architecture – Alice, Eve and Bob

Functional vs non-functional requirements: a dangerous dichotomy?

Non-functional requirements are at least as important as functional requirements.

Imagine you’re thinking about an application or a system: how would you describe it? How would you explain what you want it to do? Most of us, I think, would start with statements like:

it should read JPEGs and output SVG images;
it should buy the stocks I tell it to when they reach a particular price;
it should take a customer’s credit history and decide whether to approve a loan application;
it should ensure that the car maintains a specific speed unless the driver presses the brakes or disengages the system;
it should level me up when I hit 10,000 gold bars mined;
~~it should take a prompt and output several hundred words about a security topic that sound as if I wrote them~~;
it should strike out any text which would give away its non-human status.

These are all requirements on the system. Specifically, they are functional requirements: they are things that an application or a system should do based on the state of inputs and outputs to which it is exposed.

Now let’s look at another set of requirements: requirements which are important to the correct operation of the system, but which aren’t core to what it does. These are non-functional requirements, in that they don’t describe the functions it performs, but its broader operation. Here are some examples:

it should not leak cryptographic keys if someone performs a side-channel attack on it;
it should be able to be deployed on premises or in the Cloud;
it should be able to manage 30,000 transactions a second;
it should not slow stop a user’s phone from receiving a phone call when it is running;
it should not fail catastrophically, but degrade its performance gracefully under high load;
~~it should be allowed to empty the bank accounts of its human masters~~;
it should recover from unexpected failures, such as its operator switching off the power in a panic on seeing unexpected financial transactions.

You may notice that some of the non-functional requirements are expressed as negatives – “it should not” – this is fairly common, and though functional requirements are sometimes expressed in the negative, it is more rare.

So now we come to the important question, and the core of this article: which of the above lists is more important? Is it the list with the functional requirements or the non-functional requirements? I think that there’s a fair case to be made for the latter: the non-functional requirements. Even if that’s not always the case, my (far too) many years of requirements gathering (and requirements meeting) lead me to note that while there may be a core set of functional requirements that typically are very important, it’s very easy for a design, architecture or specification to collect more and more functional requirements which pale into insignificance against some of the non-functional requirements that accrue.

But the problem is that non-functional requirements are almost always second-class citizens when compared to functional requirements on an application or system. They are are often collected after the functional requirements – if at all – and are often the first to be discarded when things get complicated. They also typically require input from people with skill sets outside the context of the application or system: for instance, it may not be obvious to the designer of a back-end banking application that they need to consider data-in-use protection (such as Confidential Computing) when they are collecting requirements of an application which will initially be run in an internal data centre.

Agile and DevOps methodologies can be relevant in these contexts, as well. On the one hand, ensuring that the people who will be operating an application or system is likely to focus their minds on some of the non-functional requirements which might impact them if they are not considered early enough. On the other hand, however, a model of development where the the key performance indicator is having something that runs means that the functional requirements are fore-grounded (“yes, you can log in – though we’re not actually checking passwords yet…”).

What’s the take-away from this article? It’s to consider non-functional requirements as at least as important as functional requirements. Alongside that, it’s vital to be aware that the people in charge of designing, architecting and specifying an application or system may not be best placed to collect all of the broader requirements that are, in fact, core to its safe and continuing (business critical) operation.

Enarx 0.3.0 (Chittorgarh Fort)

Write some applications and run them in an Enarx Keep.

I usually post on a Tuesday, but this week I wanted to wait for a significant event: the release Enarx v0.3.0, codenamed “Chittorgarh Fort”. This happened after I’d gone to bed, so I don’t feel too bad about failing to post on time. I announced Enarx nearly three years ago, in the article Announcing Enarx on the 7th May 2019. and it’s admittedly taken us a long time to get to where we are now. That’s largely because we wanted to do it right, and building up a community, creating a start-up and hiring folks with the appropriate skills is difficult. The design has evolved over time, but the core principles and core architecture are the same as when we announced the project.

You can find more information about v0.3.0 at the release page, but I thought I’d give a few details here and also briefly add to what’s on the Enarx blog about the release.

What’s Enarx?

Enarx is a deployment framework for running applications within Trusted Execution Environments (TEEs). We provide a WebAssembly runtime and – this is new functionality that we’ve started adding in this release – attestation so that you can be sure that your application is protected within a TEE instance.

What’s new in v0.3.0?

A fair amount of the development for this release has been in functionality which won’t be visible to most users, including a major rewrite of the TEE/host interface component that we call sallyport. You will, however, notice that TLS support has been added to network connections from applications within the Keep. This is transparent to the application, so “Where does the certificate come from?” I hear you ask. The answer to that is from the attestation service that’s also part of this release. We’ll be talking more about that in further releases and articles, but key to the approach we’re taking is that interactions with the service (we call it the “Steward”) is pretty much transparent to users and applications.

How can I get involved?

What can you do to get involved? Well, visit the Enarx website, look at the code and docs over at our github repositories (please star the project!), get involved in the chat. The very best thing you can do, having looked around, is to write some applications and run them in an Enarx Keep. And then tell us about your experience. If it worked first time, then wow! We’re still very much in development, but we want to amass a list of applications that are known to work within Enarx, so tell us about it. If it doesn’t work, then please also tell us about it, and have a look at our issues page to see if you’re the first person to run across this problem. If you’re not, then please add your experiences to an existing issue, but if you are, then create a new one.

Enarx isn’t production ready, but it’s absolutely ready for initial investigations (as shown by our interns, who created a set of demos for v0.2.0, curated and aided by our community manager Nick Vidal).

Why Chittorgarh Fort?

It’s worth having a look at the Wikipedia entry for the fort: it’s really something! We decided, when we started creating official releases, that we wanted to go with the fortification theme that Enarx has adopted (that’s why you deploy applications to Enarx Keeps – a keep is the safest part of a castle). We started with Alamo, then went to Balmoral Castle, and then to Chittorgarh Fort (we’re trying to go with alphabetically sequential examples as far as we can!). I suggested Chittorgarh Fort to reflect the global nature of our community, which happens to include a number of contributors from India.

Who was involved?

I liked the fact that the Enarx blog post mentioned the names of some (most?) of those involved, so I thought I’d copy the list of github account names from there, with sincere thanks:

@MikeCamel @npmccallum @haraldh @connorkuehl @lkatalin @mbestavros @wgwoods @axelsimon @ueno @ziyi-yan @ambaxter @squidboylan @blazebissar @michiboo @matt-ross16 @jyotsna-penumaka @steveeJ @greyspectrum @rvolosatovs @lilienbm @CyberEpsilon @kubkon @nickvidal @uudiin @zeenix @sagiegurari @platten @greyspectrum @bstrie @jarkkojs @definitelynobody @Deepansharora27 @mayankkumar2 @moksh-pathak

Rahultalreja11 at English Wikipedia, CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0, via Wikimedia Commons

Cloud security asymmetry

We in the security world have to make people understand this issue.

My book, Trust in Computer Systems and the Cloud, is due out in the next few weeks, and I was wondering as I walked the dogs today (a key part of the day for thinking!) what the most important message in the book is. I did a bit of thinking and a bit of searching, and decided that the following two paragraphs expose the core thesis of the book. I’ll quote them below and then explain briefly why (the long explanation would require me to post most of the book here!). The paragraph is italicised in the book.

“A CSP [Cloud Service Provider] can have computational assurances that a tenant’s workloads cannot affect its hosts’ normal operation, but no such computational assurances are available to a tenant that a CSP’s hosts will not affect their workloads’ normal operation.

In other words, the tenant has to rely on commercial relationships for trust establishment, whereas the CSP can rely on both commercial relationships and computational techniques. Worse yet, the tenant has no way to monitor the actions of the CSP and its host machines to establish whether the confidentiality of its workloads has been compromised (though integrity compromise may be detectable in some situations): so even the “trust, but verify” approach is not available to them.”

What does this mean? There is, in cloud computing, a fundamental asymmetry: CSPs can protect themselves from you (their customer), but you can’t protect yourself from them.

Without Confidential Computing – the use of Trusted Execution Environments to protect your workloads – there are no technical measures that you can take which will stop Cloud Service Providers from looking into and/or altering not only your application, but also the data it is processing, storing and transmitting. CSPs can stop you from doing the same to them using standard virtualisation techniques, but those techniques provide you with no protection from a malicious or compromised host, or a malicious or compromised CSP.

I attended a conference recently attended by lots of people whose job it is to manage and process data for their customers. Many of them do so in the public cloud. And a scary number of them did not understand that all of this data is vulnerable, and that the only assurances they have are commercial and process-based.

We in the security world have to make people understand this issue, and realise that if they are looking after our data, they need to find ways to protect it with strong technical controls. These controls are few:

architectural: never deploy sensitive data to the public cloud, ever.
HSMs: use Hardware Security Modules. These are expensive, difficult to use and don’t scale, but they are appropriate for some sensitive data.
Confidential Computing: use Trusted Execution Environments (TEEs) to protect data and applications in use[1].

Given my interest – and my drive to write and publish my book – it will probably come as no surprise that this is something I care about: I’m co-founder of the Enarx Project (an open source Confidential Computing project) and co-founder and CEO of Profian (a start-up based on Enarx). But I’m not alone: the industry is waking up to the issue, and you can find lots more about the subject at the Confidential Computing Consortium‘s website (including a list of members of the consortium). If this matters to you – and if you’re an enterprise company who uses the cloud, it almost certainly already does, or will do so – then please do your research and consider joining as well. And my book is available for pre-order!

Win a copy of my book!

What’s better than excerpts? That’s right: the entire book.

As regular readers of this blog will know, I’ve got a book coming out with Wiley soon. It’s called “Trust in Computer Systems and the Cloud”, and the publisher’s blurb is available here. We’ve now got to the stage where we’ve completed not only the proof-reading for the main text, but also the front matter (acknowledgements, dedication, stuff like that), cover and “praise page”. I’d not heard the term before, but it’s where endorsements of the book go, and I’m very, very excited by the extremely kind comments from a variety of industry leaders which you’ll find quoted there and, in some cases, on the cover. You can find a copy of the cover (without endorsement) below.

Trust book front cover (without endorsement)

I’ve spent a lot of time on this book, and I’ve written a few articles about it, including providing a chapter index and summary to let you get a good idea of what it’s about. More than that, some of the articles here actually contain edited excerpts from the book.

What’s better than excerpts, though? That’s right: the entire book. Instead of an article today, however, I’m offering the opportunity to win a copy of the book. All you need to do is follow this blog (with email updates, as otherwise I can’t contact you), and when it’s published (soon, we hope – the March date should be beaten), I’ll choose one lucky follower to receive a copy.

No Wiley employees, please, but other than that, go for it, and I’ll endeavour to get you a copy as soon as I have any available. I’ll try to get it to you pretty much anywhere in the world, as well. So far, it’s only available in English, so apologies if you were hoping for an immediate copy in another language (hint: let me know, and I’ll lobby my publisher for a translation!).

Trust book – chapter index and summary

I thought it might be interesting to provide the chapter index and a brief summary of each chapter addresses.

In a previous article, I presented the publisher’s blurb for my upcoming book with Wiley, Trust in Computer Systems and the Cloud. I thought it might be interesting, this time around, to provide the chapter index of the book and to give a brief summary of what each chapter addresses.

While it’s possible to read many of the chapters on their own, I haved tried to maintain a logical progression of thought through the book, building on earlier concepts to provide a framework that can be used in the real world. It’s worth noting that the book is not about how humans trust – or don’t trust – computers (there’s a wealth of literature around this topic), but about how to consider the issue of trust between computing systems, or what we can say about assurances that computing systems can make, or can be made about them. This may sound complex, and it is – which is pretty much why I decided to write the book in the first place!

Introduction
- Why I think this is important, and how I came to the subject.
Chapter 1 – Why Trust?
- Trust as a concept, and why it’s important to security, organisations and risk management.
Chapter 2 – Humans and Trust
- Though the book is really about computing and trust, and not humans and trust, we need a grounding in how trust is considered, defined and talked about within the human realm if we are to look at it in our context.
Chapter 3 – Trust Operations and Alternatives
- What are the main things you might want to do around trust, how can we think about them, and what tools/operations are available to us?
Chapter 4 – Defining Trust in Computing
- In this chapter, we delve into the factors which are specific to trust in computing, comparing and contrasting them with the concepts in chapter 2 and looking at what we can and can’t take from the human world of trust.
Chapter 5 – The Importance of Systems
- Regular readers of this blog will be unsurprised that I’m interested in systems. This chapter examines why systems are important in computing and why we need to understand them before we can talk in detail about trust.
Chapter 6 – Blockchain and Trust
- This was initially not a separate chapter, but is an important – and often misunderstood or misrepresented – topic. Blockchains don’t exist or operate in a logical or computational vacuum, and this chapter looks at how trust is important to understanding how blockchains work (or don’t) in the real world.
Chapter 7 – The Importance of Time
- One of the important concepts introduced earlier in the book is the consideration of different contexts for trust, and none is more important to understand than time.
Chapter 8 – Systems and Trust
- Having introduced the importance of systems in chapter 5, we move to considering what it means to have establish a trust relationship from or to a system, and how the extent of what is considered part of the system is vital.
Chapter 9 – Open Source and Trust
- Another topc whose inclusion is unlikely to surprise regular readers of this blog, this chapter looks at various aspects of open source and how it relates to trust.
Chapter 10 – Trust, the Cloud, and the Edge
- Definitely a core chapter in the book, this addresses the complexities of trust in the modern computing environments of the public (and private) cloud and Edge networks.
Chapter 11 – Hardware, Trust, and Confidential Computing
- Confidential Computing is a growing and important area within computing, but to understand its strengths and weaknesses, there needs to be a solid theoretical underpinning of how to talk about trust. This chapter also covers areas such as TPMs and HSMs.
Chapter 12 – Trust Domains
- Trust domains are a concept that allow us to apply the lessons and frameworks we have discussed through the book to real-world situations at large scale. They also allow for modelling at the business level and for issues like risk management – introduced at the beginning of the book – to be considered more explicitly.
Chapter 13 – A World of Explicit Trust
- Final musings on what a trust-centric (or at least trust-inclusive) view of the world enables and hopes for future work in the field.
References
- List of works cited within the book.

Trust book preview

What it means to trust in the context of computer and network security

Just over two years ago, I agreed a contract with Wiley to write a book about trust in computing. It was a long road to get there, starting over twenty years ago, but what pushed me to commit to writing something was a conference I’d been to earlier in 2019 where there was quite a lot of discussion around “trust”, but no obvious underlying agreement about what was actually meant by the term. “Zero trust”, “trusted systems”, “trusted boot”, “trusted compute base” – all terms referencing trust, but with varying levels of definition, and differing understanding if what was being expected, by what components, and to what end.

I’ve spent a lot of time thinking about trust over my career and also have a major professional interest in security and cloud computing, specifically around Confidential Computing (see Confidential computing – the new HTTPS? and Enarx for everyone (a quest) for some starting points), and although the idea of a book wasn’t a simple one, I decided to go for it. This week, we should have the copy-editing stage complete (technical editing already done), with the final stage being proof-reading. This means that the book is close to down. I can’t share a definitive publication date yet, but things are getting there, and I’ve just discovered that the publisher’s blurb has made it onto Amazon. Here, then, is what you can expect.

Learn to analyze and measure risk by exploring the nature of trust and its application to cybersecurity

Trust in Computer Systems and the Cloud delivers an insightful and practical new take on what it means to trust in the context of computer and network security and the impact on the emerging field of Confidential Computing. Author Mike Bursell’s experience, ranging from Chief Security Architect at Red Hat to CEO at a Confidential Computing start-up grounds the reader in fundamental concepts of trust and related ideas before discussing the more sophisticated applications of these concepts to various areas in computing.

The book demonstrates in the importance of understanding and quantifying risk and draws on the social and computer sciences to explain hardware and software security, complex systems, and open source communities. It takes a detailed look at the impact of Confidential Computing on security, trust and risk and also describes the emerging concept of trust domains, which provide an alternative to standard layered security.

Foundational definitions of trust from sociology and other social sciences, how they evolved, and what modern concepts of trust mean to computer professionals
A comprehensive examination of the importance of systems, from open-source communities to HSMs, TPMs, and Confidential Computing with TEEs.
A thorough exploration of trust domains, including explorations of communities of practice, the centralization of control and policies, and monitoring

Perfect for security architects at the CISSP level or higher, Trust in Computer Systems and the Cloud is also an indispensable addition to the libraries of system architects, security system engineers, and master’s students in software architecture and security.

Does my TCB look big in this?

The smaller your TCB the less there is to attack, and that’s a good thing.

This isn’t the first article I’ve written about Trusted Compute Bases (TCBs), so if the concept is new to you, I suggest that you have a look at What’s a Trusted Compute Base? to get an idea of what I’ll be talking about here. In that article, I noted the importance of the size of the TCB: “what you want is a small, easily measurable and easily auditable TCB on which you can build the rest of your system – from which you can build a ‘chain of trust’ to the other parts of your system about which you care.” In this article, I want to take some time to discuss the importance of the size of a TCB, how we might measure it, and how difficult it can be to reduce the TCB size. Let’s look at all of those issues in order.

Size does matter

However you measure it – and we’ll get to that below – the size of the TCB matters for two reasons:

the larger the TCB is, the more bugs there are likely to be;
the larger the TCB is, the larger the attack surface.

The first of these is true of any system, and although there may be ways of reducing the number of bugs, proving the correctness of all or, more likely, part of the system, bugs are both tricky to remove and resilient – if you remove one, you may well be introducing another (or worse, several). Now, the kinds or bugs you have, and the number of them, can be reduced through a multitude of techniques, from language choice (choosing Rust over C/C++ to reduce memory allocation errors, for instance) to better specification and on to improved test coverage and fuzzing. In the end, however, the smaller the TCB, the less code (or hardware – we’re considering the broader system here, don’t forget), you have to trust, the less space there is for there to be bugs in it.

The concept of an attack surface is important, and, like TCBs, one I’ve introduced before (in What’s an attack surface?). Like bugs, there may be no absolute measure of the ratio of danger:attack surface, but the smaller your TCB, well, the less there is to attack, and that’s a good thing. As with bug reduction, there are number of techniques you may want to apply to reduce your attack surface, but the smaller it is, then, by definition, the fewer opportunities attackers have to try to compromise your system.

Measurement

Measuring the size of your TCB is really, really hard – or, maybe I should say that coming up with an absolute measure that you can compare to other TCBs is really, really hard. The problem is that there are so many measurements that you might take. The ones you care about are probably those that can be related to attack surface – but there are so many different attack vectors that might be relevant to a TCB that there are likely to be multiple attack surfaces. Let’s look at some of the possible measurements:

number of API methods
amount of data that can be passed across each API method
number of parameters that can be passed across each API method
number of open network sockets
number of open local (e.g. UNIX) sockets
number of files read from local storage
number of dynamically loaded libraries
number of DMA (Direct Memory Access) calls
number of lines of code
amount of compilation optimisation carried out
size of binary
size of executing code in memory
amount of memory shared with other processes
use of various caches (L1, L2, etc.)
number of syscalls made
number of strings visible using strings command or similar
number of cryptographic operations not subject to constant time checks

This is not meant to be an exhaustive list, but just to show the range of different areas in which vulnerabilities might appear. Designing your application to reduce one may increase another – one very simple example being an attempt to reduce the number of API calls exposed by increasing the number of parameters on each call, another being to reduce the size of the binary by using more dynamically linked libraries.

This leads us to an important point which I’m not going to address in detail in this article, but which is fundamental to understanding TCBs: that without a threat model, there’s actually very little point in considering what your TCB is.

Reducing the TCB size

We’ve just seen one of the main reasons that reducing your TCB size is difficult: it’s likely to involve trade-offs between different measures. If all you’re trying to do is produce competitive marketing material where you say “my TCB is smaller than yours”, then you’re likely to miss the point. The point of a TCB is to have a well-defined computing base which can protect against specific threats. This requires you to be clear about exactly what functionality requires that it be trusted, where it sits in the system, and how the other components in the system rely on it: what trust relationships they have. I was speaking to a colleague just yesterday who was relaying a story of software project who said, “we’ve reduced our TCB to this tiny component by designing it very carefully and checking how we implement it”, but who overlooked the fact that the rest of the stack – which contained a complete Linux distribution and applications – could be no more trusted than before. The threat model (if there was one – we didn’t get into details) seemed to assume that only the TCB would be attacked, which missed the point entirely: it just added another “turtle” to the stack, without actually fixing the problem that was presumably at issue: that of improving the security of the system.

Reducing the TCB by artificially defining what the TCB is to suit your capabilities or particular beliefs around what the TCB specifically should be protecting against is not only unhelpful but actively counter-productive. This is because it ignores the fact that a TCB is there to serve the needs of a broader system, and if it is considered in isolation, then it becomes irrelevant: what is it acting as a base for?

In conclusion, it’s all very well saying “we have a tiny TCB”, but you need to know what you’re protecting, from what, and how.

Dependencies and supply chains

A dependency on a component is one which that an application or component needs to work

Supply chain security is really, really hot right now. It’s something which folks in the “real world” of manufactured things have worried about for years – you might be surprised (and worried) how much effort aircraft operators need to pay to “counterfeit parts”, and I wish I hadn’t just searched online the words “counterfeit pharmaceutical” – but the world of software had a rude wake-up call recently with the Solarwinds hack (or crack, if you prefer). This isn’t the place to go over that: you’ll be able to find many, many articles if you search on that. In fact, many companies have been worrying about this for a while, but the change is that it’s an issue which is now out in the open, giving more leverage to those who want more transparency around what software they consume in their products or services.

When we in computing (particularly software) think about supply chains, we generally talk about “dependencies”, and I thought it might be useful to write a short article explaining the main dependency types.

What is a dependency?

A dependency on a component is one which that an application or component needs to work, and they are generally considered to come in two types:

build-time dependencies
run-time dependencies.

Let’s talk about those two types in turn.

Build-time dependencies

these are components which are required in order to build (typically compile and package) your application or library. For example, if I’m writing a program in Rust, I have a dependency on the compiler if I want to create an application. I’m actually likely to have many more run-time dependencies, however. How those dependencies are made visible to me will depend on the programming language and the environment that I’m building in.

Some languages, for instance, may have filesystem support built in, but others will require you to “import” one or more libraries in order to read and write files. Importing a library basically tells your build-time environment to look somewhere (local disk, online repository, etc.) for a library, and then bring it into the application, allowing its capabilities to be used. In some cases, you will be taking pre-built libraries, and in others, your build environment may insist on building them itself. Languages like Rust have clever environments which can look for new versions of a library, download it and compile it without your having to worry about it yourself (though you can if you want!).

To get back to your file system example, even if the language does come with built-in filesystem support, you may decide to import a different library – maybe you need some fancy distributed, sharded file system, for instance – from a different supplier. Other capabilities may not be provided by the language, or may be higher-level capabilities: JSON serialisation or HTTPS support, for instance. Whether that library is available in open source may have a large impact on your decision as to whether or not to use it.

Build-time dependencies, then, require you to have the pieces you need – either pre-built or in source code form – at the time that you’re building your application or library.

Run-time dependencies

Run-time dependencies, as the name implies, only come into play when you actually want to run your application. We can think of there being two types of run-time dependency:

service dependency – this may not be the official term, but think of an application which needs to write some data to a window on a monitor screen: in most cases, there’s already a display manager and a window manager running on the machine, so all the application needs to do is contact it, and communicate the right data over an API. Sometimes, the underlying operating system may need to start these managers first, but it’s not the application itself which is having to do that. These are local services, but remote services – accessing a database, for instance – operate in the same sort of way. As long as the application can contact and communicate with the database, it doesn’t need to do much itself. There’s still a dependency, and things can definitely go wrong, but it’s a weak coupling to an external application or service.
dynamic linking – this is where an application needs access to a library at run-time, but rather than having added it at build-time (“static linking”), it relies on the underlying operating system to provide a link to the library when it starts executing. This means that the application doesn’t need to be as large (it’s not “carrying” the functionality with it when it’s installed), but it does require that the version that the operating system provides is compatible with what’s expected, and does the right thing.

Conclusion

I’ve resisted the temptation to go into the impacts of these different types of dependency in terms of their impact on security. That’s a much longer article – or set of articles – but it’s worth considering where in the supply chain we consider these dependencies to live, and who controls them. Do I expect application developers to check every single language dependency, or just imported libraries? To what extent should application developers design in protections from malicious (or just poorly-written) dynamically-linked libraries? Where does the responsibility lie for service dependencies – particularly remote ones?

These are all complex questions: the supply chain is not a simple topic (partly because there is not just one supply chain, but many of them), and organisations need to think hard about how they work.

They won’t get security right

Save users from themselves: make it difficult to do the wrong thing.

I’m currently writing a book at Trust in computing and the cloud – I’ve mentioned it before – and I confidently expect to reach 50% of my projected word count today, as I’m on holiday, have more time to write it, and got within about 850 words of the goal yesterday. Little boast aside, one of the topics that I’ve been writing about is the need to consider the contexts in which the systems you design and implement will be used.

When we design systems, there’s a temptation – a laudable one, in many cases – to provide all of the features and functionality that anyone could want, to implement all of the requests from customers, to accept every enhancement request that comes in from the community. Why is this? Well, for a variety of reasons, including:

we want our project or product to be useful to as many people as possible;
we want our project or product to match the capabilities of another competing one;
we want to help other people and be seen as responsive;
it’s more interesting implementing new features than marking an existing set complete, and settling down to bug fixing and technical debt management.

These are all good – or at least understandable – reasons, but I want to argue that there are times that you absolutely should not give in to this temptation: that, in fact, on every occasion that you consider adding a new feature or functionality, you should step back and think very hard whether your product would be better if you rejected it.

Don’t improve your product

This seems, on the face of it, to be insane advice, but bear with me. One of the reasons is that many techies (myself included) are more interested getting code out of the door than weighing up alternative implementation options. Another reason is that every opportunity to add a new feature is also an opportunity to deal with technical debt or improve the documentation and architectural information about your project. But the other reasons are to do with security.

Reason 1 – attack surface

Every time that you add a feature, a new function, a parameter on an interface or an option on the command line, you increase the attack surface of your code. Whether by fuzzing, targeted probing or careful analysis of your design, the larger the attack surface of your code, the more opportunities there are for attackers to find vulnerabilities, create exploits and mount attacks on instances of your code. Strange as it may seem, adding options and features for your customers and users can often be doing them a disservice: making them more vulnerable to attacks than they would have been if you had left well enough alone.

If we do not need an all-powerful administrator account after initial installation, then it makes sense to delete it after it has done its job. If logging of all transactions might yield information of use to an attacker, then it should be disabled in production. If older versions of cryptographic functions might lead to protocol attacks, then it is better to compile them out than just to turn them off in a configuration file. All of these lead to reductions in attack surface which ultimately help safeguard users and customers.

Reason 2 – saving users from themselves

The other reason is also about helping your users and customers: saving them from themselves. There is a dictum – somewhat unfair – within computing that “users are stupid”. While this is overstating the case somewhat, it is fairer to note that Murphy’s Law holds in computing as it does everywhere else: “Anything that can go wrong, will go wrong”. Specific to our point, some user somewhere can be counted upon to use the system that you are designing, implementing or operating in ways which are at odds with your intentions. IT security experts, in particular, know that we cannot stop people doing the wrong thing, but where there are opportunities to make it difficult to do the wrong thing, then we should embrace them.

Not adding features, disabling capabilities and restricting how your product is used might seem counter-intuitive, but if it leads to a safer user experience and fewer vulnerabilities associated with your product or project, then in the end, everyone benefits. And you can use the time to go and write some documentation. Or go to the beach. Enjoy!

An Enarx milestone: binaries

Demoing the same binary in very different TEEs.

This week is Red Hat Summit, which is being held virtually for the first time because of the Covid-19 crisis. The lock-down has not affected the productivity of the Enarx team, however (at least not negatively), as we have a very exciting demo that we will be showing at Summit. This post should be published at 1100 EDT, 1500 BST, 1400 GMT on Tuesday, 2020-04-28, which is the time that the session which Nathaniel McCallum and I recorded will be released to the world. I hope to be able to link to that once it’s released to the world. But what will we be showing?

Well, to set the scene, and to discover a little more about the Enarx project, you might want to read these articles first (also available in Japanese – visit each article of a link):

Enarx, as you’ll discover, is about running workloads in TEEs (Trusted Execution environments), using WebAssembly, in what we call “Keeps”. It’s a mammoth job, particularly as we’re abstracting away the underlying processor architectures (currently two: Intel’s SGX and AMD’s SEV), so that you, the user, don’t need to worry about them: all you need to do is write and compile your application, then request that it be deployed. Enarx, then, has lots of moving parts, and one of the key tasks for us has been to start the work to abstract away the underlying processor architectures so that we can prepare the runtime layers on top. Here’s a general picture of the software layers, and how they sit on top of the hardware platforms:

What we’re announcing – and demoing – today is that we have an initial implementation of code to allow us to abstract away process-based and VM-based types of architecture (with examples for SGX and SEV), so that we can do this:

This seems deceptively simple, but what’s actually going on under the covers is rather more than is exposed in the picture above. The reality is more like this:

This gives more detail: the application that’s running on both architectures (SGX on the left, SEV on the right) is the very same ELF static-PIE binary. To be clear, this is not only the same source code, compiled for different platforms, but exactly the same binary, with the very same hash signature. What’s pretty astounding about this is that in order to make it run on both platforms, the engineering team has had to write two sets of seriously low-level code, including more than a little Assembly language, providing the “plumbing” to allow the binary to run on both.

This is a very big deal, because although we’ve only implemented a handful of syscalls on each platform – enough to make our simple binary run and print out a message – we now have a framework on which we know we can build. And what’s next? Well, we need to expand that framework so that we can then build the WebAssembly layers which will allow WebAssembly applications to run on top:

There’s a long way to go, but this milestone shows that we have an initial framework which we can improve, and on which we can build.

What’s next?

What’s exciting about this milestone from our point of view is that we think it puts Enarx at a stage where more people can join and take part. There’s still lots of low-level work to be done, but it’s going to be easier to split up now, and also to start some of the higher level work, too. Enarx is completely open source, and we do all of our design work in the open, along with our daily stand-ups. You’re welcome to browse our documentation, RFCs (mostly in draft at the moment), raise issues, and join our calls. You can find loads more information on the Enarx wiki: we look forward to your involvement in the project.

Last, and not least, I’d like to take a chance to note that we now have testing/CI/CD resources available for the project with both Intel SGX and AMD SEV systems available to us, all courtesy of Packet. This is amazingly generous, and we both thank them and encourage you to visit them and look at their offerings for yourself!