| Internet-Draft | Key Transparency Architecture | January 2024 |
| McMillion | Expires 22 July 2024 | [Page] |
This document defines the terminology and interaction patterns involved in the deployment of Key Transparency (KT) in a general secure group messaging infrastructure, and specifies the security properties that the protocol provides. It also gives more general, non-prescriptive guidance on how to securely apply KT to a number of common applications.¶
This note is to be removed before publishing as an RFC.¶
The latest revision of this draft can be found at https://ietf-wg-keytrans.github.io/draft-arch/draft-ietf-keytrans-architecture.html. Status information for this document may be found at https://datatracker.ietf.org/doc/draft-ietf-keytrans-architecture/.¶
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Before any information can be exchanged in an end-to-end encrypted system, two things must happen. First, participants in the system must provide the service operator with any public keys they wish to use to receive messages. Second, the service operator must somehow distribute these public keys amongst the participants that wish to communicate with each other.¶
Typically this is done by having users upload their public keys to a simple directory where other users can download them as necessary, or by providing public keys in-band with the communication being secured. With this approach, the service operator needs to be trusted to provide the correct public keys, which means that the underlying encryption protocol can only protect users against passive eavesdropping on their messages.¶
However most messaging systems are designed such that all messages exchanged between users flow through the service operator's servers, so it's extremely easy for an operator to launch an active attack. That is, the service operator can provide fake public keys which it knows the private keys for, associate those public keys with a user's account without the user's knowledge, and then use them to impersonate or eavesdrop on conversations with that user.¶
Key Transparency (KT) solves this problem by requiring the service operator to store user public keys in a cryptographically-protected append-only log. Any malicious entries added to such a log will generally be visible to all users, in which case a user can detect that they're being impersonated by viewing the public keys attached to their account. However, if the service operator attempts to conceal some entries of the log from some users but not others, this creates a "forked view" which is permanent and easily detectable with out-of-band communication.¶
The critical improvement of KT over related protocols like Certificate Transparency [RFC6962] is that KT includes an efficient protocol to search the log for entries related to a specific participant. This means users don't need to download the entire log, which may be substantial, to find all entries that are relevant to them. It also means that KT can better preserve user privacy by only showing entries of the log to participants that genuinely need to see them.¶
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all capitals, as shown here.¶
A communications service that allows end-users to engage in text, voice, video, or other forms of communication over the Internet, that uses public key cryptography to ensure that communications are only accessible to their intended recipients.¶
The device at the final point in a digital communication, which may either send or receive encrypted data in an end-to-end encrypted communication service.¶
A unique and user-visible identity associated with an account (and therefore one or more end-user devices) in an end-to-end encrypted communication service. In the case where an end-user explicitly requests to communicate with (or is informed they are communicating with) an end-user uniquely identified by the name "Alice", the end-user identity is the string "Alice".¶
A single end-user of an end-to-end encrypted communication service, which may be represented by several end-user identities and end-user devices. For example, a user may be represented simultaneously by multiple identities (email, phone number, username) and interact with the service on multiple devices (phone, laptop).¶
The primary organization that provides the infrastructure and software resources necessary to operate an end-to-end encrypted communication service.¶
A specialized service capable of securely attesting to the information (such as public keys) associated with a given end-user identity. The transparency log is usually run either entirely or partially by the service operator.¶
From a networking perspective, KT follows a client-server architecture with a central Transparency Log, acting as a server, which holds the authoritative copy of all information and exposes endpoints that allow users to query or modify stored data. Users coordinate with each other through the server by uploading their own public keys and/or downloading the public keys of other users. Users are expected to maintain relatively little state, limited only to what is required to interact with the log and ensure that it is behaving honestly.¶
From an application perspective, KT works as a versioned key-value database. Users insert key-value pairs into the database where, for example, the key is their username and the value is their public key. Users can update a key by inserting a new version with new data. They can also look up the most recent version of a key or any past version. Users are considered to own a key if, in the normal operation of the application, they should be the only one making changes to it. From this point forward, "key" will refer to a lookup key in a key-value database and "public key" or "private key" will be specified if otherwise.¶
KT does not require the use of a specific transport protocol. This is intended to allow applications to layer KT on top of whatever transport protocol their application already uses. In particular, this allows applications to continue relying on their existing access control system.¶
Applications may enforce arbitrary access control rules on top of KT such as requiring a user to be logged in to make KT requests, only allowing a user to lookup the keys of another user if they're "friends", or simply applying a rate limit. Applications SHOULD prevent users from modifying keys that they don't own. The exact mechanism for rejecting requests, and possibly explaining the reason for rejection, is left to the application.¶
As discussed in Section 3, KT follows a client-server architecture. This means that all user interaction is directly with the transparency log. The operations that can be executed by a user are as follows:¶
Search: Performs a lookup on a specific key in the most recent version of the log. Users may request either a specific version of the key, or the most recent version available. If the key-version pair exists, the server returns the corresponding value and a proof of inclusion.¶
Update: Adds a new key-value pair to the log, for which the server returns a proof of inclusion. Note that this means that new values are added to the log immediately and are not queued for later insertion with a batch of other values.¶
Monitor: While Search and Update are run by the user as necessary, monitoring is done in the background on a recurring basis. It both checks that the log is continuing to behave honestly (all previously returned keys remain in the tree) and that no changes have been made to keys owned by the user without the user's knowledge.¶
These operations are executed over an application-provided transport layer, where the transport layer enforces access control by blocking queries which are not allowed:¶
TODO diagram showing a search request over an application-provided transport layer getting accepted / rejected¶
It is sometimes possible for a Transparency Log to present forked views of data to different users. This means that, from an individual user's perspective, a log may appear to be operating correctly in the sense that all of a user's requests succeed and proofs verify correctly. However, the Transparency Log has presented a view to the user that's not globally consistent with what it has shown other users. As such, the log may be able to associate data with keys without the key owner's awareness.¶
The protocol is designed such that users always require subsequent queries to prove consistency with previous queries. As such, users always stay on a linearizable view of the log. If a user is ever presented with a forked view, they hold on to this forked view forever and reject the output of any subsequent queries that are inconsistent with it.¶
This provides ample opportunity for users to detect when a fork has been presented, but isn't in itself sufficient for detection. To detect forks, users must either use out-of-band communication with other users or anonymous communication with the Transparency Log.¶
With out-of-band communication, two users gossip with each other to establish that they both have the same view of the log's data. This gossip is able to happen over any supported out-of-band channel, even if it is heavily bandwidth-limited, such as scanning a QR code or talking over the phone.¶
With anonymous communication, a single user accesses the Transparency Log over an anonymous channel and tries to establish that the log is presenting the same view of data over the anonymous channel as it does over authenticated channels.¶
In the event that a fork is successfully detected, the user is able to produce non-repudiable proof of log misbehavior which can be published.¶
TODO diagram showing a user talking to a log over an authenticated & anonymous channel, gossipping with other users¶
In the interest of satisfying the widest range of use-cases possible, three different modes for deploying a Transparency Log are supported. Each mode has slightly different requirements and efficiency considerations for both the transparency log and the end-user.¶
Third-Party Management and Third-Party Auditing are two deployment modes that require the transparency log to delegate part of its operation to a third party. Users are able to run more efficiently as long as they can assume that the transparency log and the third party won't collude to trick them into accepting malicious results.¶
With both third-party modes, all requests from end-users are initially routed to the transparency log and the log coordinates with the third party itself. End-users never contact the third party directly, however they will need a signature public key from the third party to verify its assertions.¶
With Third-Party Management, the third party performs the majority of the work of actually storing and operating the service, and the transparency log only signs new entries as they're added. With Third-Party Auditing, the transparency log performs the majority of the work of storing and operating the service, and obtains signatures from a lightweight third-party auditor at regular intervals asserting that the tree has been constructed correctly.¶
Contact Monitoring, on the other hand, supports a single-party deployment with no third party. The cost of this is that executing the background monitoring protocol requires an amount of work that's proportional to the number of keys a user has looked up in the past. As such, it's less suited to use-cases where users look up a large number of ephemeral keys, but would work ideally in a use-case where users look up a small number of keys repeatedly (for example, the keys of regular contacts).¶
| Deployment Mode | Supports ephemeral keys? | Single party? |
|---|---|---|
| Contact Monitoring | No | Yes |
| Third-Party Auditing | Yes | No |
| Third-Party Management | Yes | No |
TODO diagram showing user request going to transparency log, followed by monitoring queries later.¶
With the Third-Party Auditing deployment mode, the transparency log obtains signatures from a lightweight third-party auditor attesting to the fact that the tree has been constructed correctly. These signatures are provided to users along with the responses for their queries.¶
The third-party auditor is expected to run asynchronously, downloading and authenticating a log's contents in the background, so as not to become a bottleneck for the transparency log.¶
TODO diagram showing a user request going to a transparency log and a response with an auditor signature coming back. Batched changes going to auditor in background.¶
With the Third-Party Management deployment mode, a third party is responsible for the majority of the work of storing and operating the log, while the transparency log serves mainly to enforce access control and authenticate the addition of new entries to the log. All user queries are initially sent by users directly to the transparency log, and the log operator proxies them to the third-party manager if they pass access control.¶
TODO diagram showing user request going to transparency log, immediately being proxied to manager with operator signature.¶
A user that correctly verifies a proof from the Transparency Log (and does any required monitoring afterwards) receives a guarantee that the Transparency Log operator executed the key-value lookup correctly, and in a way that's globally consistent with what it has shown all other users. That is, when a user searches for a key, they're guaranteed that the result they receive represents the same result that any other user searching for the same key would've seen. When a user modifies a key, they're guaranteed that other users will see the modification the next time they search for the key.¶
If the Transparency Log operator does not execute a key-value lookup correctly, then either:¶
The user will detect the error immediately and reject the proof, or¶
The user will permanently enter an invalid state.¶
Depending on the exact reason that the user enters an invalid state, it will either be detected by background monitoring or the next time that out-of-band communication is available. Importantly, this means that users must stay online for some bounded amount of time after entering an invalid state for it to be successfully detected.¶
Alternatively, instead of executing a lookup incorrectly, the Transparency Log can attempt to prevent a user from learning about more recent states of the log. This would allow the log to continue executing queries correctly, but on outdated versions of data. To prevent this, applications configure an upper bound on how stale a query response can be without being rejected.¶
The exact caveats of the above guarantees depend naturally on the security of underlying cryptographic primitives, and also the deployment mode that the Transparency Log relies on:¶
Third-Party Management and Third-Party Auditing require an assumption that the transparency log and the third-party manager/auditor do not collude to trick users into accepting malicious results.¶
Contact Monitoring requires an assumption that the user that owns a key and all users that look up the key do the necessary monitoring afterwards.¶
In short, assuming that the underlying cryptographic primitives used are secure, any deployment-specific assumptions hold (such as non-collusion), and that user devices don't go permanently offline, then malicious behavior by the Transparency Log is always detected within a bounded amount of time. The parameters that determine the maximum amount of time before malicious behavior is detected are as follows:¶
How stale an application allows query responses to be (ie, how long an application is willing to go without seeing updates to the tree).¶
How frequently users execute background monitoring.¶
How frequently users exercise out-of-band communication.¶
For third-party auditing: the maximum amount of lag that an auditor is allowed to have, with respect to the most recent tree head.¶
For applications deploying KT, service operators expect to be able to control when sensitive information is revealed. In particular, an operator can often only reveal that a user is a member of their service, and information about that user's account, to that user's friends or contacts.¶
KT only allows users to learn whether or not a lookup key exists in the Transparency Log if the user obtains a valid search proof for that key. Similarly, KT only allows users to learn about the contents of a log entry if the user obtains a valid search proof for the exact key and version stored at that log entry.¶
Applications are primarily able to manage the privacy of their data in KT by relying on these properties when they enforce access control policies on the queries issued by users, as discussed in Section 3. For example if two users aren't friends, an application can block these users from searching for each other's lookup keys. This prevents the two users from learning about each other's existence. If the users were previously friends but no longer are, the application can prevent the users from searching for each other's keys and learning the contents of any subsequent account updates.¶
Service operators also expect to be able to control sensitive population-level metrics about their users. These metrics include the size of their userbase, the frequency with which new users join, and the frequency with which existing users update their keys.¶
KT allows service operators to hide the total size of their userbase from end-users and other outside observers. It also allows service operators to obscure the rate at which changes are made to the tree by padding real changes with fake ones, causing outsiders to observe a baseline constant rate of changes. Note however, that this information is not obscured from a third-party manager or auditor if one is used. Since the third-party plays a crucial role in ensuring correct operation of the log, it necessarily is able to distinguish real changes from fake ones, and therefore also the total number of real keys.¶
In the event that a third-party auditor or manager is used, there's additional information leaked to the third-party that's not visible to outsiders.¶
In the case of a third-party auditor, the auditor is able to learn the total number of distinct keys in the log. It is also able to distinguish between real and fake modifications to the tree, and keep track of when individual keys are modified. However, auditors are not able to learn the plaintext values of any keys or values. This is because keys are masked with a VRF, and values are only provided to auditors as commitments.¶
In the case of a third-party manager, the manager generally learns everything that the service operator would know. This includes the total set of plaintext keys and values and their modification history. It also includes traffic patterns, such as how often a specific key is looked up.¶
Fundamentally, KT can be thought of as guaranteeing that all the users of a service agree on the contents of a key-value database. Using this guarantee, that all users agree on a set of keys and values, to authenticate the relationship between end-user identities and the end-users of a communication service takes special care. Critically, in order to authenticate an end-user identity, it must be both unique and user-visible. However, what exactly constitutes a unique and user-visible identifier varies greatly from application to application.¶
Consider, for example, a communication service where users are uniquely identified by a fixed username, but KT has been deployed using an internal UUID as the lookup key. While the UUID might be unique, it is not user-visible. When a user attempts to lookup a contact by username, the service operator must translate the username into its UUID. Since this mapping (from username to UUID) is unauthenticated, the service operator can manipulate it to eavesdrop on conversations by returning the UUID for an account that it controls. From a security perspective, this is equivalent to not using KT at all. An example of this kind of application would be email.¶
However in other applications, the use of internal UUIDs in KT may be appropriate. For example, many applications don't have this type of fixed username and instead use their UI (underpinned internally by a UUID) to indicate to users whether a conversation is with a new person or someone they've previously contacted. The fact that the UI behaves in this way makes the UUID a user-visible identifer, even if a user may not be able to actually see it written out. An example of this kind of application would be Slack.¶
A primary end-user identity is one that is unique, user-visible, and unable to change. (Or equivalently, if it changes, it appears in the application UI as a new conversation with a new user.) A primary end-user identity should always be a lookup key in KT, with the end-user's public keys as the associated value.¶
A secondary end-user identity is one that is unique, user-visible, and able to change without being interpreted as a different account due to its association with a primary identity. Examples of this type of identity include phone numbers, or most usernames. These identities are used solely for initial user discovery, in which they're converted to a primary identity that's used by the application from then on. A secondary end-user identity should be a lookup key in KT, for the purpose of authenticating user discovery, with the primary end-user identity as the associated value.¶
While likely helpful to most common applications, the distinction between handling primary and secondary identities is not a hard-and-fast rule. Applications must be careful to ensure they fully capture the semantics of identity in their application with the key-value structure they put in KT.¶
This document has no IANA actions.¶
TODO acknowledge.¶