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Deserialization Attacks Surge Motivated by Illegal Crypto-mining

Deserialization Attacks Surge Motivated by Illegal Crypto-mining

Imperva’s research group is constantly monitoring new web application vulnerabilities. In doing so, we’ve noticed at least four major insecure deserialization vulnerabilities that were published in the past year.
Our analysis shows that, in the past three months, the number of deserialization attacks has grown by 300 percent on average, turning them into a serious security risk to web applications.
To make things worse, many of these attacks are now launched with the intent of installing crypto-mining malware on vulnerable web servers, which gridlocks their CPU usage.
In this blog post we will explain what insecure deserialization vulnerabilities are, show the growing trend of attacks exploiting these vulnerabilities and explain what attackers do to exploit them (including real-life attack examples).

What Is Serialization?

The process of serialization converts a “live” object (structure and/or state), like a Java object, into a format that can be sent over the network, or stored in memory or on disk. Deserialization converts the format back into a “live” object.
The purpose of serialization is to preserve an object, meaning that the object will exist outside the lifetime of the local machine on which it is created.
For example, when withdrawing money from an ATM, the information of the account holder and the required operation is stored in a local object. Before this object is sent to the main server, it is serialized in order to perform and approve the needed operations. The server then deserializes the object to complete the operation.

Types of Serialization

There are many types of serialization available, depending on the object which is being serialized and on the purpose. Almost all modern programming languages support serialization. In Java for example an object is converted into a compact representation using byte stream, and the byte stream can then be reverted back into a copy of that object.
Other types of serialization include converting an object into a hierarchical format like JSON or XML. The advantage of this serialization is that the serialized objects can be read as plain text, instead of a byte stream.

Deserialization Vulnerabilities from the Past Three Months

In the OWASP top 10 security risks of 2017 insecure deserialization came in at eighth place and rightfully so as we argued in our previous blog about the state of web application vulnerabilities in 2017.
In 2017, major new vulnerabilities related to insecure serialization, mostly in Java, were published (see Figure 1).

Name Release Date (Day/Month/Year) Vulnerability details
CVE-2017-12149 01/08/2017 Vulnerability in the JBoss Application Server allows execution of arbitrary code via crafted serialized data because the HTTP Invoker does not restrict classes for which it performs deserialization
CVE-2017-10271 21/06/2017 Vulnerability in the Oracle WebLogic Server allows execution of arbitrary code due to insufficient sanitizing of user supplied inputs in the wls-wsat component
21/06/2017 The REST Plugin in Apache Struts uses an XStreamHandler with an instance of XStream for deserialization without any type filtering, which can lead to remote code execution when deserializing XML payloads.
CVE-2017-7504 05/04/2017 The HTTPServerILServlet.java in JMS allows remote attackers to execute arbitrary code via crafted serialized data because it does not restrict the classes for which it performs deserialization

Figure 1: CVEs related to insecure deserialization
In order to understand the magnitude of these vulnerabilities, we analyzed attacks from the past three months (October to December of 2017) that try to exploit insecure deserialization. A key observation is the steep increase of deserialization attacks in the past few months, as can be seen in the Figure 2.

Figure 2: Insecure deserialization attacks over the course of three months
Most of the attackers used no attack vectors other than insecure deserialization. We noticed that each attacker was trying to exploit different vulnerabilities, with the above-mentioned CVEs being the most prevalent.
For a full list of CVEs related to insecure deserialization from the past few years see Figure 3.

Name Relevant System Public Exploit Name Relevant System Public Exploit
CVE-2017-9844 SAP NetWeaver Yes CVE-2016-2170 Apache OFBiz No
CVE-2017-9830 Code42 CrashPlan No CVE-2016-2003 HP P9000, XP7 Command View Advanced Edition (CVAE) Suite No
CVE-2017-9805 Apache Struts Yes CVE-2016-2000 HP Asset Manager No
CVE-2017-7504 Red Hat JBoss Yes CVE-2016-1999 HP Release Control No
CVE-2017-5878 Apache OpenMeetings Yes CVE-2016-1998 HP Service Manager No
CVE-2017-5645 Apache Log4j No CVE-2016-1997 HP Operations Orchestration No
CVE-2017-5641 Apache BlazeDS Yes CVE-2016-1986 HP Continuous Delivery Automation No
CVE-2017-5586 OpenText Documentum D2 Yes CVE-2016-1985 HP Operations Manager No
CVE-2017-3159 Apache Camel Yes CVE-2016-1487 Lexmark Markvision Enterprise No
CVE-2017-3066 Adobe ColdFusion Yes CVE-2016-1291 Cisco Prime Infrastructure Yes
CVE-2017-2608 Jenkins Yes CVE-2016-0958 Adobe Experience Manager No
CVE-2017-12149 Red Hat JBoss Yes CVE-2016-0788 Jenkins Yes
CVE-2017-11284 Adobe ColdFusion No CVE-2016-0779 Apache TomEE No
CVE-2017-11283 Adobe ColdFusion No CVE-2016-0714 Apache Tomcat No
CVE-2017-1000353 CloudBees Jenkins Yes CVE-2015-8765 McAfee ePolicy Orchestrator No
CVE-2016-9606 Resteasy Yes CVE-2015-8581 Apache TomEE No
CVE-2016-9299 Jenkins Yes CVE-2015-8545 NetApp No
CVE-2016-8749 Jackson (JSON) Yes CVE-2015-8360 Atlassian Bamboo No
CVE-2016-8744 Apache Brooklyn Yes CVE-2015-8238 Unify OpenScape No
CVE-2016-8735 Apache Tomcat JMX Yes CVE-2015-8237 Unify OpenScape No
CVE-2016-7462 VMWare vRealize Operations No CVE-2015-8103 Jenkins Yes
CVE-2016-6809 Apache Tika No CVE-2015-7501 Red Hat JBoss Yes
CVE-2016-5229 Atlassian Bamboo Yes CVE-2015-7501 Oracle Application Testing Suite No
CVE-2016-5004 Apache Archiva Yes CVE-2015-7450 IBM Websphere Yes
CVE-2016-4385 HP Network Automation No CVE-2015-7253 Commvault Edge Server Yes
CVE-2016-4372 HP iMC No CVE-2015-6934 VMWare vCenter/vRealize No
CVE-2016-3642 Solarwinds Virtualization Manager Yes CVE-2015-6576 Atlassian Bamboo No
CVE-2016-3461 Oracle MySQL Enterprise Monitor Yes CVE-2015-6555 Symantec Endpoint Protection Manager Yes
CVE-2016-3427 JMX Yes CVE-2015-6420 Cisco (various frameworks) No
CVE-2016-3415 Zimbra Collaboration No CVE-2015-5348 Apache Camel No
CVE-2016-2510 Red Hat JBoss BPM Suite No CVE-2015-5254 Apache ActiveMQ No
CVE-2016-2173 Spring AMPQ No CVE-2015-4852 Oracle WebLogic Yes
CVE-2016-2170 Apache OFBiz No CVE-2015-3253 Jenkins Yes
CVE-2016-2003 HP P9000, XP7 Command View Advanced Edition (CVAE) Suite No CVE-2012-4858 IBM Congnos BI No

Figure 3: CVEs related to insecure deserialization

Deserialization Attacks in the Wild

Most of the attacks that we saw are related to byte-stream serialization of Java objects. Also, we saw some attacks related to serialization to XML and other formats, see Figure 4.

Figure 4: Distribution of vulnerabilities over different serialization formats
In the following attack (see Figure 5) the attacker is trying to exploit CVE-2017-10271. The payload is sent in the HTTP request’s body using a serialized Java object through XML representation.
Attack vector containing serialized java array into XML fig 5
Figure 5: Attack vector containing a serialized java array into an XML
The fact that this is a Java array can be seen by the hierarchical structure of the parameters, with the suffix of “java/void/array/void/string”. The attacker is trying to run a bash script on the attacked server.
This bash script tries to send an HTTP request using “wget” OS command, download a shell script disguised as a picture file (note the jpg file extension) and run it. Few interesting notes can be made examining this command:

  • The existence of shell and “wget” commands indicate that this payload is targeting Linux systems
  • Using a picture file extension is usually done to evade security controls
  • The “-q” parameter to “wget” stands for “quiet”, this means that “wget” will have no output to the console, hence it will be harder to note that such a request was even made. Once the downloaded script runs the server is infected with a crypto mining malware trying to mine Monero digital coins (a crypto currency similar to Bitcoin).

The next script (see Figure 6) tries to exploit the same vulnerability, but this time the payload is targeting Windows servers using cmd.exe and Powershell commands to download the malware and run it.
Attack vector infect Windows server with crypto mining malware fig 6
Figure 6: Attack vector trying to infect Windows server with crypto mining malware
This indicates that there are two different infection methods for Windows and Linux server, each system with its designated script.
Another example is the following payload (Figure 7) that we pulled from an attack trying to exploit a deserialization vulnerability with a Java serialized object.
Attack vector containing java serialized object
Figure 7: Attack vector containing a Java serialized object trying to download a crypto miner
The “bad” encoding is an artifact of Java serialization, where the object is represented in the byte stream.
Still, we can see a script in plain text marked in yellow. Shown as an image below is a variable that defines an internal field separator, where in this case it is just a variable for space. The variable is probably used instead of a space to try to make the payload harder to detect.

Just as in the previous examples, this Bash script targets Linux servers that send an HTTP request using “wget” to download a crypto miner.

Beyond Insecure Deserialization

The common denominator of the attacks above is that attackers are trying to infect the server with a crypto mining malware by using an insecure deserialization vulnerability. However insecure deserialization is not the only method to achieve this goal.
Below (Figure 8) we see an example of another attack payload, this time at the “Content-Type” header.
Attack vector using RCE vulnerability of Apache Struts fig 8
Figure 8: Attack vector using an RCE vulnerability of Apache Struts
This attack tries to exploit CVE-2017-5638, a well-known RCE vulnerability related to Apache Struts which was published in March 2017 and was covered in a previous blog post.
When it was originally published we saw no indications of crypto miners in the attacks’ payloads related to this CVE, and most of the payloads were reconnaissance attacks.
However, in this attack the payload (marked in yellow above) is very similar to the payload from the previous example. Using the same remote server and the exact same script, it infected the server with crypto mining malware.
This old attack method with a new payload suggests a new trend in the cyber arena – attackers try to exploit RCE vulnerabilities, new and old, to turn vulnerable servers into crypto miners and get a faster ROI for their “effort”.


Given the many new vulnerabilities related to insecure deserialization that were discovered this year, and its appearance in the OWASP top 10 security risks, we expect to see newer related vulnerabilities released in 2018. In the meantime, organizations using affected servers are advised to use the latest patch to mitigate these vulnerabilities.
An alternative to manual patching is virtual patching. Virtual patching actively protects web applications from attacks, reducing the window of exposure and decreasing the cost of emergency patches and fix cycles.
A WAF that provides virtual patching doesn’t interfere with the normal application workflow, and keeps the site protected while allowing the site owners to control the patching process timeline.
Learn more about how to protect your web applications from vulnerabilities with Imperva WAF solutions.