Detect unwanted dependencies in your software like versions of faker.js or colors.js

Last weekend the Open Source world was shaken up a bit when a developer maintaining the highly popular libraries faker.js and colors.js sabotaged both projects by breaking their function.

The supply-chain dangers from underlying open-source projects were highlighted many times in 2021, the year that ended with the Log4j disaster. But as the new year shows, it’s not just about vulnerabilities, it’s about detecting any kind of dependencies to mitigate risk if something unwanted happens to them.
This blog doesn’t comment on the reasoning of the developer and focuses on a bigger problem:

How can a developer, project manager, DevOps engineer or CISO make sure that important applications are not affected by a certain version of a dependency!

Most tools out there focus on vulnerabilities and malicious code inside applications and dependencies, but this kind of “attack” is more subtle. As a developer or application maintainer, I just want to make sure not to use a certain library or a certain version in my code.

Quick wrap up of what happened to faker and colors

A developer inserted code into two very popular open-source npm software libraries and published it on the npm package repository. The code added generated a string of characters into applications that use those libraries. The libraries are not just less-known pet projects but highly popular ones used by thousands of projects and are downloaded millions of times a week. You can read more here: Bleeping Computer

What does remediation look like?

  • Projects and software using the affected versions of colors and faker were forced to revert to older versions (and find out what version to use first) to fix their apps. (currently Colors.js 1.40 and Faker.js 5.5.3)
  • Stop new build pipelines using the affected libraries and change the code accordingly before resuming the pipelines
  • Stop using the affected version of the popular Amazon AWS’s Cloud Development Kit

The bigger issue

Despite the trouble making sure all applications are back to normal, there is a bigger issue at hand. The same scenario can happen to any Open Source library out there and instead of breaking the functions immediately, it could start at a certain time in the future, when the library is already pushed to production. Also, the Open Source license could change, or … so many other unwanted things can happen.

The only real solution here is to be on top of the dependency usage and deployment. Software Bill of Materials (SBOMs) can be a solution to that issue, but they need to be tamperproof, queryable in a fast and scalable manner, and versioned.

Codenotary Cloud and the tamper-proof, queryable dependency

Using Codenotary Cloud and the vcn command-line tool, you can send all artifacts including their SBOM (dependency list) to an immutable data structure and give it a trust level in a tamperproof and auditable way.

Notarize your artifacts including SBOM: vcn notarize –bom dir://folder or vcn notarize –bom docker://image

That is typically automated in your CI/CD pipeline or using Github actions, so you eventually have a full catalog of everything and are always up to date.

At any point in time, you can simply search by a name or a checksum to know where and when your artifact or dependency is used:

Summary

Software is never complete and the code base including its dependencies is an always updating document. That automatically means you need to track it, good and bad, keeping in mind that something good can turn bad.

And the downside of simply trusting project maintainers or digitally signed builds are getting more obvious every day. Therefore, maintaining the integrity of software supply chains will be an ongoing problem for users and vendors for the years to come.

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Use Case - Tamper-resistant Clinical Trials

Goal:

Blockchain PoCs were unsuccessful due to complexity and lack of developers.

Still the goal of data immutability as well as client verification is a crucial. Furthermore, the system needs to be easy to use and operate (allowing backup, maintenance windows aso.).

Implementation:

immudb is running in different datacenters across the globe. All clinical trial information is stored in immudb either as transactions or the pdf documents as a whole.

Having that single source of truth with versioned, timestamped, and cryptographically verifiable records, enables a whole new way of transparency and trust.

Use Case - Finance

Goal:

Store the source data, the decision and the rule base for financial support from governments timestamped, verifiable.

A very important functionality is the ability to compare the historic decision (based on the past rulebase) with the rulebase at a different date. Fully cryptographic verifiable Time Travel queries are required to be able to achieve that comparison.

Implementation:

While the source data, rulebase and the documented decision are stored in verifiable Blobs in immudb, the transaction is stored using the relational layer of immudb.

That allows the use of immudb’s time travel capabilities to retrieve verified historic data and recalculate with the most recent rulebase.

Use Case - eCommerce and NFT marketplace

Goal:

No matter if it’s an eCommerce platform or NFT marketplace, the goals are similar:

  • High amount of transactions (potentially millions a second)
  • Ability to read and write multiple records within one transaction
  • prevent overwrite or updates on transactions
  • comply with regulations (PCI, GDPR, …)


Implementation:

immudb is typically scaled out using Hyperscaler (i. e. AWS, Google Cloud, Microsoft Azure) distributed across the Globe. Auditors are also distributed to track the verification proof over time. Additionally, the shop or marketplace applications store immudb cryptographic state information. That high level of integrity and tamper-evidence while maintaining a very high transaction speed is key for companies to chose immudb.

Use Case - IoT Sensor Data

Goal:

IoT sensor data received by devices collecting environment data needs to be stored locally in a cryptographically verifiable manner until the data is transferred to a central datacenter. The data integrity needs to be verifiable at any given point in time and while in transit.

Implementation:

immudb runs embedded on the IoT device itself and is consistently audited by external probes. The data transfer to audit is minimal and works even with minimum bandwidth and unreliable connections.

Whenever the IoT devices are connected to a high bandwidth, the data transfer happens to a data center (large immudb deployment) and the source and destination date integrity is fully verified.

Use Case - DevOps Evidence

Goal:

CI/CD and application build logs need to be stored auditable and tamper-evident.
A very high Performance is required as the system should not slow down any build process.
Scalability is key as billions of artifacts are expected within the next years.
Next to a possibility of integrity validation, data needs to be retrievable by pipeline job id or digital asset checksum.

Implementation:

As part of the CI/CD audit functionality, data is stored within immudb using the Key/Value functionality. Key is either the CI/CD job id (i. e. Jenkins or GitLab) or the checksum of the resulting build or container image.

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