Distributed Software Build Assurance for Software Supply Chain Integrity

Introduction

In the quest for enhanced software supply chain integrity, the authors propose two pivotal concepts aimed at ensuring the reliability and authenticity of software products.

Key Concepts

Comprehensive Proof Creation: The first idea centers on the necessity of consolidating all essential components of the software into a single, verifiable proof. This proof includes:
- Source Code: The actual code that composes the software.
- Documentation: All relevant documentation that explains how the software operates and how to utilize it.
- Build Output and Artifacts: The results generated from the build process, which are crucial for verifying that the software is built according to its specifications.
By merging these elements into one cohesive proof, both the creator and the recipient are assured of the software's authenticity.
Independent Hosting for Verification: The second idea advocates for the storage of this comprehensive proof in an independent location. This means the proof can be verified by third parties, ensuring that it can be independently checked for legitimacy and accuracy.

Detailed Implementation

To facilitate this verification process effectively, both the software creator and the recipient will utilize a data structure called a Merkle tree. This tree structure plays a vital role in ensuring data integrity. The implementation would proceed as follows:

Collecting Data: Both parties will gather the source code, compiler output from the reproducible build process, and the necessary documentation.
Utilizing the Merkle CPP Library: Utilizing the Merkle CPP Library authored by Microsoft, they will input the collected data into their respective Merkle trees.
Balancing the Tree: After feeding the data into the Merkle trees, both parties will carry out a process known as cyclic extension to balance the trees. While the specifics of balancing may not be critical in this context, the ultimate goal is to generate a hash at the tree's root node.

The notable advantage of a Merkle tree is that it compresses extensive data into a concise hash string. This string is extremely sensitive to any alterations in the data structure, meaning that even a slight change in any part of the input will lead to a drastically different hash at the root. This quality ensures that the proof remains secure and verifiable.

Through the implementation of these two ideas, the integrity of the software supply chain can be substantially enhanced, allowing both creators and recipients to confidently validate the software they are dealing with.

Keywords

Software Supply Chain
Build Assurance
Source Code
Documentation
Build Output
Merkle Tree
Data Integrity
Verification

FAQ

Q1: What is the purpose of creating a comprehensive proof for software?
A1: The comprehensive proof serves to merge all essential components of software—source code, documentation, and build artifacts—into a single verifiable entity, ensuring its authenticity.

Q2: Why is independent hosting of the proof important?
A2: Independent hosting allows third parties to verify the proof without bias, reinforcing trust in the software's reliability and integrity.

Q3: What is a Merkle tree and why is it used in verifying software builds?
A3: A Merkle tree is a data structure that summarizes and secures large sets of data. It is used in verifying software builds because it generates a hash that is sensitive to changes in the input, ensuring data integrity.

Q4: How does the balancing of a Merkle tree contribute to verification?
A4: Balancing the Merkle tree ensures that the hash generated at the root accurately represents all underlying data, thus maintaining the integrity needed for reliable verification.

Q5: What happens if the data in the Merkle tree changes?
A5: Any change in the input data will cause a significant change in the root hash, indicating that the data integrity has been compromised, and prompting further investigation.