Tag Archives: advogato

Digital forgeries are hard

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/69507.html

Closing arguments in the trial between various people and Craig Wright over whether he’s Satoshi Nakamoto are wrapping up today, amongst a bewildering array of presented evidence. But one utterly astonishing aspect of this lawsuit is that expert witnesses for both sides agreed that much of the digital evidence provided by Craig Wright was unreliable in one way or another, generally including indications that it wasn’t produced at the point in time it claimed to be. And it’s fascinating reading through the subtle (and, in some cases, not so subtle) ways that that’s revealed.

One of the pieces of evidence entered is screenshots of data from Mind Your Own Business, a business management product that’s been around for some time. Craig Wright relied on screenshots of various entries from this product to support his claims around having controlled meaningful number of bitcoin before he was publicly linked to being Satoshi. If these were authentic then they’d be strong evidence linking him to the mining of coins before Bitcoin’s public availability. Unfortunately the screenshots themselves weren’t contemporary – the metadata shows them being created in 2020. This wouldn’t fundamentally be a problem (it’s entirely reasonable to create new screenshots of old material), as long as it’s possible to establish that the material shown in the screenshots was created at that point. Sadly, well.

One part of the disclosed information was an email that contained a zip file that contained a raw database in the format used by MYOB. Importing that into the tool allowed an audit record to be extracted – this record showed that the relevant entries had been added to the database in 2020, shortly before the screenshots were created. This was, obviously, not strong evidence that Craig had held Bitcoin in 2009. This evidence was reported, and was responded to with a couple of additional databases that had an audit trail that was consistent with the dates in the records in question. Well, partially. The audit record included session data, showing an administrator logging into the data base in 2011 and then, uh, logging out in 2023, which is rather more consistent with someone changing their system clock to 2011 to create an entry, and switching it back to present day before logging out. In addition, the audit log included fields that didn’t exist in versions of the product released before 2016, strongly suggesting that the entries dated 2009-2011 were created in software released after 2016. And even worse, the order of insertions into the database didn’t line up with calendar time – an entry dated before another entry may appear in the database afterwards, indicating that it was created later. But even more obvious? The database schema used for these old entries corresponded to a version of the software released in 2023.

This is all consistent with the idea that these records were created after the fact and backdated to 2009-2011, and that after this evidence was made available further evidence was created and backdated to obfuscate that. In an unusual turn of events, during the trial Craig Wright introduced further evidence in the form of a chain of emails to his former lawyers that indicated he had provided them with login details to his MYOB instance in 2019 – before the metadata associated with the screenshots. The implication isn’t entirely clear, but it suggests that either they had an opportunity to examine this data before the metadata suggests it was created, or that they faked the data? So, well, the obvious thing happened, and his former lawyers were asked whether they received these emails. The chain consisted of three emails, two of which they confirmed they’d received. And they received a third email in the chain, but it was different to the one entered in evidence. And, uh, weirdly, they’d received a copy of the email that was submitted – but they’d received it a few days earlier. In 2024.

And again, the forensic evidence is helpful here! It turns out that the email client used associates a timestamp with any attachments, which in this case included an image in the email footer – and the mysterious time travelling email had a timestamp in 2024, not 2019. This was created by the client, so was consistent with the email having been sent in 2024, not being sent in 2019 and somehow getting stuck somewhere before delivery. The date header indicates 2019, as do encoded timestamps in the MIME headers – consistent with the mail being sent by a computer with the clock set to 2019.

But there’s a very weird difference between the copy of the email that was submitted in evidence and the copy that was located afterwards! The first included a header inserted by gmail that included a 2019 timestamp, while the latter had a 2024 timestamp. Is there a way to determine which of these could be the truth? It turns out there is! The format of that header changed in 2022, and the version in the email is the new version. The version with the 2019 timestamp is anachronistic – the format simply doesn’t match the header that gmail would have introduced in 2019, suggesting that an email sent in 2022 or later was modified to include a timestamp of 2019.

This is by no means the only indication that Craig Wright’s evidence may be misleading (there’s the whole argument that the Bitcoin white paper was written in LaTeX when general consensus is that it’s written in OpenOffice, given that’s what the metadata claims), but it’s a lovely example of a more general issue.

Our technology chains are complicated. So many moving parts end up influencing the content of the data we generate, and those parts develop over time. It’s fantastically difficult to generate an artifact now that precisely corresponds to how it would look in the past, even if we go to the effort of installing an old OS on an old PC and setting the clock appropriately (are you sure you’re going to be able to mimic an entirely period appropriate patch level?). Even the version of the font you use in a document may indicate it’s anachronistic. I’m pretty good at computers and I no longer have any belief I could fake an old document.

(References: this Dropbox, under “Expert reports”, “Patrick Madden”. Initial MYOB data is in “Appendix PM7”, further analysis is in “Appendix PM42”, email analysis is “Sixth Expert Report of Mr Patrick Madden”)

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Debugging an odd inability to stream video

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/69343.html

We have a cabin out in the forest, and when I say “out in the forest” I mean “in a national forest subject to regulation by the US Forest Service” which means there’s an extremely thick book describing the things we’re allowed to do and (somewhat longer) not allowed to do. It’s also down in the bottom of a valley surrounded by tall trees (the whole “forest” bit). There used to be AT&T copper but all that infrastructure burned down in a big fire back in 2021 and AT&T no longer supply new copper links, and Starlink isn’t viable because of the whole “bottom of a valley surrounded by tall trees” thing along with regulations that prohibit us from putting up a big pole with a dish on top. Thankfully there’s LTE towers nearby, so I’m simply using cellular data. Unfortunately my provider rate limits connections to video streaming services in order to push them down to roughly SD resolution. The easy workaround is just to VPN back to somewhere else, which in my case is just a Wireguard link back to San Francisco.

This worked perfectly for most things, but some streaming services simply wouldn’t work at all. Attempting to load the video would just spin forever. Running tcpdump at the local end of the VPN endpoint showed a connection being established, some packets being exchanged, and then… nothing. The remote service appeared to just stop sending packets. Tcpdumping the remote end of the VPN showed the same thing. It wasn’t until I looked at the traffic on the VPN endpoint’s external interface that things began to become clear.

This probably needs some background. Most network infrastructure has a maximum allowable packet size, which is referred to as the Maximum Transmission Unit or MTU. For ethernet this defaults to 1500 bytes, and these days most links are able to handle packets of at least this size, so it’s pretty typical to just assume that you’ll be able to send a 1500 byte packet. But what’s important to remember is that that doesn’t mean you have 1500 bytes of packet payload – that 1500 bytes includes whatever protocol level headers are on there. For TCP/IP you’re typically looking at spending around 40 bytes on the headers, leaving somewhere around 1460 bytes of usable payload. And if you’re using a VPN, things get annoying. In this case the original packet becomes the payload of a new packet, which means it needs another set of TCP (or UDP) and IP headers, and probably also some VPN header. This still all needs to fit inside the MTU of the link the VPN packet is being sent over, so if the MTU of that is 1500, the effective MTU of the VPN interface has to be lower. For Wireguard, this works out to an effective MTU of 1420 bytes. That means simply sending a 1500 byte packet over a Wireguard (or any other VPN) link won’t work – adding the additional headers gives you a total packet size of over 1500 bytes, and that won’t fit into the underlying link’s MTU of 1500.

And yet, things work. But how? Faced with a packet that’s too big to fit into a link, there are two choices – break the packet up into multiple smaller packets (“fragmentation”) or tell whoever’s sending the packet to send smaller packets. Fragmentation seems like the obvious answer, so I’d encourage you to read Valerie Aurora’s article on how fragmentation is more complicated than you think. tl;dr – if you can avoid fragmentation then you’re going to have a better life. You can explicitly indicate that you don’t want your packets to be fragmented by setting the Don’t Fragment bit in your IP header, and then when your packet hits a link where your packet exceeds the link MTU it’ll send back a packet telling the remote that it’s too big, what the actual MTU is, and the remote will resend a smaller packet. This avoids all the hassle of handling fragments in exchange for the cost of a retransmit the first time the MTU is exceeded. It also typically works these days, which wasn’t always the case – people had a nasty habit of dropping the ICMP packets telling the remote that the packet was too big, which broke everything.

What I saw when I tcpdumped on the remote VPN endpoint’s external interface was that the connection was getting established, and then a 1500 byte packet would arrive (this is kind of the behaviour you’d expect for video – the connection handshaking involves a bunch of relatively small packets, and then once you start sending the video stream itself you start sending packets that are as large as possible in order to minimise overhead). This 1500 byte packet wouldn’t fit down the Wireguard link, so the endpoint sent back an ICMP packet to the remote telling it to send smaller packets. The remote should then have sent a new, smaller packet – instead, about a second after sending the first 1500 byte packet, it sent that same 1500 byte packet. This is consistent with it ignoring the ICMP notification and just behaving as if the packet had been dropped.

All the services that were failing were failing in identical ways, and all were using Fastly as their CDN. I complained about this on social media and then somehow ended up in contact with the engineering team responsible for this sort of thing – I sent them a packet dump of the failure, they were able to reproduce it, and it got fixed. Hurray!

(Between me identifying the problem and it getting fixed I was able to work around it. The TCP header includes a Maximum Segment Size (MSS) field, which indicates the maximum size of the payload for this connection. iptables allows you to rewrite this, so on the VPN endpoint I simply rewrote the MSS to be small enough that the packets would fit inside the Wireguard MTU. This isn’t a complete fix since it’s done at the TCP level rather than the IP level – so any large UDP packets would still end up breaking)

I’ve no idea what the underlying issue was, and at the client end the failure was entirely opaque: the remote simply stopped sending me packets. The only reason I was able to debug this at all was because I controlled the other end of the VPN as well, and even then I wouldn’t have been able to do anything about it other than being in the fortuitous situation of someone able to do something about it seeing my post. How many people go through their lives dealing with things just being broken and having no idea why, and how do we fix that?

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Dealing with weird ELF libraries

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/69070.html

Libraries are collections of code that are intended to be usable by multiple consumers (if you’re interested in the etymology, watch this video). In the old days we had what we now refer to as “static” libraries, collections of code that existed on disk but which would be copied into newly compiled binaries. We’ve moved beyond that, thankfully, and now make use of what we call “dynamic” or “shared” libraries – instead of the code being copied into the binary, a reference to the library function is incorporated, and at runtime the code is mapped from the on-disk copy of the shared object[1]. This allows libraries to be upgraded without needing to modify the binaries using them, and if multiple applications are using the same library at once it only requires that one copy of the code be kept in RAM.

But for this to work, two things are necessary: when we build a binary, there has to be a way to reference the relevant library functions in the binary; and when we run a binary, the library code needs to be mapped into the process.

(I’m going to somewhat simplify the explanations from here on – things like symbol versioning make this a bit more complicated but aren’t strictly relevant to what I was working on here)

For the first of these, the goal is to replace a call to a function (eg, printf()) with a reference to the actual implementation. This is the job of the linker rather than the compiler (eg, if you use the -c argument to tell gcc to simply compile to an object rather than linking an executable, it’s not going to care about whether or not every function called in your code actually exists or not – that’ll be figured out when you link all the objects together), and the linker needs to know which symbols (which aren’t just functions – libraries can export variables or structures and so on) are available in which libraries. You give the linker a list of libraries, it extracts the symbols available, and resolves the references in your code with references to the library.

But how is that information extracted? Each ELF object has a fixed-size header that contains references to various things, including a reference to a list of “section headers”. Each section has a name and a type, but the ones we’re interested in are .dynstr and .dynsym. .dynstr contains a list of strings, representing the name of each exported symbol. .dynsym is where things get more interesting – it’s a list of structs that contain information about each symbol. This includes a bunch of fairly complicated stuff that you need to care about if you’re actually writing a linker, but the relevant entries for this discussion are an index into .dynstr (which means the .dynsym entry isn’t sufficient to know the name of a symbol, you need to extract that from .dynstr), along with the location of that symbol within the library. The linker can parse this information and obtain a list of symbol names and addresses, and can now replace the call to printf() with a reference to libc instead.

(Note that it’s not possible to simply encode this as “Call this address in this library” – if the library is rebuilt or is a different version, the function could move to a different location)

Experimentally, .dynstr and .dynsym appear to be sufficient for linking a dynamic library at build time – there are other sections related to dynamic linking, but you can link against a library that’s missing them. Runtime is where things get more complicated.

When you run a binary that makes use of dynamic libraries, the code from those libraries needs to be mapped into the resulting process. This is the job of the runtime dynamic linker, or RTLD[2]. The RTLD needs to open every library the process requires, map the relevant code into the process’s address space, and then rewrite the references in the binary into calls to the library code. This requires more information than is present in .dynstr and .dynsym – at the very least, it needs to know the list of required libraries.

There’s a separate section called .dynamic that contains another list of structures, and it’s the data here that’s used for this purpose. For example, .dynamic contains a bunch of entries of type DT_NEEDED – this is the list of libraries that an executable requires. There’s also a bunch of other stuff that’s required to actually make all of this work, but the only thing I’m going to touch on is DT_HASH. Doing all this re-linking at runtime involves resolving the locations of a large number of symbols, and if the only way you can do that is by reading a list from .dynsym and then looking up every name in .dynstr that’s going to take some time. The DT_HASH entry points to a hash table – the RTLD hashes the symbol name it’s trying to resolve, looks it up in that hash table, and gets the symbol entry directly (it still needs to resolve that against .dynstr to make sure it hasn’t hit a hash collision – if it has it needs to look up the next hash entry, but this is still generally faster than walking the entire .dynsym list to find the relevant symbol). There’s also DT_GNU_HASH which fulfills the same purpose as DT_HASH but uses a more complicated algorithm that preforms even better. .dynamic also contains entries pointing at .dynstr and .dynsym, which seems redundant but will become relevant shortly.

So, .dynsym and .dynstr are required at build time, and bother are required along with .dynamic at runtime. This seems simple enough, but obviously there’s a twist and I’m sorry it’s taken so long to get to this point.

I bought a Synology NAS for home backup purposes (my previous solution was a single external USB drive plugged into a small server, which had uncomfortable single point of failure properties). Obviously I decided to poke around at it, and I found something odd – all the libraries Synology ships were entirely lacking any ELF section headers. This meant no .dynstr, .dynsym or .dynamic sections, so how was any of this working? nm asserted that the libraries exported no symbols, and readelf agreed. If I wrote a small app that called a function in one of the libraries and built it, gcc complained that the function was undefined. But executables on the device were clearly resolving the symbols at runtime, and if I loaded them into ghidra the exported functions were visible. If I dlopen()ed them, dlsym() couldn’t resolve the symbols – but if I hardcoded the offset into my code, I could call them directly.

Things finally made sense when I discovered that if I passed the --use-dynamic argument to readelf, I did get a list of exported symbols. It turns out that ELF is weirder than I realised. As well as the aforementioned section headers, ELF objects also include a set of program headers. One of the program header types is PT_DYNAMIC. This typically points to the same data that’s present in the .dynamic section. Remember when I mentioned that .dynamic contained references to .dynsym and .dynstr? This means that simply pointing at .dynamic is sufficient, there’s no need to have separate entries for them.

The same information can be reached from two different locations. The information in the section headers is used at build time, and the information in the program headers at run time[3]. I do not have an explanation for this. But if the information is present in two places, it seems obvious that it should be able to reconstruct the missing section headers in my weird libraries? So that’s what this does. It extracts information from the DYNAMIC entry in the program headers and creates equivalent section headers.

There’s one thing that makes this more difficult than it might seem. The section header for .dynsym has to contain the number of symbols present in the section. And that information doesn’t directly exist in DYNAMIC – to figure out how many symbols exist, you’re expected to walk the hash tables and keep track of the largest number you’ve seen. Since every symbol has to be referenced in the hash table, once you’ve hit every entry the largest number is the number of exported symbols. This seemed annoying to implement, so instead I cheated, added code to simply pass in the number of symbols on the command line, and then just parsed the output of readelf against the original binaries to extract that information and pass it to my tool.

Somehow, this worked. I now have a bunch of library files that I can link into my own binaries to make it easier to figure out how various things on the Synology work. Now, could someone explain (a) why this information is present in two locations, and (b) why the build-time linker and run-time linker disagree on the canonical source of truth?

[1] “Shared object” is the source of the .so filename extension used in various Unix-style operating systems
[2] You’ll note that “RTLD” is not an acryonym for “runtime dynamic linker”, because reasons
[3] For environments using the GNU RTLD, at least – I have no idea whether this is the case in all ELF environments

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Making SSH host certificates more usable

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/68721.html

Earlier this year, after Github accidentally committed their private RSA SSH host key to a public repository, I wrote about how better support for SSH host certificates would allow this sort of situation to be handled in a user-transparent way without any negative impact on security. I was hoping that someone would read this and be inspired to fix the problem but sadly that didn’t happen so I’ve actually written some code myself.

The core part of this is straightforward – if a server presents you with a certificate associated with a host key, then make the trust in that host be whoever signed the certificate rather than just trusting the host key. This means that if someone needs to replace the host key for any reason (such as, for example, them having published the private half), you can replace the host key with a new key and a new certificate, and as long as the new certificate is signed by the same key that the previous certificate was, you’ll trust the new key and key rotation can be carried out without any user errors. Hurrah!

So obviously I wrote that bit and then thought about the failure modes and it turns out there’s an obvious one – if an attacker obtained both the private key and the certificate, what stops them from continuing to use it? The certificate isn’t a secret, so we basically have to assume that anyone who possesses the private key has access to it. We may have silently transitioned to a new host key on the legitimate servers, but a hostile actor able to MITM a user can keep on presenting the old key and the old certificate until it expires.

There’s two ways to deal with this – either have short-lived certificates (ie, issue a new certificate every 24 hours or so even if you haven’t changed the key, and specify that the certificate is invalid after those 24 hours), or have a mechanism to revoke the certificates. The former is viable if you have a very well-engineered certificate issuing operation, but still leaves a window for an attacker to make use of the certificate before it expires. The latter is something SSH has support for, but the spec doesn’t define any mechanism for distributing revocation data.

So, I’ve implemented a new SSH protocol extension that allows a host to send a key revocation list to a client. The idea is that the client authenticates to the server, receives a key revocation list, and will no longer trust any certificates that are contained within that list. This seems simple enough, but a naive implementation opens the client to various DoS attacks. For instance, if you simply revoke any key contained within the received KRL, a hostile server could revoke any certificates that were otherwise trusted by the client. The easy way around this is for the client to ensure that any revoked keys are associated with the same CA that signed the host certificate – that way a compromised host can only revoke certificates associated with that CA, and can’t interfere with anyone else.

Unfortunately that still means that a single compromised host can still trigger revocation of certificates inside that trust domain (ie, a compromised host a.test.com could push a KRL that invalidated the certificate for b.test.com), because there’s no way in the KRL format to indicate that a given revocation is associated with a specific hostname. This means we need a mechanism to verify that the KRL update is legitimate, and the easiest way to handle that is to sign it. The KRL format specifies an in-band signature but this was deprecated earlier this year – instead KRLs are supposed to be signed with the sshsig format. But we control both the server and the client, which means it’s easy enough to send a detached signature as part of the extension data.

Putting this all together: you ssh to a server you’ve never contacted before, and it presents you with a host certificate. Instead of the host key being added to known_hosts, the CA key associated with the certificate is added. From now on, if you ssh to that host and it presents a certificate signed by that CA, it’ll be trusted. Optionally, the host can also send you a KRL and a signature. If the signature is generated by the CA key that you already trust, any certificates in that KRL associated with that CA key will be incorporated into local storage. The expected flow if a key is compromised is that the owner of the host generates a new keypair, obtains a new certificate for the new key, and adds the old certificate to a KRL that is signed with the CA key. The next time the user connects to that host, they receive the new key and new certificate, trust it because it’s signed by the same CA key, and also receive a KRL signed with the same CA that revokes trust in the old certificate.

Obviously this breaks down if a user is MITMed with a compromised key and certificate immediately after the host is compromised – they’ll see a legitimate certificate and won’t receive any revocation list, so will trust the host. But this is the same failure mode that would occur in the absence of keys, where the attacker simply presents the compromised key to the client before trust in the new key has been created. This seems no worse than the status quo, but means that most users will seamlessly transition to a new key and revoke trust in the old key with no effort on their part.

The work in progress tree for this is here – at the point of writing I’ve merely implemented this and made sure it builds, not verified that it actually works or anything. Cleanup should happen over the next few days, and I’ll propose this to upstream if it doesn’t look like there’s any showstopper design issues.

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Why does Gnome fingerprint unlock not unlock the keyring?

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/68537.html

There’s a decent number of laptops with fingerprint readers that are supported by Linux, and Gnome has some nice integration to make use of that for authentication purposes. But if you log in with a fingerprint, the moment you start any app that wants to access stored passwords you’ll get a prompt asking you to type in your password, which feels like it somewhat defeats the point. Mac users don’t have this problem – authenticate with TouchID and all your passwords are available after login. Why the difference?

Fingerprint detection can be done in two primary ways. The first is that a fingerprint reader is effectively just a scanner – it passes a graphical representation of the fingerprint back to the OS and the OS decides whether or not it matches an enrolled finger. The second is for the fingerprint reader to make that determination itself, either storing a set of trusted fingerprints in its own storage or supporting being passed a set of encrypted images to compare against. Fprint supports both of these, but note that in both cases all that we get at the end of the day is a statement of “The fingerprint matched” or “The fingerprint didn’t match” – we can’t associate anything else with that.

Apple’s solution involves wiring the fingerprint reader to a secure enclave, an independently running security chip that can store encrypted secrets or keys and only release them under pre-defined circumstances. Rather than the fingerprint reader providing information directly to the OS, it provides it to the secure enclave. If the fingerprint matches, the secure enclave can then provide some otherwise secret material to the OS. Critically, if the fingerprint doesn’t match, the enclave will never release this material.

And that’s the difference. When you perform TouchID authentication, the secure enclave can decide to release a secret that can be used to decrypt your keyring. We can’t easily do this under Linux because we don’t have an interface to store those secrets. The secret material can’t just be stored on disk – that would allow anyone who had access to the disk to use that material to decrypt the keyring and get access to the passwords, defeating the object. We can’t use the TPM because there’s no secure communications channel between the fingerprint reader and the TPM, so we can’t configure the TPM to release secrets only if an associated fingerprint is provided.

So the simple answer is that fingerprint unlock doesn’t unlock the keyring because there’s currently no secure way to do that. It’s not intransigence on the part of the developers or a conspiracy to make life more annoying. It’d be great to fix it, but I don’t see an easy way to do so at the moment.

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Why ACPI?

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/68350.html

“Why does ACPI exist” – – the greatest thread in the history of forums, locked by a moderator after 12,239 pages of heated debate, wait no let me start again.

Why does ACPI exist? In the beforetimes power management on x86 was done by jumping to an opaque BIOS entry point and hoping it would do the right thing. It frequently didn’t. We called this Advanced Power Management (Advanced because before this power management involved custom drivers for every machine and everyone agreed that this was a bad idea), and it involved the firmware having to save and restore the state of every piece of hardware in the system. This meant that assumptions about hardware configuration were baked into the firmware – failed to program your graphics card exactly the way the BIOS expected? Hurrah! It’s only saved and restored a subset of the state that you configured and now potential data corruption for you. The developers of ACPI made the reasonable decision that, well, maybe since the OS was the one setting state in the first place, the OS should restore it.

So far so good. But some state is fundamentally device specific, at a level that the OS generally ignores. How should this state be managed? One way to do that would be to have the OS know about the device specific details. Unfortunately that means you can’t ship the computer without having OS support for it, which means having OS support for every device (exactly what we’d got away from with APM). This, uh, was not an option the PC industry seriously considered. The alternative is that you ship something that abstracts the details of the specific hardware and makes that abstraction available to the OS. This is what ACPI does, and it’s also what things like Device Tree do. Both provide static information about how the platform is configured, which can then be consumed by the OS and avoid needing device-specific drivers or configuration to be built-in.

The main distinction between Device Tree and ACPI is that Device Tree is purely a description of the hardware that exists, and so still requires the OS to know what’s possible – if you add a new type of power controller, for instance, you need to add a driver for that to the OS before you can express that via Device Tree. ACPI decided to include an interpreted language to allow vendors to expose functionality to the OS without the OS needing to know about the underlying hardware. So, for instance, ACPI allows you to associate a device with a function to power down that device. That function may, when executed, trigger a bunch of register accesses to a piece of hardware otherwise not exposed to the OS, and that hardware may then cut the power rail to the device to power it down entirely. And that can be done without the OS having to know anything about the control hardware.

How is this better than just calling into the firmware to do it? Because the fact that ACPI declares that it’s going to access these registers means the OS can figure out that it shouldn’t, because it might otherwise collide with what the firmware is doing. With APM we had no visibility into that – if the OS tried to touch the hardware at the same time APM did, boom, almost impossible to debug failures (This is why various hardware monitoring drivers refuse to load by default on Linux – the firmware declares that it’s going to touch those registers itself, so Linux decides not to in order to avoid race conditions and potential hardware damage. In many cases the firmware offers a collaborative interface to obtain the same data, and a driver can be written to get that. this bug comment discusses this for a specific board)

Unfortunately ACPI doesn’t entirely remove opaque firmware from the equation – ACPI methods can still trigger System Management Mode, which is basically a fancy way to say “Your computer stops running your OS, does something else for a while, and you have no idea what”. This has all the same issues that APM did, in that if the hardware isn’t in exactly the state the firmware expects, bad things can happen. While historically there were a bunch of ACPI-related issues because the spec didn’t define every single possible scenario and also there was no conformance suite (eg, should the interpreter be multi-threaded? Not defined by spec, but influences whether a specific implementation will work or not!), these days overall compatibility is pretty solid and the vast majority of systems work just fine – but we do still have some issues that are largely associated with System Management Mode.

One example is a recent Lenovo one, where the firmware appears to try to poke the NVME drive on resume. There’s some indication that this is intended to deal with transparently unlocking self-encrypting drives on resume, but it seems to do so without taking IOMMU configuration into account and so things explode. It’s kind of understandable why a vendor would implement something like this, but it’s also kind of understandable that doing so without OS cooperation may end badly.

This isn’t something that ACPI enabled – in the absence of ACPI firmware vendors would just be doing this unilaterally with even less OS involvement and we’d probably have even more of these issues. Ideally we’d “simply” have hardware that didn’t support transitioning back to opaque code, but we don’t (ARM has basically the same issue with TrustZone). In the absence of the ideal world, by and large ACPI has been a net improvement in Linux compatibility on x86 systems. It certainly didn’t remove the “Everything is Windows” mentality that many vendors have, but it meant we largely only needed to ensure that Linux behaved the same way as Windows in a finite number of ways (ie, the behaviour of the ACPI interpreter) rather than in every single hardware driver, and so the chances that a new machine will work out of the box are much greater than they were in the pre-ACPI period.

There’s an alternative universe where we decided to teach the kernel about every piece of hardware it should run on. Fortunately (or, well, unfortunately) we’ve seen that in the ARM world. Most device-specific simply never reaches mainline, and most users are stuck running ancient kernels as a result. Imagine every x86 device vendor shipping their own kernel optimised for their hardware, and now imagine how well that works out given the quality of their firmware. Does that really seem better to you?

It’s understandable why ACPI has a poor reputation. But it’s also hard to figure out what would work better in the real world. We could have built something similar on top of Open Firmware instead but the distinction wouldn’t be terribly meaningful – we’d just have Forth instead of the ACPI bytecode language. Longing for a non-ACPI world without presenting something that’s better and actually stands a reasonable chance of adoption doesn’t make the world a better place.

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Defending abuse does not defend free software

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/68004.html

The Free Software Foundation Europe and the Software Freedom Conservancy recently released a statement that they would no longer work with Eben Moglen, chairman of the Software Freedom Law Center. Eben was the general counsel for the Free Software Foundation for over 20 years, and was centrally involved in the development of version 3 of the GNU General Public License. He’s devoted a great deal of his life to furthering free software.

But, as described in the joint statement, he’s also acted abusively towards other members of the free software community. He’s acted poorly towards his own staff. In a professional context, he’s used graphically violent rhetoric to describe people he dislikes. He’s screamed abuse at people attempting to do their job.

And, sadly, none of this comes as a surprise to me. As I wrote in 2017, after it became clear that Eben’s opinions diverged sufficiently from the FSF’s that he could no longer act as general counsel, he responded by threatening an FSF board member at an FSF-run event (various members of the board were willing to tolerate this, which is what led to me quitting the board). There’s over a decade’s evidence of Eben engaging in abusive behaviour towards members of the free software community, be they staff, colleagues, or just volunteers trying to make the world a better place.

When we build communities that tolerate abuse, we exclude anyone unwilling to tolerate being abused[1]. Nobody in the free software community should be expected to deal with being screamed at or threatened. Nobody should be afraid that they’re about to have their sexuality outed by a former boss.

But of course there are some that will defend Eben based on his past contributions. There were people who were willing to defend Hans Reiser on that basis. We need to be clear that what these people are defending is not free software – it’s the right for abusers to abuse. And in the long term, that’s bad for free software.

[1] “Why don’t people just get better at tolerating abuse?” is a terrible response to this. Why don’t abusers stop abusing? There’s fewer of them, and it should be easier.

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Reconstructing an invalid TPM event log

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/67602.html

TPMs contain a set of registers (“Platform Configuration Registers”, or PCRs) that are used to track what a system boots. Each time a new event is measured, a cryptographic hash representing that event is passed to the TPM. The TPM appends that hash to the existing value in the PCR, hashes that, and stores the final result in the PCR. This means that while the PCR’s value depends on the precise sequence and value of the hashes presented to it, the PCR value alone doesn’t tell you what those individual events were. Different PCRs are used to store different event types, but there are still more events than there are PCRs so we can’t avoid this problem by simply storing each event separately.

This is solved using the event log. The event log is simply a record of each event, stored in RAM. The algorithm the TPM uses to calculate the PCR values is known, so we can reproduce that by simply taking the events from the event log and replaying the series of events that were passed to the TPM. If the final calculated value is the same as the value in the PCR, we know that the event log is accurate, which means we now know the value of each individual event and can make an appropriate judgement regarding its security.

If any value in the event log is invalid, we’ll calculate a different PCR value and it won’t match. This isn’t terribly helpful – we know that at least one entry in the event log doesn’t match what was passed to the TPM, but we don’t know which entry. That means we can’t trust any of the events associated with that PCR. If you’re trying to make a security determination based on this, that’s going to be a problem.

PCR 7 is used to track information about the secure boot policy on the system. It contains measurements of whether or not secure boot is enabled, and which keys are trusted and untrusted on the system in question. This is extremely helpful if you want to verify that a system booted with secure boot enabled before allowing it to do something security or safety critical. Unfortunately, if the device gives you an event log that doesn’t replay correctly for PCR 7, you now have no idea what the security state of the system is.

We ran into that this week. Examination of the event log revealed an additional event other than the expected ones – a measurement accompanied by the string “Boot Guard Measured S-CRTM”. Boot Guard is an Intel feature where the CPU verifies the firmware is signed with a trusted key before executing it, and measures information about the firmware in the process. Previously I’d only encountered this as a measurement into PCR 0, which is the PCR used to track information about the firmware itself. But it turns out that at least some versions of Boot Guard also measure information about the Boot Guard policy into PCR 7. The argument for this is that this is effectively part of the secure boot policy – having a measurement of the Boot Guard state tells you whether Boot Guard was enabled, which tells you whether or not the CPU verified a signature on your firmware before running it (as I wrote before, I think Boot Guard has user-hostile default behaviour, and that enforcing this on consumer devices is a bad idea).

But there’s a problem here. The event log is created by the firmware, and the Boot Guard measurements occur before the firmware is executed. So how do we get a log that represents them? That one’s fairly simple – the firmware simply re-calculates the same measurements that Boot Guard did and creates a log entry after the fact[1]. All good.

Except. What if the firmware screws up the calculation and comes up with a different answer? The entry in the event log will now not match what was sent to the TPM, and replaying will fail. And without knowing what the actual value should be, there’s no way to fix this, which means there’s no way to verify the contents of PCR 7 and determine whether or not secure boot was enabled.

But there’s still a fundamental source of truth – the measurement that was sent to the TPM in the first place. Inspired by Henri Nurmi’s work on sniffing Bitlocker encryption keys, I asked a coworker if we could sniff the TPM traffic during boot. The TPM on the board in question uses SPI, a simple bus that can have multiple devices connected to it. In this case the system flash and the TPM are on the same SPI bus, which made things easier. The board had a flash header for external reprogramming of the firmware in the event of failure, and all SPI traffic was visible through that header. Attaching a logic analyser to this header made it simple to generate a record of that. The only problem was that the chip select line on the header was attached to the firmware flash chip, not the TPM. This was worked around by simply telling the analysis software that it should invert the sense of the chip select line, ignoring all traffic that was bound for the flash and paying attention to all other traffic. This worked in this case since the only other device on the bus was the TPM, but would cause problems in the event of multiple devices on the bus all communicating.

With the aid of this analyser plugin, I was able to dump all the TPM traffic and could then search for writes that included the “0182” sequence that corresponds to the command code for a measurement event. This gave me a couple of accesses to the locality 3 registers, which was a strong indication that they were coming from the CPU rather than from the firmware. One was for PCR 0, and one was for PCR 7. This corresponded to the two Boot Guard events that we expected from the event log. The hash in the PCR 0 measurement was the same as the hash in the event log, but the hash in the PCR 7 measurement differed from the hash in the event log. Replacing the event log value with the value actually sent to the TPM resulted in the event log now replaying correctly, supporting the hypothesis that the firmware was failing to correctly reconstruct the event.

What now? The simple thing to do is for us to simply hard code this fixup, but longer term we’d like to figure out how to reconstruct the event so we can calculate the expected value ourselves. Unfortunately there doesn’t seem to be any public documentation on this. Sigh.

[1] What stops firmware on a system with no Boot Guard faking those measurements? TPMs have a concept of “localities”, effectively different privilege levels. When Boot Guard performs its initial measurement into PCR 0, it does so at locality 3, a locality that’s only available to the CPU. This causes PCR 0 to be initialised to a different initial value, affecting the final PCR value. The firmware can’t access locality 3, so can’t perform an equivalent measurement, so can’t fake the value.

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Unix sockets, Cygwin, SSH agents, and sadness

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/67402.html

Work involves supporting Windows (there’s a lot of specialised hardware design software that’s only supported under Windows, so this isn’t really avoidable), but also involves git, so I’ve been working on extending our support for hardware-backed SSH certificates to Windows and trying to glue that into git. In theory this doesn’t sound like a hard problem, but in practice oh good heavens.

Git for Windows is built on top of msys2, which in turn is built on top of Cygwin. This is an astonishing artifact that allows you to build roughly unmodified POSIXish code on top of Windows, despite the terrible impedance mismatches inherent in this. One is that until 2017, Windows had no native support for Unix sockets. That’s kind of a big deal for compatibility purposes, so Cygwin worked around it. It’s, uh, kind of awful. If you’re not a Cygwin/msys app but you want to implement a socket they can communicate with, you need to implement this undocumented protocol yourself. This isn’t impossible, but ugh.

But going to all this trouble helps you avoid another problem! The Microsoft version of OpenSSH ships an SSH agent that doesn’t use Unix sockets, but uses a named pipe instead. So if you want to communicate between Cygwinish OpenSSH (as is shipped with git for Windows) and the SSH agent shipped with Windows, you need something that bridges between those. The state of the art seems to be to use npiperelay with socat, but if you’re already writing something that implements the Cygwin socket protocol you can just use npipe to talk to the shipped ssh-agent and then export your own socket interface.

And, amazingly, this all works? I’ve managed to hack together an SSH agent (using Go’s SSH agent implementation) that can satisfy hardware backed queries itself, but forward things on to the Windows agent for compatibility with other tooling. Now I just need to figure out how to plumb it through to WSL. Sigh.

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Updating Fedora the unsupported way

Post Syndicated from Matthew Garrett original https://mjg59.dreamwidth.org/67126.html

I dug out a computer running Fedora 28, which was released 2018-04-01 – over 5 years ago. Backing up the data and re-installing seemed tedious, but the current version of Fedora is 38, and while Fedora supports updates from N to N+2 that was still going to be 5 separate upgrades. That seemed tedious, so I figured I’d just try to do an update from 28 directly to 38. This is, obviously, extremely unsupported, but what could possibly go wrong?

Running sudo dnf system-upgrade download --releasever=38 didn’t successfully resolve dependencies, but sudo dnf system-upgrade download --releasever=38 --allowerasing passed and dnf started downloading 6GB of packages. And then promptly failed, since I didn’t have any of the relevant signing keys. So I downloaded the fedora-gpg-keys package from F38 by hand and tried to install it, and got a signature hdr data: BAD, no. of bytes(88084) out of range error. It turns out that rpm doesn’t handle cases where the signature header is larger than a few K, and RPMs from modern versions of Fedora. The obvious fix would be to install a newer version of rpm, but that wouldn’t be easy without upgrading the rest of the system as well – or, alternatively, downloading a bunch of build depends and building it. Given that I’m already doing all of this in the worst way possible, let’s do something different.

The relevant code in the hdrblobRead function of rpm’s lib/header.c is:

int32_t il_max = HEADER_TAGS_MAX;
int32_t dl_max = HEADER_DATA_MAX;

if (regionTag == RPMTAG_HEADERSIGNATURES) {
il_max = 32;
dl_max = 8192;
}

which indicates that if the header in question is RPMTAG_HEADERSIGNATURES, it sets more restrictive limits on the size (no, I don’t know why). So I installed rpm-libs-debuginfo, ran gdb against librpm.so.8, loaded the symbol file, and then did disassemble hdrblobRead. The relevant chunk ends up being:

0x000000000001bc81 <+81>: cmp $0x3e,%ebx
0x000000000001bc84 <+84>: mov $0xfffffff,%ecx
0x000000000001bc89 <+89>: mov $0x2000,%eax
0x000000000001bc8e <+94>: mov %r12,%rdi
0x000000000001bc91 <+97>: cmovne %ecx,%eax

which is basically “If ebx is not 0x3e, set eax to 0xffffffff – otherwise, set it to 0x2000”. RPMTAG_HEADERSIGNATURES is 62, which is 0x3e, so I just opened librpm.so.8 in hexedit, went to byte 0x1bc81, and replaced 0x3e with 0xfe (an arbitrary invalid value). This has the effect of skipping the if (regionTag == RPMTAG_HEADERSIGNATURES) code and so using the default limits even if the header section in question is the signatures. And with that one byte modification, rpm from F28 would suddenly install the fedora-gpg-keys package from F38. Success!

But short-lived. dnf now believed packages had valid signatures, but sadly there were still issues. A bunch of packages in F38 had files that conflicted with packages in F28. These were largely Python 3 packages that conflicted with Python 2 packages from F28 – jumping this many releases meant that a bunch of explicit replaces and the like no longer existed. The easiest way to solve this was simply to uninstall python 2 before upgrading, and avoiding the entire transition. Another issue was that some data files had moved from libxcrypt-common to libxcrypt, and removing libxcrypt-common would remove libxcrypt and a bunch of important things that depended on it (like, for instance, systemd). So I built a fake empty package that provided libxcrypt-common and removed the actual package. Surely everything would work now?

Ha no. The final obstacle was that several packages depended on rpmlib(CaretInVersions), and building another fake package that provided that didn’t work. I shouted into the void and Bill Nottingham answered – rpmlib dependencies are synthesised by rpm itself, indicating that it has the ability to handle extensions that specific packages are making use of. This made things harder, since the list is hard-coded in the binary. But since I’m already committing crimes against humanity with a hex editor, why not go further? Back to editing librpm.so.8 and finding the list of rpmlib() dependencies it provides. There were a bunch, but I couldn’t really extend the list. What I could do is overwrite existing entries. I tried this a few times but (unsurprisingly) broke other things since packages depended on the feature I’d overwritten. Finally, I rewrote rpmlib(ExplicitPackageProvide) to rpmlib(CaretInVersions) (adding an extra ‘\0’ at the end of it to deal with it being shorter than the original string) and apparently nothing I wanted to install depended on rpmlib(ExplicitPackageProvide) because dnf finished its transaction checks and prompted me to reboot to perform the update. So, I did.

And about an hour later, it rebooted and gave me a whole bunch of errors due to the fact that dbus never got started. A bit of digging revealed that I had no /etc/systemd/system/dbus.service, a symlink that was presumably introduced at some point between F28 and F38 but which didn’t get automatically added in my case because well who knows. That was literally the only thing I needed to fix up after the upgrade, and on the next reboot I was presented with a gdm prompt and had a fully functional F38 machine.

You should not do this. I should not do this. This was a terrible idea. Any situation where you’re binary patching your package manager to get it to let you do something is obviously a bad situation. And with hindsight performing 5 independent upgrades might have been faster. But that would have just involved me typing the same thing 5 times, while this way I learned something. And what I learned is “Terrible ideas sometimes work and so you should definitely act upon them rather than doing the sensible thing”, so like I said, you should not do this in case you learn the same lesson.

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Roots of Trust are difficult

Post Syndicated from original https://mjg59.dreamwidth.org/66907.html

The phrase “Root of Trust” turns up at various points in discussions about verified boot and measured boot, and to a first approximation nobody is able to give you a coherent explanation of what it means[1]. The Trusted Computing Group has a fairly wordy definition, but (a) it’s a lot of words and (b) I don’t like it, so instead I’m going to start by defining a root of trust as “A thing that has to be trustworthy for anything else on your computer to be trustworthy”.

(An aside: when I say “trustworthy”, it is very easy to interpret this in a cynical manner and assume that “trust” means “trusted by someone I do not necessarily trust to act in my best interest”. I want to be absolutely clear that when I say “trustworthy” I mean “trusted by the owner of the computer”, and that as far as I’m concerned selling devices that do not allow the owner to define what’s trusted is an extremely bad thing in the general case)

Let’s take an example. In verified boot, a cryptographic signature of a component is verified before it’s allowed to boot. A straightforward implementation of a verified boot implementation has the firmware verify the signature on the bootloader or kernel before executing it. In this scenario, the firmware is the root of trust – it’s the first thing that makes a determination about whether something should be allowed to run or not[2]. As long as the firmware behaves correctly, and as long as there aren’t any vulnerabilities in our boot chain, we know that we booted an OS that was signed with a key we trust.

But what guarantees that the firmware behaves correctly? What if someone replaces our firmware with firmware that trusts different keys, or hot-patches the OS as it’s booting it? We can’t just ask the firmware whether it’s trustworthy – trustworthy firmware will say yes, but the thing about malicious firmware is that it can just lie to us (either directly, or by modifying the OS components it boots to lie instead). This is probably not sufficiently trustworthy!

Ok, so let’s have the firmware be verified before it’s executed. On Intel this is “Boot Guard”, on AMD this is “Platform Secure Boot”, everywhere else it’s just “Secure Boot”. Code on the CPU (either in ROM or signed with a key controlled by the CPU vendor) verifies the firmware[3] before executing it. Now the CPU itself is the root of trust, and, well, that seems reasonable – we have to place trust in the CPU, otherwise we can’t actually do computing. We can now say with a reasonable degree of confidence (again, in the absence of vulnerabilities) that we booted an OS that we trusted. Hurrah!

Except. How do we know that the CPU actually did that verification? CPUs are generally manufactured without verification being enabled – different system vendors use different signing keys, so those keys can’t be installed in the CPU at CPU manufacture time, and vendors need to do code development without signing everything so you can’t require that keys be installed before a CPU will work. So, out of the box, a new CPU will boot anything without doing verification[4], and development units will frequently have no verification.

As a device owner, how do you tell whether or not your CPU has this verification enabled? Well, you could ask the CPU, but if you’re doing that on a device that booted a compromised OS then maybe it’s just hotpatching your OS so when you do that you just get RET_TRUST_ME_BRO even if the CPU is desperately waving its arms around trying to warn you it’s a trap. This is, unfortunately, a problem that’s basically impossible to solve using verified boot alone – if any component in the chain fails to enforce verification, the trust you’re placing in the chain is misplaced and you are going to have a bad day.

So how do we solve it? The answer is that we can’t simply ask the OS, we need a mechanism to query the root of trust itself. There’s a few ways to do that, but fundamentally they depend on the ability of the root of trust to provide proof of what happened. This requires that the root of trust be able to sign (or cause to be signed) an “attestation” of the system state, a cryptographically verifiable representation of the security-critical configuration and code. The most common form of this is called “measured boot” or “trusted boot”, and involves generating a “measurement” of each boot component or configuration (generally a cryptographic hash of it), and storing that measurement somewhere. The important thing is that it must not be possible for the running OS (or any pre-OS component) to arbitrarily modify these measurements, since otherwise a compromised environment could simply go back and rewrite history. One frequently used solution to this is to segregate the storage of the measurements (and the attestation of them) into a separate hardware component that can’t be directly manipulated by the OS, such as a Trusted Platform Module. Each part of the boot chain measures relevant security configuration and the next component before executing it and sends that measurement to the TPM, and later the TPM can provide a signed attestation of the measurements it was given. So, an SoC that implements verified boot should create a measurement telling us whether verification is enabled – and, critically, should also create a measurement if it isn’t. This is important because failing to measure the disabled state leaves us with the same problem as before; someone can replace the mutable firmware code with code that creates a fake measurement asserting that verified boot was enabled, and if we trust that we’re going to have a bad time.

(Of course, simply measuring the fact that verified boot was enabled isn’t enough – what if someone replaces the CPU with one that has verified boot enabled, but trusts keys under their control? We also need to measure the keys that were used in order to ensure that the device trusted only the keys we expected, otherwise again we’re going to have a bad time)

So, an effective root of trust needs to:

1) Create a measurement of its verified boot policy before running any mutable code
2) Include the trusted signing key in that measurement
3) Actually perform that verification before executing any mutable code

and from then on we’re in the hands of the verified code actually being trustworthy, and it’s probably written in C so that’s almost certainly false, but let’s not try to solve every problem today.

Does anything do this today? As far as I can tell, Intel’s Boot Guard implementation does. Based on publicly available documentation I can’t find any evidence that AMD’s Platform Secure Boot does (it does the verification, but it doesn’t measure the policy beforehand, so it seems spoofable), but I could be wrong there. I haven’t found any general purpose non-x86 parts that do, but this is in the realm of things that SoC vendors seem to believe is some sort of value-add that can only be documented under NDAs, so please do prove me wrong. And then there are add-on solutions like Titan, where we delegate the initial measurement and validation to a separate piece of hardware that measures the firmware as the CPU reads it, rather than requiring that the CPU do it.

But, overall, the situation isn’t great. On many platforms there’s simply no way to prove that you booted the code you expected to boot. People have designed elaborate security implementations that can be bypassed in a number of ways.

[1] In this respect it is extremely similar to “Zero Trust”
[2] This is a bit of an oversimplification – once we get into dynamic roots of trust like Intel’s TXT this story gets more complicated, but let’s stick to the simple case today
[3] I’m kind of using “firmware” in an x86ish manner here, so for embedded devices just think of “firmware” as “the first code executed out of flash and signed by someone other than the SoC vendor”
[4] In the Intel case this isn’t strictly true, since the keys are stored in the motherboard chipset rather than the CPU, and so taking a board with Boot Guard enabled and swapping out the CPU won’t disable Boot Guard because the CPU reads the configuration from the chipset. But many mobile Intel parts have the chipset in the same package as the CPU, so in theory swapping out that entire package would disable Boot Guard. I am not good enough at soldering to demonstrate that.

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Twitter’s e2ee DMs are better than nothing

Post Syndicated from original https://mjg59.dreamwidth.org/66791.html

Elon Musk appeared on an interview with Tucker Carlson last month, with one of the topics being the fact that Twitter could be legally compelled to hand over users’ direct messages to government agencies since they’re held on Twitter’s servers and aren’t encrypted. Elon talked about how they were in the process of implementing proper encryption for DMs that would prevent this – “You could put a gun to my head and I couldn’t tell you. That’s how it should be.”

tl;dr – in the current implementation, while Twitter could subvert the end-to-end nature of the encryption, it could not do so without users being notified. If any user involved in a conversation were to ignore that notification, all messages in that conversation (including ones sent in the past) could then be decrypted. This isn’t ideal, but it still seems like an improvement over having no encryption at all. More technical discussion follows.

For context: all information about Twitter’s implementation here has been derived from reverse engineering version 9.86.0 of the Android client and 9.56.1 of the iOS client (the current versions at time of writing), and the feature hasn’t yet launched. While it’s certainly possible that there could be major changes in the protocol between now launch, Elon has asserted that they plan to launch the feature this week so it’s plausible that this reflects what’ll ship.

For it to be impossible for Twitter to read DMs, they need to not only be encrypted, they need to be encrypted with a key that’s not available to Twitter. This is what’s referred to as “end-to-end encryption”, or e2ee – it means that the only components in the communication chain that have access to the unencrypted data are the endpoints. Even if the message passes through other systems (and even if it’s stored on other systems), those systems do not have access to the keys that would be needed to decrypt the data.

End-to-end encrypted messengers were initially popularised by Signal, but the Signal protocol has since been incorporated into WhatsApp and is probably much more widely used there. Millions of people per day are sending messages to each other that pass through servers controlled by third parties, but those third parties are completely unable to read the contents of those messages. This is the scenario that Elon described, where there’s no degree of compulsion that could cause the people relaying messages to and from people to decrypt those messages afterwards.

But for this to be possible, both ends of the communication need to be able to encrypt messages in a way the other end can decrypt. This is usually performed using AES, a well-studied encryption algorithm with no known significant weaknesses. AES is a form of what’s referred to as a symmetric encryption, one where encryption and decryption are performed with the same key. This means that both ends need access to that key, which presents us with a bootstrapping problem. Until a shared secret is obtained, there’s no way to communicate securely, so how do we generate that shared secret? A common mechanism for this is something called Diffie Hellman key exchange, which makes use of asymmetric encryption. In asymmetric encryption, an encryption key can be split into two components – a public key and a private key. Both devices involved in the communication combine their private key and the other party’s public key to generate a secret that can only be decoded with access to the private key. As long as you know the other party’s public key, you can now securely generate a shared secret with them. Even a third party with access to all the public keys won’t be able to identify this secret. Signal makes use of a variation of Diffie-Hellman called Extended Triple Diffie-Hellman that has some desirable properties, but it’s not strictly necessary for the implementation of something that’s end-to-end encrypted.

Although it was rumoured that Twitter would make use of the Signal protocol, and in fact there are vestiges of code in the Twitter client that still reference Signal, recent versions of the app have shipped with an entirely different approach that appears to have been written from scratch. It seems simple enough. Each device generates an asymmetric keypair using the NIST P-256 elliptic curve, along with a device identifier. The device identifier and the public half of the key are uploaded to Twitter using a new API endpoint called /1.1/keyregistry/register. When you want to send an encrypted DM to someone, the app calls /1.1/keyregistry/extract_public_keys with the IDs of the users you want to communicate with, and gets back a list of their public keys. It then looks up the conversation ID (a numeric identifier that corresponds to a given DM exchange – for a 1:1 conversation between two people it doesn’t appear that this ever changes, so if you DMed an account 5 years ago and then DM them again now from the same account, the conversation ID will be the same) in a local database to retrieve a conversation key. If that key doesn’t exist yet, the sender generates a random one. The message is then encrypted with the conversation key using AES in GCM mode, and the conversation key is then put through Diffie-Hellman with each of the recipients’ public device keys. The encrypted message is then sent to Twitter along with the list of encrypted conversation keys. When each of the recipients’ devices receives the message it checks whether it already has a copy of the conversation key, and if not performs its half of the Diffie-Hellman negotiation to decrypt the encrypted conversation key. One it has the conversation key it decrypts it and shows it to the user.

What would happen if Twitter changed the registered public key associated with a device to one where they held the private key, or added an entirely new device to a user’s account? If the app were to just happily send a message with the conversation key encrypted with that new key, Twitter would be able to decrypt that and obtain the conversation key. Since the conversation key is tied to the conversation, not any given pair of devices, obtaining the conversation key means you can then decrypt every message in that conversation, including ones sent before the key was obtained.

(An aside: Signal and WhatsApp make use of a protocol called Sesame which involves additional secret material that’s shared between every device a user owns, hence why you have to do that QR code dance whenever you add a new device to your account. I’m grossly over-simplifying how clever the Signal approach is here, largely because I don’t understand the details of it myself. The Signal protocol uses something called the Double Ratchet Algorithm to implement the actual message encryption keys in such a way that even if someone were able to successfully impersonate a device they’d only be able to decrypt messages sent after that point even if they had encrypted copies of every previous message in the conversation)

How’s this avoided? Based on the UI that exists in the iOS version of the app, in a fairly straightforward way – each user can only have a single device that supports encrypted messages. If the user (or, in our hypothetical, a malicious Twitter) replaces the device key, the client will generate a notification. If the user pays attention to that notification and verifies with the recipient through some out of band mechanism that the device has actually been replaced, then everything is fine. But, if any participant in the conversation ignores this warning, the holder of the subverted key can obtain the conversation key and decrypt the entire history of the conversation. That’s strictly worse than anything based on Signal, where such impersonation would simply not work, but even in the Twitter case it’s not possible for someone to silently subvert the security.

So when Elon says Twitter wouldn’t be able to decrypt these messages even if someone held a gun to his head, there’s a condition applied to that – it’s true as long as nobody fucks up. This is clearly better than the messages just not being encrypted at all in the first place, but overall it’s a weaker solution than Signal. If you’re currently using Twitter DMs, should you turn on encryption? As long as the limitations aren’t too limiting, definitely! Should you use this in preference to Signal or WhatsApp? Almost certainly not. This seems like a genuine incremental improvement, but it’d be easy to interpret what Elon says as providing stronger guarantees than actually exist.

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PSA: upgrade your LUKS key derivation function

Post Syndicated from original https://mjg59.dreamwidth.org/66429.html

Here’s an article from a French anarchist describing how his (encrypted) laptop was seized after he was arrested, and material from the encrypted partition has since been entered as evidence against him. His encryption password was supposedly greater than 20 characters and included a mixture of cases, numbers, and punctuation, so in the absence of any sort of opsec failures this implies that even relatively complex passwords can now be brute forced, and we should be transitioning to even more secure passphrases.

Or does it? Let’s go into what LUKS is doing in the first place. The actual data is typically encrypted with AES, an extremely popular and well-tested encryption algorithm. AES has no known major weaknesses and is not considered to be practically brute-forceable – at least, assuming you have a random key. Unfortunately it’s not really practical to ask a user to type in 128 bits of binary every time they want to unlock their drive, so another approach has to be taken.

This is handled using something called a “key derivation function”, or KDF. A KDF is a function that takes some input (in this case the user’s password) and generates a key. As an extremely simple example, think of MD5 – it takes an input and generates a 128-bit output, so we could simply MD5 the user’s password and use the output as an AES key. While this could technically be considered a KDF, it would be an extremely bad one! MD5s can be calculated extremely quickly, so someone attempting to brute-force a disk encryption key could simply generate the MD5 of every plausible password (probably on a lot of machines in parallel, likely using GPUs) and test each of them to see whether it decrypts the drive.

(things are actually slightly more complicated than this – your password is used to generate a key that is then used to encrypt and decrypt the actual encryption key. This is necessary in order to allow you to change your password without having to re-encrypt the entire drive – instead you simply re-encrypt the encryption key with the new password-derived key. This also allows you to have multiple passwords or unlock mechanisms per drive)

Good KDFs reduce this risk by being what’s technically referred to as “expensive”. Rather than performing one simple calculation to turn a password into a key, they perform a lot of calculations. The number of calculations performed is generally configurable, in order to let you trade off between the amount of security (the number of calculations you’ll force an attacker to perform when attempting to generate a key from a potential password) and performance (the amount of time you’re willing to wait for your laptop to generate the key after you type in your password so it can actually boot). But, obviously, this tradeoff changes over time – defaults that made sense 10 years ago are not necessarily good defaults now. If you set up your encrypted partition some time ago, the number of calculations required may no longer be considered up to scratch.

And, well, some of these assumptions are kind of bad in the first place! Just making things computationally expensive doesn’t help a lot if your adversary has the ability to test a large number of passwords in parallel. GPUs are extremely good at performing the sort of calculations that KDFs generally use, so an attacker can “just” get a whole pile of GPUs and throw them at the problem. KDFs that are computationally expensive don’t do a great deal to protect against this. However, there’s another axis of expense that can be considered – memory. If the KDF algorithm requires a significant amount of RAM, the degree to which it can be performed in parallel on a GPU is massively reduced. A Geforce 4090 may have 16,384 execution units, but if each password attempt requires 1GB of RAM and the card only has 24GB on board, the attacker is restricted to running 24 attempts in parallel.

So, in these days of attackers with access to a pile of GPUs, a purely computationally expensive KDF is just not a good choice. And, unfortunately, the subject of this story was almost certainly using one of those. Ubuntu 18.04 used the LUKS1 header format, and the only KDF supported in this format is PBKDF2. This is not a memory expensive KDF, and so is vulnerable to GPU-based attacks. But even so, systems using the LUKS2 header format used to default to argon2i, again not a memory expensive KDF. New versions default to argon2id, which is. You want to be using argon2id.

What makes this worse is that distributions generally don’t update this in any way. If you installed your system and it gave you pbkdf2 as your KDF, you’re probably still using pbkdf2 even if you’ve upgraded to a system that would use argon2id on a fresh install. Thankfully, this can all be fixed-up in place. But note that if anything goes wrong here you could lose access to all your encrypted data, so before doing anything make sure it’s all backed up (and figure out how to keep said backup secure so you don’t just have your data seized that way).

First, make sure you’re running as up-to-date a version of your distribution as possible. Having tools that support the LUKS2 format doesn’t mean that your distribution has all of that integrated, and old distribution versions may allow you to update your LUKS setup without actually supporting booting from it. Also, if you’re using an encrypted /boot, stop now – very recent versions of grub2 support LUKS2, but they don’t support argon2id, and this will render your system unbootable.

Next, figure out which device under /dev corresponds to your encrypted partition. Run

lsblk

and look for entries that have a type of “crypt”. The device above that in the tree is the actual encrypted device. Record that name, and run

sudo cryptsetup luksHeaderBackup /dev/whatever --header-backup-file /tmp/luksheader

and copy that to a USB stick or something. If something goes wrong here you’ll be able to boot a live image and run

sudo cryptsetup luksHeaderRestore /dev/whatever --header-backup-file luksheader

to restore it. Next, run

sudo cryptsetup luksDump /dev/whatever

and look for the Version: line. If it’s version 1, you need to update the header to LUKS2. Run

sudo cryptsetup convert /dev/whatever --type luks2

and follow the prompts. Make sure your system still boots, and if not go back and restore the backup of your header. Assuming everything is ok at this point, run

sudo cryptsetup luksDump /dev/whatever

again and look for the PBKDF: line in each keyslot (pay attention only to the keyslots, ignore any references to pbkdf2 that come after the Digests: line). If the PBKDF is either “pbkdf2” or “argon2i” you should convert to argon2id. Run the following:

sudo cryptsetup luksConvertKey /dev/whatever --pbkdf argon2id

and follow the prompts. If you have multiple passwords associated with your drive you’ll have multiple keyslots, and you’ll need to repeat this for each password.

Distributions! You should really be handling this sort of thing on upgrade. People who installed their systems with your encryption defaults several years ago are now much less secure than people who perform a fresh install today. Please please please do something about this.

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Booting modern Intel CPUs

Post Syndicated from original https://mjg59.dreamwidth.org/66109.html

CPUs can’t do anything without being told what to do, which leaves the obvious problem of how do you tell a CPU to do something in the first place. On many CPUs this is handled in the form of a reset vector – an address the CPU is hardcoded to start reading instructions from when power is applied. The address the reset vector points to will typically be some form of ROM or flash that can be read by the CPU even if no other hardware has been configured yet. This allows the system vendor to ship code that will be executed immediately after poweron, configuring the rest of the hardware and eventually getting the system into a state where it can run user-supplied code.

The specific nature of the reset vector on x86 systems has varied over time, but it’s effectively always been 16 bytes below the top of the address space – so, 0xffff0 on the 20-bit 8086, 0xfffff0 on the 24-bit 80286, and 0xfffffff0 on the 32-bit 80386. Convention on x86 systems is to have RAM starting at address 0, so the top of address space could be used to house the reset vector with as low a probability of conflicting with RAM as possible.

The most notable thing about x86 here, though, is that when it starts running code from the reset vector, it’s still in real mode. x86 real mode is a holdover from a much earlier era of computing. Rather than addresses being absolute (ie, if you refer to a 32-bit address, you store the entire address in a 32-bit or larger register), they are 16-bit offsets that are added to the value stored in a “segment register”. Different segment registers existed for code, data, and stack, so a 16-bit address could refer to different actual addresses depending on host it was being interpreted – jumping to a 16 bit address would result in that address being added to the code segment register, while reading from a 16 bit address would result in that address being added to the data segment register, and so on. This is all in order to retain compatibility with older chips, to the extent that even 64-bit x86 starts in real mode with segments and everything (and, also, still starts executing at 0xfffffff0 rather than 0xfffffffffffffff0 – 64-bit mode doesn’t support real mode, so there’s no way to express a 64-bit physical address using the segment registers, so we still start just below 4GB even though we have massively more address space available).

Anyway. Everyone knows all this. For modern UEFI systems, the firmware that’s launched from the reset vector then reprograms the CPU into a sensible mode (ie, one without all this segmentation bullshit), does things like configure the memory controller so you can actually access RAM (a process which involves using CPU cache as RAM, because programming a memory controller is sufficiently hard that you need to store more state than you can fit in registers alone, which means you need RAM, but you don’t have RAM until the memory controller is working, but thankfully the CPU comes with several megabytes of RAM on its own in the form of cache, so phew). It’s kind of ugly, but that’s a consequence of a bunch of well-understood legacy decisions.

Except. This is not how modern Intel x86 boots. It’s far stranger than that. Oh, yes, this is what it looks like is happening, but there’s a bunch of stuff going on behind the scenes. Let’s talk about boot security. The idea of any form of verified boot (such as UEFI Secure Boot) is that a signature on the next component of the boot chain is validated before that component is executed. But what verifies the first component in the boot chain? You can’t simply ask the BIOS to verify itself – if an attacker can replace the BIOS, they can replace it with one that simply lies about having done so. Intel’s solution to this is called Boot Guard.

But before we get to Boot Guard, we need to ensure the CPU is running in as bug-free a state as possible. So, when the CPU starts up, it examines the system flash and looks for a header that points at CPU microcode updates. Intel CPUs ship with built-in microcode, but it’s frequently old and buggy and it’s up to the system firmware to include a copy that’s new enough that it’s actually expected to work reliably. The microcode image is pulled out of flash, a signature is verified, and the new microcode starts running. This is true in both the Boot Guard and the non-Boot Guard scenarios. But for Boot Guard, before jumping to the reset vector, the microcode on the CPU reads an Authenticated Code Module (ACM) out of flash and verifies its signature against a hardcoded Intel key. If that checks out, it starts executing the ACM. Now, bear in mind that the CPU can’t just verify the ACM and then execute it directly from flash – if it did, the flash could detect this, hand over a legitimate ACM for the verification, and then feed the CPU different instructions when it reads them again to execute them (a Time of Check vs Time of Use, or TOCTOU, vulnerability). So the ACM has to be copied onto the CPU before it’s verified and executed, which means we need RAM, which means the CPU already needs to know how to configure its cache to be used as RAM.

Anyway. We now have an ACM loaded and verified, and it can safely be executed. The ACM does various things, but the most important from the Boot Guard perspective is that it reads a set of write-once fuses in the motherboard chipset that represent the SHA256 of a public key. It then reads the initial block of the firmware (the Initial Boot Block, or IBB) into RAM (or, well, cache, as previously described) and parses it. There’s a block that contains a public key – it hashes that key and verifies that it matches the SHA256 from the fuses. It then uses that key to validate a signature on the IBB. If it all checks out, it executes the IBB and everything starts looking like the nice simple model we had before.

Except, well, doesn’t this seem like an awfully complicated bunch of code to implement in real mode? And yes, doing all of this modern crypto with only 16-bit registers does sound like a pain. So, it doesn’t. All of this is happening in a perfectly sensible 32 bit mode, and the CPU actually switches back to the awful segmented configuration afterwards so it’s still compatible with an 80386 from 1986. The “good” news is that at least firmware can detect that the CPU has already configured the cache as RAM and can skip doing that itself.

I’m skipping over some steps here – the ACM actually does other stuff around measuring the firmware into the TPM and doing various bits of TXT setup for people who want DRTM in their lives, but the short version is that the CPU bootstraps itself into a state where it works like a modern CPU and then deliberately turns a bunch of the sensible functionality off again before it starts executing firmware. I’m also missing out the fact that this entire process only kicks off after the Management Engine says it can, which means we’re waiting for an entirely independent x86 to boot an entire OS before our CPU even starts pretending to execute the system firmware.

Of course, as mentioned before, on modern systems the firmware will then reprogram the CPU into something actually sensible so OS developers no longer need to care about this[1][2], which means we’ve bounced between multiple states for no reason other than the possibility that someone wants to run legacy BIOS and then boot DOS on a CPU with like 5 orders of magnitude more transistors than the 8086.

tl;dr why can’t my x86 wake up with the gin protected mode already inside it

[1] Ha uh except that on ACPI resume we’re going to skip most of the firmware setup code so we still need to handle the CPU being in fucking 16-bit mode because suspend/resume is basically an extremely long reboot cycle

[2] Oh yeah also you probably have multiple cores on your CPU and well bad news about the state most of the cores are in when the OS boots because the firmware never started them up so they’re going to come up in 16-bit real mode even if your boot CPU is already in 64-bit protected mode, unless you were using TXT in which case you have a different sort of nightmare that if we’re going to try to map it onto real world nightmare concepts is one that involves a lot of teeth

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We need better support for SSH host certificates

Post Syndicated from original https://mjg59.dreamwidth.org/65874.html

Github accidentally committed their SSH RSA private key to a repository, and now a bunch of people’s infrastructure is broken because it needs to be updated to trust the new key. This is obviously bad, but what’s frustrating is that there’s no inherent need for it to be – almost all the technological components needed to both reduce the initial risk and to make the transition seamless already exist.

But first, let’s talk about what actually happened here. You’re probably used to the idea of TLS certificates from using browsers. Every website that supports TLS has an asymmetric pair of keys divided into a public key and a private key. When you contact the website, it gives you a certificate that contains the public key, and your browser then performs a series of cryptographic operations against it to (a) verify that the remote site possesses the private key (which prevents someone just copying the certificate to another system and pretending to be the legitimate site), and (b) generate an ephemeral encryption key that’s used to actually encrypt the traffic between your browser and the site. But what stops an attacker from simply giving you a fake certificate that contains their public key? The certificate is itself signed by a certificate authority (CA), and your browser is configured to trust a preconfigured set of CAs. CAs will not give someone a signed certificate unless they prove they have legitimate ownership of the site in question, so (in theory) an attacker will never be able to obtain a fake certificate for a legitimate site.

This infrastructure is used for pretty much every protocol that can use TLS, including things like SMTP and IMAP. But SSH doesn’t use TLS, and doesn’t participate in any of this infrastructure. Instead, SSH tends to take a “Trust on First Use” (TOFU) model – the first time you ssh into a server, you receive a prompt asking you whether you trust its public key, and then you probably hit the “Yes” button and get on with your life. This works fine up until the point where the key changes, and SSH suddenly starts complaining that there’s a mismatch and something awful could be happening (like someone intercepting your traffic and directing it to their own server with their own keys). Users are then supposed to verify whether this change is legitimate, and if so remove the old keys and add the new ones. This is tedious and risks users just saying “Yes” again, and if it happens too often an attacker can simply redirect target users to their own server and through sheer fatigue at dealing with this crap the user will probably trust the malicious server.

Why not certificates? OpenSSH actually does support certificates, but not in the way you might expect. There’s a custom format that’s significantly less complicated than the X509 certificate format used in TLS. Basically, an SSH certificate just contains a public key, a list of hostnames it’s good for, and a signature from a CA. There’s no pre-existing set of trusted CAs, so anyone could generate a certificate that claims it’s valid for, say, github.com. This isn’t really a problem, though, because right now nothing pays attention to SSH host certificates unless there’s some manual configuration.

(It’s actually possible to glue the general PKI infrastructure into SSH certificates. Please do not do this)

So let’s look at what happened in the Github case. The first question is “How could the private key have been somewhere that could be committed to a repository in the first place?”. I have no unique insight into what happened at Github, so this is conjecture, but I’m reasonably confident in it. Github deals with a large number of transactions per second. Github.com is not a single computer – it’s a large number of machines. All of those need to have access to the same private key, because otherwise git would complain that the private key had changed whenever it connected to a machine with a different private key (the alternative would be to use a different IP address for every frontend server, but that would instead force users to repeatedly accept additional keys every time they connect to a new IP address). Something needs to be responsible for deploying that private key to new systems as they’re brought up, which means there’s ample opportunity for it to accidentally end up in the wrong place.

Now, best practices suggest that this should be avoided by simply placing the private key in a hardware module that performs the cryptographic operations, ensuring that nobody can ever get at the private key. The problem faced here is that HSMs typically aren’t going to be fast enough to handle the number of requests per second that Github deals with. This can be avoided by using something like a Nitro Enclave, but you’re still going to need a bunch of these in different geographic locales because otherwise your front ends are still going to be limited by the need to talk to an enclave on the other side of the planet, and now you’re still having to deal with distributing the private key to a bunch of systems.

What if we could have the best of both worlds – the performance of private keys that just happily live on the servers, and the security of private keys that live in HSMs? Unsurprisingly, we can! The SSH private key could be deployed to every front end server, but every minute it could call out to an HSM-backed service and request a new SSH host certificate signed by a private key in the HSM. If clients are configured to trust the key that’s signing the certificates, then it doesn’t matter what the private key on the servers is – the client will see that there’s a valid certificate and will trust the key, even if it changes. Restricting the validity of the certificate to a small window of time means that if a key is compromised an attacker can’t do much with it – the moment you become aware of that you stop signing new certificates, and once all the existing ones expire the old private key becomes useless. You roll out a new private key with new certificates signed by the same CA and clients just carry on trusting it without any manual involvement.

Why don’t we have this already? The main problem is that client tooling just doesn’t handle this well. OpenSSH has no way to do TOFU for CAs, just the keys themselves. This means there’s no way to do a git clone ssh://[email protected]/whatever and get a prompt asking you to trust Github’s CA. Instead, you need to add a @cert-authority github.com (key) line to your known_hosts file by hand, and since approximately nobody’s going to do that there’s only marginal benefit in going to the effort to implement this infrastructure. The most important thing we can do to improve the security of the SSH ecosystem is to make it easier to use certificates, and that means improving the behaviour of the clients.

It should be noted that certificates aren’t the only approach to handling key migration. OpenSSH supports a protocol for key rotation, basically by allowing the server to provide a set of multiple trusted keys that the client can cache, and then invalidating old ones. Unfortunately this still requires that the “new” private keys be deployed in the same way as the old ones, so any screwup that results in one private key being leaked may well also result in the additional keys being leaked. I prefer the certificate approach.

Finally, I’ve seen a couple of people imply that the blame here should be attached to whoever or whatever caused the private key to be committed to a repository in the first place. This is a terrible take. Humans will make mistakes, and your systems should be resilient against that. There’s no individual at fault here – there’s a series of design decisions that made it possible for a bad outcome to occur, and in a better universe they wouldn’t have been necessary. Let’s work on building that better universe.

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Blocking free API access to Twitter doesn’t stop abuse

Post Syndicated from original https://mjg59.dreamwidth.org/65647.html

In one week from now, Twitter will block free API access. This prevents anyone who has written interesting bot accounts, integrations, or tooling from accessing Twitter without paying for it. A whole number of fascinating accounts will cease functioning, people will no longer be able to use tools that interact with Twitter, and anyone using a free service to do things like find Twitter mutuals who have moved to Mastodon or to cross-post between Twitter and other services will be blocked.

There’s a cynical interpretation to this, which is that despite firing 75% of the workforce Twitter is still not profitable and Elon is desperate to not have Twitter go bust and also not to have to tank even more of his Tesla stock to achieve that. But let’s go with the less cynical interpretation, which is that API access to Twitter is something that enables bot accounts that make things worse for everyone. Except, well, why would a hostile bot account do that?

To interact with an API you generally need to present some sort of authentication token to the API to prove that you’re allowed to access it. It’s easy enough to restrict issuance of those tokens to people who pay for the service. But, uh, how do the apps work? They need to be able to communicate with the service to tell it to post tweets, retrieve them, and so on. And the simple answer to that is that they use some hardcoded authentication tokens. And while registering for an API token yourself identifies that you’re not using an official client, using the tokens embedded in the clients makes it look like you are. If you want to make it look like you’re a human, you’re already using tokens ripped out of the official clients.

The Twitter client API keys are widely known. Anyone who’s pretending to be a human is using those already and will be unaffected by the shutdown of the free API tier. Services like movetodon.org do get blocked. This isn’t an anti-abuse choice. It’s one that makes it harder to move to other services. It’s one that blocks a bunch of the integrations and accounts that bring value to the platform. It’s one that hurts people who follow the rules, without hurting the ones who don’t. This isn’t an anti-abuse choice, it’s about trying to consolidate control of the platform.

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Further adventures in Apple PKCS#11 land

Post Syndicated from original https://mjg59.dreamwidth.org/65462.html

After my previous efforts, I wrote up a PKCS#11 module of my own that had no odd restrictions about using non-RSA keys and I tested it. And things looked much better – ssh successfully obtained the key, negotiated with the server to determine that it was present in authorized_keys, and then went to actually do the key verification step. At which point things went wrong – the Sign() method in my PKCS#11 module was never called, and a strange
debug1: identity_sign: sshkey_sign: error in libcrypto
sign_and_send_pubkey: signing failed for ECDSA “testkey”: error in libcrypto”

error appeared in the ssh output. Odd. libcrypto was originally part of OpenSSL, but Apple ship the LibreSSL fork. Apple don’t include the LibreSSL source in their public source repo, but do include OpenSSH. I grabbed the OpenSSH source and jumped through a whole bunch of hoops to make it build (it uses the macosx.internal SDK, which isn’t publicly available, so I had to cobble together a bunch of headers from various places), and also installed upstream LibreSSL with a version number matching what Apple shipped. And everything worked – I logged into the server using a hardware-backed key.

Was the difference in OpenSSH or in LibreSSL? Telling my OpenSSH to use the system libcrypto resulted in the same failure, so it seemed pretty clear this was an issue with the Apple version of the library. The way all this works is that when OpenSSH has a challenge to sign, it calls ECDSA_do_sign(). This then calls ECDSA_do_sign_ex(), which in turn follows a function pointer to the actual signature method. By default this is a software implementation that expects to have the private key available, but you can also register your own callback that will be used instead. The OpenSSH PKCS#11 code does this by calling EC_KEY_set_method(), and as a result calling ECDSA_do_sign() ends up calling back into the PKCS#11 code that then calls into the module that communicates with the hardware and everything works.

Except it doesn’t under macOS. Running under a debugger and setting a breakpoint on EC_do_sign(), I saw that we went down a code path with a function called ECDSA_do_sign_new(). This doesn’t appear in any of the public source code, so seems to be an Apple-specific patch. I pushed Apple’s libcrypto into Ghidra and looked at ECDSA_do_sign() and found something that approximates this:

nid = EC_GROUP_get_curve_name(curve);
if (nid == NID_X9_62_prime256v1) {
  return ECDSA_do_sign_new(dgst,dgst_len,eckey);
}
return ECDSA_do_sign_ex(dgst,dgst_len,NULL,NULL,eckey);

What this means is that if you ask ECDSA_do_sign() to sign something on a Mac, and if the key in question corresponds to the NIST P256 elliptic curve type, it goes down the ECDSA_do_sign_new() path and never calls the registered callback. This is the only key type supported by the Apple Secure Enclave, so I assume it’s special-cased to do something with that. Unfortunately the consequence is that it’s impossible to use a PKCS#11 module that uses Secure Enclave keys with the shipped version of OpenSSH under macOS. For now I’m working around this with an SSH agent built using Go’s agent module, forwarding most requests through to the default session agent but appending hardware-backed keys and implementing signing with them, which is probably what I should have done in the first place.

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Build security with the assumption it will be used against your friends

Post Syndicated from original https://mjg59.dreamwidth.org/65272.html

Working in information security means building controls, developing technologies that ensure that sensitive material can only be accessed by people that you trust. It also means categorising people into “trustworthy” and “untrustworthy”, and trying to come up with a reasonable way to apply that such that people can do their jobs without all your secrets being available to just anyone in the company who wants to sell them to a competitor. It means ensuring that accounts who you consider to be threats shouldn’t be able to do any damage, because if someone compromises an internal account you need to be able to shut them down quickly.

And like pretty much any security control, this can be used for both good and bad. The technologies you develop to monitor users to identify compromised accounts can also be used to compromise legitimate users who management don’t like. The infrastructure you build to push updates to users can also be used to push browser extensions that interfere with labour organisation efforts. In many cases there’s no technical barrier between something you’ve developed to flag compromised accounts and the same technology being used to flag users who are unhappy with certain aspects of management.

If you’re asked to build technology that lets you make this sort of decision, think about whether that’s what you want to be doing. Think about who can compel you to use it in ways other than how it was intended. Consider whether that’s something you want on your conscience. And then think about whether you can meet those requirements in a different way. If they can simply compel one junior engineer to alter configuration, that’s very different to an implementation that requires sign-offs from multiple senior developers. Make sure that all such policy changes have to be clearly documented, including not just who signed off on it but who asked them to. Build infrastructure that creates a record of who decided to fuck over your coworkers, rather than just blaming whoever committed the config update. The blame trail should never terminate in the person who was told to do something or get fired – the blame trail should clearly indicate who ordered them to do that.

But most importantly: build security features as if they’ll be used against you.

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PKCS#11. hardware keystores, and Apple frustrations

Post Syndicated from original https://mjg59.dreamwidth.org/64968.html

There’s a bunch of ways you can store cryptographic keys. The most obvious is to just stick them on disk, but that has the downside that anyone with access to the system could just steal them and do whatever they wanted with them. At the far end of the scale you have Hardware Security Modules (HSMs), hardware devices that are specially designed to self destruct if you try to take them apart and extract the keys, and which will generate an audit trail of every key operation. In between you have things like smartcards, TPMs, Yubikeys, and other platform secure enclaves – devices that don’t allow arbitrary access to keys, but which don’t offer the same level of assurance as an actual HSM (and are, as a result, orders of magnitude cheaper).

The problem with all of these hardware approaches is that they have entirely different communication mechanisms. The industry realised this wasn’t ideal, and in 1994 RSA released version 1 of the PKCS#11 specification. This defines a C interface with a single entry point – C_GetFunctionList. Applications call this and are given a structure containing function pointers, with each entry corresponding to a PKCS#11 function. The application can then simply call the appropriate function pointer to trigger the desired functionality, such as “Tell me how many keys you have” and “Sign this, please”. This is both an example of C not just being a programming language and also of you having to shove a bunch of vendor-supplied code into your security critical tooling, but what could possibly go wrong.

(Linux distros work around this problem by using p11-kit, which is a daemon that speaks d-bus and loads PKCS#11 modules for you. You can either speak to it directly over d-bus, or for apps that only speak PKCS#11 you can load a module that just transports the PKCS#11 commands over d-bus. This moves the weird vendor C code out of process, and also means you can deal with these modules without having to speak the C ABI, so everyone wins)

One of my work tasks at the moment is helping secure SSH keys, ensuring that they’re only issued to appropriate machines and can’t be stolen afterwards. For Windows and Linux machines we can stick them in the TPM, but Macs don’t have a TPM as such. Instead, there’s the Secure Enclave – part of the T2 security chip on x86 Macs, and directly integrated into the M-series SoCs. It doesn’t have anywhere near as many features as a TPM, let alone an HSM, but it can generate NIST curve elliptic curve keys and sign things with them and that’s good enough. Things are made more complicated by Apple only allowing keys to be used by the app that generated them, so it’s hard for applications to generate keys on behalf of each other. This can be mitigated by using CryptoTokenKit, an interface that allows apps to present tokens to the systemwide keychain. Although this is intended for allowing a generic interface for access to such tokens (kind of like PKCS#11), an app can generate its own keys in the Secure Enclave and then expose them to other apps via the keychain through CryptoTokenKit.

Of course, applications then need to know how to communicate with the keychain. Browsers mostly do so, and Apple’s version of SSH can to an extent. Unfortunately, that extent is “Retrieve passwords to unlock on-disk keys”, which doesn’t help in our case. PKCS#11 comes to the rescue here! Apple ship a module called ssh-keychain.dylib, a PKCS#11 module that’s intended to allow SSH to use keys that are present in the system keychain. Unfortunately it’s not super well maintained – it got broken when Big Sur moved all the system libraries into a cache, but got fixed up a few releases later. Unfortunately every time I tested it with our CryptoTokenKit provider (and also when I retried with SecureEnclaveToken to make sure it wasn’t just our code being broken), ssh would tell me "provider /usr/lib/ssh-keychain.dylib returned no slots" which is not especially helpful. Finally I realised that it was actually generating more debug output, but it was being sent to the system debug logs rather than the ssh debug output. Well, when I say “more debug output”, I mean "Certificate []: algorithm is not supported, ignoring it", which still doesn’t tell me all that much. So I stuck it in Ghidra and searched for that string, and the line above it was

iVar2 = __auth_stubs::_objc_msgSend(uVar7,"isEqual:",*(undefined8*)__got::_kSecAttrKeyTypeRSA);

with it immediately failing if the key isn’t RSA. Which it isn’t, since the Secure Enclave doesn’t support RSA. Apple’s PKCS#11 module appears incapable of making use of keys generated on Apple’s hardware.

There’s a couple of ways of dealing with this. The first, which is taken by projects like Secretive, is to implement the SSH agent protocol and have SSH delegate key management to that agent, which can then speak to the keychain. But if you want this to work in all cases you need to implement all the functionality in the existing ssh-agent, and that seems like a bunch of work. The second is to implement a PKCS#11 module, which sounds like less work but probably more mental anguish. I’ll figure that out tomorrow.

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Blogging and microblogging

Post Syndicated from original https://mjg59.dreamwidth.org/64660.html

Long-term Linux users may remember that Alan Cox used to write an online diary. This was before the concept of a “Weblog” had really become a thing, and there certainly weren’t any expectations around what one was used for – while now blogging tends to imply a reasonably long-form piece on a specific topic, Alan was just sitting there noting small life concerns or particular technical details in interesting problems he’d solved that day. For me, that was fascinating. I was trying to figure out how to get into kernel development, and was trying to read as much LKML as I could to figure out how kernel developers did stuff. But when you see discussion on LKML, you’re frequently missing the early stages. If an LKML patch is a picture of an owl, I wanted to know how to draw the owl, and most of the conversations about starting in kernel development were very “Draw two circles. Now draw the rest of the owl”. Alan’s musings gave me insight into the thought processes involved in getting from “Here’s the bug” to “Here’s the patch” in ways that really wouldn’t have worked in a more long-form medium.

For the past decade or so, as I moved away from just doing kernel development and focused more on security work instead, Twitter’s filled a similar role for me. I’ve seen people just dumping their thought process as they work through a problem, helping me come up with effective models for solving similar problems. I’ve learned that the smartest people in the field will spend hours (if not days) working on an issue before realising that they misread something back at the beginning and that’s helped me feel like I’m not unusually bad at any of this. It’s helped me learn more about my peers, about my field, and about myself.

Twitter’s now under new ownership that appears to think all the worst bits of Twitter were actually the good bits, so I’ve mostly bailed to the Fediverse instead. There’s no intrinsic length limit on posts there – Mastodon defaults to 500 characters per post, but that’s configurable per instance. But even at 500 characters, it means there’s more room to provide thoughtful context than there is on Twitter, and what I’ve seen so far is more detailed conversation and higher levels of meaningful engagement. Which is great! Except it also seems to discourage some of the posting style that I found so valuable on Twitter – if your timeline is full of nuanced discourse, it feels kind of rude to just scream “THIS FUCKING PIECE OF SHIT IGNORES THE HIGH ADDRESS BIT ON EVERY OTHER WRITE” even though that’s exactly the sort of content I’m there for.

And, yeah, not everything has to be for me. But I worry that as Twitter’s relevance fades for the people I’m most interested in, we’re replacing it with something that’s not equivalent – something that doesn’t encourage just dropping 50 characters or so of your current thought process into a space where it can be seen by thousands of people. And I think that’s a shame.

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