sandlock 0.8.2

Lightweight process sandbox using Landlock, seccomp, and seccomp user notification

sandlock Python SDK

Python bindings for sandlock, a lightweight process sandbox using Landlock and seccomp. No root, no Docker, no namespaces required.

Requires Linux 6.7+ with Landlock ABI v6.

pip install sandlock

Quick start

from sandlock import Sandbox

sandbox = Sandbox(
    fs_readable=["/usr", "/lib", "/lib64", "/bin", "/etc", "/proc", "/dev"],
    fs_writable=["/tmp"],
)
result = sandbox.run(["echo", "hello"], timeout=10)
assert result.success
print(result.stdout)  # b"hello\n"

API reference

Platform

sandlock.landlock_abi_version() -> int

Return the Landlock ABI version supported by the running kernel. Returns -1 if Landlock is unavailable.

sandlock.min_landlock_abi() -> int

Return the minimum Landlock ABI version required by sandlock (currently 6).

Confine

Apply a Sandbox's Landlock rules to the current process, in place. No fork, no exec.

from sandlock import Sandbox, confine

confine(Sandbox(
    fs_readable=["/usr", "/lib"],
    fs_writable=["/tmp"],
))

sandlock.confine(sandbox) -> None

Set PR_SET_NO_NEW_PRIVS and install the sandbox's Landlock ruleset on the live process. The confinement is irreversible.

Only Landlock fields are honored (fs_readable, fs_writable, fs_denied); IPC and signal scoping are always applied. Sandbox config that requires a supervisor or a fresh child (seccomp, network, resource limits, COW, env, policy_fn, etc.) is rejected rather than silently ignored. Raises ConfinementError on failure.

Sandbox

sandlock.Sandbox(**kwargs)

Sandbox configuration and runtime handle. Holds both the policy (filesystem, network, resource limits, etc.) and runtime state. Construct once, then call run() (blocking) or spawn() + lifecycle methods, or use as a context manager.

All config fields are optional. Unset fields mean "no restriction" unless noted otherwise. Runtime kwargs (name, policy_fn, init_fn, work_fn) are set at construction time alongside config fields.

A single Sandbox instance holds at most one running process at a time. For concurrent execution, create multiple instances.

Runtime kwargs:

• name -- sandbox name (also its virtual hostname inside the sandbox). Auto-generated as sandbox-{pid} when omitted.
• policy_fn -- optional callback for dynamic per-event policy decisions (see Dynamic policy).
• init_fn / work_fn -- callbacks for COW fork mode (see Fork).

Sandbox is a context manager:

with Sandbox(fs_readable=["/usr", "/lib"]) as sb:
    result = sb.run(["echo", "hello"])

Filesystem (Landlock)

Parameter	Type	Default	Description
fs_readable	list[str]	[]	Paths the sandbox can read
fs_writable	list[str]	[]	Paths the sandbox can write
fs_denied	list[str]	[]	Paths explicitly denied
workdir	str | None	None	Working directory; enables COW protection
chroot	str | None	None	Path to chroot into before confinement
fs_mount	dict[str, str]	{}	Map virtual paths to host directories inside chroot
cwd	str | None	None	Child working directory

Network

Parameter	Type	Default	Description
net_allow	list[str]	[]	Outbound endpoint rules. Bare host:port is TCP; protocol prefixes opt others in: tcp://host:port, udp://host:port (or udp://*:* for any UDP), icmp://host (or icmp://* for any ICMP echo via the kernel ping socket — gated by net.ipv4.ping_group_range on the host). Empty = deny all. Raw ICMP is not exposed.
net_bind	list[int | str]	[]	TCP ports the sandbox may bind (empty = deny all)
port_remap	bool	False	Transparent TCP port virtualization

HTTP ACL

Enforce method + host + path rules on HTTP traffic via a transparent MITM proxy. When http_allow is set, all non-matching HTTP requests are denied by default. Block rules are checked first and take precedence.

Parameter	Type	Default	Description
http_allow	list[str]	[]	Allow rules in "METHOD host/path" format
http_deny	list[str]	[]	Block rules in "METHOD host/path" format
http_ports	list[int]	[80]	TCP ports to intercept (443 added when http_ca is set)
http_ca	str | None	None	CA certificate for HTTPS MITM
http_key	str | None	None	CA private key for HTTPS MITM

Rule format: "METHOD host/path" where method and host can be * for wildcard, and path supports trailing * for prefix matching. Paths are normalized (percent-decoding, .. resolution, // collapsing) before matching to prevent bypasses.

sandbox = Sandbox(
    fs_readable=["/usr", "/lib", "/etc"],
    http_allow=[
        "GET docs.python.org/*",
        "POST api.openai.com/v1/chat/completions",
    ],
    http_deny=["* */admin/*"],
)
result = sandbox.run(["python3", "agent.py"])

Chroot with mount mapping

Map host directories into a chroot — like Docker's -v /host:/container but without kernel bind mounts or root privileges. Each sandbox gets its own persistent workspace while sharing a read-only rootfs.

sandbox = Sandbox(
    chroot="/opt/rootfs",
    fs_mount={"/work": "/tmp/sandbox-1/work"},
    fs_readable=["/usr", "/bin", "/lib", "/etc"],
    cwd="/work",
)
result = sandbox.run(["python3", "task.py"])

Combine with workdir + max_disk for quota-enforced writes:

sandbox = Sandbox(
    chroot="/opt/rootfs",
    fs_mount={"/work": "/tmp/sandbox-1/work"},
    workdir="/tmp/sandbox-1/work",
    fs_storage="/tmp/sandbox-1/cow",
    max_disk="100M",
    on_exit="commit",
    fs_readable=["/usr", "/bin", "/lib", "/etc"],
)

Resource limits

Parameter	Type	Default	Description
max_memory	str | int | None	None	Memory limit, e.g. "512M" or int bytes
max_processes	int	64	Peak concurrent process limit
max_open_files	int | None	None	Max file descriptors (RLIMIT_NOFILE)
max_cpu	int | None	None	CPU throttle as percentage of one core (1-100)
cpu_cores	list[int] | None	None	CPU cores to pin sandbox to
num_cpus	int | None	None	Visible CPU count in /proc/cpuinfo

Syscall filtering (seccomp)

Parameter	Type	Default	Description
extra_deny_syscalls	list[str]	[]	Extra syscall names to block in addition to Sandlock defaults
extra_allow_syscalls	list[str]	[]	Syscall groups to allow that are blocked by default (e.g. "sysv_ipc" to enable SysV shared memory, semaphores, and message queues)

Sandlock always applies its default syscall blocklist.

Deterministic execution

Parameter	Type	Default	Description
random_seed	int | None	None	Seed for deterministic getrandom()
time_start	datetime | float | str | None	None	Start timestamp for time virtualization
no_randomize_memory	bool	False	Disable ASLR
no_huge_pages	bool	False	Disable Transparent Huge Pages
deterministic_dirs	bool	False	Sort directory entries lexicographically

Environment

Parameter	Type	Default	Description
clean_env	bool	False	Start with minimal environment
env	dict[str, str]	{}	Variables to set/override in the child

GPU access

Parameter	Type	Default	Description
gpu_devices	list[int] | None	None	GPU device indices to expose ([] = all)

Misc

Parameter	Type	Default	Description
uid	int | None	None	Map to given UID inside a user namespace (e.g. 0 for fake root)
no_coredump	bool	False	Disable core dumps

COW filesystem isolation

Parameter	Type	Default	Description
fs_storage	str | None	None	Storage directory for the seccomp COW upper layer / deltas
max_disk	str | None	None	Disk quota for COW storage (e.g. "1G")
on_exit	BranchAction	COMMIT	COMMIT, ABORT, or KEEP
on_error	BranchAction	ABORT	COMMIT, ABORT, or KEEP

sandbox.run(cmd, timeout=None) -> Result

Run a command, capturing stdout and stderr.

• cmd -- list of strings (command and arguments).
• timeout -- max execution time in seconds (float). None = no timeout.

result = sandbox.run(["python3", "-c", "print(42)"], timeout=10.0)

sandbox.spawn(cmd) -> None

Spawn cmd without waiting. Use pid, pause(), resume(), kill(), and wait() to manage the process lifecycle.

Raises RuntimeError if a process is already running.

Sugar for create(cmd) + start(); use those directly when you need the fork-park-exec split (e.g. starting several sandboxes in lockstep, or attaching external tracing to the parked PID before the child execs).

sandbox.create(cmd) -> None

Fork the sandboxed child and install policy. The child is parked between policy install and execve; call start() to release it. pid is available after this call but the child is not yet running user code.

Raises RuntimeError if a process is already running.

sandbox.start() -> None

Release a previously create()d child to execve.

Raises RuntimeError if no child has been created.

sandbox.wait() -> Result

Wait for the running process to finish and return its Result.

sandbox.dry_run(cmd, timeout=None) -> DryRunResult

Run a command in a temporary COW layer, then discard all writes. Returns the list of filesystem changes that would have been made.

result = sandbox.dry_run(["sh", "-c", "echo hi > /tmp/out.txt"])
for change in result.changes:
    print(change.kind, change.path)  # "A /tmp/out.txt"

sandbox.run_interactive(cmd) -> int

Run with inherited stdio (no capture). Returns the exit code.

sandbox.name -> str | None

The sandbox name.

sandbox.pid -> int | None

The child PID while running, None otherwise.

sandbox.is_running -> bool

True if a process is currently running in this sandbox.

sandbox.ports() -> dict[int, int]

Current port mappings {virtual_port: real_port} while running. Only contains entries where port remapping occurred. Requires port_remap=True.

sandbox.pause() / sandbox.resume() / sandbox.kill()

Send SIGSTOP / SIGCONT / SIGKILL to the sandbox process group. Raises RuntimeError if the sandbox is not running.

sandbox.checkpoint(save_fn=None) -> Checkpoint

Capture a checkpoint of the running sandbox. See Checkpoint.

Result

Returned by sandbox.run().

Attribute	Type	Description
success	bool	True if exit code is 0
exit_code	int	Process exit code
stdout	bytes	Captured standard output
stderr	bytes	Captured standard error
error	str | None	Error message on failure

DryRunResult

Returned by sandbox.dry_run().

Same attributes as Result, plus:

Attribute	Type	Description
changes	list[Change]	Filesystem changes detected

Change

Attribute	Type	Description
kind	str	"A" (added), "M" (modified), or "D" (deleted)
path	str	Path relative to workdir

Stage and Pipeline

Chain sandboxed commands with pipes using the | operator:

result = (
    sandbox_a.cmd(["echo", "hello"])
    | sandbox_b.cmd(["tr", "a-z", "A-Z"])
).run()
assert result.stdout == b"HELLO\n"

sandbox.cmd(args) -> Stage

Create a lazy Stage bound to this sandbox.

pipeline.run(stdout=None, timeout=None) -> Result

Run the pipeline. Each stage's stdout feeds the next stage's stdin.

Gather

Fan multiple producers into one consumer via named pipes. Each producer's stdout is delivered to the consumer under a label the consumer reads from a sandlock.inputs dict. This is the structural primitive behind the XOA pattern: producers and consumer are independent sandboxes, and the consumer never executes producer code inside its own LLM call.

from sandlock import Sandbox

planner  = Sandbox(...)   # writes code
searcher = Sandbox(...)   # produces data
executor = Sandbox(...)   # consumes both

result = (
    searcher.cmd(["python3", "-c", "..."]).as_("data")
    + planner.cmd(["python3", "-c", "..."]).as_("code")
    | executor.cmd(["python3", "consume.py"])
).run()

Inside consume.py:

from sandlock import inputs

code = inputs["code"]
data = inputs["data"]
exec(compile(code, "<planner>", "exec"), {"data": data})

stage.as_(name) -> NamedStage

Label a Stage's stdout so the consumer can address it by name.

named_stage + named_stage_or_gather -> Gather

Combine two or more NamedStage values into a Gather. Repeated + extends the gather:

g = a.as_("x") + b.as_("y") + c.as_("z")

gather | consumer_stage -> GatherPipeline

Compose a Gather with a consumer Stage to form the runnable pipeline.

gather_pipeline.run(timeout=None) -> Result

Run all producers in parallel; each producer's stdout is wired to a pipe the consumer reads via inputs[name]. Returns the consumer's Result.

sandlock.inputs

Lazy dict-like accessor available inside the consumer process. Reads each producer's pipe on first access and caches the value.

from sandlock import inputs

inputs["code"]        # str: the producer's full stdout, decoded as utf-8
"data" in inputs      # bool
list(inputs.keys())   # ["data", "code"]

The pipe fds are passed via the _SANDLOCK_GATHER env var (name:fd,name:fd,...); the inputs object parses it on first access. Users do not interact with the env var directly.

Dynamic policy

Use policy_fn to make per-syscall decisions at runtime:

from sandlock import Sandbox, SyscallEvent, PolicyContext

def my_policy(event: SyscallEvent, ctx: PolicyContext):
    if event.category == "network" and event.host == "evil.com":
        return True   # deny
    if event.category == "file" and "/secrets" in (event.path or ""):
        ctx.deny_path("/secrets")
        return True   # deny
    return False      # allow

sb = Sandbox(..., policy_fn=my_policy)

SyscallEvent

Attribute	Type	Description
syscall	str	Syscall name (e.g. "openat", "connect")
category	str	"file", "network", "process", or "memory"
pid	int	Process ID
parent_pid	int	Parent process ID
path	str | None	File path (for file events)
host	str | None	Hostname (for network events)
port	int	Port number (for network events)
argv	tuple[str, ...] | None	Command arguments (for execve)
denied	bool	Whether this event was already denied by static policy

Helper methods:

• event.path_contains(s) -- True if path contains substring s
• event.argv_contains(s) -- True if any argv element contains s

PolicyContext

Methods available inside policy_fn:

Method	Description
ctx.restrict_network(ips)	Restrict to given IP addresses
ctx.grant_network(ips)	Allow additional IP addresses
ctx.restrict_max_memory(bytes)	Lower memory limit
ctx.restrict_max_processes(n)	Lower process limit
ctx.restrict_pid_network(pid, ips)	Per-PID network restriction
ctx.deny_path(path)	Deny access to a path
ctx.allow_path(path)	Remove a previously denied path

Callback return values:

Return	Meaning
None, False, 0	Allow
True, -1	Deny (EPERM)
positive int	Deny with that errno
"audit", -2	Allow but flag for audit

Fork

COW fork for parallel execution with shared initialization:

sb = Sandbox(
    fs_readable=[...],
    init_fn=lambda: load_model(),
    work_fn=lambda clone_id: process(clone_id),
)
clones = sb.fork(4)  # returns ForkResult with .pids

sandbox.reduce(cmd, fork_result) -> Result

Pipe combined clone output into a reducer command:

result = sandbox.reduce(["python3", "sum.py"], clones)

Checkpoint

Save and restore sandbox state:

sb = Sandbox(...)
# ... start a long-running process ...
cp = sb.checkpoint(save_fn=lambda: my_state_bytes())
cp.save("my-snapshot")

# Later:
cp2 = Checkpoint.load("my-snapshot")
Checkpoint.restore("my-snapshot", restore_fn=lambda data: rebuild(data))

Method	Description
cp.save(name, store=None)	Persist checkpoint to disk
Checkpoint.load(name, store=None)	Load from disk
Checkpoint.restore(name, restore_fn, store=None)	Load and call restore_fn with app_state
Checkpoint.list(store=None)	List saved checkpoint names
Checkpoint.delete(name, store=None)	Delete a saved checkpoint

Properties: cp.name (str), cp.app_state (bytes or None).

Default store: ~/.sandlock/checkpoints/.

Profiles

Load sandbox configuration from TOML files: Profiles contain sandbox config only; pass the sandbox name at construction: Sandbox(..., name=...).

from sandlock import load_profile, list_profiles

sandbox = load_profile("web-scraper")
names = list_profiles()

Exceptions

SandlockError (base)
  +-- SandboxError         invalid sandbox configuration
  +-- SandboxRuntimeError  sandbox lifecycle errors
        +-- ForkError          fork failed
        +-- ChildError         child exited abnormally
        +-- BranchError        COW branch operation failed
        |     +-- BranchConflictError   sibling branch committed (ESTALE)
        +-- ConfinementError   Landlock/seccomp setup failed
              +-- LandlockUnavailableError   no Landlock support
              +-- SeccompError               seccomp filter failed
                    +-- NotifError           notif supervisor error
  +-- MemoryProtectError   mprotect failed

All exceptions are importable from sandlock.exceptions or directly from sandlock:

from sandlock import SandlockError, SandboxError, SandboxRuntimeError

Enums

BranchAction

• BranchAction.COMMIT -- merge writes on exit
• BranchAction.ABORT -- discard writes
• BranchAction.KEEP -- leave branch as-is

MCP integration

Sandboxed tool execution for AI agents. Each tool runs in a per-call sandbox with deny-by-default permissions.

pip install 'sandlock[mcp]'

McpSandbox

from sandlock.mcp import McpSandbox

mcp = McpSandbox(workspace="/tmp/agent", timeout=30.0)

• workspace -- directory the sandbox can read (default: "/tmp/sandlock").
• timeout -- default timeout in seconds per tool call (default: 30.0).

mcp.add_tool(name, func, *, description="", capabilities=None, input_schema=None)

Register a local tool. func must be a top-level function in an import-safe module: the worker imports that module by name and calls the function in a fresh per-call sandbox. Module-level imports, helpers, constants, and state are all fine; lambdas, methods, and nested functions are rejected. Guard any module startup logic under if __name__ == "__main__":.

A tool that declares a parameter named workspace receives the sandbox's workspace path automatically (injected at call time, hidden from the LLM schema, and not overridable by the model). No env wiring needed.

# tools.py  (an importable module)
import os

def read_file(path: str, *, workspace: str) -> str:
    with open(os.path.join(workspace, path)) as f:
        return f.read()

import tools

mcp.add_tool("read_file", tools.read_file,
    description="Read a file from the workspace",
)

No capabilities = read-only, clean environment, no network. Grant permissions explicitly:

Capability	Example	Description
fs_writable	["/tmp/agent"]	Paths the tool can write to
net_allow	["api.example.com:443", "udp://1.1.1.1:53"]	Outbound endpoints. Bare host:port is TCP; udp://... / icmp://... schemes opt UDP / ICMP echo in.
env	{"KEY": "val"}	Environment variables to pass
max_memory	"256M"	Memory limit

Any Sandbox field name is accepted as a capability key.

await mcp.add_mcp_session(session)

Discover tools from a remote MCP server. Capabilities are read from sandlock:* keys in the tool's annotations or meta dict.

await mcp.call_tool(name, arguments=None, *, timeout=None) -> str

Call a tool by name. Local tools run in a per-call sandbox. MCP tools are forwarded to their server session.

result = await mcp.call_tool("read_file", {"path": "data.txt"})

mcp.get_policy(tool_name) -> Sandbox

Return the computed Sandbox for a registered tool.

mcp.tool_definitions_openai() -> list[dict]

Tool definitions in OpenAI function-calling format, for use with chat completion APIs.

mcp.tools -> dict[str, Any]

All registered tools (local and MCP).

MCP server

A standalone MCP server with built-in sandboxed tools (shell, python, read_file, write_file, list_files):

# stdio (for Claude Desktop / Cursor)
sandlock-mcp --workspace /tmp/sandbox

# SSE (remote)
pip install 'sandlock[mcp-remote]'
sandlock-mcp --transport sse --host 0.0.0.0 --port 8080 --workspace /tmp/sandbox

Claude Desktop configuration:

{
  "mcpServers": {
    "sandlock": {
      "command": "sandlock-mcp",
      "args": ["--workspace", "/tmp/sandbox"]
    }
  }
}

policy_for_tool(*, workspace, capabilities=None) -> Sandbox

Build a deny-by-default Sandbox from explicit capabilities. Used internally by McpSandbox but available for direct use.

capabilities_from_mcp_tool(tool) -> dict

Extract sandlock:* capabilities from an MCP tool's annotations/meta.

License

Apache-2.0