[This post was originally authored November 27, 2009. I pushed it back to the top of the stack because I think it’s an interesting re-visitation of the benefits and challenges we are experiencing in Cloud today]
Below is an article I wrote many months ago prior to all the Nicholas Carr “electricity ain’t Cloud” discussions. The piece was one from a collection that was distributed to “…the Intelligence Community, the DoD, and Congress” with the purpose of giving a high-level overview of Cloud security issues.
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The Cloud in Context: Evolution from Gadgetry to Popular Culture
It is very likely that should one develop any interest in Cloud Computing (“Cloud”) and wish to investigate its provenance, one would be pointed to Nicholas Carr’s treatise “The Big Switch” for enlightenment. Carr offers a metaphoric genealogy of Cloud Computing, mapped to, and illustrated by, a keenly patterned set of observations from one of the most important catalysts of a critical inflection point in modern history: the generation and distribution of electricity.
Carr offers an uncannily prescient perspective on the evolution and adaptation of computing by way of this electric metaphor, describing how the scale of technology, socioeconomic, and cultural advances were all directly linked to the disruptive innovation of a shift from dedicated power generation in individual factories to a metered utility of interconnected generators powering distribution grids feeding all. He predicts a similar shift from insular, centralized, private single-function computational gadgetry to globally-networked, distributed, public service-centric collaborative fabrics of information interchange.
This phenomenon will not occur overnight nor has any other paradigm shift in computing occurred overnight; bursts of disruptive innovation have a long tail of adoption. Cloud is not the product or invocation of some singular technology, but rather an operational model that describes how computing will mature.
There is no box with blinking lights that can be simply pointed to as “Cloud” and yet it is clearly more than just timesharing with Internet connectivity. As corporations seek to drive down cost and gain efficiency force-multipliers, they have ruthlessly focused on divining what is core to their businesses, and expensive IT cost-centers are squarely in the crosshairs for rigorous valuation.
To that end, Carr wrote another piece on this very topic titled “IT Doesn’t matter” in which he argued that IT was no longer a strategic differentiator due to commoditization, standardization, and cost. This was followed by “The End of Corporate Computing” wherein he suggested that IT will simply subscribe to IT services as an outsourced function. Based upon these themes, Cloud seems a natural evolutionary outcome motivated primarily by economics as companies pare down their IT investment — outsourcing what they can and optimizing what is left.
Enter Cloud Computing
The emergence of Cloud as cult-status popular culture also has its muse anchored firmly in the little machines nestled in the hands of those who might not realize that they’ve helped create the IT revolution at all: the consumer. The consumer’s shift to an always-on, many-to-many communication model with unbridled collaboration and unfettered access to resources, sharply contrasts with traditional IT — constrained, siloed, well-demarcated, communication-restricted, and infrastructure-heavy.
Regardless of any value judgment on the fate of Man, we are evolving to a society dedicated to convenience, where we are not tied to the machine, but rather the machine is tied to us, and always on. Your applications and data are always there, consumed according to business and pricing models that are based upon what you use while the magic serving it up remains transparent.
This is Cloud in a nutshell; the computing equivalent to classical Greek theater’s Deus Ex Machina.
For the purpose of this paper, it is important that I point out that I refer mainly to so-called “Public Cloud” offerings; those services provided by parties external to the data owner who provides an “outsourced” service capability on behalf of the consumer.
This graceful surrender of control is the focus of my discussion. Private Clouds — those services that may operate on the corporation’s infrastructure or those of a provider but managed under said corporation’s control and policies, offers a different set of benefits and challenges but not to the degree of Public Cloud.
There are also hybrid and brokered models, but to keep focused, I shall not address these directly.
Cloud Reference Model
A service is generally considered to be “Cloud-based” should it meet the following characteristics and provide for:
- The abstraction of infrastructure from the resources that deliver them
- The democratization of those resources as an elastic pool to be consumed
- Services-oriented, rather than infrastructure or application-centric
- Enabling self-service, scale on-demand elasticity and dynamism
- Employs a utility-like model of consumption and allocation
Cloud exacerbates the issues we have faced for years in the information security, assurance, and survivability spaces and introduces new challenges associated with extreme levels of abstraction, mobility, scale, dynamism and multi-tenancy. It is important that one contemplate the “big picture” of how Cloud impacts the IT landscape and how given this “service- centric” view, certain things change whilst others remain firmly status quo.
Cloud also provides numerous challenges to the way in which computing and resources are organized, operated, governed and secured, given the focus on:
- Automated and autonomic resource provisioning and orchestration
- Massively interconnected and mashed-up data sources, conduits and results
- Virtualized layers of software-driven, service-centric capability rather than infrastructure or application- specific monoliths
- Dynamic infrastructure that is aware of and adjusts to the information, applications and services (workloads) running over it, supporting dynamism and abstraction in terms of scale, policy, agility, security and mobility
As a matter of correctness, virtualization as a form of abstraction may exist in many forms and at many layers, but it is not required for Cloud. Many Cloud services do utilize virtualization to achieve scale and I make liberal use of this assumptive case in this paper. As we grapple with the tradeoffs between convenience, collaboration, and control, we find that existing products, solutions and services are quickly being re-branded and adapted as “Cloud” to the confusion of all.keep focused, I shall not address these directly.
Modeling the Cloud
There exist numerous deployment, service delivery models and use cases for Cloud, each offering a specific balance of integrated features, extensibility/ openness and security hinged on high levels of automation for workload distribution.
Three archetypal models generally describe cloud service delivery, popularly referred to as the “SPI Model,” where “SPI” refers to Software, Platform and Infrastructure (as a service) respectively.
NIST – Visual Cloud Model
Using the National Institute of Standards and Technology’s (NIST) draft working definition as the basis for the model:
Software as a Service (SaaS)
The capability provided to the consumer is to use the provider’s applications running on a cloud infrastructure and accessible from various client devices through a thin client interface such as a Web browser (e.g., web-based email).
The consumer does not manage or control the underlying cloud infrastructure, network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.
Platform as a Service (PaaS)
The capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created applications using programming languages and tools supported by the provider (e.g., Java, Python, .Net). The consumer does not manage or control the underlying cloud infrastructure,
Infrastructure as a Service (IaaS)
The capability provided to the consumer is to rent processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly select networking components (e.g., firewalls, load balancers).
Understanding the relationship and dependencies between these models is critical. IaaS is the foundation of all Cloud services with PaaS building upon IaaS, and SaaS — in turn — building upon PaaS. We will cover this in more detail later in the document.
Peanut Butter & Jelly — Making the Perfect Cloud Sandwich
Infostructure/Metastructure/Infrastructure
To understand how Cloud will affect security, visualize its functional structure in three layers:
- The Infrastructure layer represents the traditional compute, network and storage hardware and operating systems familiar to us all. Virtualization platforms also exist at this layer and expose their capabilities northbound.
- The Infostructure layer represents the programmatic components such as applications and service objects that produce, operate on or interact with the content, information and metadata.
- Sitting in between Infrastructure and Infostructure is the Metastructure layer. This layer represents the underlying set of protocols and functions with layers such as DNS, BGP, and IP address management, which “glue” together and enable the applications and content at the Infostructure layer to in turn be delivered by the Infrastructure.
Certain areas of Cloud Computing’s technology underpinnings are making progress, but those things that will ultimately make Cloud the ubiquitous and transparent platform for our entire computing experience remain lacking.
Unsurprisingly, most of the deficient categories of technology or capabilities are those that need to be delivered from standards and consensus-driven action; things that have always posed challenges such as management, governance, provisioning, orchestration, automation, portability, interoperability and security. As security solutions specific to Cloud are generally slow in coming while fast innovating attackers are unconstrained by rules of engagement, it will come as no surprise that we are constantly playing catch up.
Cloud is a gradual adaptation rather than a wholesale re-tooling, and represents another cycle of investment which leaves us to consider where to invest our security dollars to most appropriately mitigate threat and vulnerability:
Typically, we react by cycling between investing in host-based controls > application controls > information controls > user controls > network controls and back again. While our security tools tend to be out of phase and less innovative than the tools of our opposition, virtualization and Cloud may act as much needed security forcing functions that get us beyond solving just the problem du jour.
The need to apply policy to workloads throughout their lifecycle, regardless of state, physical location, or infrastructure from which they are delivered, is paramount. Collapsing the atomic unit of the datacenter to the virtual machine boundary may allow for a simpler set of policy expressions that travel with the VM instance. At the same time, Cloud’s illusion of ubiquity and infinite scale means that we will not know where our data is stored, processed, or used.
Combine mobility, encryption, distributed resources with multiple providers, and a lack of open standards with economic cost pressure and even basic security capabilities seem daunting. Cloud simultaneously re-centralizes some resources while de-perimeterizing trust boundaries and distributing data. Understanding how the various layers map to traditional non-Cloud architecture is important, especially in relation to the Cloud deployment model used; there are significant trade-offs in integration, extensibility, cost, management, governance, compliance, and security.
Live by the Cloud, Die by the Cloud
Despite a tremendous amount of interest and momentum, Cloud is still very immature — pockets of innovation spread out across a long-tail of mostly-proprietary infrastructure-, platform-, and software-as-a-service offerings that do not provide for much in the way of or workload portability or interoperability.
Cloud is not limited to lower cost “server” functionality. With the fevered adoption of netbooks, virtualization, low-cost storage services, fixed/mobile convergence, the proliferation of “social networks,” and applications built to take advantage of all of this, Cloud becomes a single pane of glass for our combined computing experience. N.B., these powers are not inherently ours alone; the same upside can be used for wrongdoing.
In an attempt to whet the reader’s appetite in regards to how Cloud dramatically impacts the risk modeling, assumptions, and security postures of today, I will provide a reasonably crisp set of examples, chosen to bring pause:
Organizational and Operational Misalignment
The way in which most enterprise IT organizations are structured — in functional silos optimized to specialized, isolated functions — is diametrically opposed to the operational abstraction provided by Cloud.
The on-demand, elastic and self-service capabilities through simple interfaces and automated service layers abstract away core technology and support staff alike.
Few IT departments are prepared for what it means to apply controls, manage service levels, implement and manage security capabilities, and address compliance when the IT department is operationally irrelevant in that process. This leaves huge gaps in both identifying and managing risk, especially in outsourced models where ultimately the operational responsibility is “Cloudsourced” but the accountability is not.
The ability to apply specific security controls and measure compliance in mass-marketed Public Cloud services presents very real barriers to entry for enterprises who are heavily regulated, especially when balanced against the human capital (expertise) built-up by organizations.
Monoculture of Operating Systems, Virtualized Components, and Platforms
The standardization (de facto and de jure) on common interfaces to Cloud resources can expose uniform attack vectors that could affect one consumer, or, in the case of multi-tenant Public Cloud offerings, affect many. This is especially true in IaaS offerings where common sets of abstraction layers (such as hypervisors,) prototyped OS/application bundles (usually in the form of virtual machines) and common sets of management functions are used — and used to extend and connect the walled garden internal assets of enterprises to the public or semi-public Cloud environments of service providers operating infrastructure in proxy.
While most attack vectors target applications and information at the Infostructure layer or abuse operating systems and assorted hardware at the Infrastructure layer, the Metastructure layer is beginning to show signs of stress also. Recent attacks against key Metastructure elements such as BGP and DNS indicate that aging protocols do not fare well.
Segmentation and Isolation In Multi-tenant environments
Multi-tenancy in the Cloud (whether in the Public or Private Cloud contexts) brings new challenges to trust, privacy, resiliency and reliability model assertions by providers. Many of these assertions are based upon the premise that that we should trust — without reliably provable models or evidence — that in the absence of relevant illustration, Cloud is simply trustworthy in all of these dimensions, despite its immaturity. Vendors claim “airtight” information, process, application, and service, but short of service level agreements, there is little to demonstrate or substantiate the claims that software-enabled Cloud Computing — however skinny the codebase may be — is any more (or less) secure than what we have today, especially with commercialized and proprietary implementations.
In multi-tenant Cloud offerings, exposures can affect millions, and placing some types of information in the care of others without effective compensating controls may erode the ROI valuation offered by Cloud in the first place, and especially so as the trust boundaries used to demarcate and segregate workloads of different consumers are provided by the same monoculture operating system and virtualization platforms described above.
Privacy of Data/Metadata, Exfiltration, and Leakage
With increased adoption of Cloud for sensitive workloads, we should expect innovative attacks against Cloud assets, providers, operators, and end users, especially around the outsourcing and storage of confidential information. The uptake is that solutions focused on encryption, at rest and in motion, will have the side effect of more and more tools (legitimate or otherwise) losing visibility into file systems, application/process execution, information and network traffic. Key management becomes remarkably relevant once again — on a massive scale.
Recent proof-of-concepts such as so-called side- channel attacks demonstrate how it is possible to determine where a specific virtual instance is likely to reside in a Public multi-tenant Cloud and allow an attacker to instantiate their own instance and cause it to be located such that it is co-resident with the target. This would potentially allow for sniffing and exfiltration of confidential data — or worse, potentially exploit vulnerabilities which would violate the sanctity of isolated workloads within the Cloud itself.
Further, given workload mobility — where the OS, applications and information are contained in an instance represented by a single atomic unit such as a virtual machine image — the potential for accidental or malicious leakage and exfiltration is real. Legal intercept, monitoring, forensics, and attack detection/incident response are heavily impacted, especially at the volume and levels of traffic envisioned by large Cloud providers, creating blind spots in ways we can’t fathom today.
Inability to Deploy Compensating or Detective Controls
The architecture of Cloud services — as abstract as they ought to be — means that in many cases the security of workloads up and down the stack are still dependent upon the underlying platform for enforcement. This is problematic inasmuch as the constructs representing compute, networking and storage resources — and security — are in many cases themselves virtualized.
Further we are faced with more stealthy and evasive malware that is able to potentially evade detection while co-opting (or rootkitting) not only software and hypervisors, but exploiting vulnerabilities in firmware and hardware such as CPU chipsets.
These sorts of attack vectors are extremely difficult to detect let alone defend against. Referring back to the monoculture issue above, a so-called blue- pilled hypervisor, uniform across tens of thousands of compute nodes providing multi-tenant Cloud services could be catastrophic. It is simply not yet feasible to provide parity in security capabilities between physical and Cloud environments; the maturity of solutions just isn’t there.
These are heady issues and should not be taken lightly when considering what workloads and services are candidates for various Cloud offerings.
What’s old is news again…
Perhaps it is worth adapting familiar attack taxonomies to Cloud.
Botnets that previously required massive malware- originated endpoint compromise in order to function can easily activate in standardized fashion, in apparently legitimate form, and in large numbers by criminals who wish to harness the organized capabilities of Bots without the effort. Simply use stolen credit cards to establish fake accounts using a provider’s Infrastructure-as-a-Service and hundreds or thousands of distributed images could be activated in a very short timeframe.
Existing security threats such as DoS/DDoS attacks, SPAM and phishing will continue to be a prime set of tools for the criminal ecosystem to leverage the distributed and well-connected Cloud as well as targeted attacks against telecommuters using both corporate and consumerized versions of Cloud services.
Consider a new take on an old problem based on ecommerce: Click-fraud. I frame this new embodiment as something called EDoS — economic denial of sustainability. Distributed Denial of Service (DDoS) attacks are blunt force trauma. The goal, regardless of motive, is to overwhelm infrastructure and remove from service a networked target by employing a distributed number of attackers. An example of DDoS is where a traditional botnet is activated to swarm/overwhelm an Internet connected website using an asynchronous attack which makes the site unavailable due to an exhaustion of resources (compute, network, or storage.)
EDoS attacks, however, are death by a thousand cuts. EDoS can also utilize distributed attack sources as well as single entities, but works by making legitimate web requests at volumes that may appear to be “normal” but are done so to drive compute, network, and storage utility billings in a cloud model abnormally high.
An example of EDoS as a variant of click fraud is where a botnet is activated to visit a website whose income results from ecommerce purchases. The requests are all legitimate but purchases are never made. The vendor has to pay the cloud provider for increased elastic use of resources but revenue is never recognized to offset them.
We have anti-DDoS capabilities today with tools that are quite mature. DDoS is generally easy to spot given huge increases in traffic. EDoS attacks are not necessarily easy to detect, because the instrumentation and business logic is not present in most applications or stacks of applications and infrastructure to provide the correlation between “requests” and “ successful transactions.” In theexample above, increased requests may look like normal activity. Many customers do not invest in this sort of integration and Cloud providers generally will not have visibility into applications that they do not own.
Ultimately the most serious Cloud concern is presented by way of the “stacked turtles” analogy: layer upon layer of complex interdependencies at the Infastructure, Metastructure and Infostructure layers, predicated upon fragile trust models framed upon nothing more than politeness. Without re-engineering these models, strengthening the notion of (id)entity management, authentication and implementing secure protocols, we run the risk of Cloud simply obfuscating the fragility of the supporting layers until something catastrophic occurs.
Combined with where and how our data is created, processed, accessed, stored, and backed up — and by whom and using whose infrastructure — Cloud yields significant concerns related to on-going security, privacy, compliance and resiliency.
Moving Forward – Critical Areas of Focus
The Cloud Security Alliance (http://www. cloudsecurityalliance.org) issued its “Guidance for Critical Areas of Focus” related to Cloud Computing Security and defined fifteen domains of concern:
- Cloud Architecture
- Information lifecycle management
- Governance and Enterprise Risk Management
- Compliance & Audit
- General Legal
- eDiscovery
- Encryption and Key Management
- Identity and Access Management
- Storage
- Virtualization
- Application Security
- Portability & Interoperability
- Data Center Operations Management
- Incident Response, Notification, Remediation
- “Traditional” Security impact (business continuity, disaster recovery, physical security)
The sheer complexity of the interdependencies between the Infrastructure, Metastructure and Infostructure layers makes it almost impossible to recommend focusing on only a select subset of these items since all are relevant and important.
Nevertheless, those items in boldface most deserve initial focus just to retain existing levels of security, resilience, and compliance while information and applications are moved from the walled gardens of the private enterprise into the care of others.
Attempting to retain existing levels of security will consume the majority of Cloud transition effort. Until we see an expansion of available solutions to bridge the gaps between “traditional” IT and dynamic infrastructure 2.0 capabilities, any company can only focus on the traditional security elements of sound design, encryption, identity, storage, virtualization and application security. Similarly, until a standardized set of methods allow well-defined interaction between the Infrastructure, Metastructure and Infostructure layers, companies will be at the mercy of industry for instrumenting, much less auditing,
Cloud elements — yet, as was already stated, the very sameness of standardization creates shared risk. As with any change of this magnitude, the potential of Cloud lies between its trade-offs. In security terms, this “big switch” surrenders visibility and control so as to gain agility and efficiency. The question is, how to achieve a net positive result?
Well-established enterprise security teams who optimize their security spend on managing risk versus purely threat, should not be surprised by Cloud. To these organizations, adapting their security programs to the challenges and opportunities provided by Cloud is business as usual. For organizations unprepared for Cloud, the maturity of security programs they can buy will quickly be outmoded.
Summary
The benefits of Cloud are many. The challenges are substantial. How we deal with these challenges and their organizational, operational, architectural, and technical impacts will fundamentally change the way in which we think about assessing and assuring the security of our assets.
In the Information Security community, many of us have long come to the conclusion that we are caught in what I call my “Security Hamster Sine Wave Of Pain.” Those of us who have been doing this awhile recognize that InfoSec is a zero-sum game; it’s about staving off the inevitable and trying to ensure we can deal with the residual impact in the face of being “survivable” versus being “secure.”![Reblog this post [with Zemanta]](https://i0.wp.com/img.zemanta.com/reblog_e.png)
While I think Nick Carr’s power generation utility analogy was a fantastic discussion catalyst for the usefulness of a utility model, it is abused to extremes and constrains what might ordinarily be more open-minded debate on the present and future of computing.
Back in October 2008, I wrote a post detailing efforts around the 
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