Using git as a database is a seductive idea. You get version history for free. Pull requests give you a review workflow. It’s distributed by design. GitHub will host it for free. Everyone already knows how to use it. Package managers keep falling for this. And it keeps not working out. ## Cargo The crates.io index started as a git repository. Every Cargo client cloned it. This worked fine when the registry was small, but the index kept growing. Users would see progress bars like “Resolving deltas: 74.01%, (64415/95919)” hanging for ages, the visible symptom of Cargo’s libgit2 library grinding through delta resolution on a repository with thousands of historic commits. The problem was worst in CI. Stateless environments would download the full index, use a tiny fraction of it, and throw it away. Every build, every time. RFC 2789 introduced a sparse HTTP protocol. Instead of cloning the whole index, Cargo now fetches files directly over HTTPS, downloading only the metadata for dependencies your project actually uses. (This is the “full index replication vs on-demand queries” tradeoff in action.) By April 2025, 99% of crates.io requests came from Cargo versions where sparse is the default. The git index still exists, still growing by thousands of commits per day, but most users never touch it. ## Homebrew GitHub explicitly asked Homebrew to stop using shallow clones. Updating them was “an extremely expensive operation” due to the tree layout and traffic of homebrew-core and homebrew-cask. Users were downloading 331MB just to unshallow homebrew-core. The .git folder approached 1GB on some machines. Every `brew update` meant waiting for git to grind through delta resolution. Homebrew 4.0.0 in February 2023 switched to JSON downloads for tap updates. The reasoning was blunt: “they are expensive to git fetch and git clone and GitHub would rather we didn’t do that… they are slow to git fetch and git clone and this provides a bad experience to end users.” Auto-updates now run every 24 hours instead of every 5 minutes, and they’re much faster because there’s no git fetch involved. ## CocoaPods CocoaPods is the package manager for iOS and macOS development. It hit the limits hard. The Specs repo grew to hundreds of thousands of podspecs across a deeply nested directory structure. Cloning took minutes. Updating took minutes. CI time vanished into git operations. GitHub imposed CPU rate limits. The culprit was shallow clones, which force GitHub’s servers to compute which objects the client already has. The team tried various band-aids: stopping auto-fetch on `pod install`, converting shallow clones to full clones, sharding the repository. The CocoaPods blog captured it well: “Git was invented at a time when ‘slow network’ and ‘no backups’ were legitimate design concerns. Running endless builds as part of continuous integration wasn’t commonplace.” CocoaPods 1.8 gave up on git entirely for most users. A CDN became the default, serving podspec files directly over HTTP. The migration saved users about a gigabyte of disk space and made `pod install` nearly instant for new setups. ## Go modules Grab’s engineering team went from 18 minutes for `go get` to 12 seconds after deploying a module proxy. That’s not a typo. Eighteen minutes down to twelve seconds. The problem was that `go get` needed to fetch each dependency’s source code just to read its go.mod file and resolve transitive dependencies. Cloning entire repositories to get a single file. Go had security concerns too. The original design wanted to remove version control tools entirely because “these fragment the ecosystem: packages developed using Bazaar or Fossil, for example, are effectively unavailable to users who cannot or choose not to install these tools.” Beyond fragmentation, the Go team worried about security bugs in version control systems becoming security bugs in `go get`. You’re not just importing code; you’re importing the attack surface of every VCS tool on the developer’s machine. GOPROXY became the default in Go 1.13. The proxy serves source archives and go.mod files independently over HTTP. Go also introduced a checksum database (sumdb) that records cryptographic hashes of module contents. This protects against force pushes silently changing tagged releases, and ensures modules remain available even if the original repository is deleted. ## Beyond package managers The same pattern shows up wherever developers try to use git as a database. Git-based wikis like Gollum (used by GitHub and GitLab) become “somewhat too slow to be usable” at scale. Browsing directory structure takes seconds per click. Loading pages takes longer. GitLab plans to move away from Gollum entirely. Git-based CMS platforms like Decap hit GitHub’s API rate limits. A Decap project on GitHub scales to about 10,000 entries if you have a lot of collection relations. A new user with an empty cache makes a request per entry to populate it, burning through the 5,000 request limit quickly. If your site has lots of content or updates frequently, use a database instead. Even GitOps tools that embrace git as a source of truth have to work around its limitations. ArgoCD’s repo server can run out of disk space cloning repositories. A single commit invalidates the cache for all applications in that repo. Large monorepos need special scaling considerations. ## The pattern The hosting problems are symptoms. The underlying issue is that git inherits filesystem limitations, and filesystems make terrible databases. **Directory limits.** Directories with too many files become slow. CocoaPods had 16,000 pod directories in a single Specs folder, requiring huge tree objects and expensive computation. Their fix was hash-based sharding: split directories by the first few characters of a hashed name, so no single directory has too many entries. Git itself does this internally with its objects folder, splitting into 256 subdirectories. You’re reinventing B-trees, badly. **Case sensitivity.** Git is case-sensitive, but macOS and Windows filesystems typically aren’t. Check out a repo containing both `File.txt` and `file.txt` on Windows, and the second overwrites the first. Azure DevOps had to add server-side enforcement to block pushes with case-conflicting paths. **Path length limits.** Windows restricts paths to 260 characters, a constraint dating back to DOS. Git supports longer paths, but Git for Windows inherits the OS limitation. This is painful with deeply nested node_modules directories, where `git status` fails with “Filename too long” errors. **Missing database features.** Databases have CHECK constraints and UNIQUE constraints; git has nothing, so every package manager builds its own validation layer. Databases have locking; git doesn’t. Databases have indexes for queries like “all packages depending on X”; with git you either traverse every file or build your own index. Databases have migrations for schema changes; git has “rewrite history and force everyone to re-clone.” The progression is predictable. Start with a flat directory of files. Hit filesystem limits. Implement sharding. Hit cross-platform issues. Build server-side enforcement. Build custom indexes. Eventually give up and use HTTP or an actual database. You’ve built a worse version of what databases already provide, spread across git hooks, CI pipelines, and bespoke tooling. None of this means git is bad. Git excels at what it was designed for: distributed collaboration on source code, with branching, merging, and offline work. The problem is using it for something else entirely. Package registries need fast point queries for metadata. Git gives you a full-document sync protocol when you need a key-value lookup. If you’re building a package manager and git-as-index seems appealing, look at Cargo, Homebrew, CocoaPods, Go. They all had to build workarounds as they grew, causing pain for users and maintainers. The pull request workflow is nice. The version history is nice. You will hit the same walls they did.

Instant database clones with PostgreSQL 18 (boringsql.com) 15:58  ↑ 114 HN Points

After putting together ecosyste-ms/package-manager-resolvers, I started wondering what dependency resolution algorithm GitHub Actions uses. When you write `uses: actions/checkout@v4` in a workflow file, you’re declaring a dependency. GitHub resolves it, downloads it, and executes it. That’s package management. So I went spelunking into the runner codebase to see how it works. What I found was concerning. Package managers are a critical part of software supply chain security. The industry has spent years hardening them after incidents like left-pad, event-stream, and countless others. Lockfiles, integrity hashes, and dependency visibility aren’t optional extras. They’re the baseline. GitHub Actions ignores all of it. Compared to mature package ecosystems: Feature | npm | Cargo | NuGet | Bundler | Go | Actions ---|---|---|---|---|---|--- Lockfile | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ Transitive pinning | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ Integrity hashes | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ Dependency tree visibility | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ Resolution specification | ✓ | ✓ | ✓ | ✓ | ✓ | ✗ The core problem is the lack of a lockfile. Every other package manager figured this out decades ago: you declare loose constraints in a manifest, the resolver picks specific versions, and the lockfile records exactly what was chosen. GitHub Actions has no equivalent. Every run re-resolves from your workflow file, and the results can change without any modification to your code. Research from USENIX Security 2022 analyzed over 200,000 repositories and found that 99.7% execute externally developed Actions, 97% use Actions from unverified creators, and 18% run Actions with missing security updates. The researchers identified four fundamental security properties that CI/CD systems need: admittance control, execution control, code control, and access to secrets. GitHub Actions fails to provide adequate tooling for any of them. A follow-up study using static taint analysis found code injection vulnerabilities in over 4,300 workflows across 2.7 million analyzed. Nearly every GitHub Actions user is running third-party code with no verification, no lockfile, and no visibility into what that code depends on. **Mutable versions.** When you pin to `actions/checkout@v4`, that tag can move. The maintainer can push a new commit and retag. Your workflow changes silently. A lockfile would record the SHA that `@v4` resolved to, giving you reproducibility while keeping version tags readable. Instead, you have to choose: readable tags with no stability, or unreadable SHAs with no automated update path. GitHub has added mitigations. Immutable releases lock a release’s git tag after publication. Organizations can enforce SHA pinning as a policy. You can limit workflows to actions from verified creators. These help, but they only address the top-level dependency. They do nothing for transitive dependencies, which is the primary attack vector. **Invisible transitive dependencies.** SHA pinning doesn’t solve this. Composite actions resolve their own dependencies, but you can’t see or control what they pull in. When you pin an action to a SHA, you only lock the outer file. If it internally pulls `some-helper@v1` with a mutable tag, your workflow is still vulnerable. You have zero visibility into this. A lockfile would record the entire resolved tree, making transitive dependencies visible and pinnable. Research on JavaScript Actions found that 54% contain at least one security weakness, with most vulnerabilities coming from indirect dependencies. The tj-actions/changed-files incident showed how this plays out in practice: a compromised action updated its transitive dependencies to exfiltrate secrets. With a lockfile, the unexpected transitive change would have been visible in a diff. **No integrity verification.** npm records `integrity` hashes in the lockfile. Cargo records checksums in `Cargo.lock`. When you install, the package manager verifies the download matches what was recorded. Actions has nothing. You trust GitHub to give you the right code for a SHA. A lockfile with integrity hashes would let you verify that what you’re running matches what you resolved. **Re-runs aren’t reproducible.** GitHub staff have confirmed this explicitly: “if the workflow uses some actions at a version, if that version was force pushed/updated, we will be fetching the latest version there.” A failed job re-run can silently get different code than the original run. Cache interaction makes it worse: caches only save on successful jobs, so a re-run after a force-push gets different code _and_ has to rebuild the cache. Two sources of non-determinism compounding. A lockfile would make re-runs deterministic: same lockfile, same code, every time. **No dependency tree visibility.** npm has `npm ls`. Cargo has `cargo tree`. You can inspect your full dependency graph, find duplicates, trace how a transitive dependency got pulled in. Actions gives you nothing. You can’t see what your workflow actually depends on without manually reading every composite action’s source. A lockfile would be a complete manifest of your dependency tree. **Undocumented resolution semantics.** Every package manager documents how dependency resolution works. npm has a spec. Cargo has a spec. Actions resolution is undocumented. The runner source is public, and the entire “resolution algorithm” is in ActionManager.cs. Here’s a simplified version of what it does: // Simplified from actions/runner ActionManager.cs async Task PrepareActionsAsync(steps) { // Start fresh every time - no caching DeleteDirectory("_work/_actions"); await PrepareActionsRecursiveAsync(steps, depth: 0); } async Task PrepareActionsRecursiveAsync(actions, depth) { if (depth > 10) throw new Exception("Composite action depth exceeded max depth 10"); foreach (var action in actions) { // Resolution happens on GitHub's server - opaque to us var downloadInfo = await GetDownloadInfoFromGitHub(action.Reference); // Download and extract - no integrity verification var tarball = await Download(downloadInfo.TarballUrl); Extract(tarball, $"_actions/{action.Owner}/{action.Repo}/{downloadInfo.Sha}"); // If composite, recurse into its dependencies var actionYml = Parse($"_actions/{action.Owner}/{action.Repo}/{downloadInfo.Sha}/action.yml"); if (actionYml.Type == "composite") { // These nested actions may use mutable tags - we have no control await PrepareActionsRecursiveAsync(actionYml.Steps, depth + 1); } } } That’s it. No version constraints, no deduplication (the same action referenced twice gets downloaded twice), no integrity checks. The tarball URL comes from GitHub’s API, and you trust them to return the right content for the SHA. A lockfile wouldn’t fix the missing spec, but it would at least give you a concrete record of what resolution produced. Even setting lockfiles aside, Actions has other issues that proper package managers solved long ago. **No registry.** Actions live in git repositories. There’s no central index, no security scanning, no malware detection, no typosquatting prevention. A real registry can flag malicious packages, store immutable copies independent of the source, and provide a single point for security response. The Marketplace exists but it’s a thin layer over repository search. Without a registry, there’s nowhere for immutable metadata to live. If an action’s source repository disappears or gets compromised, there’s no fallback. **Shared mutable environment.** Actions aren’t sandboxed from each other. Two actions calling `setup-node` with different versions mutate the same `$PATH`. The outcome depends on execution order, not any deterministic resolution. **No offline support.** Actions are pulled from GitHub on every run. There’s no offline installation mode, no vendoring mechanism, no way to run without network access. Other package managers let you vendor dependencies or set up private mirrors. With Actions, if GitHub is down, your CI is down. **The namespace is GitHub usernames.** Anyone who creates a GitHub account owns that namespace for actions. Account takeovers and typosquatting are possible. When a popular action maintainer’s account gets compromised, attackers can push malicious code and retag. A lockfile with integrity hashes wouldn’t prevent account takeovers, but it would detect when the code changes unexpectedly. The hash mismatch would fail the build instead of silently running attacker-controlled code. Another option would be something like Go’s checksum database, a transparent log of known-good hashes that catches when the same version suddenly has different contents. ### How Did We Get Here? The Actions runner is forked from Azure DevOps, designed for enterprises with controlled internal task libraries where you trust your pipeline tasks. GitHub bolted a public marketplace onto that foundation without rethinking the trust model. The addition of composite actions and reusable workflows created a dependency system, but the implementation ignored lessons from package management: lockfiles, integrity verification, transitive pinning, dependency visibility. This matters beyond CI/CD. Trusted publishing is being rolled out across package registries: PyPI, npm, RubyGems, and others now let you publish packages directly from GitHub Actions using OIDC tokens instead of long-lived secrets. OIDC removes one class of attacks (stolen credentials) but amplifies another: the supply chain security of these registries now depends entirely on GitHub Actions, a system that lacks the lockfile and integrity controls these registries themselves require. A compromise in your workflow’s action dependencies can lead to malicious packages on registries with better security practices than the system they’re trusting to publish. Other CI systems have done better. GitLab CI added an `integrity` keyword in version 17.9 that lets you specify a SHA256 hash for remote includes. If the hash doesn’t match, the pipeline fails. Their documentation explicitly warns that including remote configs “is similar to pulling a third-party dependency” and recommends pinning to full commit SHAs. GitLab recognized the problem and shipped integrity verification. GitHub closed the feature request. GitHub’s design choices don’t just affect GitHub users. Forgejo Actions maintains compatibility with GitHub Actions, which means projects migrating to Codeberg for ethical reasons inherit the same broken CI architecture. The Forgejo maintainers openly acknowledge the problems, with contributors calling GitHub Actions’ ecosystem “terribly designed and executed.” But they’re stuck maintaining compatibility with it. Codeberg mirrors common actions to reduce GitHub dependency, but the fundamental issues are baked into the model itself. GitHub’s design flaws are spreading to the alternatives. GitHub issue #2195 requested lockfile support. It was closed as “not planned” in 2022. Palo Alto’s “Unpinnable Actions” research documented how even SHA-pinned actions can have unpinnable transitive dependencies. Dependabot can update action versions, which helps. Some teams vendor actions into their own repos. zizmor is excellent at scanning workflows and finding security issues. But these are workarounds for a system that lacks the basics. The fix is a lockfile. Record resolved SHAs for every action reference, including transitives. Add integrity hashes. Make the dependency tree inspectable. GitHub closed the request three years ago and hasn’t revisited it. * * * **Further reading:** * Characterizing the Security of GitHub CI Workflows - Koishybayev et al., USENIX Security 2022 * ARGUS: A Framework for Staged Static Taint Analysis of GitHub Workflows and Actions - Muralee et al., USENIX Security 2023 * New GitHub Action supply chain attack: reviewdog/action-setup - Wiz Research, 2025 * Unpinnable Actions: How Malicious Code Can Sneak into Your GitHub Actions Workflows * GitHub Actions Worm: Compromising GitHub Repositories Through the Actions Dependency Tree * setup-python: Action can be compromised via mutable dependency

XSLT RIP (xslt.rip) 15:39  ↑ 112 HN Points