Generate sandboxes for C/C++ libraries automatically
1.8k
Stars
194
Forks
22
Open issues
30
Contributors
AI Analysis
Sandboxed API (SAPI) automatically generates sandboxes for C/C++ libraries, enabling fine-grained isolation of untrusted code within larger applications. It is purpose-built for security teams and systems integrators who need to isolate vulnerable or untrusted C/C++ dependencies without rewriting source code or deploying entire sandboxed processes. General application developers seeking simple library isolation, or those working in languages other than C/C++, are not the primary audience.
Inferred from signals mentioned in the README (tests, CI, type safety) — not a review of the actual code.
AI's overall editorial judgment — not an average of the bars above, can weigh other factors too.
Google's automated C/C++ library sandboxing framework, maintained but niche adoption
Sandboxed API (SAPI) automates the creation of security sandboxes for C/C++ libraries, allowing developers to isolate untrusted code without rewriting applications. Built on Google's internal Sandbox2 and maintained by the Google Sandbox Team, it aims to reduce implementation burden through reusable sandbox templates. Adoption appears limited to organizations with high security requirements and C/C++ library integration needs; mainstream adoption remains modest despite technical maturity.
SAPI was created in 2019 by Google's Sandbox Team as a public-facing version of internal sandboxing practices. It extracts learnings from Google's production sandboxing infrastructure and exposes both SAPI and the underlying Sandbox2 framework as open-source projects. The framework has remained actively maintained since inception.
The project shows steady maintenance activity (last push 2026-06-27) but modest star growth (1,750 stars over 7 years, 0 in last week). Growth appears driven by security-conscious enterprises and researchers rather than mainstream adoption. The lack of recent acceleration suggests the project has reached a stable, specialized audience rather than expanding into new use cases.
README states 'many internal projects are using SAPI to isolate their production workloads' at Google, but no public names, scale metrics, or external case studies are documented. Google's own usage provides credibility but doesn't quantify third-party adoption. Adoption not verified outside Google ecosystem.
Based on README, SAPI provides automatic code generation for sandbox boundaries using LLVM/Clang tooling to analyze C/C++ library headers. It generates wrapper code that marshals data between trusted and untrusted processes. Appears to support both Bazel and CMake build systems. Likely architecture involves policy definition, code generation, and process isolation via Linux namespaces/seccomp (mentioned Sandbox2 dependency).
Not documented in README. Build status badges indicate CI/CD pipeline on BuildKite and GitHub Actions for Ubuntu/CMake, but specific test coverage metrics are absent.
Project shows active maintenance: last commit 2026-06-27 (same day as analysis), multiple build system support (Bazel/CMake), recent LLVM version support (LLVM 19+ mentioned for Debian 13 Trixie). Dependencies list is current and detailed. No signs of abandonment; maintenance appears ongoing but not high-velocity.
ADOPT IF: you are integrating untrusted C/C++ libraries in a Linux environment and have resources to learn SAPI's policy/code-generation model; your organization can commit to LLVM/Clang toolchain maintenance; security isolation is a first-class requirement. AVOID IF: you need out-of-box sandboxing with minimal configuration; your primary language is not C/C++; you lack Linux-specific infrastructure or kernel expertise; you require vendor support guarantees. MONITOR IF: your organization is evaluating open-source sandboxing options and your threat model centers on C/C++ library vulnerabilities; SAPI's stability and Google backing make it worth tracking even if current adoption is limited.
Independent dimensions
Mainstream potential
3/10
Technical importance
7/10
Adoption evidence
3/10
- Adoption appears heavily concentrated within Google; limited evidence of thriving external ecosystem or community-driven extensions.
- Requires deep understanding of Linux kernel, seccomp, namespaces, and LLVM/Clang tooling—high barrier to entry for typical application developers.
- LLVM version pinning and dependency on specific Linux distributions (e.g., Debian Trixie) may create maintenance friction in heterogeneous environments.
- No documented public roadmap or SLA; maintenance depends on Google's internal priorities, which may diverge from community needs.
- Limited cross-platform support (Linux-only); Windows and macOS users cannot adopt, constraining addressable market.
SAPI will likely remain a specialized tool for security-focused C/C++ projects and organizations with strong Linux infrastructure. Growth will be constrained by high technical friction and niche applicability, but maintenance is unlikely to cease given Google's ongoing internal use. Mainstream adoption outside security specialists remains improbable.
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Languages
Information
- Language
- C++
- License
- Apache-2.0
- Last updated
- 22h ago
- Created
- 89mo ago
- Analyzed with
- anthropic/claude-haiku-4-5
Stars over time
Contributors over time
Top 100 contributors only — repos with more will plateau at 100.
Open issues
can i use sandbox-api in android?
external gtest dependency importing (cmake)
Add Landlock support
Allow use on systems without unprivileged user ns
Linking issue with libunwind and zlib on aarch64
Open pull requests
No open pull requests.
Top contributors
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Sandboxie is a mature Windows application sandbox; SAPI targets Linux system-level library isolation. Different threat models and operating systems; not direct competitors.
TypeScript focus and web-oriented sandboxing; SAPI's C/C++ library isolation is orthogonal. Similar star magnitude but serves distinct markets.
Rust-based sandbox infrastructure; SAPI's focus on automatic C/C++ library wrapping is more specialized than CubeSandbox's broader sandbox runtime approach.
Python-focused; SAPI is C/C++ specific. Different language ecosystems and threat models; no direct overlap.
