Why crawling is not an adequate measurement methodology for the WebPKI

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The answer is simple — It’s an incomplete view of the use of the WebPKI.

There are a number of different methodologies a web crawler-based approach might take in measuring the size of the WebPKI. The most naive approach would be to simply scan all IPv4 address space and log all of the certificates you see during this scan.

The problem is that this only shows a small fraction of the certificates that are out there. When you connect to an IP address and the associated web server doesn’t know what host you are trying to connect to it will return its “default” website and use the associated certificate.

That same IP address may literally be responsible for serving millions of sites based on the client’s indicated hostname. With this IP-based enumeration approach at best you would get one certificate from that host, at worse you wouldn’t even get that because some servers are not configured with a default site. This is just one problem with this approach there are many more.

Though most WebPKI market share reports do not document their methodology anecdotally it appears most work on this crawler approach and at least historically some have taken periodic drops from CAs to make their view “more complete”.

Today though the only way to measure CA market share that should be used is by relying on the pre-certificate counts in Certificate Transparency logs.

How to measure the WebPKI ecosystem

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The web is dependent on there being a robust, secure, and scalable set of CAs being able to provide TLS certificates. It is unhealthy for there to be a single provider because if for any reason they have an operational or security issue they could become unavailable leaving the web in a world of hurt.

Beyond that in the name of TLS reliability TLS certificate consumers should be relying on multiple CAs for their certificates. For example, to reduce exposure to outages your certificate lifecycle management solution should support failover from one CA to the next. 

Another example of why you should use multiple CAs is to help ensure relying on party agility to changes in CAs, for example, if a CA changes which root key material they use you may lose (or gain) device compatibility, or if an issuing CA changes and someone is pinning you might break them. By to ensure device compatibility long term one should use multiple CAs to help ensure the relying party ecosystem you support is agile to these changes.

For this to work though you need to have an ecosystem of CAs you can use interchangeably, ACME (RFC 8555) helps here substantially because it provides a normalized way to interact with CAs to get these certificates. That is only helpful if there are multiple CAs that implement the protocol and if those CAs are able to scale to meet the needs of those who rely on them.

This is particularly important when you look at SaaS-like offerings the larger ones will often demand millions of certificates that need to be able to be revoked and re-issued in less than 24 hours in some cases so the scalability of the CA becomes particularly important.

Assessing the scalability of a CA is hard but one of the closest proxies you have is their overall market share.

In the US, according to the Google Transparency Report, 97% of all web traffic is protected with TLS. To put that in context there were 366.8 million registered domain names as of 2022.

Certificates can represent more than one domain name so depending on what you are measuring certificate count may not be the best metric to asses CA market share. With that said in the context of scalability, it’s probably a good metric.

What are some ways to evaluate the CA impact and market share?

  • How many certificates are issued by the CA and are unexpired.
  • How many domains are contained within the unexpired certificates issued by a CA.
  • What percentage of web traffic would be covered by the certificates issued by a CA.
  • What percentage of certificates issued by the CA are unexpired and actively in use.

Each of these answers different questions, and they progressively get harder to measure as you go down the list. The easiest by far is how many certificates are issued and still unexpired. This is because all CAs log what is called a pre-certificate to the Certificate Transparency ecosystem before issuance.

NOTE: Publication of a pre-certificate is not required by the rules of the ecosystem however not doing so would mean that users relying on that certificate would get an error.

While the existence of a pre-certificate doesn’t promise the certificate is in use it does signal that someone who controlled that domain wanted to use a certificate for that domain. They wouldn’t have bothered going to the trouble of doing that if there was not an intent to use the certificate in some way.

The easiest way to look at this data is to use the excellent https://crt.sh/cert-populations report. While it does go down from time to time it also provides very fresh views into the un-expired pre-certificate count.

NOTE: Since not all CAs publish what is referred to as the “final certificate” you can safely ignore the Certificate count data on this report.

So what does this data look like (As of July 29th, 2022)?

CertificatesPrecertificates
ALLUnexpiredALLUnexpired% of Unexpired Population
Internet Security Research Group2,834,892,521264,685,3352,553,476,280228,023,48050.18%
Sectigo109,399,9847,245,014373,669,758106,119,71323.35%
DigiCert560,740,35744,640,273497,448,38945,475,97210.01%
GoDaddy6,371,9601,874,81252,669,26031,293,3046.89%
Google Trust Services LLC17,28417828,112,66215,443,3063.40%
Amazon13,540,55698,980104,887,85914,757,6503.25%
GlobalSign nv-sa16,729,66393723,636,7786,893,7281.52%
Actalis55233,236,4931,691,7440.37%
Asseco Data Systems S.A. (previously Unizeto Certum)6,298,4726209,375,7421,571,8520.35%
Start Commercial (StartCom) Ltd.1,495,580982,866,004883,0220.19%
?1,241,4632143,924,285567,4800.12%
Entrust739,9015242,304,521554,4310.12%
SECOM Trust Systems CO., LTD.156,234-112,217,668242,8150.05%
WoSign CA Limited88,6607250,823110,1010.02%
Certainly LLC31,361205240,103101,5330.02%
Buypass186,2002702,127,22898,8350.02%
QuoVadis53,636432236,06397,4540.02%
SecureTrust311,226227301,19778,4890.02%
Microsoft Corporation Core Services Engineering & Operations ( “Microsoft CSEO”)216,44873,560212,90574,6970.02%
Deutsche Telekom Security GmbH57,57032147,94949,5560.01%
JPRS15,7383482,64236,5120.01%
SwissSign AG237,88668,27283,50426,9750.01%
Government of Spain, Fábrica Nacional de Moneda y Timbre (FNMT)86,87223,86657,20623,7720.01%

What you will see is the top 5 CAs out of 233 issue 98.59% of all TLS certificates. While I would like to see this distribution be more normalized to ensure that the ecosystem is not overly dependent on any one entity as far as health goes it does show there are several large providers out there that support the Web who have demonstrated they can scale to meet large certificate consumption needs.

One thing you will notice in this data is that the variability in the pre-certificate “ALL” and “Unexpired” count is quite large in some cases. This is because some CAs like Let’s Encrypt and Google Trust Services either predominantly, or exclusively issue shorter-lived certificates. This results in the certificate count in “All” being much higher than the “Unexpired” case.

So what can we take away from this data? I think there are four key takeaways:

  1. Support of certificate issuance via ACME has made shorter-lived certificates viable and they now represent the large majority of certificates on the web.
  2. Support of ACME has helped grow the percentage of the web that is encrypted from about half of the web to nearly 100% of the web.
  3. 2.15% of CAs issue 98.59% of all TLS certificates on the web.

Cryptographic controls and feature trade-offs

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In an earlier post, I discussed how the use of cryptographic controls can help enable those building privacy governance programs to both deliver on their objectives of meeting their privacy obligations and enabling them to do so in an enforceable and misuse-resistant manner.

As I was discussing this post with someone they brought up the topic of feature trade-offs one must take when utilizing cryptographic controls. The canonical example I hear seems to be bots/assistance in end-to-end protected messaging apps. The thesis goes that in e2e chats these features are not possible, the reality is that they are, it just is harder to do.

This is why I said in that earlier post “More work is needed to make it so the smaller organizations can adopt these patterns”. This is because the boilerplate to enable these scenarios is largely missing.

Alec Muffet talks a bit about this specific scenario in his recent talk about his IETF draft.

To be clear, my reference to cryptographic controls in that post is not limited to end-to-end encryption. There are many ways such cryptographic controls can be applied, depending on objectives and constraints. For example, a useful tool for mitigating insider threats of abused data is limiting access to real user data and auditing access via append-only ledgers.

In many respects, the points are more about moving beyond procedural and manual controls to technical controls that are both strong and demonstrable.

Evolution of privacy governance and how cryptographic controls can help

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Unfortunately, most organizations do not have a formal strategy for privacy, and those that do usually design and manage them similarly to their existing compliance programs.

This is not ideal for several reasons which I will try to explore in this post but more importantly, I want to explore how the adoption of End-To-End encryption and Client-Side encryption is changing this compliance-focused model of privacy to one backed by proper technical controls based on modern cryptographic patterns. 

If we look at compliance programs they usually evolve from something ad-hock and largely aspirational (usually greatly overselling what they deliver) and over time move to a more structured process-oriented approach that is backed with some minimum level of technical controls to ensure each process is followed. 

What is usually missing in this compliance journey is an assessment of sufficiency beyond “I completed the audit gauntlet without a finding”. This is because compliance is largely focused on one objective — proving conformance to third-party expectations rather than achieving a set of contextually relevant security or privacy objectives – This is the root of why you hear security professionals say “Compliance is not Security”.

If you watch tech news as I do, you have surely seen news articles calling the cybersecurity market “the new lemon market “, and while I do agree this is largely true I also believe there is a larger underlying issue — an overreliance on compliance programs to achieve security and privacy objectives.

To be clear, the point here is not that compliance programs for privacy are not necessary, instead, what I am saying is they need to be structured differently than general-purpose compliance programs, as the objectives are different. These differences lend themself to misuse resistant design and the use of cryptographic controls as an excellent way to achieve those objectives.

Misuse resistance is a concept from cryptography where we design algorithms to make implementation failures harder. This is in recognition of the fact that almost all cryptographic attacks are caused by implementation flaws and not fundamental breaks in the cryptographic algorithms themselves. 

Similarly, in the case of privacy, most companies will not say “we intend to share your data with anyone who asks”. Instead, they talk of their intent to keep your information confidential — the problem is that in the long run everyone experiences some sort of failure and those failures can make it impossible to live up to that intent.

So back to this compliance-focused approach to privacy — it is problematic in several cases, including:

  • Where insiders [1,2,3] are abusing their position within an organization,
  • When configuration mistakes result in leakage of sensitive data [4,5,6], 
  • When service providers fail to live up to customers’ expectations on data handling [7,8], 
  • When technical controls around data segmentation fail [9],
  • and of course when service providers fail to live up to their marketing promises for government access requests for your sensitive information [10,11].

If we move to a model where we approach these problems using engineering principles rather than process and manual controls we end can end up in a world where the data and access to it are inherently misused resistant and hopefully verifiable.

This is exactly what we see in the design patterns that have been adopted by Signal, namely they gather only the minimal level of data to deliver the service, and the data they do gather they encrypt in such a way to limit what they can do with it.

They are not the only ones though can see the similar approaches from Android and how they handle encrypted backups as well as in Apple in how they handle device pin recovery. 

Another great example is how payment providers like Stripe leverage client-side encryption to reduce exposure of payment details to intermediaries or how Square uses client-side encryption in the Cash App to limit adversaries’ access to the data.

While today these patterns are only being applied by the largest and most technically advanced organizations the reality is that as Alexander Pope once said “to err is human” and if we are to truly solve for privacy and security we have to move to models that rely less on humans doing the right thing and for privacy, this means extensive use of cryptographic patterns like those outlined above.

It could be argued that of the reasons we do not see these patterns applied more is security the nihilist’s argument that client-side encryption and cryptographic transparency are exercises of re-arranging deck chairs on a sinking ship.

While there is some truth to that argument you can both limit the amount of trust you have to place in these providers (limiting the amount of trust delegated is the essence of security after all!) and make elements of what the provider does verifiable which again furthers this misuse resistant objective.

If that is the case then why is it that only the largest providers do this today? I would argue it’s just too darn hard right now. For example, when you start applying client-side encryption and cryptographic controls to systems there is still a substantial lift, especially when compared to the blind trust paradigm most systems operate within.

There are a few reasons, but one of the largest in the case of client-side encryption is that you end up having to build the associated key management frameworks yourself and that takes time, and expertise that many projects simply do not have access to.

With that said just like modern systems have moved from self-hosted monoliths to microservices that are globally scaled thanks to solutions like Kubernetes which in turn gives them node to node compartmentalization and other by default security controls, I believe we will see a similar move for sensitive data handling where these cryptographic controls and usage policies become a key tool in the developer’s toolbox.

More work is needed to make it so the smaller organizations can adopt these patterns but, unquestionably, this is where we end up long term. When we do get here, to borrow an over-used marketing term, we end up what might be called Zero Trust Data Protection in today’s market.

How is ACME different than XCEP/WSTEP anyway?

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If you read my blog there is a reasonable chance that you are familiar with RFC 8555, the standard for Automatic Certificate Management Environment (ACME). Even though ACME is a relatively young protocol it is already used by the majority of websites on the internet for certificate lifecycle management.

While I won’t go into a lot of detail for this post to make sense you have to understand a couple of things about the ACME protocol. 

The first is that it works on the concept of dynamic “account” registration. By that I mean requestors can in real-time, request that an “account” be created for them. This account is represented by a public key pair that the ACME service will use to persist meta-data about the requestor. The ACME service can deny this request for any reason it likes but commonly in Web PKI as long as the request is wellformed it is accepted.

The next thing you need to understand is that it has the concept of “challenges” that can be used to communicate conditions that must be met before a certificate is issued. For example, an ACME service may request that the account holder demonstrate that they are authorized to get a certificate for a given domain name by placing a specific value in DNS at a well-known location. Since only a DNS administrator could perform that action the ACME service can have confidence the requestor controls the name it has requested a certificate for.

And finally, there is nothing in the ACME protocol that limits its use to just web server certificates. It is a general framework that can be used to acquire and manage certificates of any type. For example, CISCO is using ACME in their WebEx offering to facilitate the acquisition of what are essentially email certificates via OIDC authentication as a way to authenticate chat members.

But there is another very popular protocol, a well set of protocols that fewer people know about, that is XCEP and WSTEP. These protocols are used by Windows machines to both determine what kind of certificates a machine or user should enroll for as well as enabling the enrollment for those certificates. 

Similar to ACME these protocols also support, although in a more ridged rigid way, the ability for the issuer to challenge the client for additional information necessary to get a certificate of a particular type. For example, you can configure a certificate type (known as a template) to require that the requestor provide a cryptographic attestation backed by a TPM to be used to prove the machine belongs to the organization operating the certificate authority.

There are differences though, the first of which is the concept of a template, this enables XCEP/WSTEP to have one URL endpoint issue many types of certificates which is very important within an enterprise which is where certificates are used for many different scenarios.

Another difference is that XCEP/WSTEP presume the authorization of the client happened out of the band before the client requested the certificate. The dynamic approach to challenges that was adopted by ACME allowed it to tackle this problem in-band or rely on the out-of-band authorization. It supports this out-of-band concept through the concept of External Account Binding which allows the requestor to use an API key gathered out of band to prove on account creation the account key is associated with some pre-enrolled user.

And finally, ACME has a clear model for extensibility built into it. What this means is that one can easily extend it with additional capabilities. The most fundamental part of this is the Directory resource which lists all of the APIs supported by this ACME instance. One could use this, for example, to add a “Templates” API that would allow an ACME client to request specific types of certificates from the ACME endpoint.

Similarly, the concept of the challenge allows the server to demand the client do any number of things before the certificate is to be issued so the idea of adding a TPM challenge, for example, is trivial within this framework.

In short, ACME, contrary to popular belief, is not a protocol for getting and managing website certificates it is a framework for getting and managing any certificate. More importantly, it is extensible in such a way that with just a few minor additions it would be a proper superset of all the capabilities within the Windows enrollment protocol suite.

Why is this important? That’s easy! When I talk to anyone who is using certificates at any reasonable scale their concerns almost instantly come to the complexity of managing the certificate lifecycle management of those certificates across the various products and services that use them.

When we look at this complexity most of it arises from the use of a mish-mash of solutions for lifecycle management that when viewed in isolation seemed sufficient but when looked at holistically were actually woefully insufficient. 

If as an industry we move these legacy systems to a single protocol so that certificates regardless of them being for public or private PKI or representing users, machines or workloads use one protocol we will have a reliable substrate that we can use to authenticate and authorize with agility.

The next decade of Public Key Infrastructure…

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Background

Before we talk about the future we need to make sure we have a decent understanding of the past. X.509 based Public Key Infrastructure originally was created in the late 80s with a focus on enterprise and government use cases.  These use cases were largely for private systems, it was not until a decade later this technology was applied to the internet at large.

Since the standards for enrollment and lifecycle management at the time were building blocks rather than solutions and were designed for government and enterprise use cases rather than the internet, the Web PKI, as it became known, relied largely on manual certificate lifecycle management and a mix of proprietary automation solutions.

While the use of PKI in the enterprise continued, primarily thanks to Microsoft AD/CS and its automatic certificate lifecycle management (I worked on this project), the Web PKI grew in a far more visible way. This was primarily a result of the fact that these certificates had to be acquired manually which led to the creation of an industry focused on sales and marketing of individual certificates.

The actors in this system had no incentive to push automation as it would accelerate the commoditization of their products. The reality was that these organizations had also lost much of their technical chops as they became sales and marketing organizations and could no longer deliver the technology needed to bring this automation anyways.

This changed in 2016 when the Internet Security Research Group, an organization I am involved in, launched Let’s Encrypt. This was an organization of technologists looking to accelerate the adoption of TLS on the web and as such started with a focus on automation as it was clear that without automation growth of HTTPS adoption would continue to be anemic. What many don’t know is in when Let’s Encrypt launched HTTPS adoption was at about 40% and year over year growth was hovering around 2-3%, about the rate of growth of the internet and — it was not accelerating. 

Beyond that TLS related outages were becoming more frequent in the press, even for large organizations. Post mortems would continuously identify the same root causes, a manual process did not get executed or was executed incorrectly.

The launch of Let’s Encrypt gave the Internet the first CA with a standards-based certificate enrollment protocol (ACME), this combined with the short-lived nature of the certificates they issued meant those that adopted it would have to use automation for their services to reliably offer TLS. This enabled products to make TLS work reliably and by default, a great example of this is the Caddy web server. This quickly took the TLS adoption rate to around 10% year over year and now we are hovering around 90%+ HTTPS on the internet.

While this was going on the concept of microservices merged with containers which led to container-orchestration, which later adopted the concept of mesh networking. This mesh networking was often based on mutual-TLS (mTLS). The most visible manifestation of that being SPIFFE, the solution used by Kubernetes.

At the same time, we saw networks becoming more composable, pushing authentication and authorization decisions out to the edge of the network. While this pattern has had several names over the years we now call it Zero Trust and a visible example of that today is Beyond Corp from Google. These solutions again are commonly implemented ontop of mutual TLS (mTLS).

We now also see the concept of Secure Access Service Edge (SASE) or Zero-Trust Edge gaining speed which extends this same pattern to lower-level network definition. Again commonly implemented ontop of mTLS.

The reality is that the Web PKI CAs were so focused on sales and marketing they missed almost all of these trends. You can see them now paying lip service to this by talking about DevOps in their sales and marketing but the reality is that the solutions they offer in this area are both too late and too little. This is why cloud technology providers like Hashicorp and cloud providers like Amazon and Google (I am involved in this also) had to step in and provide their offerings.

We now see that Web PKI CAs are starting to more seriously embrace automation for the public PKI use cases, for example, most of the major CAs now offer ACME support to some degree and generally have begun to more seriously invest in the certificate lifecycle management for other use cases.

That being said many of these CAs are making the same mistakes they have made in the past. Instead of working together and ensuring standards and software exist to make lifecycle management work seamlessly across vendors, most are investing in proprietary solutions that only solve portions of the problems at hand.

What’s next?

The usage of certificates and TLS has expanded massively in the last decade and there is no clear alternative to replace its use so I do not expect the adoption of TLS to wain anytime soon.

What I do think is going to happen is a unification of certificate lifecycle management for private PKI use cases and public PKI use cases. Mesh networking, Zero-Trust, and Zero-Trust edge is going to drive this unification.

This will manifest into the use of ACME for these private PKI use cases, in-fact this has already started, just take a look at Cert Manager and Small Step Certificates as small examples of this trend. 

This combined with the ease of deploying and managing private CAs via the new generation of Cloud CA offerings will result in more private PKIs being deployed and the availability problems from issues like certificate expiration and scalability will no longer be an issue.

We will also see extensions to the ACME protocol that make it easier to leverage existing trust relationships which will simplify the issuance process for private use cases as well as ways to leverage hardware-backed device identity and key protection to make the use of these certificate-based credentials even more secure.

As is always the case the unification of common protocols will enable interoperability across solutions, improve reliability and as a result accelerate the adoption of these patterns across many products and problems.

It will also mean that over time the legacy certificate enrollment protocols such as SCEP, WSTEP/XCEP, CMC, EST, and others will become less common.

Once this transition happens this will lead us to a world where we can apply policy based on subjects, resources, claims, and context across L3 to L7 which will transform the way we think about access control and security segmentation. It will give both more control and visibility into who has access to what.

What does this mean for the Web PKI?

First I should say that Web PKI is not going anywhere – with that said it is evolving.

Beyond the increase in automation and shorter certificate validities over the next decade we will see several changes, one of the more visible will be the move to using dedicated PKI hierarchies for different use cases. For example, we will ultimately see server authentication, client authentication, and document signing move to their own hierarchies. This move will better reflect the intent of the Web PKI and prevent these use cases from holding the Web PKI’s evolution back.

This change will also minimize the browser influence on those other scenarios. It will do this at the expense of greater ecosystem complexity around root distribution but the net positive will be felt regardless. I do think this shift will give the European CAs an advantage in that they can rely on the EUTL for distribution and many non-web user agents simply do not want to manage a root program of their own so the EUTL has the potential to be adopted more. I will add that is my hope these user agents instead adopt solution-specific root programs vs relying on a generic one not built for purpose.

The Web PKI CAs that have not re-built their engineering chops are going to fall further behind the innovation curve. Their shift from engineering companies to sales and marketing companies resulted in them missing the move to the cloud and those companies that are going through digital transformation via the adoption of SaaS, PaaS, and modern cloud infrastructures are unlikely to start that journey by engaging with a traditional Web PKI CA.

To address this reality the Web PKI CAs will need to re-invent themselves into product companies focusing on solving business problems rather than selling certificates that can be used to solve business problems. This will mean, for example, directly offering identity verification services (not selling certificates that contain assertions of identity), providing complete solutions for document signing rather than certificates one can use to sign a document or turnkey solutions for certificate and key lifecycle management for enterprise wireless and other related use cases.

This will all lead to workloads that were once on the Web PKI by happenstance being moved to dedicated workload/ecosystem-specific private PKIs. The upside of this is that the certificates used by these infrastructures will have the opportunity to aggressively profile X.509 vs being forced to carry the two decades of cruft surrounding it like they are today.

The Web PKI CAs will have an opportunity to outsource the root certificate and key management for these use cases and possibly subcontract out CA management for the issuing CAs but many of these “issuing CA” use cases are likely to go to the cloud providers since that is where the workloads will be anyway.

Due to the ongoing balkanization of the internet that is happening through increased regional regulation, we will see smaller CAs get acquired, mainly for their market presence to let the larger providers play more effectively in those markets.

At the same time, new PKI ecosystems like those used for STIR/SHAKEN and various PKIs to support IoT deployments will pop up and as the patterns used by them are found to be inexpensive, effective, and easily deployable they will become more common.

We will also see that the lifecycle management for both public and private PKI will unify ontop of the ACME enrollment protocol and that through that a new generation of device management platforms will be built around a certificate-based device identity anchored in keys bound to hardware where the corresponding certificates contain metadata about the device it is bound to.

This will lay the groundwork for improved network authentication within the enterprise using protocols like EAP-TTLS and EAP-TLS, enable Zero-Trust and Zero-Trust Edge deployments to be more easily deployed which will, in turn, blur the lines further between what is on-premise and what is in the cloud.

This normalization of the device identity concepts we use across solutions and the use of common protocols for credential lifecycle will result in better key hygiene for all use cases, and simplify deployment for those use cases.

Accountability and Transparency in Modern Systems

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Over the last several decades we have seen the rate of technological innovation greatly accelerate. A key enabler of that acceleration has been the move to cloud computing which has made it possible for hardware, software, and services to be shared. This significantly reduced both the capital and time necessary to adopt and operate the infrastructure and services built on these platforms.

This migration started by enabling existing software to run using dedicated computers and networks owned and operated by someone else. As these computers got faster and the tools to share the physical hardware and networks were built, the cost of technological innovation reduced significantly. This is what democratized modern startup entrepreneurship as it made it cost-effective for individuals and small businesses to gain access to the resources once only available to the largest companies.

This flipped technological innovation on its head. It used to be that government and big businesses were the exclusive sources of technological innovation because they were the ones who could afford to buy technology. The lowering of the cost of innovation is what gave us the consumer startups we have today. This drew the attention of large companies to this emerging market and led to the creation of the modern smartphone which was fundamental to creating the market opportunity we see in consumer startups. This was a scale opportunity that was fundamentally different than the prior government and enterprise models of innovation.

As enterprises saw the rate of innovation and agility this new model provided, it became clear that they too needed to embrace this model in their businesses. It is this reality that led to the creation of Salesforce, the first Software As a Service, and AWS, the first to market with a modern Cloud Service Provider. It was these offerings that gave us Software As a Service (SaaS), Platform As a Service (PaaS), and what we think of as modern cloud infrastructure.

At first, these enterprises only moved greenfield or very isolated projects to the cloud but as the benefits of the new model became irrefutable and the capabilities of these offerings were enriched in ways that were impractical to replicate in their environments, they started moving more business-critical offerings. We can see this trend continues today, a recent survey found that 55% of IT organizations are now looking at ways to reduce their on-premise spending. This will lead to many legacy systems being replaced with more modern, scalable, agile, and secure solutions.

That same survey found that digital transformation and security are the two biggest reasons for this shift. This is no surprise when we look at how capital efficient modern businesses are relative to those based on legacy IT and manual processes, or how vulnerable legacy IT systems are to modern attacks. 

This does beg the question, what is next?. I believe that two trends are emerging. The first being the democratization of compliance for modern systems and the second being the shift in expectations of what does it mean to be “secure”.

If we look at the first trend, the democratization of compliance, we see the internet becoming balkanized through regulation and governments seeking to get more control over what people do on the internet. Increased regulation makes it significantly harder for new entrants to compete, which in turn helps entrench the incumbents who can often eat the engineering and compliance costs associated with the regulations. When you think about this in the context of the global economy in which the internet exists, an economy made up of 195 independent sovereign countries, the compliance burden becomes untenable.

Modern Cloud Service Providers can make a significant dent in this by making it possible for those who build on them to meet many of these compliance obligations as a byproduct of adopting their platforms.

In the near term, this will likely be focused on the production of the artifacts and audit reports that are needed to meet an organization’s current compliance requirements but if we project out, it will surely evolve to include services for legal identity verification, content moderation, and other areas of regulatory oversight. A decade from now I believe we will see systems being built on these platforms in such a way that they will be continually compliant producing the artifacts necessary to pass audit as a natural byproduct of the way they work. 

This will in turn make it easier to demonstrate compliance and create new opportunities such as auditors continually monitoring an organization for its compliance with guidelines rather than just doing annual point-in-time assessments as is done today.

This has also led to companies like Coalition building offerings that let customers augment existing systems with the artifacts to demonstrate conformance with security best practices are being met so that insurance companies can offer more affordable risk-based insurance policies.

As we look at the second trend, the redefinition of what it means to be secure, we can see consumers becoming more aware of security risks and as a result, their expectations around the sovereignty of their data and the confidentiality of their information evolving. 

One response to this realization is the idea of decentralization. The thesis here is arguably is that there can be no sovereignty as long as there is centralization. In practice, most of these decentralized systems are in-fact quite centralized. While there are many examples of this, one of the more visible has been the DAO hard fork which was done to recover stolen funds or the simple fact that 65% of Bitcoin mining happens in China. Additionally, for the most part, the properties that enable sovereignty typically come from the use of verifiable data-structures and cryptography and not decentralization. That is not to say these systems do not have a place, I would argue that their success and durability so far at least suggests there is “a there, there” but I would also say that, at least currently, they do not yet live up to their full promise. 

Another response to this is the consumer adoption of End-To-End encryption in messaging applications (even iMessage is end-to-end encrypted!) and by extension to that problem the verifiability of the systems that implement these schemes. 

The best example here is probably Signal, they spent time designing security and privacy into their messaging protocol and implementing systems from the beginning, modeling its design on modern threats and decades of learning about what does, and does not work. This approach led to the protocol that they defined being adopted by many of their competitors, including WhatsApp, Facebook Messenger, Skype, and Google Allo.

Signal is also a great example of the verifiability property, in particular, the work they have done with Contact Discovery is exciting. What they have done with this feature is first to minimize what information they need to deliver the capability in the hope to limit future abuse. Secondly, they leveraged technologies like SGX, which is an example of a Confidential Compute, that enables them to demonstrate what they are doing with the information they do collect. This introduces transparency and accountability which both are important ingredients to earning trust.

The use of hardware security as a key component of the security boundary has already found its way from consumer phones, laptops, and tablets to the cloud. For example, Google Cloud‘s Shielded VMs and Azure Trusted Launch use hardware to provide verifiable integrity to VM instances to make it possible to detect VMs compromised by boot- or kernel-level malware or rootkits similar to how Apple does with the iPhone. We also now see AMD Sev and SGX seeing broader deployment in the larger Cloud Service Providers (I will be the first to admit these technologies have room to grow if they are to live up to their promises but they are promising none the less).

With this foundation, the industry is starting to look at how they can bring similar levels of transparency and accountability into applications and ecosystems too. One of the projects that have demonstrated that doing this can have a big impact is Certificate Transparency. As a result of the investments in deploying Certificate Transparency, the internet is now materially more secure than it was before and this is a direct result of introducing accountability into an opaque ecosystem based on blind trust.

Another example in this space is the Golang Checksum Database where verifiable data-structures like Merkle Trees are being used to introduce accountability into the software supply chain as a means to mitigate risks for those who rely on the Golang ecosystem. 

For many problems in the security space, you can solve from one of two philosophical bases. You can either create privileged systems only visible to a few that you hope aren’t corruptible or you can build democratizing transparency into the system as a check on corruption.

Dino A. Dai Zovi

While the earlier examples are using combinations of hardware, cryptography, and verifiable data-structures to deliver on these properties, other examples take a more humble approach. For example, Google Cloud’s Access Transparency uses privilege separation, audit logs, and workflows to provide the fundamental ability to track business justifications for access to systems and data. The existence of these systems is further validation that the trend of verifiability is emerging.

So what should you take away from this post? I suppose there are four key messages:

  1. The definition of security in modern Cloud services is continuing to be influenced by the consumer space which is leading to the concepts of verifiability, accountability, data sovereignty, and confidentiality becoming table stakes.
  2. Globalization and regulation are going to accelerate the adoption of these technologies and patterns as they will ultimately become necessary to meet regulatory expectations.
  3. Increasingly verifiable data structures, cryptography, and hardware security capabilities are being used to make all of this possible.
  4. These trends will lead to the democratization of compliance to the many regulatory schemes that exist in the world.

I believe when we look back, these trends will have significantly changed the way we build systems and a new generation of businesses will emerge enabling these shifts to take place.

Information system security and how little things have changed

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When I was a boy my father had me read Plato’s Republic – he wanted to give an oral report on what the key points of the book were and what my personal takeaways were after reading the book.

The first question was easy to answer from the dust jacket or maybe a Cliff Notes (For those of you who have not read the book it is an exploration of the ideas of justice and the ideal government).

With that said, I knew from experience that those personal takeaways are buried in the nuance and no shortcut would satisfy him so off to read I went. What were those takeaways? According to him what I said was: 

  1. The nature of people has not changed much,
  2. The problems we have in government have not changed much.

Why do I bring this up in the context of security? Unfortunately, it is because I do not think things have changed much in security either! I’ll give two examples that stand out to me:

Every program and every privileged user of the system should operate using the least amount of privilege necessary to complete the job.

— Jerome Saltzer, 1974, Communications of the ACM

The moral is obvious. You can’t trust code that you did not totally create yourself. (Especially code from companies that employ people like me.) No amount of source-level verification or scrutiny will protect you from using untrusted code.

Ken Thompson, 1984, Reflections on Trusting Trust

The first quote is the seminal quote referring to the term “least privilege” – a concept we still struggle to see deployed nearly 50 years later. The term is old enough now the marketers have latched onto it so when you speak to many enterprises they talk about it in the scope of group management and not the more fundamental design paradigm it actually represents.

To put this concept in the context of the network in the 90s we talked about how Firewalls, however necessary, were a bit of an antipattern since they represented “the hard candy shell” containing the “soft gooey sweet stuff” the attacker wants to get at and that as a result, it was better to design security into each endpoint. 

A decade later we were talking about using network-level enforcement via “Network Admission Control” at the switch, later yet via DirectAccess and Network Access Protection we were pushing those same decisions down as close to the end device as we could, and in some cases making each of those endpoints capable of enforcing these access requests.

Today we call this pattern ZeroTrust networking, a leading example of this pattern is called BeyondCorp, but again marketers have latched onto ZeroTrust and as a result, it seems almost every enterprise product I hear about these days claims to offer some sort of ZeroTrust story but few objectively meet the criteria I would define for such a lofty term.

Similarly, if we look at the second quote all we have to do is take a look at the recent SolarWinds debacle and realize that almost nothing has changed since Ken Thompson wrote that paper. We also have dozens of examples of keys being compromised being used to attack the software supply chain, or package repositories and open source dependencies being used as attack vectors. Despite us knowing how significant these issues can be for nearly 40 years we have made very little progress in mitigating these issues.

As they say, there is nothing new under the sun, and this appears to be especially true with security. If so why is this the case? How is it we have made so little progress on these fundamental problems as an industry?

Unfortunately, I think it boils down to that customers don’t care until it is too late and this makes it hard for the industry to justify the kinds of fundamental investments necessary to protect the next generation from these decades old.

How do we improve the state of affairs here? Thats really the question, one I don’t have a good answer to.

Safes and Transparency

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Lately, I have been thinking about the history of defensive security technology. One of the purest examples here can be found in safes and vaults. The core purpose of a safe is obvious, to make it cost-prohibitive for an attacker to gain access to whatever is inside without being detected.

With that said, the topic is a lot more nuanced than it seems on the surface. If we look at a safe used by a typical community bank in the 1800s, one of the things you will notice is that they often have ornate decorations on their exteriors, beautifully designed locking mechanisms and their locking mechanisms are covered by specific patents. These traits were clearly designed to signal something to the visitors of the bank, namely that they use the latest technology to keep your valuables safe.

Beyond the messaging buried in the design, these safes were also designed to mitigate specific threats, for example, In the mid-1800s it was common for attackers to steal safes, use explosives to open them and to kidnap those that had access to the secrets necessary to open a safe, or those near and dear to them. 

In response to this reality, safe manufacturers started to use materials like manganese to manufacture safes, making the walls very thick and as a result very heavy (often 3 tons or more!), rounding corners, and using locking cylinder-shaped doors in combination to make theft or the use of explosives no longer interesting vectors for an attack.

These changes, combined with artful customizations also provided a way for banks to ensure that sophisticated thieves could not replace a safe in order to delay the detection time and have a safer getaway.

They also started incorporating time locks, to make it so if someone was kidnapped, they would still not be able to open the safe outside core business hours, essentially enabling the creation of a fully disclosed ledger of all goods stored in or withdrawn from the safe.

A famous example here is from 1876 in the robbery of the Great Northfield Minnesota Bank by Jesse James and the Cole Younger gang, it was foiled due to a safe with these design characteristics.

As I think about the parallels in modern technology, I can not help but to come back to a post I did this last year titled “An Evolution of Security Thinking’, in particular how we have gone from security as something you added after the fact to one where it is built into a system from the get-go. Moreover, it seems that these safes may also represent one fo the first examples of transparency being applied as a technique used to dissuade an attacker.

If a safe has no tumbler on the outside, what good would it do to kidnap the bank manager? As a result, the attacker is forced to attempt their theft during business hours when the bank was busy and they would have a larger chance of getting caught.

If it is obvious a safe has 12” thick walls and weighs in at over 3 tons, then stealing the safe at night, or using explosives to open the safe, given the skills and resources of the attacker, is no longer a viable path of compromise either. As a result, forcing the assailant to attack the bank during the day, when the vault may already be opened.

The safe manufactures, by making their designs, and mitigations clear, were attempting to dissuade attackers from even attempting their attack. This is not materially different from how today we are applying the concepts of cryptographic transparency as a tool to mitigate other attacks.

In short, transparent systems are essentially the antithesis of security by obscurity. While designing a system to be cryptographically verifiable does not necessarily require the contents of that system to be known, just as the safe design doesn’t require the contents of the safe itself to be known, the use of these patterns makes it possible to intelligently reason about the security and integrity of the system.

Just a thought…..

P.S. Thanks to Fotis Loukos and Yael Grauer for providing feedback on this post. 

Software Supply Chain Risk Mitigation

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Increasingly we are seeing attacks against what is now commonly referred to as the software supply chain.

One of the more notable examples in the last few months was from the Nodejs package management ecosystem [1]. In this case, an attacker convinced the owner of a popular but unmaintained Node package to transfer ownership to them. The attacker than crafted a version of the package that unsuccessfully attacked Copay, a bitcoin wallet platform.

This is just one example of this class of attack, insider attacks of the software supply chain are also becoming more prevalent. When looking at this risk it holistically it is also important to realize that as deployments move to the Cloud the lines between software and services also blur.

Though, not specifically an example of a Cloud deployment issue, in 2015 there was a public story of how some Facebooks employees have the ability to log into users accounts without the target user’s knowledge [2]. This insider risk variant of the supply chain exists in the Cloud in a number of different areas.

Probably the most notable being in the container images provided by their Cloud provider. It is conceivable that a Cloud provider could be compelled by government to build images that would attack a specific or set of customers as part of an investigation, or that an employee would do so under compulsion or in service of personal interests.

This is not a new risk, in fact, management of internal and external dependencies has always been core to building secure systems. What has changed is that in the rush to the Cloud and Open Source users have adopted the tools and resources these cloud providers have built to make this migration easier without fully understanding and managing this risk that they have assumed in doing so.

In response to this reality, Cloud providers are starting to provide tools to help mitigate this risk, some such examples include:

  • Providing audit records of employee access to customer data and services,
  • Building solutions to provide hardware-based trusted execution environments that provide some level of protection from cloud providers.
  • Offering hardware key management solutions provided by third-parties to protect sensitive key material,
  • Cryptographically signing the binaries and images that are published so that their distribution is controlled and tampering post-production can be detected.

Despite these advancements, there is still a long way to go to mitigate these risks in a holistic fashion.

One effort in this area I am actively involved in is in the adoption of the concept of Binary Transparency. This can be thought of as an evolution of legacy code signing models. In these solutions, a publisher places a cryptographic signature using a private key associated with a public certificate of some sort that is either directly trusted based on package origin and signature (such as with GPG signatures) or is authenticated based on the legal identity of the publisher of the package (as is the case with Authenticode).

These solutions, while valuable, help you authenticate a package but they do not provide you the tools to understand the history of that package. As a result, these publishers can produce packages either accidentally or on purpose that are malicious in nature that is signed with their “trusted keys” and it is not detectable until it is too late.

As an example of this risk, you only need to look at RealTek, over the years numerous times their code signing key has been compromised and used to produce malware, some of it targeted such as in the case of Stuxnet [3].

Binary Transparency addresses this risk in a few ways. At its core Binary Transparency can be thought of as an append-only ledger listing of all versions of a given binary, each of these versions having a pointer to a content addressable store where that binary is available.

This design enables the runtime that will execute the binary to do a few things that were not possible, It can, for example, ensure it is running the most recent version of a binary and to only run the binary when it, and some number of previous revisions are publicly discoverable. This also enables the relying parties of the published binaries and images to comp it can inspect all versions and potentially diff those versions to understand the differences.

When this technique is combined with the concept of reproducible builds, as is provided by Go [4] and a community of these append-only logs and auditors of those logs you can get strong assurances that:

  • You are running the same version as everyone else,
  • That the binary you are running is reproducible from the source you can review,
  • The binary are running has not neen modified since it was published,
  • That you, and others, will not run binaries or images that have not been made publicly available for inspection.

A system with these properties disincentivizes the attacker from executing these attacks as it significantly increases the probability of being caught and helps bound the impact of any compromise.

Importantly, by doing these things, it makes it possible to increase the trust in the Cloud offering because it minimizes the amount of trust the user must put into the Cloud provider to remain honest.

A recent project that implements these concepts is the Go Module Transparency project [5] [6].

Over time we will see these same techniques applied to other areas [7] [8] of the software supply chain, and with that trend, users of open source packages, automatic update systems, and the Cloud will be able to have increased peace of mind that their external dependencies are truly delivering on their promises.

  • [1] Node.js Event-Stream Hack Exposes Supply Chain Security Risks
  • [2] Facebook Engineers Can Access Your Account Without A Password
  • [3] STUXNET Malware Targets SCADA Systems
  • [4] REPRODUCING GO BINARIES BYTE-BY-BYTE
  • [5] Proposal: Secure the Public Go Module Ecosystem
  • [6] Transparent Logs for Skeptical Clients
  • [7] Firefox Security/Binary Transparency
  • [8] Contour: A Practical System for Binary Transparency