moving from protocol reporting to comprehensive traffic interpretation. nDPI now includes functions for efficiently serialising data in both JSON and binary …
nDPI

Effective TLS Fingerprinting Beyond JA3
JA3 is a popular method to fingerprint TLS connections used by many monitoring tools and IDSs. JA3 focuses on encryption options specified during TLS connection setup to fingerprint the encryption library used by the application. Image courtesy of Cisco So in essence the same JA3 fingerprint will match multiple applications, making JA3 unreliable (when used as single feature) to fingerprint traffic. There are several JA3 fingerprint databases available on the Internet you can use to identify (remember with some grade of uncertainty, thus with false positives) client applications or malware …
nDPI

Encrypted Traffic Analysis: A Primer
Monitoring encrypted traffic is must for providing visibility in modern traffic. Due to this we’ve put a lot of energy in extending nDPI so that it could be useful in this context. DPI (deep packet inspection) however is not enough for complete visibility, and thus we have started to add classification techniques and algorithm to nDPI to merge visibility and behavioural analysis. In fact flow-based analysis is not enough to understand what’s happening on a network without having a big picture. An this is what we’re doing in our tools, …
nDPI

Rethinking Network Flow Visualisation
Traffic monitoring applications often aggregate traffic in flows, that in essence is a way to divide traffic according to a 5-tuple key (Protocol, IP/port source/destination). Flows are then aggregated for instance according to IP address or protocol, and often represented with timeseries as the one below. What is missing in all this is how the traffic is distributed over time as everything is flattened, protocols are merged (for instance according the source IP address) and it is not possible to understand intra-flow relationships. For instance to see that when I …
nDPI

How to use nDPI from CLI to analyse network traffic
Most people use nDPI indirectly being it part of ntopng and many other non-ntop developed tools. However not many people know that nDPI can also be used from the command line to analyse network traffic. This is useful to create scripts to automate detection of specific issues. ndpiReader is a testing tool used to demonstrate the library features as well run validation tests. With this tool is also possible to generate a report in CSV format that can be analysed with tools such as q. Below you can find some …

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