Additional virtualisation infrastructure

27 11 2014

Virtual environments introduce a host of new features that are designed to increase the availability and manageability of computer systems. These features include the ability to move live virtual machines across physical hosts with little to no disruption to service and even automatically shift entire workloads and power off unnecessary physical hosts, to better utilise power consumption.

These features rely heavily on networks to transmit information between physical hosts. An example of one feature that is dependent on one of these new networks is VMware’s vMotion. VMotion allows virtual machines to be moved across hosts in an infrastructure, allowing hosts to be taken down for maintenance or patching. This is done by transmitting a snapshot of the VM’s RAM across a network to the receiving host. Features like vMotion mean that systems benefit from extremely high uptime, with relatively low cost implications, in comparison to their traditional counterparts. Although vMotion is a VMware product, the concept of live migration is the same concept across numerous implementations, including Xen’s implementation named ‘XenMotion’.

The information that is now transmitted over these networks as a result of these features can pose serious security considerations that are not comparable in traditional systems. The movement of RAM from outside the chassis of a server tower is something that has not been an issue prior to these features. Now is it possible (in poorly designed implementation) for entire portions of RAM to be sent unencrypted over user-accessible networks.

The new networks introduced into virtual infrastructures are not exclusively reserved for HA features however. The centralisation of storage has also introduced fast, multi-connected, multipath routing storage networks, which connect the hosts to the data stores. The information that traverses these networks is that same that would have been transmitted over the internal SCSI or SATA connection in traditional servers. Storage offers increased capability when compared to its predecessor, an example of its capability is described by (Meth, et al., 2003):

“In a storage area network, it is possible to perform LAN-free and server-free backup operations that copy data from a storage device directly to another storage device without transferring the data across the general-purpose network and the servers.  In other words, data are sent across the dedicated storage area network directly between the source and destination storage devices.”

The Storage area network is an element of the virtual infrastructure that is often left unsecured as it is not uncommonly configured by separate groups of specialists who are not as security conscious as the networking teams (Lewis, 2002). While SAN security is a very pertinent threat when discussing virtual environments, I will not be detailing how attacks and mitigation techniques can be achieved in this blog because of the level of familiarity that is required and the difference in technologies when compared to regular networking. There are however numerous pre-existing guides to SAN security that should be consulted before introducing the technology into any environment (BROCADE, 2007), (Haron, 2002), (Majstor, 2004).

Microsoft , 2012. The OSI Model’s Seven Layers Defined and Functions Explained. [Online] Available at: http://support.microsoft.com/kb/103884?wa=wsignin1.0

Lewis, M., 2002. Unsecure SANs invitation for hackers. [Online] Available at: http://searchstorage.techtarget.com/news/812240/Unsecure-SANs-invitation-for-hackers

BROCADE, 2007. The Growing Need for Security in Storage Area Networks. [Online] Available at: http://www.hds.com/assets/pdf/white-paper-for-security-in-storage-area-networks.pdf

Haron, M., 2002. Is Your Storage Area Network Secure? An Overview of Storage Area Network from Security Perspective. [Online] Available at: http://www.sans.org/reading_room/whitepapers/storage/storage-area-network-secure-overview-storage-area-network-security-perspective_516

Majstor, F., 2004. Storage Area Networks Security Protocols and Mechanisms. [Online] Available at: http://www.employees.org/~franjo/papers/SAN_Security_WP_v1.pdf

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Mitigation techniques for management interfaces

13 11 2014

In VMware’s hardening guide, they offer a number of mitigation techniques that can be used to further secure vCenter from exploitation. The majority of the recommended measures around securing vCenter are of an operational nature rather than reconfiguring settings within VMware. A total of six of the options concerning vCenter alone in the documentation include measures that should be taken in the network to avoid the likelihood of MiTM attacks. Much the same as in my earlier post on hypervisors and throughout my blog, isolating these networks from any user reachable subnet is an advised approach for all management interfaces. If an attacker is unable to directly query the target, they are not able to directly exploit it without exploiting another system or finding a flaw in the software controlling the ACL’s. Although the segmentation approach will thwart the majority of conventional attacks, it is the authors opinion that securing such high target interfaces with usernames and passwords is inadequate and that further authentication processes are necessary.

In an article regarding storage security (Schulz, et al., 2005) commented:

“The strength of any authentication mechanism is based on the quality of the implementation and the strength of credentials. If the credentials are weak, or if authentication data is exposed due to faulty implementation, the mechanism itself can and will be defeated”

While not native to the vSphere product, it is possible to use third party solutions, such as HyTrust (HyTrust, 2012) to require ‘two factor authentication’ for access to the interface. It is also possible to enable two-factor authentication on other admin interfaces such as HP’s iLO. This adopts the defence-in-depth model that is used to ensure that the integrity of a system is not dependent on only one element.

When two-factor authentication is not available, standard network protection measures should be followed that are intransigent with traditional aspects of network security, such as strong passwords and account lockout policies.  It is also advisable to use the method of least privilege when creating the accounts that will have access to the management interfaces, to reduce the result of an attack. All management interfaces have differing levels of customization from the lesser granular options of the Cisco UCS to the highly configurable VMware vCenter. When configuring a user account in VMware’s vCenter, an administrator has the ability to granularly allow/deny individual actions on individual machines that are managed in that environment. An example of the granularity of vCenter’s permissions can be seen in Figure 1. Restricting user’s access to only allow access to the areas of the interface that are needed will reduce the total impact to the environment should a compromise of that account occur.

A small percentage of the options available when configuring permissions in vCenter

A small percentage of the options available when configuring permissions in vCenter

Schulz, G. et al., 2005. Virtualization Journal. [Online] Available at: http://virtualization.sys-con.com/node/48056

HyTrust, 2012. Two factors are better than one. [Online] Available at: http://www.hytrust.com/solutions/security/two-factor





Post exploitation on management interfaces

7 11 2014

Once an attacker successfully gains admin access to a particular element of the management infrastructure, what is possible? In traditional networks, the compromise of an ‘Enterprise admin’ or ‘root’ would be a worst case scenario. Using this account, an attacker could logon to servers, delete accounts and data/policies and affect services running on those servers. Although without pre-defined scripting, all the actions would need to be done manually on each server, which of course would have time implications. The attack would be effective, but once identified, action could be taken on uncompromised servers and machines not connected on the network by a domain trust would remain unaffected.

Now consider a fully virtualised environment that is fully managed by a single management interface (which, from the author’s experience, is not uncommon). Should an attacker obtain admin access to a management interface, then the implications are much greater.

Data centre management system (vCenter, SCOM)

If an attacker was to gain admin access to the management software that controls the environment, the implications from a defensive point are devastating. From inside the console they would be able to delete configurations, virtual switches and even full machines from both a management and disk perspective. What is often done in large environments is to create a disaster recovery environment in another location of the campus/business, so in the event of a loss of service in one location, the mirror environment could be used. It is not uncommon for both locations to be managed by the same management software as it allows increased replication and failover. While this may increase availability and functionality, it also means that gaining access to the one system could potentially allow an attacker to erase an entire site including any recovery environment.

While it may not have the same initial impact, there are also a number of other actions that could be completed by the attacker once access to a management interface is gained. Misconfigurations in the way the hardware performs could go unnoticed for a long period of time, but still cause huge disruption to services that may be harder and more time consuming to identify. There are also persistent attacks that could be configured for snooping, such as placing switches into promiscuous mode in order to preform undetected information gathering. It is also possible from the interface to copy full machines offline and boot them up using consumer tools such as VMware Player (VMware, 2012) for analysis and offline attacks (Siebert, 2011).

Storage interfaces

While there are only so many actions that can be done as a result of gaining access to the interfaces that manage the storage, they are equally disruptive. Entire disk arrays can be

remotely wiped, resulting in the loss of multiple servers and data stored on that storage in one action. Disks could also be misconfigured to affect performance on all machines operating on that array

Hardware management (iLO, DRAC, RSA, On-board Administrator)

With access to the hardware management interface an attacker would be able to perform physical actions on the infrastructure remotely. These control the hardware that manages the hardware of the hypervisors, the interface fabric, power and cooling on blade systems. Although most of the actions from here are reversible, they still present a single targetable area that has the potential to severely affect service for a considerable period of time.

 

Siebert, E., 2011. Five VMware security breaches that should never happen. [Online] Available at: http://searchvmware.techtarget.com/tip/Five-VMware-security-breaches-that-should-never-happen





Attacking management interfaces

29 09 2014

The management interfaces and everything that is incorporated into that software is, in the author’s opinion the most problematic area in virtualisation security today. There have been numerous attempts over the last few years to demonstrate how management interfaces can be breeched. The majority of these attacks are general attacks that use pre-existing attack methods such as brute forcing, MiTM (man-in-the-middle) and the numerous flaws with the PKI infrastructure. There are multiple proven attack methods available for exploiting management interfaces and below are descriptions of some of these attacks that have been discovered by researchers.

In an online blog (Mluft, 2011)  talks about how a brute force attack is achievable on the Amazon Web Services (AWS) portal by leveraging existing hacking software tools. In the attack (Mluft, 2011) demonstrated how it is possible to determine a successful logon using the exemplary payloads in the Burp Suite (Burp Suite, 2012). The use of the burp suite in this example is to simply automate the process of attempting logins to the interface. The payload in the software is also able to identify failed login attempts to the portal by returning a HTTP status code of 200 (Network Working Group , 1999). A correct password attempt is identified by a returned HTTP status code of 302. Using the documentation provided by Amazons services in relation to password policies (Mluft, 2011) created an appropriate wordlist and used the burp suite to attempt all the possible permutations. After 400,000 attempts the attack was paused and the results purged for the 302 status code. The code was found and also shown alongside was the value and the password attempted. This gave the attacker the username and password for the administration of all servers managed by that account. It should be noted that all of these attempts were originated from one IP address without the account being locked-out or subject to any account throttling.

As discussed earlier my earlier blog artical regarding the hypervisor, the Virtualization Assessment Toolkit (VASTO) has been developed to exploit multiple weaknesses, predominantly in the VMware family. As well as the identification module that returns the exact version of the server, it includes numerous attacks on virtual systems including a specific VMware brute forcing module, which mimics the attack on the AWS portal by (Mluft, 2011). One of the main contributors to the VASTO project (Criscione, 2010) demonstrated a number of the different functions found in VASTO at Blackhat USA 2010.  Although (Criscione, 2010) demonstrated how VASTO can be used at multiple layers of the virtual stack (Client, Hypervisor, Support, Management and internal), the majority concentrated on the management portion. (Criscione, 2010) confirms that although the (VMware, 2012) hardening guide recommends segmentation of management networks, these recommendations are often ignored and left situated on the same networks as traditional servers.

These servers that manage the entire fabric of the infrastructure have multiple attack vectors – from the operating systems they are installed on to the web services running the interfaces. Vulnerabilities in any one of these platforms can potentially jeopardise the security of an entire environment and should be taken very seriously.

The other element used in the VASTO modules which can target the management portion of the virtual infrastructure uses target flaws in the VMware components and implementation to expose threats in the infrastructure. One of the exploits that is included in the VASTO suite that best demonstrates how multiple components in these systems can be used for exploitation, originates via a flaw in the Jetty (Eclipse, 2012) web server that is used by vCenter Update manager. In the author’s opinion, this attack signifies how the complexity and code overhead that these management servers introduce, make securing virtual environments in an efficient manner, one that needs to be understood and prioritised. I will briefly give a breakdown of this attack to highlight the multiple elements that were used to complete the attack.

The Update Manager component of the vSphere suite is designed to secure the environment by automating the patching and updating process of hosts that fall under its management scope. However, (Criscione, 2010) recognised that the update manager requires a version of Jetty web server to operate. This is an additional component that is added to the total footprint of the management server. The version of Jetty installed prior to version 4.1 u1 (update 1) of the update manager was a version vulnerable to a directory traversal attack (Wilkins, 2009), which allowed attackers to view any files on a server that the Windows SYSTEM user has privileges. Consequentially vCenter stored a file on the server called “vpxd-profiler-*” which is a file used by administrators for debugging purposes. In this extensive file the, SOAP Session ID’s of all the users that have connected to that server are contained. With this ID the vmware_session_rider module, found in the VASTO toolkit, acts as a proxy server to allow the attacker to then connect through it into the vCenter server using the selected administrator SOAP ID. Once this is completed, the attacker is able to create a new admin credential within vCenter to ensure future access.

Another example of how different elements of the management interface could be used to gain access to vCenter is through VMware’s use of Apache Tomcat technology (The Apache Software Foundation, 2012). When navigating to a vCenter server through a web browser one is presented with the standard vSphere “Getting started” screen as is shown in figure 1

Web browser connection to vCenter server

Web browser connection to vCenter server

Connection to that same servers IP address, but specifying the default tomcat Tomcats index page port of “8443” over an SSL connection shows further information, including a link to login as the “Tomcat manager”. This page is shown in figure 2

The web interface seen when you navigate to vCenter with a port of 8443

The web interface seen when you navigate to vCenter with a port of 8443

In VMware version 4.1 there is a user named “VMwareAdmin” that is automatically added to the Tomcat server, which has full admin rights to the Tomcat service. In the earlier versions of VMware, the password for this admin account was 5 characters long starting with 3 uppercase, 1 number and one lowercase. This leaves an attacker with a number of options for an attacking perspective. The most obvious is to brute force the credentials with a compatible tools or script such as the Apache tomcat brute force tool (Snipt, 2011). A second (and more sophisticated attack) would be to use the folder traversal vulnerability introduced by the Jetty service to gain read access to the server. From here the attacker could navigate to the “tomcat-users.xml” file (C:\Program Files\VMware\Infrastructure\tomcat\conf) as shown in Figure 3, which is an XML file found in VMware 4.1 and which shows the clear text credentials of the account.

(left) The tomcat-users.xml file showing the username and password of a default admin account (Right) tomcat manager login prompt

(left) The tomcat-users.xml file showing the username and password of a default admin account (Right) tomcat manager login prompt

Using this access, an attacker is able to control elements of the web service with admin rights. As shown in Figure 4, one is able to change a number of settings through the tomcat interface, including the ability to upload custom WAR files, which can be created using Metaspolit to upload meterpreter payloads to the server.

Logged in to the tomcat manager using the credentials found on server

Logged in to the tomcat manager using the credentials found on server

Although some of the attacks using the VASTO toolkit are specific and use vulnerabilities that have almost all been patched by VMware (at the time of writing), the management interfaces are still vulnerable to more general network attacks that are not as fundamental to secure as simply applying a patch or updating to the newest version. As is explained briefly in by post on hypervisors, access to these interfaces are vulnerable to MiTM attacks and the implementations dependence on a highly insecure certificate/PKI model. These vulnerabilities are not directly the responsibility of the vendors, but certainly nothing has been done by them to address this issue.

I will not be explaining the process of how MiTM attacks and flaws in the certificate infrastructure can be used to capture login credentials, as this a fundamental part of security and has been covered on numerous occasions by multiple sources (Irongeek, 2012) (Schneier, 2011). I have also written about the overarching problems with the certificate model and how it can be bypassed by in a blog post from 2011.

 

Mluft, 2011. The Key to your Datacenter. [Online] Available at: http://www.insinuator.net/2011/07/the-key-to-your-datacenter/

Criscione, C., 2010. Blackhat 2010 – Virtually Pwned. USA: Youtube.

Wilkins, G., 2009. Vulnerability in ResourceHandler and DefaultServlet with aliases. [Online] Available at: http://jira.codehaus.org/browse/JETTY-1004

Irongeek, 2012. Using Cain to do a “Man in the Middle” attack by ARP poisoning. [Online] Available at: http://www.irongeek.com/i.php?page=videos/using-cain-to-do-a-man-in-the-middle-attack-by-arp-poisoning

Schneier, B., 2011. Schneier on Security. [Online] Available at: http://www.schneier.com/blog/archives/2011/09/man-in-the-midd_4.html





Mitigation techniques for shared hardware

4 06 2014

The concept of mitigation techniques to reduce the likelihood of shared hardware attacks are similar to that of the hypervisor techniques in terms of determining which machines have access to which host. To ensure isolation of the hosts, the same measures can be used as described in an earlier post regarding hypervisors, such as using DRS groups and in larger cloud environments specific hardware-conscious options such as the ‘Dedicated VDC’ in VMware’s vCloud Datacentre. While host isolation techniques can be achievable using these methods, they only address physical component allocation at the host portion such as RAM, CPM, mezzanine cards/NIC’s etc. What these do not address however is the issue of shared storage and blade infrastructures.

Where ‘in house’ storage is concerned, separate groups of arrays could be used to reduce the implications an attack could have due to what systems they could affect. In the same way that DRS groups were created in the hypervisor demonstrations, machines could be grouped by security rating so that less secure machines are not placed on the same array as other higher valued machines. This mitigates the risk of a less secure system threatening the performance of a group of higher target machines due to vulnerabilities found in the VM. With this measure however there is also the consideration that in doing so, you are creating one high target area that could be attacked, affecting all the core services. The increase to security that segmentation of disk arrays creates unfortunately has an adverse effect on resource efficiency, as the smaller the array the higher the disk overhead (Shangle, 2012), (International Computer Concepts, 2012).

There are options within some VMMM’s (certainly within vCenter) to evenly distribute and limit the amount of IOPS a single machine is able to request. This can be set at the machine level using the resource allocation section, and set based on a per machine level. Within the vCenter suite ‘share values’ can also be set to individual machines and automatically limit disk allocation, should disk latency reach a certain threshold. The latter option is not included into the core functionality of the vSphere suite and therefore is at an additional licence cost. In the figure below you will see that the limit has been set to 1000 IOP’s for the ‘Public-Web’ virtual machine. While this option does stop the ability for one machine to overwhelm the entire storage, it can also unnecessarily restrict genuine requests from VM’s, should they experience a higher than normal workload.

Using the free IOPs limiting ability in vCenter

Using the free IOPs limiting ability in vCenter

 

The additional licencing cost of VMware’s ‘Storage I/O Control’ allows one to associate a share value with machines rather than a set resource threshold. A latency figure can be set on a LUN and should that threshold be reached vCenter will ensure that the machine with the highest costing will get the specified disk allocation required. To protect internally hosted environments, core servers would be given the highest costing while less importance, more vulnerable machines would be allocated lower figures to ensure that key functions of the business continue to function, should this type of attack take place.

In circumstances where these options are not available in the VMMM, such as is the case with the standard Hyper-V manager, which “does not have any built in mechanism to dynamically or even statically control storage I/O”  (Berg, 2011), alternative solutions will be required.

Avoiding sharing is undoubtedly the simplest option when securing high risk, mission critical systems. The challenge becomes more complicated when considering public cloud environments. Avoiding storage contention due to noisy or malicious neighbours on a public cloud service is one that should be seriously considered before any cloud adoption takes place. Many big companies are now using the public cloud infrastructure to host their services. Amazon has had impressive adoption rates with online services including Netflix (Buisiness Wire, 2010), Reddit (Berg, 2010), MySpace (High Scalibility, 2010) and many others now opting to migrate their entire business onto Amazons EC2/EC3 infrastructure.

One example of how resource contention can be avoided within a public cloud was undertaken by Netflix’s (Cockcroft, 2011), who extensively researched the inner workings of Amazons EBS (Elastic Block Store) so that they could best utilize the service and not be affected by neighbours’ disk requirements. (Cockcroft, 2011) discovered that Amazons EBS volumes were between 1 GB and 1Tb in allocated size and it was deemed that allocating volumes in 1TB blocks to the Netflix servers regardless of their actual storage requirements avoids the likelihood of co-tenancy and, in turn, storage contention. Amazon makes this a more feasible option to determine the sizing of disks as the whole EC2 service has a large amount of information available, especially when compared to other providers. Having access to this level of information should be a key consideration when planning any cloud migration.

The threat of an exploit at the blade hardware layer is an extremely difficult attack to mitigate against and one that cannot be achieved without taking unrealistic precautions that undermine the reasoning and benefits of a blade system altogether. While there may be scope within the larger blade systems to use separate physical interconnect modules to ensure that secure and insecure machines use different routes in and out of the enclosure, there is still the backplane of the chassis, which is completely shared among all hosts. As mentioned prior, hardware attacks at this layer of the system would most likely be DOS attacks rather than disclosure and have yet to be demonstrated.

Shangle, R., 2012. Level 0,1,2,3,4,5,0/1. [Online]  Available at: http://it.toolbox.com/wiki/index.php/Level_0,1,2,3,4,5,0/1

Buisiness Wire, 2010. Netflix Selects Amazon Web Services To Power Mission-Critical Technology Infrastructure. [Online]  Available at: http://www.thestreet.com/story/10749647/netflix-selects-amazon-web-services-to-power-mission-critical-technology-infrastructure.html

Cockcroft, A., 2011. Understanding and using Amazon EBS – Elastic Block Store. [Online] Available at: http://perfcap.blogspot.co.uk/2011/03/understanding-and-using-amazon-ebs.html

Berg, . M. v. d., 2011. Storage I/O control for Hyper-V. [Online]  Available at: http://up2v.nl/2011/06/20/storage-io-control-for-hyper-v/





Attacking shared hardware used for virtualisation

5 05 2014

There are a number of conjectural and proven attacks that involve the exploitation of shared hardware. One of the more relevant attacks that threaten virtual environments is the ability to degrade the performance of other machines by causing an unpredictable strain on the shared hardware. This could be possible either by taking control of a virtual machine in the environment through an existing software exploit or in the case of a cloud provider, simply by purchasing one. Amazon has multiple security measures in place to deal with inside attacks on their Amazon Web Services (AWS) platform, although with the pricing of a Microsoft Windows instance costing as little as $0.115 per hour, there is a very low cost entry for attackers.  While one moderately powered machine would not be able to affect numerous neighbouring client’s ‘performance’ on Amazon’s infrastructure, this low entry figure demonstrates how little it would cost to rent multiple instances for a clustered attack.

Although not primarily considered a security issue, resource contention is a major issue within virtual systems, especially when operating in multi-tenant environments. The term “noisy neighbours” is used to describe virtual instances of a machine sharing the same host or storage as another and affecting its performance. Problems caused by noisy neighbours or resource intensive virtual machines are typically due to either a misconfiguration or simply from being unfortunate enough to be placed on the same hardware as other high performance machines. However, when considering this issue from a security perspective, if an attacker is able to place a number of machines on the shared hardware as a competitor’s machine, they have the ability to degrade the performance. There has been prior research conducted into determining the internal mappings of a machine within large cloud infrastructures. One paper entitled “Hey, You, Get Off of My Cloud!”  by (Ristenpart, et al., 2009), the authors use the Amazon EC2 service as their environment to test the ability to map the internal location of machines and discuss how this information can be used to construct machines that co-reside with specific targets.  While the specific methods involved in determining the internal location of a machine in large cloud environments are out of scope of this article, in the paper “Hey, You, Get Off of My Cloud!” (Ristenpart, et al., 2009) a description of how an accurate mapping can be achieved using “timestamp fingerprinting” and “Cache-Based Detection” is given.

Studies often measure the impact that noisy neighbours cause on co-residing tenants by analysing RAM, CPU or network usage. While these are relative elements that are affected, one major drawback in only measuring these aspects is that disk activity, such as the IOPS (Input/Output Operations Per Second) on to shared storage is not taken into consideration. This can be one of the more difficult elements to measure, as storage arrays can differ greatly in both size and performance, even within the same provider. Misbehaving disk activity can also be much more erratic in its usage, especially when compared to RAM, which tends to gradually increase rather than produce the spikes in performance that are seen in IOPS.

One attack that would be possible using shared storage would be to use the mapping techniques discovered by (Ristenpart, et al., 2009) to place a group of machines on the same storage array or LUN as a target before generating high I/O. If the activity generated was high enough, contention for disk access would be experienced by all machines using that storage and as a result, machines become noticeably slower, due to the disk latency created. Amazon EC2 does not limit the amount of I/O that a machine can use, as it is a chargeable resource that is billed based on usage to the owning customers account. These charges would obviously not be a problem for an attacker using a stolen credit card for example. While there are a number of articles (Cockcroft, 2011) about the consequences of sharing storage with other busy or malfunctioning VM’s, the author has not found any documentation on using heavily crafted IOPS as being a documented or recognised attack.  A demonstration of how this attack could be carried out is shown later in this section.

Attacks that use shared hardware as a vector are not only capable of producing new attack vectors that affect the availability, but all three aspects of the Confidentiality, Integrity, Availability (CIA) Triad (Perrin, 2008). The confidentiality of machines on virtual systems should also be a consideration before the adoption takes place.  While some of the attacks that surround exploiting the confidentiality and integrity portion of the CIA Triad using shared hardware can fall on the academic side of the spectrum rather than active exploits, these concepts should at least be taken into consideration, especially by high risk targets.

One example of how a shared CPU can be manipulated is (Phil, 2012) demonstration of how two machines running on the same host can communicate with each other without using any networking protocols. This types of attack is typically knows as side-channel attack and has been a known issue for a number of years (Page, 2003), (Osvik, et al., 2005).  In (Phil, 2012) ‘virtualisation specific attack’, there are a number of pre-requisites required for the attack to be successful. These include both of the virtual machines requiring the same number of processors and running on the VMware platform with unlimited CPU resources. However, once all of the appropriate elements are in place (Phil, 2012) was able to send data bits from one VM to another over the CPU by oversubscribing the hardware. While these attacks may be an extremely niche and inefficient with transfer rates being as slow as 0.5bits/sec (depending on the noise of other machines on that host), it does show the principals of how attacking virtual machines at this layer is possible.

An area that the author would be interested in investigating further (due to being unable to find any research that has been undertaken in the area) would be the security implications of shared hardware involved in blade environments. The most effective way to ensure the integrity of an environment is to adopt the ultra-cautious approach of disconnecting machines from the internet and any other connecting networks. This is known as an ‘air-gap’, and is typically used to secure high target environments such as SCATA (supervisory control and data acquisition) systems. Blade systems such as PowerEdge M1000e offer “compelling operational benefits, such as improved cabling, rapid hardware provisioning, high compute density, energy-efficient design and increasing management automation”, which can offer enough resources to individually power an entire large organisation or business. Using VLAN’s, multiple networks can be hosted within the one enclosure including Demilitarized Zones (DMZ) and Virtual Desktop Infrastructures (VDI). While research has been done into the sharing of components such as RAM, CPU etc., elements of the blade environment such as the chassis backplane and connection fabric into the system pose an equal if not greater risk. If malicious software was able to infect the software that manages these physical elements of the system they could potentially monitor and affect the integrity of information to and from any virtual machine or host.

As discussed earlier, when placed on the same storage array as a number of machines, an attacker may be able to affect the performance of other machines by requesting large amounts of disk I/O on a shared storage array. To demonstrate the plausibility of this attack the author conducted a simulation of two attack machines and one target machines that were placed on the same storage array. I will post a full description of the simulation in a separate posting. To demonstrate the disruption caused by this attack, the experiment will be using the built-in monitoring tool ‘esxtop’. The figure indicated under the GAVG/cmd column is the figure that will best demonstrate the impact the attack has on the storage array. This figure identifies the “response time as it is perceived by the guest operating system” by adding the “average response time in milliseconds per command being sent to the device” (DAVG/cmd)  to “the amount of time the command spends in the VMkernel” (KAVG/cmd).

The simulation used three machines to demonstrate this process, two representing the controlled machines of the attacker and one the victim machine. Both of the attacking machines are running a freely available Microsoft SQL I/O stress testing/benchmarking utility named “SQLIO”. To simulate high I/O the author initiates the utility using a snippet of the parameters shown below.

“sqlio -kW -s10 -frandom -o8 -b8 -LS -Fparam.txt

sqlio -kR -s360 -frandom -o8 -b8 -LS -Fparam.txt…”

 The ‘frandom’ perimeter in the SQLIO utility generates random reads and writes rather than sequential, as random disk activity is known for being more intensive on storage devices (Kelkar, 2011). This resulted in the number of read operations on one of the attacking machines to rise to a consistent rate of 5323.41 commands per second, causing the GAVG to rise from zero to 82.31 milliseconds on the attacking machine and from zero to 47.41ms on the victim machine. While these contention results fluctuated during the tests, the GAVG was consistently above 30 ms on both one of the attacking machines and the victim machine during the test as is shown in Figure 1 and on the graph in Figure 2.

Statistics for each machine during the I/O tests

Figure 1 – statistics for each machine during the I/O tests

The average figures that were shown by the monitoring software also demonstrate the high latency that was experienced by each machine. To demonstrate the impact that the attack has on the machines response time (GAVG), Figure 2 shows the average GAVG figure that was reported by each VM before the script is run and then for the following 5 minutes. The graph shows that the average GAVG before the script was run was instant at 0ms, but once the script was initiated this figure increased, peaking at around 82ms. The average response time for the victim machine throughout the 5 minute period was 46.77ms, which is 36.77ms above that recommended by VMware.

Figure 9 - Graph showing the average millisecond GAVG response time reported for each guest OS during the testing

Figure 2 – Graph showing the average millisecond GAVG response time reported for each guest OS during the testing

This graph demonstrates that it is possible for an attacker with machines located on the same shared storage array as their target, to be able to adversely affect the performance of other machines through over subscription of the hardware.

 

Sources:

Ristenpart, T., Tromer, E., Shacham, H. & Savage, S., 2009. Hey, You, Get Off of My Cloud: Exploring Information Leakage in Third-Party Compute Clouds. [Online]  Available at: http://cseweb.ucsd.edu/~hovav/dist/cloudsec.pdf

Cockcroft, A., 2011. Understanding and using Amazon EBS – Elastic Block Store. [Online]  Available at: http://perfcap.blogspot.co.uk/2011/03/understanding-and-using-amazon-ebs.html

Perrin, C., 2008. The CIA Triad. [Online]
Available at: http://www.techrepublic.com/blog/security/the-cia-triad/488

Osvik, D. A., Shamir, A. & Tromer, E., 2005. Cache Attacks and Countermeasures: the Case of AES. Rehovot: Department of Computer Science and Applied Mathematics.

 





Introduction to Shared hardware

10 04 2014

The ability to distribute resources across multiple physical machines has played a pivotal role in the growth of virtualisation today. The term elastic computing is sometimes used to describe the nature of virtualised environments as resources can be added and retracted dependent on their need. In traditional environments, high performance CPU’s were often required to accommodate fluctuations in processing requirements, however the average utilisation of the CPU is typically below 10% . Shown in the table below is a VMware comparison of the hardware requirement for three different industries and their CPU average utilisation, when compared to that of a virtual implementation. The chart compares the computing requirements for three different industries and demonstrates how the use of virtualisation can lower the number of physical servers, while also improving elements of services and setup time.

Table demonstrating the benefits of virtualisation by comparing the typical computing requirement of three different industries (VMware, 2006)

Table demonstrating the benefits of virtualisation by comparing the typical computing requirement of three different industries (VMware, 2006)

The benefits of virtualisation span further than processing however, storage being another area that benefits tremendously. Storage area networks (SAN’s) are used to centrally manage storage in one location rather than managing multiple RAID sets in an individual chassis. Much like CPU’s, resources can be added to machines dynamically rather than requiring all resources to be factored in during initial installation, thus reducing the total cost of ownership (TCO).

The ability to share resources also results in exponential improvements in availability. As entire infrastructures can effectively run on one piece of hardware such as with blade systems, adding multiple layers of redundancy is a one-time process that benefits all machines residing in that system throughout the lifetime of all the servers within the infrastructure. Equipping traditional tower or rack servers with the level of redundancy that is seen in a blade system or datacentre would be highly impractical and costly.
However, with this new capacity to share resources across multiple machines comes a host of vectors that require planning and mitigation methods to be in place before adoption. When removing oneself from the obvious benefits offered by shared resources and observing from a security perspective, the idea of having multiple machines sharing the same sticks of RAM, CPU and hard disks seems likely to introduce some negative security implications.

As is covered in an earlier article on hypervisors, machines hosted on the same host can be vulnerable to attacks through misconfigurations and software exploits within the hypervisor and this is no different with the hardware aspect. Guests residing on the same host as other guests can potentially interfere with each other using the very hardware they both run on. All of these attacks and opportunities to interfere with host neighbours are especially pertinent when considering the implications associated with a public cloud perspective.

In the same way it is possible for attackers to craft exploits against the software to exploit the hypervisor and it is also possible to target behaviours in the hardware of virtual systems to exchange information and disrupt service. When describing hardware attacks, the author will not discuss the implications and methods in obtaining physical access to the hardware in this section, as in the author’s opinion once physical access is gained to any hardware system then it is easy to compromise the security. All of the attacks in this next article are achievable through remote access to the system.