Trillian: General Transparency

• Overview
• Support
• Using the Code
  • MySQL Setup
  • Integration Tests
• Working on the Code
  • Rebuilding Generated Code
  • Updating Dependencies
  • Running Codebase Checks
• Design
  • Design Overview
  • Personalities
  • Log Mode
• Use Cases
  • Certificate Transparency Log

Overview

Trillian is an implementation of the concepts described in the Verifiable Data Structures white paper, which in turn is an extension and generalisation of the ideas which underpin Certificate Transparency.

Trillian implements a Merkle tree whose contents are served from a data storage layer, to allow scalability to extremely large trees. On top of this Merkle tree, Trillian provides the following:

• An append-only Log mode, analogous to the original Certificate Transparency logs. In this mode, the Merkle tree is effectively filled up from the left, giving a dense Merkle tree.

Note that Trillian requires particular applications to provide their own personalities on top of the core transparent data store functionality.

Certificate Transparency (CT) is the most well-known and widely deployed transparency application, and an implementation of CT as a Trillian personality is available in the certificate-transparency-go repo.

Other examples of Trillian personalities are available in the trillian-examples repo.

Support

• Mailing list: https://groups.google.com/forum/#!forum/trillian-transparency
• Slack: https://transparency-dev.slack.com/ (invitation)

Using the Code

The Trillian codebase is stable and is used in production by multiple organizations, including many large-scale Certificate Transparency log operators.

Given this, we do not plan to add any new features to this version of Trillian, and will try to avoid any further incompatible code and schema changes but cannot guarantee that they will never be necessary.

The current state of feature implementation is recorded in the Feature implementation matrix.

To build and test Trillian you need:

• Go 1.22 or later (go 1.22 matches cloudbuild, and is preferred for developers that will be submitting PRs to this project).

To run many of the tests (and production deployment) you need:

• MySQL or MariaDB to provide the data storage layer; see the MySQL Setup section.

Note that this repository uses Go modules to manage dependencies; Go will fetch and install them automatically upon build/test.

To fetch the code, dependencies, and build Trillian, run the following:

git clone https://github.com/google/trillian.git
cd trillian

go build ./...

To build slimmer Trillian binaries that only include the storage and quota implementations that you need, consider specifying build tags.

To build and run tests, use:

go test ./...

The repository also includes multi-process integration tests, described in the Integration Tests section below.

MySQL Setup

To run Trillian's integration tests you need to have an instance of MySQL running and configured to:

• listen on the standard MySQL port 3306 (so mysql --host=127.0.0.1 --port=3306 connects OK)
• not require a password for the root user

You can then set up the expected tables in a test database like so:

./scripts/resetdb.sh
Warning: about to destroy and reset database 'test'
Are you sure? y
> Resetting DB...
> Reset Complete

Integration Tests

Trillian includes an integration test suite to confirm basic end-to-end functionality, which can be run with:

./integration/integration_test.sh

This runs a multi-process test:

• A test that starts a Trillian server in Log mode, together with a signer, logs many leaves, and checks they are integrated correctly.

Deployment

You can find instructions on how to deploy Trillian in deployment and examples/deployment directories.

Working on the Code

Developers who want to make changes to the Trillian codebase need some additional dependencies and tools, described in the following sections. The Cloud Build configuration and the scripts it depends on are also a useful reference for the required tools and scripts, as it may be more up-to-date than this document.

Anyone wanting to add a new storage and/or quota implementation should understand how Trillian uses build tags.

Rebuilding Generated Code

Some of the Trillian Go code is autogenerated from other files:

• gRPC message structures are originally provided as protocol buffer message definitions. See also, https://grpc.io/docs/protoc-installation/.
• Some unit tests use mock implementations of interfaces; these are created from the real implementations by GoMock.
• Some enums have string-conversion methods (satisfying the fmt.Stringer interface) created using the stringer tool (go get golang.org/x/tools/cmd/stringer).

Re-generating mock or protobuffer files is only needed if you're changing the original files. The recommended way to do this is by using the Docker image used by the Cloud Build:

docker build -f ./integration/cloudbuild/testbase/Dockerfile -t trillian-builder .
docker run -it --mount type=bind,src="$(pwd)",target=/src trillian-builder /bin/bash -c "cd /src; ./scripts/install_deps.sh; go generate -x ./..."

These commands first create a docker image from the Dockerfile in this repo, and then launch a container based on this image with the local directory mounted. The correct versions of the tools are determined using the go.mod file in this repo, and these tools are installed. Finally, all of the generated files are regenerated and Docker exits.

Alternatively, you can install the prerequisites locally:

• a series of tools, using go install to ensure that the versions are compatible and tested:

  cd $(go list -f '{{ .Dir }}' github.com/google/trillian); \
  go install github.com/golang/mock/mockgen; \
  go install google.golang.org/protobuf/proto; \
  go install google.golang.org/protobuf/cmd/protoc-gen-go; \
  go install google.golang.org/grpc/cmd/protoc-gen-go-grpc; \
  go install github.com/pseudomuto/protoc-gen-doc/cmd/protoc-gen-doc; \
  go install golang.org/x/tools/cmd/stringer
  

and run the following:

go generate -x ./...  # hunts for //go:generate comments and runs them

Updating Dependencies

The Trillian codebase uses go.mod to declare fixed versions of its dependencies. With Go modules, updating a dependency simply involves running go get:

go get package/path       # Fetch the latest published version
go get package/path@X.Y.Z # Fetch a specific published version
go get package/path@HEAD  # Fetch the latest commit 

To update ALL dependencies to the latest version run go get -u. Be warned however, that this may undo any selected versions that resolve issues in other non-module repos.

While running go build and go test, go will add any ambiguous transitive dependencies to go.mod To clean these up run:

go mod tidy

Running Codebase Checks

The scripts/presubmit.sh script runs various tools and tests over the codebase.

Install golangci-lint.

go install github.com/golangci/golangci-lint/cmd/golangci-lint@v1.55.1

Run code generation, build, test and linters

./scripts/presubmit.sh

Or just run the linters alone

golangci-lint run

Design

Design Overview

Trillian is primarily implemented as a gRPC service; this service receives get/set requests over gRPC and retrieves the corresponding Merkle tree data from a separate storage layer (currently using MySQL), ensuring that the cryptographic properties of the tree are preserved along the way.

The Trillian service is multi-tenanted – a single Trillian installation can support multiple Merkle trees in parallel, distinguished by their TreeId – and each tree operates in one of two modes:

• Log mode: an append-only collection of items; this has two sub-modes:
  • normal Log mode, where the Trillian service assigns sequence numbers to new tree entries as they arrive
  • 'preordered' Log mode, where the unique sequence number for entries in the Merkle tree is externally specified

In either case, Trillian's key transparency property is that cryptographic proofs of inclusion/consistency are available for data items added to the service.

Personalities

To build a complete transparent application, the Trillian core service needs to be paired with additional code, known as a personality, that provides functionality that is specific to the particular application.

In particular, the personality is responsible for:

• Admission Criteria – ensuring that submissions comply with the overall purpose of the application.
• Canonicalization – ensuring that equivalent versions of the same data get the same canonical identifier, so they can be de-duplicated by the Trillian core service.
• External Interface – providing an API for external users, including any practical constraints (ACLs, load-balancing, DoS protection, etc.)

This is described in more detail in a separate document. General design considerations for transparent Log applications are also discussed separately.

Log Mode

When running in Log mode, Trillian provides a gRPC API whose operations are similar to those available for Certificate Transparency logs (cf. RFC 6962). These include:

• GetLatestSignedLogRoot returns information about the current root of the Merkle tree for the log, including the tree size, hash value, timestamp and signature.
• GetLeavesByRange returns leaf information for particular leaves, specified by their index in the log.
• QueueLeaf requests inclusion of the specified item into the log.
  • For a pre-ordered log, AddSequencedLeaves requests the inclusion of specified items into the log at specified places in the tree.
• GetInclusionProof, GetInclusionProofByHash and GetConsistencyProof return inclusion and consistency proof data.

In Log mode (whether normal or pre-ordered), Trillian includes an additional Signer component; this component periodically processes pending items and adds them to the Merkle tree, creating a new signed tree head as a result.

(Note that each of the components in this diagram can be distributed, for scalability and resilience.)

Use Cases

Certificate Transparency Log

The most obvious application for Trillian in Log mode is to provide a Certificate Transparency (RFC 6962) Log. To do this, the CT Log personality needs to include all of the certificate-specific processing – in particular, checking that an item that has been suggested for inclusion is indeed a valid certificate that chains to an accepted root.