slsa VS checkov

Short answer: not where it counts.

My work focuses on recognizing known functions in obfuscated binaries, but there are some papers you might want to check out related to deobfuscation, if not necessarily using ML for deobfuscation or decompilation.

My take is that ML can soundly defeat the "easy" and more static obfuscation types (encodings, control flow flattening, splitting functions). It's low hanging fruit, and it's what I worked on most, but adoption is slow. On the other hand, "hard" obfuscations like virtualized functions or programs which embed JIT compilers to obfuscate at runtime... as far as I know, those are still unsolved problems.

This is a good overview of the subject, but pretty old and doesn't cover "hard" obfuscations: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1566145.

https://www.jinyier.me/papers/DATE19_Obf.pdf uses deobfuscation for RTL logic (FGPA/ASIC domain) with SAT solvers. Might be useful for a point of view from a fairly different domain.

https://advising.cs.arizona.edu/~debray/Publications/generic... uses "semantics-preserving transformations" to shed obfuscation. I think this approach is the way to go, especially when combined with dynamic/symbolic analysis to mitigate virt/jit types of transformations.

I'll mention this one as a cautionary tale: https://dl.acm.org/doi/pdf/10.1145/2886012 has some good general info but glosses over the machine learning approach. It considers Hex-rays' FLIRT to be "machine learning", but FLIRT just hashes signatures, can be spoofed (i.e. https://siliconpr0n.org/uv/issues_with_flirt_aware_malware.p...), and is useless against obfuscation.

Eventually I think SBOM tools like Black Duck[1] and SLSA[2] will incorporate ML to improve the accuracy of even figuring out what dependencies a piece of software actually has.

[1]: https://www.synopsys.com/software-integrity/software-composi...

[2]: https://slsa.dev/

The dependency chain is certified! SLSA!

The things you mentioned are not solved by a typical "SBOM" but e.g. CycloneDX has extra fields to record provenance and pedigree and things like in-toto (https://in-toto.io/) or SLSA (https://slsa.dev/) also aim to work in this field.

I've spent the last six months in this field and people will tell you that this or that is an industry best practice or "a standard" but in my experience none of that is true. Everyone is still trying to figure out how best to protect the software supply chain security and things are still very much in flux.

It's multi-pronged and I imagine adopters may use a subset of features. Broadly, I think folks are going to be interested in a) branch/tag/reference protection rules, b) file protection rules (monorepo or otherwise, though monorepos do pose a very apt usecase for gittuf), and c) general key management for those who primarily care about Git signing.

For those who care about a and b, I think the work we want to do to support [in-toto attestations](https://github.com/in-toto/attestation) for [SLSA's upcoming source track](https://github.com/slsa-framework/slsa/issues/956) could be very interesting as well.

It doesn't have to be. Corporations which are FedRAMP[1] compliant, have to build software reproducibly in a fully isolated environment, only from reviewed code.[2]

[1] https://en.wikipedia.org/wiki/FedRAMP

[2] https://slsa.dev/

SLSA stands for Supply chain Levels for Software Artifacts, and it is a framework that aims to provide a set of best practices for the software supply chain, with a focus on OSS. It was created by Google, and it is now part of the OpenSSF. It consists of four levels of assurance, from Level 1 to Level 4, that correspond to different degrees of protection against supply chain attacks. Our CTO Paolo Mainardi mentioned SLSA in a very good article on software supply chain security, and we also mentioned it in another article about securing OCI Artifacts on Kubernetes.

SLSA.dev

1. Checkov: https://github.com/bridgecrewio/checkov Checkov is a static code analysis tool that helps developers prevent cloud misconfigurations during the development phase by scanning Terraform, CloudFormation, Kubernetes, and more.

Checkov Owner/Maintainer: Prisma Cloud by Palo Alto Networks (acquired in 2021) Age: First released on GitHub on March 31st, 2021 License: Apache License 2.0

‍Checkov is another great tool that examines your Terraform files (.tf), parsing the configurations and evaluating them against a comprehensive set of predefined policies. It scans Terraform-managed infrastructure and detects misconfigurations that could lead to security issues or non-compliance with best practices and regulations.

Bridgecrew — Infrastructure as code (IaC) security powered by the open source tool - Checkov. The core Bridgecrew platform is free for up to 50 IaC resources.

Kustomize: It provides a solution to customize the Kubernetes resource base configuration and differential configuration without template and DSL. It does not solve the constraint problem itself, but needs to cooperate with a large number of additional tools to check constraints, such as Kube-linter, Checkov and kubescape.

Checkov is a versatile static code analysis tool designed for infrastructure as code (IaC) and software composition analysis (SCA). It supports a wide range of technologies, including Terraform, CloudFormation, Kubernetes, Docker, and others, to detect security and compliance issues through graph-based scanning. Checkov also performs SCA scans, identifying vulnerabilities in open source packages and images by checking for Common Vulnerabilities and Exposures (CVEs). Additionally, it is integrated into Prisma Cloud Application Security, a platform that helps developers secure cloud resources and infrastructure-as-code files, enabling the identification, rectification, and prevention of misconfigurations throughout the development lifecycle.

For your Dockerfiles, you can also scan them. There are lots of tools that can check your Dockerfiles. They will validate if Dockerfile is compliant with Docker best practices such as not using root user, making sure a health check exists, and not exposing the SSH port. You can use Snyk and Checkov.

You could try https://www.checkov.io/

We use https://www.checkov.io/ for this, it's very simple to get started with and works really well as PR quality gate

Once there is a CI pipeline for delivering infra changes you can add static code analysis tools (checkov) and even start testing changes (terratest)