The Package Analysis Project: Scalable detection of malicious open source packages

April 28, 2022

Posted by Caleb Brown, Open Source Security Team
Despite open source software’s essential role in all software built today, it’s far too easy for bad actors to circulate malicious packages that attack the systems and users running that software. Unlike mobile app stores that can scan for and reject malicious contributions, package repositories have limited resources to review the thousands of daily updates and must maintain an open model where anyone can freely contribute. As a result, malicious packages like ua-parser-js, and node-ipc are regularly uploaded to popular repositories despite their best efforts, with sometimes devastating consequences for users.

Google, a member of the Open Source Security Foundation (OpenSSF), is proud to support the OpenSSF’s Package Analysis project, which is a welcome step toward helping secure the open source packages we all depend on. The Package Analysis program performs dynamic analysis of all packages uploaded to popular open source repositories and catalogs the results in a BigQuery table. By detecting malicious activities and alerting consumers to suspicious behavior before they select packages, this program contributes to a more secure software supply chain and greater trust in open source software. The program also gives insight into the types of malicious packages that are most common at any given time, which can guide decisions about how to better protect the ecosystem.

To better understand how the Package Analysis program is contributing to supply chain security, we analyzed the nearly 200 malicious packages it captured over a one-month period. Here’s what we discovered:
Results
All signals collected are published in our BigQuery table. Using simple queries on this table, we found around 200 meaningful results from the packages uploaded to NPM and PyPI in a period of just over a month. Here are some notable examples, with more available in the repository.
PyPI: discordcmdThis Python package will attack the desktop client for Discord on Windows. It was found by spotting the unusual requests to raw.githubusercontent.com, Discord API, and ipinfo.io.

First, it downloaded a backdoor from GitHub and installed it into the Discord electron client.

Next, it looked through various local databases for the user's Discord token.

Finally, it grabbed the data associated with the token from the Discord API and exfiltrated it back to a Discord server controlled by the attacker.
NPM: @roku-web-core/ajax
During install, this NPM package exfiltrates details of the machine it is running on and then opens a reverse shell, allowing the remote execution of commands.

This package was discovered from its requests to an attacker-controlled address.

Dependency Confusion / Typosquatting
The vast majority of the malicious packages we detected are dependency confusion and typosquatting attacks.

The packages we found usually contain a simple script that runs during an install and calls home with a few details about the host. These packages are most likely the work of security researchers looking for bug bounties, since most are not exfiltrating meaningful data except the name of the machine or a username, and they make no attempt to disguise their behavior.

These dependency confusion attacks were discovered through the domains they used, such as burpcollaborator.net, pipedream.com, interact.sh, which are commonly used for reporting back attacks. The same domains appear across unrelated packages and have no apparent connection to the packages themselves. Many packages also used unusual version numbers that were high (e.g. v5.0.0, v99.10.9) for a package with no previous versions.

Conclusions
The short time frame and low sophistication needed for finding the results above underscore the challenge facing open source package repositories. While many of the results above were likely the work of security researchers, any one of these packages could have done far more to hurt the unfortunate victims who installed them.

These results show the clear need for more investment in vetting packages being published in order to keep users safe. This is a growing space, and having an open standard for reporting would help centralize analysis results and offer consumers a trusted place to assess the packages they’re considering using. Creating an open standard should also foster healthy competition, promote integration, and raise the overall security of open source packages.
Over time we hope that the Package Analysis program will offer comprehensive knowledge about the behavior and capabilities of packages across open source software, and help guide the future efforts needed to make the ecosystem more secure for everyone. To get involved, please check out the GitHub Project and Milestones for opportunities to contribute.

How we fought bad apps and developers in 2021

April 27, 2022

Posted by Steve Kafka and Khawaja Shams, Android Security and Privacy Team Providing a safe experience to billions of users continues to be one of the highest priorities for Google Play. Last year we introduced multiple privacy focused features, enhanced our protections against bad apps and developers, and improved SDK data safety. In addition, Google Play Protect continues to scan billions of installed apps each day across billions of devices to keep people safe from malware and unwanted software. We continue to enhance our machine learning systems and review processes, and in 2021 we blocked 1.2 million policy violating apps from being published on Google Play, preventing billions of harmful installations. We also continued in our efforts to combat malicious and spammy developers, banning 190k bad accounts in 2021. In addition, we have closed around 500k developer accounts that are inactive or abandoned. In May we announced our new Data safety section for Google Play where developers will be required to give users deeper insight into the privacy and security practices of the apps they download, and provide transparency into the data the app may collect and why. The Data safety section launched this week, and developers are required to complete this section for their apps by July 20th. We’ve also invested in making life easier for our developers. We added the Policy and Programs section to Google Play Console to help developers manage all their app compliance issues in one central location. This includes the ability to appeal a decision and track its status from this page. In addition, we continued to partner with SDK developers to improve app safety, limit how user data is shared, and improve lines of communication with app developers. SDKs provide functionality for app developers, but it can sometimes be tricky to know when an SDK is safe to use. Last year, we engaged with SDK developers to build a safer Android and Google Play ecosystem. As a result of this work, SDK developers have improved the safety of SDKs used by hundreds of thousands of apps impacting billions of users. This remains a huge investment area for our team, and we will continue in our efforts to make SDKs safer across the ecosystem. Limiting access The best way to ensure users' data stays safe is to limit access to it in the first place. As a result of new platform protections and policies, developer collaboration and education, 98% of apps migrating to Android 11 or higher have reduced their access to sensitive APIs and user data. We've also significantly reduced the unnecessary, dangerous, or disallowed use of Accessibility APIs in apps migrating to Android 12, while preserving the functionality of legitimate use cases. We also continued in our commitment to make Android a great place for families. Last year we disallowed the collection of Advertising ID (AAID) and other device identifiers from all users in apps solely targeting children, and gave all users the ability to delete their Advertising ID entirely, regardless of the app. Pixel enhancements For Pixel users, we had even more great features to help keep you safe. Our new Security hub helps protect your phone, apps, Google Account, and passwords by giving you a central view of your device’s current configuration. Security hub also provides recommendations to improve your security, helping you decide what settings best meet your needs. In addition, Pixels now use new machine learning models that improve the detection of malware in Google Play Protect. The detection runs on your Pixel, and uses a privacy preserving technology called federated analytics to discover bad apps. Our global teams are dedicated to keeping our billions of users safe, and look forward to many exciting announcements in 2022.

How to SLSA Part 3 - Putting it all together

April 14, 2022

Posted by Tom Hennen, software engineer, BCID & GOSST
12

The Squirrel package ‘foo’

The Oppy package ‘baz’

A custom executable, ‘bar’, written by Acme employees.

source attestation

bar is compiled from source code stored in the same source repo as the Dockerfile.

acorn install downloads ‘foo’ from the Squirrel repo, verifying the VSA, and recording the use of acorn://foo@abc and its VSA in the build.

acme_oppy_get install (a custom script made by Acme) downloads the latest version of the Oppy ‘baz’ package and queries its SLSA provenance and other attestations from Rekor. It then performs a full verification checking that it was built by ‘https://oppy.example/slsa/builder/v1’ and the publicized key. Once verification is complete it records the use of oppy://baz@def and the associated attestations in the build.

The build process assembles the SLSA provenance for the container by:

Recording the Acme git repo the bar source and Dockerfile came from, into materials.
Copying the reported dependencies of acorn://foo@abc and oppy://baz@def into materials and adding their attestations to the output in-toto bundle.
Recording the CI/CD entrypoint as the invocation.
Creating a signed DSSE with the SLSA provenance and adding it to the output in-toto bundle.

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How to SLSA Part 2 - The Details

April 13, 2022

Posted by Tom Hennen, software engineer, BCID & GOSST
In our last post we introduced a fictional example of Squirrel, Oppy, and Acme learning to use SLSA and covered the basics of what their implementations might look like. Today we’ll cover the details: where to store attestations and policies, what policies should check, and how to handle key distribution and trust.

Attestation storage

Attestations play a large role in SLSA and it’s essential that consumers of artifacts know where to find the attestations for those artifacts.

Co-located in repo

Attestations could be colocated in the repository that hosts the artifact. This is how Squirrel plans to store attestations for packages. They even want to add support to the Squirrel CLI (e.g. acorn get-attestations foo@1.2.3).

Acme really likes this approach because the attestations are always available and it doesn’t introduce any new dependencies.
Rekor
Meanwhile, Oppy plans to store attestations in Rekor. They like being able to direct users to an existing public instance while not having to maintain any new infrastructure themselves, and the in-depth defense the transparency log provides against tampering with the attestations.

Though the latency of querying attestations from Rekor is likely too high for doing verification at time of use, Oppy isn’t too concerned since they expect users to query Rekor at install time.

Hybrid

A hybrid model is also available where the publisher stores the attestations in Rekor as well as co-located with the artifact in the repo—along with Rekor’s inclusion proof. This provides confidence the data was added to Rekor while providing the benefits of co-locating attestations in the repository.

Policy content

‘Policy’ refers to the rules used to determine if an artifact should be allowed for a use case.

Policies often use the package name as a proxy for determining the use case. An example being, if you want to find the policy to apply you could look up the policy using the package name of the artifact you’re evaluating.

Policy specifics may vary based on ease of use, availability of data, risk tolerance and more. Full verification needs more from policies than delegated verification does.

Default policy

Default policies allow admission decisions without the need to create specific policies for each package. A default policy is a way of saying “anything that doesn’t have a more specific policy must comply with this policy”.

Squirrel plans to eventually implement a default policy of “any package without a more specific policy will be accepted as long as it meets SLSA 3”, but they recognize that most packages don’t support this yet. Until they achieve critical mass they’ll have a default SLSA 0 policy (all artifacts are accepted).

While Oppy is leaving verification to their users, they’ll suggest a default policy of “any package built by ‘https://oppy.example/slsa/builder/v1’”.

Specific policy

Squirrel also plans to allow users to create policies for specific packages. For example, this policy requires that package ‘foo’ must have been built by GitHub Actions, from github.com/foo/acorn-foo, and be SLSA 4.

scope: 'acorn://foo'

target_level: SLSA_L4

allow_github_actions {

workflow: 'https://github.com/gossts/slsa-acorn/.github/workflows/builder.yml@main'

source_repo: 'https://github.com/foo/acorn-foo.git'

allow_branch: 'main'

}

Squirrel will also allow packages to create SLSA 0 policies if they’re not using SLSA compliant infrastructure.

scope: 'acorn://qux'

target_level: SLSA_L0

Policy auto generation
Squirrel has an enormous number of existing packages. It’s not feasible to get all those package maintainers to create specific policies themselves. Therefore, Squirrel plans to leverage process mining to auto generate policies for packages based on the history of the package. E.g. “The last 10 times Squirrel package foo was published it was built by GitHub Actions from github.com/foo/acorn-foo, and met SLSA 4 (this is the policy above). Let’s create a policy that requires that and send it to the maintainers to review.”
Policy add-ons

Policy evaluation could do more than just evaluate the SLSA requirements. The same policies that check SLSA requirements are well placed to check other properties that are important to organizations like “was static analysis performed”, “are there any known CVEs in this artifact”, “was integration testing successful”, etc…

Acme is really interested in some of these policy add-ons. They’d like to avoid the embarrassing situation of publishing a new container image with known CVEs. They’re not sure how to implement it yet but they’ll be on the lookout for tools that can help them do so.

Delegated policies

When using delegated verification there’s much less that actually needs to be checked and they can be hard-coded directly in tooling. A minimal delegated verification policy might be “allow if trusted-party verified this artifact (identified by digest) as <package name>”. This can be tightened further by adding requirements on the artifact & its dependencies SLSA levels (data which is available in the VSA). For example, “allow if trusted-party verified this artifact as <package name> at SLSA 3 and it doesn’t have any dependencies less than SLSA 2”.

# Delegated verification implicitly checks that the package name we're

# checking matches the VSA's subject.name field.

allow_delegated_verification {

trusted_verifier: 'https://delegatedverifier.com/slsa/v1'

minimum_level: SLSA_L3

minimum_dependency_level: SLSA_L2

}

Policy storage

When using specific, non-default, policies verifiers need to know where to find the policy they need to evaluate.

Co-located in repo

Squirrel plans to store specific policies as a property of the package in the repository. This makes them very easy for users and their tooling to find. It also allows the maintainer of the package to easily set the policy (they already have write permissions!).

A potential downside is that the write permissions are the same as for the package itself. An attacker that compromises the developer’s credentials could also change the policy. This may not be as bad as it seems. Policies are human-readable so anyone paying attention would notice that package foo’s policy now says that it can be built from github.com/not-foo/acorn-foo. Squirrel plans to notify interested parties (including the maintainer!) when the policy changes, potentially letting them “sound the alarm” if anything nefarious happens.

A similar approach is taken in a number of contact-change workflows. For example, when you change your address with your bank, the bank will send you an email (and a letter to the old address) letting you know the address has been changed. This type of notification would alert the maintainer to a potential compromise.

Squirrel would also consider requiring a second person to review any policy changes for packages with over 10,000 users.
Public canonical Git repo

Another option might be to just create a canonical git repo (e.g. github.com/slsa-framework/slsa-acorn-policies) and let people publish proposed policies there. This has the advantage of using a separate ACL control mechanism from the package repository itself, but the disadvantages of being difficult to ensure the author of the policy is actually allowed to set the policy for that package and not scaling well as the repo grows.

The approach outlined in policy auto generation could help here. Automation in the repo could just look at the last N releases of the package and determine if the proposed policy matches what’s actually been published. Proactive changes to the policy (like deciding to switch from GitHub Actions to CircleCI) would be harder to coordinate however.
Org specific repo

Acme plans to establish their own org specific repo for policy storage. This gives them a single place to store all their policies, regardless of ecosystem type, and lets them provide more specific policies for packages provided by upstream repos. Since Oppy doesn’t have any plans to provide package-specific policies this gives Acme a place to store their own policies for Oppy packages (if they ever get around to it).

Organizations can also use their policy repo to vet any upstream changes to policy and potentially add additional checks (e.g. “doesn’t have any known vulnerabilities”).

Trusted Verifier

Acme wants to use delegated verification and that relies on having trusted verifiers to make decisions for downstream users. Who are these trusted verifiers?

Public verifier

A public repo is in a great position to act as a trusted verifier for their users. Users already trust these repos and they may already be doing verification on import.

Squirrel plans to make use of this by making VSAs available for each artifact published, publicizing their verifier ID (i.e. ‘https://squirrel.example/slsa-verifier’) and the public key used to sign the VSAs. They even plan to build VSA verification directly into the Squirrel tooling, so that users can get SLSA protection by default.
Org-wide verifier

While Acme is happy to use Squirrel’s verifier (and the verification built into the tooling) they still need their own verifier so they can publish VSAs to Acme customers. So Acme plans to stand up their own verification service and publish their verifier ID (i.e. ‘https://acme.example/private-verifier’) and signing key. Acme customers can then verify the software they get from Acme.

In the future Acme could require all software used throughout the company to be verified with this verifier (instead of relying on public verifiers). They’d do the verification and generate VSAs whenever artifacts are imported into their private Artifactory instance. They could then configure this ID/key pair for use throughout Acme and be confident that any software used has been verified according to Acme policy. That’s not Acme’s highest priority at the moment, but they like having this option open to them.

Key distribution & Trust

Both full and delegated verification depend upon key distribution to the users doing the verification. Depending on the specifics and what’s getting verified this can be a difficult problem.

Org-specific keys

When using delegated verification this could be the easiest case. Squirrel can just build the key they used for delegated verification directly into the Squirrel tooling. Acme can also fairly easily configure the use of their keys through the company using existing configuration control mechanisms.

When using full verification this can be harder. If there are multiple builders that could be accepted the keys that sign the attestations need to be distributed to everyone that might use that builder. For Squirrel this would be really difficult since they plan to allow package maintainers to use whatever builder they want. How those keys get configured would be tricky just for Squirrel, and much more difficult if downstream Squirrel users wanted to do full verification of the Squirrel packages.

The situation is easier, however, for Oppy. That’s because Oppy plans to only accept artifacts built by their autobuilder network. Oppy can configure this network to use a single (or small set) of keys and then publish those keys (and the SLSA level Oppy believes it meets) for downstream users.

Fulcio

Squirrel plans to solve the problem of which keys they accept by leveraging Fulcio. Squirrel will build support for Fulcio root keys into their verifier and then express which Fulcio subject is allowed to sign attestations in the specific policy of each package. E.g. “Squirrel package ‘foo’ must have been built & signed by ‘spiffe://foobar.com/foo-builder, from github.com/foo/acorn-foo, and be SLSA 4”.

scope: 'acorn://foo'

target_level: SLSA_L4

allow_fulcio_builder {

id: 'spiffe://foobar.com/foo-builder'

source_repo: 'https://github.com/foo/acorn-foo.git'

allow_branch: 'main'

allow_entrypoint: 'package.json'

}

The Update Framework (TUF)

The above methods could be further enhanced with TUF to allow the secure maintenance of keys. TUF metadata could include all the SLSA keys, the build services and other entities they’re valid for, and the SLSA levels they’re qualified at. Oppy is considering using TUF to let verifiers securely fetch and update keys used by the Autobuilder network. Oppy would use a TUF delegation to indicate that these keys should only be used for the builder id ‘https://oppy.example/slsa/builder/v1’. Squirrel might do something similar to allow for updating the Fulcio key in its tooling.

Recording & verifying dependencies

Acme wants to record and verify the dependencies that go into its container into the SLSA provenance. Acme would prefer that this functionality were just built-in their build service, but that feature isn’t available yet. Instead they’ll need to do something themselves. They have a few options at their disposal:

Tool wrappers

Since Oppy doesn’t build SLSA into it’s tooling Acme will create wrapper scripts for dependency import/installation that record and verify (using cosign) dependencies as they’re installed. Acme will update their build scripts to replace all instances of Oppy package installation with the wrapper script and then use the recorded results to help populate the materials section of the provenance.

A downside is that this approach, if run in the build itself, is not guaranteed to be complete and cannot meet the “non-falsifiable” requirement (since the results reported by the wrapper could be falsified by the build process), relegating this approach to SLSA 2. Still, it allows Acme to make progress SLSA-fying their builds and provides a starting point for achieving higher SLSA levels.
Built into ecosystem tooling

Since Squirrel does build verification into their tooling, Acme can just use acorn install to verify the dependencies and record what was installed. Acme can use this information to populate the Squirrel packages installed in the materials section of the provenance and it can include the attestations of those dependencies in the in-toto bundle for their container image.

As with tool wrappers, if this method is used in the build itself it cannot meet “non-falsifiable” requirement.

Proxied verification

Acme considered creating a proxy for their existing builder to proxy outbound connections. This proxy could verify everything fetched and use its logs to populate the provenance. Since this proxy is trusted it would be easier to meet “non-falsifiable” requirement. Unfortunately it’s also a lot of work for Acme so they’re going to defer this idea for now.

Next time

In the first two parts of this series, we’ve covered the basics of getting started with SLSA and the details of policy and provenance storage, policy verification, and key handling. In our next post we’ll cover how Squirrel, Oppy, and Acme put this all together to protect a heterogeneous supply chain.

How to SLSA Part 1 - The Basics

April 12, 2022

Posted by Tom Hennen, Software Engineer, BCID & GOSST
Supply-chain Levels for Software Artifacts

How and when do you verify a package with SLSA?

How to handle artifacts without provenance?

Where is the provenance stored?

Where is the appropriate policy stored and who should verify it?

What should the policies check?

How do you establish trust & distribute keys?

What does a secure, heterogeneous supply chain look like?

The Situation

The Squirrel package ‘foo’

The Oppy package ‘baz’

A custom executable, ‘bar’, written by Acme employees

Basics

In order to SLSA, Squirrel, Oppy, and Acme will all need SLSA capable build services. Squirrel wants to give their maintainers wide latitude to pick a builder service of their own. To support this, Squirrel will qualify some build services at specific SLSA levels (meaning they can produce artifacts up to that level). To start, Squirrel plans to qualify GitHub Actions using an approach like this, and hopes it can achieve SLSA 4 (pending the result of an independent audit). They’re also willing to qualify other build services as needed. Oppy on the other hand, doesn’t need to support arbitrary build services. They plan to have everyone use their Autobuilder network which they hope to qualify at SLSA 4 (they’ll conduct the audit/certification themselves). Finally, Acme plans to use Google Cloud Build which they’ll self-certify at SLSA 4 (pending the result of a Google-conducted audit).

Squirrel, Oppy, and Acme will follow a similar qualification process for the source control systems they plan to support.

Verification options

Full verification

At some point, one or more of the organizations will need to do full verification of each artifact to determine if it is acceptable for a given use case. This is accomplished by checking if the artifact meets the appropriate policy.

Typically, full verification would take place with SLSA provenance, source attestations, and perhaps other specialized attestations (like vulnerability scan results). While having to coordinate this data for all of its dependencies seems like a lot of work to Acme, they’re prepared to do full verification if Squirrel and Oppy are unable to.
Delegated verification

When Acme isn’t using full verification, they can instead use delegated verification where they check if an artifact is acceptable for a use case by checking if some other trusted party who performed a full verification (such as Squirrel or Oppy) believes the artifact is acceptable.

Delegated verification is easier to perform quickly with limited data and network connectivity. It may also be easier for some users who value if someone they trust verified the artifact is good.

Squirrel likes how easy delegated verification would make things for their users and plans to support it by creating a Verification Summary Attestation (VSA) when they perform full verification.

When to verify

Verification (full or delegated) could happen at a number of different times.

On import to repo

Squirrel plans to perform full verification when an artifact is published to their repo. This will ensure that packages in the repo have met their corresponding policy. It’s also helpful because all the required data can be gathered when latency isn’t critical.

If this were the only time verification is performed, it would put the repository's storage in the trusted computing base (TCB) of its users. Squirrel’s plans to use delegated verification (and issue VSAs) can prevent this. The signature on the VSA will prevent the artifacts from being tampered with while sitting in storage, even if they’re just SLSA 0. Downstream users will just need to verify the VSA.

Acme also wants to do some sort of verification on the import to their internal repo since it simplifies their security story. They’re not quite sure what this will look like yet.

On install

Acme also wants to do verification when an artifact is actually installed since it can remove a number of intermediaries from their TCB (their repo, the network, upstream storage systems).

If they perform full verification at install then they must gather all the required information. That could be a lot of data, but it might be simplified by gathering the data from external sources and caching it in their internal repo. A larger problem is that it requires Acme to have established trust in all parties that produced that information (e.g. every builder of every package). For a complex supply chain that may be difficult.

If Acme performs delegated verification, they only need the VSA for the packages being installed and to explicitly trust a handful of parties. This allows the complex full verification to be performed once while allowing all users of that package to perform a much simpler operation.

Given these tradeoffs Acme prefers delegated verification at install time. Squirrel also really likes the idea and plans to build install time verification directly into the Squirrel tool.
On use
Verification could also take place each time an artifact is actually used. In this model, latency and reliability are very important (a sudden increase in site traffic may necessitate a scaling operation launching many new jobs).

Time of use verification allows the most context with which decisions can be made (“is this job allowed to run this code and is it free from vulns right now?”). It also allows policy changes to affect already built & installed software (which may or may not be desirable).

Acme wants their users to be able to verify on use without too many dependencies so they plan to provide VSAs users can use to perform delegated verification when they start the container (perhaps using something like Kyverno).

How to handle artifacts without provenance?

Inevitably a build or system may require that an artifact without ‘original’ provenance is used. In these cases it may be desirable for the importer to generate provenance that details where it got this artifact. For example, this generated provenance shows that http://example.com/foo.tgz with sha256:abc was imported by ‘auto-importer’:

Such an artifact would likely not be accepted at higher SLSA levels, but the provenance can be used to: 1) prevent tampering with the artifact after it’s been imported and 2) be a data point for future analysis (e.g. should we prioritize asking for foo.tgz to be distributed with native SLSA provenance?).

Acme might be interested in taking this approach at some point, but they don’t need it at the moment.

Next time

In our next post we’ll cover specific approaches that can be used to answer questions like “where should attestations and policies be stored?” and “how do I trust the attestations that I receive?”

Improving software supply chain security with tamper-proof builds

April 7, 2022

Posted by Asra Ali and Laurent Simon, Google Open Source Security Team (GOSST)
use malicious source filesinject malicious artifactsupload malicious artifactsTekton ChainsGitHub Actions workflowsSigstore’sSLSA 3

Provenance

SLSA ("Supply-chain Levels for Software Artifacts”) is a framework to help improve the integrity of your project throughout its development cycle, allowing consumers to trace the final piece of software you release all the way back to the source. Achieving a high SLSA level helps to improve the trust that your artifacts are what you say they are.

This blog post focuses on build provenance, which gives users important information about the build: who performed the release process? Was the build artifact protected against malicious tampering? Source provenance describes how the source code was protected, which we’ll cover in future blog posts, so stay tuned.

Go prototype to generate non-forgeable build provenance

To create tamperless evidence of the build and allow consumer verification, you need to:

Isolate the provenance generation from the build process;
Isolate against maintainers interfering in the workflow;
Provide a mechanism to identify the builder during provenance verification.

The full isolation described in the first two points allows consumers to trust that the provenance was faithfully recorded; entities that provide this guarantee are called trusted builders.

Our Go prototype solves all three challenges. It also includes running the build inside the trusted builder, which provides a strong guarantee that the build achieves SLSA 3’s ephemeral and isolated requirement.

How does it work?

The following steps create the trusted builder that is necessary to generate provenance in isolation from the build and maintainer’s interference.

Step One: Create a reusable workflow on GitHub runners

Leveraging GitHub’s reusable workflows provides the isolation mechanism from both maintainers’ caller workflows and from the build process. Within the workflow, Github Actions creates fresh instances of virtual machines (VMs), called runners, for each job. These separate VMs give the necessary isolation for a trusted builder, so that different VMs compile the project and generate and sign the SLSA provenance (see diagram below).

Running the workflow on GitHub-hosted runners gives the guarantee that the code run is in fact the intended workflow, which self-hosted runners do not. This prototype relies on GitHub to run the exact code defined in the workflow.

The reusable workflow also protects against possible interference from maintainers, who could otherwise try to define the workflow in a way that interferes with the builder. The only way to interact with a reusable workflow is through the input parameters it exposes to the calling workflow, which stops maintainers from altering information via environment variables, steps, services and defaults.

To protect against the possibility of one job (e.g. the build step) tampering with the other artifacts used by another job (the provenance step), this approach uses a trusted channel to protect the integrity of the data. We use job outputs to send hashes (due to size limitations) and then use the hashes to verify the binary received via the untrusted artifact registry.

Step 2: Use OpenID Connect (OIDC) to prove the identity of the workflow to an external service (Sigstore)

OpenID Connect (OIDC) is a standard used across the web for identity providers (e.g., Google) to attest to the identity of a user for a third party. GitHub now supports OIDC in their workflows. Each time a workflow is run, a runner can mint a unique JWT token from GitHub’s OIDC provider. The token contains verifiable information of the workflow identity, including the caller repository, commit hash, trigger, and the current (reuseable) workflow path and reference.

Using OIDC, the workflow proves its identity to Sigstore's Fulcio root Certificate Authority, which acts as an external verification service. Fulcio signs a short-lived certificate attesting to an ephemeral signing key generated in the runner and tying it to the workload identity. A record of signing the provenance is kept in Sigstore’s transparency log Rekor. Users can use the signing certificate as a trust anchor to verify that the provenance was authenticated and non-forgeable; it must have been created inside the trusted builder.

Verification

The consumer can verify the artifact and its signed provenance with these steps:

Look up the corresponding Rekor log entry and verify the signature;
Verify the trusted builder identity by extracting it from the signing certificate;
Check that the provenance information matches the expected source and build.

See an example in action in the official repository.

Performing these steps guarantees to the consumer that the binary was produced in the trusted builder at a given commit hash attested to in the provenance. They can trust that the information in the provenance was non-forgeable, allowing them to trust the build “recipe” and trace their artifact verifiably back to the source.

Extra Bonus: Keyless signing

One extra benefit of this method is that maintainers don’t need to manage or distribute cryptographic keys for signing, avoiding the notoriously difficult problem of key management. The OIDC protocol requires no hardcoded, long-term secrets be stored in GitHub's secrets, which sidesteps the potential problem of key mismanagement invalidating the SLSA provenance. Consumers simply use OIDC to verify that the binary artifact was built from a trusted builder that produced the expected provenance.

Next Steps

Utilizing the SLSA framework is a proven way for ensuring software supply-chain integrity at scale. This prototype shows that achieving high SLSA levels is easier than ever thanks to the newest features of popular CI/CD systems and open-source tooling. Increased adoption of tamper-safe (SLSA 3+) build services will contribute to a stronger open-source ecosystem and help close one easily exploited gap in the current supply chain.

We encourage testing and adoption and welcome any improvements to the project. Please share feedback, comments and suggestions at slsa-github-generator-go and slsa-verifier project repositories. We will officially release v1 in a few weeks!

In follow-up posts, we will demonstrate adding non-forgeable source provenance attesting to secure repository settings, and showcase the same techniques for other build toolchains and package managers, etc. Stay tuned!

Find and $eek! Increased rewards for Google Nest & Fitbit devices

April 5, 2022

Posted by Medha Jain, Program Manager, Devices & Services Security
Google Nest security commitmentssmart homewearablesBug HuntersBonus!
We are paying higher rewards retroactively for eligible Google Nest and Fitbit devices reports submitted in 2021. And, starting today, for the next six months, will double the reward amount for all new eligible reports applicable to Google Nest & Fitbit devices in scope.

We will continue to take reports on our web applications, services, and mobile apps at their existing reward levels. Please keep those coming!

An enhanced rewards program
Building on our previous programs to improve devices' embedded security posture, we’re bringing all our first-party devices under a single program, starting with Google Nest, Fitbit, and Pixel.
This program extends the Android Security Reward Program, making it easier for researchers to submit a vulnerability in first-party devices and improving consistency across our severity assignments. Refer to the Android and Google Devices Security Reward Program for more details.

What interests us?
We encourage researchers to report firmware, system software, and hardware vulnerabilities. Our wide diversity of platforms provides researchers with a smorgasbord of environments to explore.

What's next?
We will be at the Hardwear.io conference this year! The VRP team is looking forward to meeting our security peers in person. We’ll be talking about the architecture of a couple of our devices, hoping to give security researchers a head start in finding vulnerabilities. We’ll have plenty of swag, too!

We will continue to enhance the researchers' experience and participation. We intend to add training documentations and target areas that interest us as we grow the program.

A huge thanks to Sarah Jacobus, Adam Bacchus, Ankur Chakraborty, Eduardo' Vela" <Nava>, Jay Cox, and Nic Watson.