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:

  1. the larger the TCB is, the more bugs there are likely to be;
  2. 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.

Review of CCC members by business interests

Reflections on the different types of member in the Confidential Computing Consortium

This is a brief post looking at the Confidential Computing Consortium (the “CCC”), a Linux Foundation project “to accelerate the adoption of Trusted Execution Environment (TEE) technologies and standards.” First, a triple disclaimer: I’m a co-founder of the Enarx project (a member project of the CCC), an employee of Red Hat (which donated Enarx to the CCC and is a member) and an officer (treasurer) and voting member of two parts of the CCC (the Governing Board and Technical Advisory Committee), and this article represents my personal views, not (necessarily) the views of any of the august organisations of which I am associated.

The CCC was founded in October 2019, and is made up of three different membership types: Premier, General and Associate members. Premier members have a representative who gets a vote on various committees, and General members are represented by elected representatives on the Governing Board (with a representative elected for every 10 General Members). Premier members pay a higher subscription than General Members. Associate membership is for government entities, academic and nonprofit organisations. All members are welcome to all meetings, with the exception of “closed” meetings (which are few and far between, and are intended to deal with issues such as hiring or disciplinary matters). At the time of writing, there are 9 Premier members, 20 General members and 3 Associate members. There’s work underway to create an “End-User Council” to allow interested organisations to discuss their requirements, use cases, etc. with members and influence the work of the consortium “from the outside” to some degree.

The rules of the consortium allow only one organisation from a “group of related companies” to appoint a representative (where they are Premier), with similar controls for General members. This means, for instance, that although Red Hat and IBM are both active within the Consortium, only one (Red Hat) has a representative on the Governing Board. If Nvidia’s acquisition of Arm goes ahead, the CCC will need to decide how to manage similar issues there.

What I really wanted to do in this article, however, was to reflect on the different types of member, not by membership type, but by their business(es). I think it’s interesting to look at various types of business, and to reflect on why the CCC and confidential computing in general are likely to be of interest to them. You’ll notice a number of companies – most notably Huawei and IBM (who I’ve added in addition to Red Hat, as they represent a wide range of business interests between them) – appearing in several of the categories. Another couple of disclaimers: I may be misrepresenting both the businesses of the companies represented and also their interests! This is particularly likely for some of the smaller start-up members with whom I’m less familiar. These are my thoughts, and I apologise for errors: please feel free to contact me with suggestions for corrections.

Cloud Service Providers (CSPs)

Cloud Service Providers are presented with two great opportunities by confidential computing: the ability to provide their customers with greater isolation from other customers’ workloads, and the chance to avoid having to trust the CSP themselves. The first is the easiest to implement, and the one on which the CSPs have so far concentrated, but I hope we’re going to see more of the latter in the future, as regulators (and customers’ CFOs/auditors) realise that deploying to the cloud does not require a complex trust relationship with the operators of the hosts running the workload.

  • Google
  • IBM
  • Microsoft

The most notable missing player in this list is Amazon, whose AWS offering would seem to make them a good fit for the CCC, but who have not joined up to this point.

Silicon vendors

Silicon vendors produce their own chips (or license their designs to other vendors). They are the ones who are providing the hardware technology to allow TEE-based confidential computing. All of the major silicon vendors are respresented in the CCC, though not all of them have existing products in the market. It would be great to see more open source hardware (RISC-V is not represented in the CCC) to increase the trust the users can have in confidential computing, but the move to open source hardware has been slow so far.

  • AMD
  • Arm
  • Huawei
  • IBM
  • Intel
  • Nvidia

Hardware manufacturers

Hardware manufacturers are those who will be putting TEE-enabled silicon in their equipment and providing services based on it. It is not surprising that we have no “commodity” hardware manufacturers represented, but interesting that there are a number of companies who create dedicated or specialist hardware.

  • Cisco
  • Google
  • Huawei
  • IBM
  • Nvidia
  • Western Digital
  • Xilinx

Service companies

In this category I have added companies which provide services of various kinds, rather than acting as ISVs or pure CSPs. We can expect a growing number of service companies to realise the potential of confidential computing as a way of differentiating their products and providing services with interesting new trust models for their customers.

  • Accenture
  • Ant Group
  • Bytedance
  • Facebook
  • Google
  • Huawei
  • IBM
  • Microsoft
  • Red Hat
  • Swisscom

ISVs

There are a number of ISVs (Independent Software Vendors) who are members of the CCC, and this heading is in some ways a “catch-all” for members who don’t necessarily fit cleanly under any of the other headings. There is a distinct subset, however, of blockchain-related companies which I’ve separated out below.

What is particularly interesting about the ISVs represented here is that although the CCC is dedicated to providing open source access to TEE-based confidential computing, most of the companies in this category do not provide open source code, or if they do, do so only for a small part of the offering. Membership of the CCC does not in any way require organisations to open source all of their related software, however, so their membership is not problematic, at least from the point of view of the charter. As a dedicated open source fan, however, I’d love to see more commitment to open source from all members.

  • Anjuna
  • Anqlave
  • Bytedance
  • Cosmian
  • Cysec
  • Decentriq
  • Edgeless Systems
  • Fortanix
  • Google
  • Huawei
  • IBM
  • r3
  • Red Hat
  • VMware

Blockchain

As permissioned blockchains gain traction for enterprise use, it is becoming clear that there are some aspects and components of their operation which require strong security and isolation to allow trust to be built into the operating model. Confidential computing provides ways to provide many of the capabilities required in these contexts, which is why it is unsurprising to see so many blockchain-related companies represented in the CCC.

  • Appliedblockchain
  • Google
  • IBM
  • iExec
  • Microsoft
  • Phala network
  • r3

Enarx end-to-end complete!

We now have a fully working end-to-end proof of concept, with no smoke and mirrors.

I’ve written lots about the Enarx project, a completely open source project around deploying workloads to Trusted Execution Environments, and you can find a few of the articles here:

I have some very exciting news to announce.

A team effort

Yesterday was a huge day for the Enarx project, in that we now have a fully working end-to-end proof of concept, with no smoke and mirrors (we don’t believe in those). The engineers on the team have been working really hard on getting all of the low-level pieces in place, with support from other members on CI/CD, infrastructure, documentation, community outreach and beyond. I won’t mention everyone, as I don’t want to miss anyone out, and I also don’t have their permission, but it’s been fantastic working with everyone. We’ve been edging closer and closer to having all the main pieces ready to go, and just before Christmas/New Year we got attested AMD SEV Keeps working, with the ability to access information from that attestation within the Keep. This allowed us to move to the final step, which is creating an end-to-end client-server architecture. It is this that we got running yesterday.

I happened to be the lucky person to be able to complete this part of the puzzle, building on work by the rest of the team. I don’t have the low-level expertise that many of the team have, but my background is in client-server and peer-to-peer distributed systems, and after I started learning Rust around March 2020, I decided to see if I could do something useful for the project code base: this is my contribution to the engineering. To give you an idea of what we’ve implemented, let’s look at a simple architectural diagram of an Enarx deployment.

Simple Enarx architectural diagram

Much of the work that’s been going on has been concentrated in the Enarx runtime component, getting WebAssembly working in SGX and SEV Trusted Execution Environments, working on syscall implementations and attestation. There’s also been quite a lot of work on glue – how we transfer information around the system in a standards-compliant way (we’re using CBOR encoding throughout). The pieces that I’ve been putting together have been the Enarx client agent, the Enarx host agent (or Enarx Keep Manager) and two pieces which aren’t visible in this diagram (but are in the more detailed one below): the Enarx Keep Loader and Enarx Wasm Loader (“App loader” in the detailed view).

Detailed Enarx architectural diagram

The components

Let’s look at what these components do, and then explain exactly what we’ve achieved. The name in bold refers to the diagram, the name in italics relates to the Rust crate (and, where already merged, the github repository) associated with the component.

  • Enarx Client Agent (client) – responsible to talking to the enarx-keepmgr and requesting a Keep. It checks that the Keep is correctly set up and attested and then sends the workload (a WebAssembly package) to the enarx-wasmldr component, using HTTPS with a one-use certificate derived from the attestation process.
  • Enarx Keep Manager (enarx-keepmgr) – creates enarx-keepldr components at the request of the client, proxying communications to them from the client as required (for certain attestation flows, for instance). It is untrusted by the client.
  • Enarx Keep Loader (enarx-keepldr) – there is an enarx-keepldr per Keep, and it performs the loading of components into the Trusted Execution Environment itself. It sits outside the TEE instance, and is therefore untrusted by the client.
  • Enarx App Loader (enarx-wasmldr) – the enarx-wasmldr component resides within the TEE instance, and is therefore has confidentiality and integrity protection from the rest of the host. It receives the WebAssembly (Wasm) workload from the client component and may access secret information provisioned into the Keep during the attestation process.

Here’s the post I made to the Enarx chat #development channel yesterday to announce what we managed to achieve:

  1. client -> keepmgr: “create sev keep”
  2. keepmgr launches sev keep via systemd
  3. client -> keepmgr: “perform attestation, include this private key” (note – private key is encrypted from keepmgr)
  4. keepmgr -> keepldr: “attestation + private key”
  5. keepldr creates keep, passes private key to it
  6. wasmldr creates certificate from private key
  7. wasmldr waits for workload
  8. client sends workload of HTTPS to wasmldr
  9. wasmldr accepts workload over HTTPS
  10. wasmldr executes workload

WE HAVE A FULLY WORKING END-TO-END DEMO! Thank you everyone

What does this mean? Well, everything works! The client requests a Keep using with an AMD SEV instance, it’s created, attested, listens for an incoming connection over HTTPS, and the client sends the workload, which then executes. The workload was written in Rust and compiled to WebAssembly – it’s a real application, in other words, and not a hand-crafted piece of WebAssembly for the purposes of testing.

What’s next?

There’s lots left to do, including:

  • merging all of the code into the main repositories (I was working in a separate set to avoid undue impact on other efforts)
  • tidying it to make it more presentable (both what the demo shows and the quality of the code!)
  • add SGX support – we hope that we’re closing in on this very soon
  • make the various components production-ready (the keepmgr, for instance, doesn’t manage multiple enarx-keepldr components very well yet)
  • define the wire protocol fully (somewhere other than in my head)
  • document everything!

But most of that’s easy: it’s just engineering. 🙂

We’d love you to become involved. If you’re interested, read some of my articles, visit project home page and repositories, hang out on our chat server or watch some of our videos on YouTube. We really welcome involvement – and not just from engineers, either. Come and have a play!

Trust in Computing and the Cloud

I wrote a book.

I usually write and post articles first thing in the morning, before starting work, but today is different. For a start, I’m officially on holiday (so definitely not planning to write any code for Enarx, oh no), and second, I decided that today would be the day that I should finish my book, if I could.

Towards the end of 2019, I signed a contract with Wiley to write a book (which, to be honest, I’d already started) on trust. There’s lots of literature out there on human trust, organisational trust and how humans trust each other, but despite a growing interest in concepts such as zero trust, precious little on how computer systems establish and manage trust relationships to each other. I decided it was time to write a book on this, and also on how trust works (or maybe doesn’t) in the Cloud. I gave myself a target of 125,000 words, simply by looking at a couple of books at the same sort of level and then doing some simple arithmetic around words per page and number of pages. I found out later that I’d got it a bit wrong, and this will be quite a long book – but it turns out that the book that needed writing (or that I needed to write, which isn’t quite the same thing) was almost exactly this long, as when I finished around 1430 GMT today, I found that I was at 124,939 words. I have been tracking it, but not writing to the target, given that my editor told me that I had some latitude, but I’m quite amused by how close it was.

Anyway, I emailed my editor on completion, who replied (despite being on holiday), and given that I’m 5 months or so ahead of schedule, he seems happy (I think they prefer early to late).

I don’t have many more words in me today, so I’m going to wrap up here, but do encourage you to read articles on this blog labelled with “trust”, several of which are edited excerpts from the book. I promise I’ll keep you informed as I get information about publication dates, etc.

Keep safe and have a Merry Christmas and Happy New Year, or whatever you celebrate.

Why I’m writing a book about trust

Who spends their holiday in their office? Authors.

Last week, I was on holiday. That is, I took 5 days off work in which I could have relaxed, read novels, watched TV, played lots of games, gone for long walks on the countryside and (in happier, less Covid-19 times) have spend time away from home, wrapped up warm enjoying a view of waves crashing onto a beach. Instead, I spent those 5 days – and fair amount of the 4 weekend days that bracketed them – squirreled away in my office, sitting at my computer. Which is rather similar to what I would have been doing if I hadn’t taken the time off.

The reason I did this is that I’m writing a book at the moment. Last week I managed to write well over 12,500 words of it, taking me to more than 80% of my projected word count (over 82% if you could bibliographic material), so the time felt well-spent. But why am I doing this in the first place?

I’m doing it at one level because I have a contract to do it. Around July-August last year (2019), I sent emails to a few (3-4) publishers pitching the idea for a book. I included a detailed Table of Contents, evidence that I’ve written before (including some links to this blog), and a bit about me, including a link to my LinkedIn profile. One of the replies I had (within 24 hours, to my amazement) was from Jim Minatel, a commissioning editor from Wiley Technology. Over a number of weeks, I talked to him and editors from other publishers, finally signing a contract with Wiley for a book on Trust in Computing and the Cloud, with a planned word count of 125,000 words. I’m not going to provide details of the contract, but I can say that :

  1. I don’t expect it to make me rich (which was never the point anyway);
  2. it has options for another book or books (I must be insane even to be considering the idea, but Jim and I have already have some preliminary conversations);
  3. there are clauses in it about film/movie rights (nobody, but nobody, is ever going to want to make or watch a film about this book: fascinating as it may be, Tom Clancy or John Grisham it is not).

This kind of explains why I spent last week closeted in my office, tapping away on a computer keyboard, but why did I get in touch with these publishers in the first place, pitching the idea of a book that is consuming a fair number of my non-work waking hours?

The basic reason is that I got cross. In fact, I got so annoyed about something that I went to a couple of people – my boss was one, a good friend with a publishing background was another – and announced that I planned to write a book. I was half hoping that they would dissuade me, but they both enthusiastically endorsed the idea, which meant that I had, at least in my head, now committed to doing it. This was in early May 2019, and it took me a couple of months to gather my thoughts, put together some materials and a find few candidate publishers before actually pitching the book to them and ending up with a contract.

But what actually got me to a position where I was cross enough about something to pitch an idea which would take up so much of my time and energy? The answer? I was tipped over the edge by hearing someone speak about trust in a way that made it clear that they had no idea what they were talking about. It was a session at a conference – I can remember the conference, but I can’t remember the session or the speaker – where the subject was security: IT security. This is my field, so that’s good. What wasn’t good was what the speaker said when speaking about trust: it didn’t hold together, it wasn’t consistent with how I felt about trust, and I didn’t feel that it was broadly applicable to computing or the Cloud.

This made me cross. And then I thought: why is there no consensus on what we mean by “trust”? Why do people talk about “zero trust” without really knowing what trust actually means? Why is there no literature on this subject that I’ve been thinking about for nearly 20 years? Why do I keep having conversations with people where they agree that trust is really interesting, but we discover that we don’t have a common starting point as there’s no theoretical underpinning describing exactly we’re discussing? Why are people deploying important workloads and designing business-critical systems without a good framework around what seems like a fundamental concept that everybody is always eager to include in their architectures? Why are we pushing forward with Confidential Computing when people don’t even understand the impact of the trust relationships which underlie it?

And I realised that I could keep asking these questions, and keep having these increasingly frustrating conversations, whilst waiting for somebody to publish some sort of definitive meisterwerk on the subject, or I could just admit that no-one was going to do it, and that I might get on and write something, even if it was never going to be the perfect treatment of what is, after all, a very complex subject.

And so that’s what I decided to do. I thought about what interests me in the field of trust in the realms of computing and the Cloud, about what I’ve heard people talk very badly about, and about what I’d had interesting conversations, decided that I might have something to say about all of those, and then put together a book structure. Wiley liked the idea, and asked me to flesh it out and then write something. It turns out that there’s loads of literature around human-to-human and human-to-organisational trust, and also on human-to-computer system trust, but very little on how computers can trust each other. Given how many organisations run much of their business in the Cloud these days, and the complex trust relationships that exist there, I wanted to write something about how to manage and understand these.

These are topics I’ve thought about (and, increasingly, written about) for around 20 years, since I did some research into the possibility of a PhD (which never materialised) in a related topic. They’ve stayed with me since, and I was involved in some theoretical and standards-based work around trust while involved with the ETSI NFV group nearly 10 years ago. I’m not pretending that I’m perfectly qualified to discuss this topic, but then again, I’m not sure that anybody is, and I feel that putting out some sort of book on this topic makes sense, if only to get the conversation started, and to give people an opportunity to converse with a shared language. The book starts with some theoretical underpinnings, looks at some of the technologies, what their implications are, the place of open source, the commercial and organisational impacts, and then suggests some future and frameworks. I hope to have the manuscript (well, typescript) completed and with Wiley by mid-spring (Northern Hemisphere) 2021: I don’t know when it’s actually likely to appear in print.

I hope people find it interesting, and that it acts as a catalyst for further discussion. I don’t expect it to be the last word on the subject – in fact I hope it’s not – but I do hope that it forces more people to realise that trust is really important in our world of computers, security and risk, and currently ill-understood. And if you happen to be a successful producer of Hollywood blockbusters, then I’m available to talk. Just as soon as I get these last couple of chapters submitted. ..

How open source builds distributed trust

Trust in open source is a positive feedback loop

This is an edited excerpt from my forthcoming book on Trust in Computing and the Cloud for Wiley, and leads on from a previous article I wrote called Trust & choosing open source.

In that article, I asked the question: what are we doing when we say “I trust open source software”? In reply, I suggested that what we are doing is making a determination that enough of the people who have written and tested it have similar requirements to mine, and that their expertise, combined, is such that the risk to my using the software is acceptable. I also introduced the idea of distributed trust.

The concept of distributing trust across a community is an application of the theory of the wisdom of the crowd, posited by Aristotle, where the assumption is that the opinions of many typically show more wisdom than the opinion of one, or a few. While demonstrably false in its simplest form in some situations – the most obvious example being examples of popular support for totalitarian regimes – this principle can provide a very effective mechanism for establishing certain information.

This distillation of collective experience allows what we refer as distributed trust, and is collected through numerous mechanisms on the Internet. Some, like TripAdvisor or Glassdoor, record information about organisations or the services they provide, while others, like UrbanSitter or LinkedIn, allow users to add information about specific people (see, for instance, LinkedIn’s “Recommendations” and “Skills & Endorsements” sections in individual’s profiles). The benefits that can accrue from of these examples are significantly increased by the network effect, as the number of possible connections between members increases exponentially as the number of members increases. Other examples of distributed trust include platforms like Twitter, where the number of followers that an account receives can be seen as a measure of their reputation, and even of their trustworthiness, a calculation which we should view with a strong degree of scepticism: indeed, the company Twitter felt that it had to address the social power of accounts with large numbers of followers and instituted a “verified accounts” mechanism to let people know “that an account of public interest is authentic”. Interestingly, the company had to suspend the service after problems related to users’ expectations of exactly what “verified” meant or implied: a classic case of differing understandings of context between different groups.

Where is the relevance to open source, then? The community aspect of open source is actually a driver towards building distributed trust. This is because once you become a part of the community around an open source project, you assume one or more of the roles that you start trusting once you say that you “trust” an open source project (see my previous article): examples include: architect, designer, developer, reviewer, technical writer, tester, deployer, bug reporter or bug fixer. The more involvement you have in a project, the more one becomes part of the community, which can, in time, become a community of practice. Jean Lave and Etienne Wenger introduced the concept of communities of practice in their book Situated Learning: Legitimate Peripheral Participation, where groups evolve into communities as their members share a passion and participate in shared activities, leading to their improving their skills and knowledge together. The core concept here is that as participants learn around a community of practice, they become members of it at the same time:

“Legitimate peripheral participation refers both to the development of knowledgeably skilled identities in practice and to the reproduction and transformation of communities of practice.”

Wenger further explored the concept of communities of practice, how they form, requirements for their health and how they encourage learning in Communities of Practice: Learning, meaning and identity. He identified negotiability of meaning (“why are we working together, what are we trying to achieve?”) as core to a community of practice, and noted that without engagement, imagination and alignment by individuals, communities of practice will not be robust.

We can align this with our views of how distributed trust is established and built: when you realise that your impact on open source can be equal to that of others, the distributed trust relationships that you hold to members of a community become less transitive (second- or third-hand or even more remote), and more immediate. You understand that the impact that you can have on the creation, maintenance, requirements and quality of the software which you are running can be the same as all of those other, previously anonymous contributors with whom you are now forming a community of practice, or whose existing community of practice you are joining. Then you yourself become part of a network of trust relationships which are distributed, but at less of a remove to that which you experience when buying and operating proprietary software. The process does not stop there, however: a common property of open source projects is cross-pollination, where developers from one project also work on others. This increases as the network effect of multiple open source projects allow reuse and dependencies on other projects to rise, and greater take-up across the entire set of projects.

It is easy to see why many open source contributors become open source enthusiasts or evangelists not just for a single project, but for open source as a whole. In fact, work by Mark Granovetter suggests that too many strong ties within communities can lead to cliques and stagnation, but weak ties provide for movement of ideas and trends around communities. This awareness of other projects and the communities that exist around them, and the flexibility of ideas across projects, leads to distributed trust being able to be extended (albeit with weaker assurances) beyond the direct or short-chain indirect relationships that contributors experience within projects of which they have immediate experience and out towards other projects where external observation or peripheral involvement shows that similar relationships exist between contributors. Put simply, the act of being involved in an open source project and building trust relationships through participation leads to stronger distributed trust towards similar open source projects, or just to other projects which are similarly open source.

What does this mean for each of us? It means that the more we get involved in open source, the more trust we can have in open source, as there will be a corresponding growth in the involvement – and therefore trust – of other people in open source. Trust in open source isn’t just a network effect: it’s a positive feedback loop!

Do I trust this package?

The area of software supply chain management is growing in importance.

This isn’t one of those police dramas where a suspect parcel arrives at the precinct and someone realises just in time that it may be a bomb – what we’re talking about here is open source software packages (though the impact on your application may be similar if you’re not sufficiently suspicious). Open source software is everywhere these days – which is great – but how can you be sure that you should trust the software you’ve downloaded to do what you want? The area of software supply chain management – of which this discussion forms a part – is fairly newly visible in the industry, but is growing in importance. We’re going to consider a particular example.

There’s a huge conversation to be had here about what trust means (see my article “What is trust?” as a starting point, and I have a forthcoming book on Trust in Computing and the Cloud for Wiley), but let’s assume that you have a need for a library which provides some cryptographic protocol implementation. What do you need to know, and what are you choices? We’ll assume, for now, that you’ve already made what is almost certainly the right choice, and gone with an open source implementation (see many of my articles on this blog for why open source is just best for security), and that you don’t want to be building everything from source all the time: you need something stable and maintained. What should be your source of a new package?

Option 1 – use a vendor

There are many vendors out there now who provide open source software through a variety of mechanisms – typically subscription. Red Hat, my employer (see standard disclosure) is one of them. In this case, the vendor will typically stand behind the fitness for use of a particular package, provide patches, etc.. This is your easiest and best choice in many cases. There may be times, however, when you want to use a package which is not provided by a vendor, or not packaged by your vendor of choice: what do you do then? Equally, what decisions do vendors need to make about how to trust a package?

Option 2 – delve deeper

This is where things get complex. So complex, in fact, that I’m going to be examining them at some length in my book. For the purposes of this article, though, I’ll try to be brief. We’ll start with the assumption that there is a single maintainer of the package, and multiple contributors. The contributors provide code (and tests and documentation, etc.) to the project, and the maintainer provides builds – binaries/libraries – for you to consume, rather than your taking the source code and compiling it yourself (which is actually what a vendor is likely to do, though they still need to consider most of the points below). This is a library to provide cryptographic capabilities, so it’s fairly safe to assume that we care about its security. There are at least five specific areas which we need to consider in detail, all of them relying on the maintainer to a large degree (I’ve used the example of security here, though very similar considerations exist for almost any package): let’s look at the issues.

  1. build – how is the package that you are consuming created? Is the build process performed on a “clean” (that is, non-compromised) machine, with the appropriate compilers and libraries (there’s a turtles problem here!)? If the binary is created with untrusted tools, then how can we trust it at all, so what measures does the maintainer take to ensure the “cleanness” of the build environment? It would be great if the build process is documented as a repeatable build, so that those who want to check it can do so.
  2. integrity – this is related to build, in that we want to be sure that the source code inputs to the build process – the code coming, for instance, from a git repository – are what we expect. If, somehow, compromised code is injected into the build process, then we are in a very bad position. We want to know exactly which version of the source code is being used as the basis for the package we are consuming so that we can track features – and bugs. As above, having a repeatable build is a great bonus here.
  3. responsiveness – this is a measure of how responsive – or not – the maintainer is to changes. Generally, we want stable features, tied to known versions, but a quick response to bug and (in particular) security patches. If the maintainer doesn’t accept patches in a timely manner, then we need to worry about the security of our package. We should also be asking questions like, “is there a well-defined security disclosure of vulnerability management process?” (See my article Security disclosure or vulnerability management?), and, if so, “is it followed”?
  4. provenance – all code is not created equal, and one of the things of which a maintainer should be keeping track is the provenance of contributors. If a large amount of code in a part of the package which provides particularly sensitive features is suddenly submitted by an unknown contributor with a pseudonymous email address and no history of contributions of security functionality, this should raise alarm bells. On the other hand, if there is a group of contributors employed by a company with a history of open source contributions and well-reviewed code who submit a large patch, this is probably less troublesome. This is a difficult issue to manage, and there are typically no definite “OK” or “no-go” signs, but the maintainer’s awareness and management of contributors and their contributions is an important point to consider.
  5. expertise – this is the most tricky. You may have a maintainer who is excellent at managing all of the points above, but is just not an expert in certain aspects of the functionality of the contributed code. As a consumer of the package, however, I need to be sure that it is fit for purpose, and that may include, in the case of the security-related package we’re considering, being assured that the correct cryptographic primitives are used, that bounds-checking is enforced on byte streams, that proper key lengths are used or that constant time implementations are provided for particular primitives. This is very, very hard, and the job of maintainer can easily become a full-time one if they are acting as the expert for a large and/or complex project. Indeed, best practice in such cases is to have a team of trusted, experienced experts who work either as co-maintainers or as a senior advisory group for the project. Alternatively, having external people or organisations (such as industry bodies) perform audits of the project at critical junctures – when a major release is due, or when an important vulnerability is patched, for instance – allows the maintainer to share this responsibility. It’s important to note that the project does not become magically “secure” just because it’s open source (see Disbelieving the many eyes hypothesis), but that the community, when it comes together, can significantly improve the assurance that consumers of a project can have in the packages which is produces.

Once we consider these areas, we then need to work out how we measure and track each of them. Who is in a position to judge the extent to which any particular maintainer is fulfilling each of the areas? How much can we trust them? These are a set of complex issues, and one about which much more needs to be written, but I am passionate about exposing the importance of explicit trust in computing, particularly in open source. There is work going on around open source supply chain management, for instance the new (at time of writing Project Rekor – but there is lots of work still to be done.

Remember, though: when you take a package – whether library or executable – please consider what you’re consuming, what about it you can trust, and on what assurances that trust is founded.

Security is (only) subjective

What aspects of security does it provide?

This article covers ground covered in more detail within (but is not quite an excerpt from) my forthcoming book on Trust in Computing and the Cloud for Wiley.

In 1985, the US Department of Defense [sic] published the “Orange Book”[1], officially named Trusted Computer System Evaluation Criteria. It was a guide to how to create a “trusted system”, and was hugely influential within the IT and security industry as a whole. Eight years later, in 1993, Dorothy Denny published a devastating critique of the Orange Book called A New Paradigm for Trusted Systems[1]. It is a brilliant step-by-step analysis of why the approach taken by the DoD was fundamentally flawed. Denning starts:

“The current paradigm for trusted computer systems holds that trust is a property of a system. It is a property that can be formally modeled, specified, and verified. It can be designed into a system using a rigorous design methodology.”

Later, she explains why this just doesn’t work in the real world:

“The current paradigm of treating trust as a property is inconsistent, with the way trust is actually established in the world. It is not a property, but rather an assessment that is based on experience and shared through networks of people in the world-wide market. It is a declaration made by an observer, rather than a property of the observed.”

Demolishing the idea that trust is an inherent property of a system, and making it relational instead, changed the way that systems designed for security would be considered (and ushered in a new approach by the US Government and associated organisations, known was Common Criteria). Denning was writing about trust, but very similar issues exist around the concept of “security”. Too often, security is considered an inherent or intrinsic property of a system: “it’s secure”, someone will say, or “this fix will secure your computer”. It isn’t, and it won’t.

The first problem with such statements is that it’s not clear what “secure” means. There are a number of properties associated with systems that are relevant to security: three of the ones most often quoted are confidentiality, integrity and availability (which I discuss in more detail in the post The Other CIA: Confidentiality, Integrity and Availability). Specifying which of these you’re interested in removes the temptation just to say that something is “secure”, and if someone says, “it provides security”, we’re now in a position to start asking what that assertion actually means. Which aspects of security does it provide?

I also don’t think it makes sense to say that a system is “confidential” or “available” (there’s no obvious equivalent adjective for integrity – “integral” means something rather different): what we may be able to say is that it exhibits properties associated with confidentiality, integrity and availability, or better, that it has measures associated with it which are designed and intended to provide confidentiality, integrity and availability. These measures can be listed, examined and evaluated, hopefully against well-defined criteria.

This seems like a much better approach: not only have we addressed the suggestion that there is such as thing as “security” that we can apply to a system, but following Denning, we have also challenged the suggestion that it is inherent to – or in – a system. Instead, we have introduced the alternative approach of describing security-related properties which can be subjected to scrutiny by the users of the system. This allows the type of relational understanding of security that Denning was proposing, but it also raises the possibility of differing parties having different views of the security (or not) of a system, depending on who they are, and how it is going to be used.

It turns out, when you think about it, that this makes a lot of sense. A laptop which provides sufficient confidentiality, integrity and availability protection for the computing needs of my retired uncle may not provide sufficient protections for the uses to which an operative of a government security service might put it[3]. Equally, a system which a telecommunications company runs in a physically protected data centre may well be considered to have appropriate security protections, whereas the same system, attached to a pole somewhere on a residential street, might not. The measures applied to provide the protections associated with the properties (e.g. 128 bit AES encryption for the confidentiality) may be objectively specifiable, but the extent to which they provide “security” is not, because they are relative to specific requirements.

One last point, and it’s one which regular readers of my blog will be unsurprised to see: how can you assess the applicability of a system’s security properties to your requirements if it is not open? Open source helps significantly with security. Yes, there are assessment regimes to say that systems meet certain criteria – and sometimes these can be very helpful – but they are generally broad criteria, and difficult to apply to your specific use cases. Equally, most are just a starting point, and many such certified systems will require “exceptions” to be met in order to function in the real world, exceptions which require significant expertise to understand, judge and apply safely (that is, with appropriate levels of risk). If the system you want to use is open, then you, a party who you trust, or the wider community can evaluate the appropriateness of controls and measures, and make an informed decision about whether a system’s security properties are what you need. Without open source, this is impossible.


1 – it had an orange cover.

2 – Denning, Dorothy E. (1993) A New Paradigm for Trusted Systems [online]. Available at: https://www.researchgate.net/publication/234793347_A_New_Paradigm_for_Trusted_Systems [Accessed 3 Apr. 2020]

3 – I’m assuming that my uncle isn’t an operative of a government security service[4].

4 – or at least that his security needs are reduced in retirement[5].

5 – that is, if he has really retired…