slsa
trivy
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slsa | trivy | |
---|---|---|
35 | 82 | |
1,422 | 21,388 | |
3.0% | 3.9% | |
8.7 | 9.8 | |
7 days ago | about 12 hours ago | |
Shell | Go | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
slsa
- SLSA – Supply-Chain Levels for Software Artifacts
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Dogbolt Decompiler Explorer
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/
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10 reasons you should quit your HTTP client
The dependency chain is certified! SLSA!
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UEFI Software Bill of Materials Proposal
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.
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Gittuf – a security layer for Git using some concepts introduced by TUF
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.
- SLSA • Supply-Chain Levels for Software Artifacts
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Password-stealing Linux malware served for 3 years and no one noticed
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/
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OSCM: The Open Source Consumption Manifesto
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.
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CLOUD SECURITY PODCAST BY GOOGLE - EP116 SBOMs: A Step Towards a More Secure Software Supply Chain -
SLSA.dev
- Supply Chain Levels for Software Artifacts (SLSA)
trivy
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A Deep Dive Into Terraform Static Code Analysis Tools: Features and Comparisons
Trivy Owner/Maintainer: Aqua Security Age: First released on GitHub on May 7th, 2019 License: Apache License 2.0 backward-compatible with tfsec
- Suas imagens de container não estão seguras!
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General Docker Troubleshooting, Best Practices & Where to Go From Here
Trivy. A Simple and Comprehensive Vulnerability Scanner for Containers.
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Distroless images using melange and apko
Using Trivy:
- Friends - needs help choosing solution for SBOM vulnerability
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An Overview of Kubernetes Security Projects at KubeCon Europe 2023
Trivy is a mature and comprehensive open source tool from Aqua Security that supports scanning multiple sources, from file systems to containers and VMs. Trivy also looks beyond vulnerabilities, to scan licenses, secrets, infrastructure as code misconfiguration, and more.
- Best vulnerability scanner for DevOps
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About Cloudflare Tunnels
I would suggest to think about the thread model that you are facing so you can have a better mental model of the weak points of your environment. The very very big majority of these attacks will be automated probing for publicly known vulnerabilities or default credentials. That means the maintainers of the software you are running and the channels on which their updates are shipped to you and deployed are very important factors. For software that is not installed from a trusted and well maintained source (e.g. Ubuntus main repository), you want to make extra sure that vulnerabilities are updated. E.g. your deployed docker containers might contain security issues, you can run checks on these with tools like trivy. The same is also true for appliances, in case your router or firewall contains a software vulnerability, how will you be notified and how will the required updates be deployed?
- Docker image vulnerabilities scanning trivy vs synk.io
What are some alternatives?
grype - A vulnerability scanner for container images and filesystems
snyk - Snyk CLI scans and monitors your projects for security vulnerabilities. [Moved to: https://github.com/snyk/cli]
ClojureDart - Clojure dialect for Flutter and Dart
DependencyCheck - OWASP dependency-check is a software composition analysis utility that detects publicly disclosed vulnerabilities in application dependencies.
clair - Vulnerability Static Analysis for Containers
sig-security - 🔐CNCF Security Technical Advisory Group -- secure access, policy control, privacy, auditing, explainability and more!
checkov - Prevent cloud misconfigurations and find vulnerabilities during build-time in infrastructure as code, container images and open source packages with Checkov by Bridgecrew.
syft - CLI tool and library for generating a Software Bill of Materials from container images and filesystems
jspolicy - jsPolicy - Easier & Faster Kubernetes Policies using JavaScript or TypeScript
falco - Cloud Native Runtime Security