secimport combines USDT probes with eBPF and DTrace to trace, profile, and enforce per-module syscall restrictions on Python code, defending authorized applications from vulnerable third-party dependencies.
| Tool | avilum/secimport — eBPF/DTrace-based toolkit that enforces syscall restrictions per Python module on Linux and macOS |
| Category | Runtime sandboxing and syscall-level policy enforcement |
| Primary Use | Tracing a Python workload with secimport trace, generating a tailored policy with secimport build, and running hardened code under secimport run |
| Safe Use | Hardening your own or your organization's authorized Python applications and supply chains in production or lab environments; purely defensive containment |
| Telemetry Note | Because it hooks USDT probes via bpftrace/DTrace, its tracing activity is visible on the host as elevated-privilege BPF programs; enforcement itself runs in-kernel with negligible overhead, so sandbox violations appear as stopped or killed processes, not network traffic |
Most sandboxing technology operates at the process boundary: you sequester an entire application inside a container, an nsjail namespace, or a seccomp-bpf filter, and every line of code inside shares the same syscall budget. secimport, the MIT-licensed project from avilum/secimport, takes a fundamentally finer-grained approach on both Linux and macOS. It treats each imported Python module as its own security principal and enforces syscall restrictions at that granularity, which the README aptly summarizes as seccomp-bpf for Linux, but operating at the Python module level. For defenders wrestling with the reality that a single pip install drags in dozens of semi-trusted dependencies, this is a meaningful architectural shift.
The internals are what make this credible rather than aspirational. secimport leverages USDT probes — statically defined tracepoints compiled into the Python interpreter itself (via --enable-dtrace) — and attaches eBPF programs on Linux or DTrace scripts on macOS to observe which module executes which syscall. Because the probes fire inside the interpreter's import and call machinery, the tool can attribute kernel activity to a specific module such as requests or a model-loading routine in PyTorch, something a naive strace-style wrapper cannot do. The project ships with bpftrace as its primary tracing backend on Ubuntu/Debian, and the README notes a python-publish CI workflow, indicating it is distributed on PyPI as an installable package.
The operational workflow the README prescribes is a clean three-step pipeline: secimport trace, secimport build, and secimport run. Tracing can attach to a fresh interpreter via secimport trace, to an interactive session with secimport shell, or to an already-running workload with secimport trace_pid <PID>. During the trace window you exercise the code paths you consider legitimate — the README's example imports requests and performs the actions worth profiling — and the tool records the exact syscall set each module touched. secimport build then compiles that trace log into a sandbox profile, and secimport run executes the target inside the resulting policy. An interactive command chains all three steps inside a guided Python shell, which makes first contact with the tool genuinely low-friction.
Enforcement is where the defensive value concentrates. The README documents two escalation modes: secimport run --stop_on_violation=true halts a process the moment a module attempts a syscall outside its profile, and secimport run --kill_on_violation=true terminates it outright. There is also an implicit log-only posture useful for canary deployments, where you observe what a legacy dependency would attempt without disrupting production. The performance claim is worth noting: enforcement happens in kernel space through eBPF, so the steady-state cost is described as negligible — a critical property if the sandbox is to survive in production rather than being disabled the first time latency budgets tighten.
For teams that prefer policy as code over profile generation, secimport exposes a Python API. The README shows secimport.secure_import('requests', allowed_syscalls=['open', 'read', ...]) as a drop-in replacement for the standard import statement, letting developers declare a module's syscall allowlist inline at the import site. This is a nice fit for the supply-chain protection use case the README highlights: when you must keep using a vulnerable or untrusted dependency, you can at least cap what it is mechanically capable of, converting a hypothetical remote-code-execution primitive in a parser library into an attacker who suddenly cannot open, connect, or execve anything useful.
A second enforcement layer deserves separate attention. Beyond the eBPF module-level sandbox, secimport build additionally generates an nsjail wrapper — Google's namespace-isolation tool — complete with an automatically derived seccomp profile, emitted as an executable bash script. This constrains the syscall surface of the entire Python process rather than individual modules, and the README explicitly frames it as another layer of defence. The layered design is sound: even if the module-level attribution were somehow evaded, the coarse process-wide seccomp filter remains, and defenders get defense-in-depth rather than a single policy chokepoint.
Installation is straightforward for a tool with this much kernel coupling. The README recommends a Docker path (git clone followed by ./build.sh && ./run.sh inside the secimport/docker directory), which sidesteps the one genuinely fiddly prerequisite: a Python interpreter built with --enable-dtrace so the USDT probes exist. On a bare-metal install you need apt-get install bpftrace (or the platform-equivalent backend) followed by pip install secimport. macOS users get DTrace support instead of eBPF, which is a rare cross-platform story for this class of tooling and makes secimport viable for developer workstations as well as Linux servers.
The surrounding ecosystem signals genuine engineering rather than a weekend experiment. The project links a PyCon talk, a BSides presentation, and a series of technical writeups covering concrete integrations: sandboxing PyTorch model loading, hardening FastAPI services, and combining DTrace with module-level policies. The repo carries topics spanning ebpf, bpftrace, dtrace, seccomp, sandbox, and rce, and the documentation lives in an organized wiki covering installation, command-line usage, the Python API, and worked sandbox examples. At roughly 245 stars, it is a known quantity in the Python-hardening niche without being so mature that its design decisions are frozen.
From a defensive tradecraft perspective, the profiling workflow itself is a discovery instrument. Even if you never enable --kill_on_violation, running secimport trace over a third-party library in a lab tells you precisely which syscalls it touches — and a dependency that claims to be a pure formatting library but reaches for socket or ptrace-adjacent calls has just told you something important. This makes the tool dual-purpose: containment in production, and behavioral characterization during supply-chain triage or incident review of a suspicious package.
The caveats are the usual ones for eBPF-based enforcement: you need a Python build with USDT probes (which stock distro interpreters may lack), elevated privileges to load BPF programs, and a Linux kernel new enough for the tracing backend — or macOS with DTrace available. Policies are only as good as the trace that generated them, so an incomplete profiling run produces an allowlist that will either break legitimate functionality under --stop_on_violation or, worse, over-permit. Treat profile generation as a CI artifact that is regenerated and reviewed whenever dependencies change, not a one-time setup task.
Within the authorized-assessment and hardening toolkit, secimport occupies a distinctive slot: it is not a scanner, not a detector, but a runtime containment technology that turns knowledge of what your code should do into an enforceable kernel-level contract. For blue teams running Python services that must tolerate imperfect dependencies — ML inference pipelines, API backends, data-processing jobs — it offers a practical path from observation to enforcement on systems you own and are authorized to defend, with documentation thorough enough that the barrier to a first sandbox is a single secimport interactive session.
avilum/secimport.Educational analysis for authorized security professionals. Use only in controlled, authorized environments.
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