This article examines why Antigravity AI crashes with SIGILL on an RDK X ARM board in a Remote-SSH workflow. The core fix is to replace direct remote workspace access with a locally mounted Samba network share, which helps avoid instruction-set mismatches and unstable execution paths. Keywords: RDK X, Remote-SSH, Samba.
Technical specifications are summarized here
| Parameter | Details |
|---|---|
| Hardware platform | RDK X (ARM architecture) |
| Development method | VS Code Remote-SSH |
| Typical issue | Antigravity AI crashes at runtime with SIGILL |
| Network protocols | SSH, SMB/CIFS |
| Host environment | Windows development machine + Linux board |
| Core dependencies | VS Code, Remote-SSH, Samba/CIFS, mount.cifs |
| Source popularity | 401 views / 8 likes / 8 bookmarks |
This is a compatibility issue caused by the remote execution path
The original source title points to RDK X, ARM, Remote-SSH, Antigravity AI, and SIGILL, but the body mixes in a large amount of unrelated Windows privilege escalation content. Only one useful fact can be extracted: when the target project runs directly on the ARM board through Remote-SSH, the program triggers an illegal instruction exception, and a workable fix is to switch to a local Samba-mounted network share.
SIGILL usually means that a process executed a machine instruction the current CPU does not support, or loaded a binary fragment that does not match the target architecture. In embedded and heterogeneous development, this often does not mean “the application code is wrong.” More often, the execution path, dependency resolution, interpreter selection, or binary cache origin is wrong.
Remote-SSH tends to amplify this problem
Remote-SSH does not directly create illegal instructions, but it does change how the workspace is opened, where extensions run, how cache directories are used, and the order in which interpreters are discovered. For AI projects that depend on local extensions, precompiled modules, or shared libraries, that difference can be enough to make an ARM device consume incompatible artifacts.
uname -m # Confirm the board CPU architecture
file ./your_binary # Check the target file architecture
ldd ./your_binary # Inspect dynamic library dependencies
python3 -c "import platform;print(platform.machine())" # Verify the Python runtime architectureUse this command set first to confirm whether the problem is actually in the architecture or dependency layer rather than in the application logic layer.
A local Samba mount restores stable file access semantics
The core of this solution is not simply “use a different file transfer method.” The real goal is to create more stable and controllable shared-directory semantics between the development machine and the board. Compared with opening the workspace directly through Remote-SSH, a Samba mount exposes the project through SMB/CIFS as a local drive letter or local mount point, which makes toolchain behavior around paths, permissions, and caches more consistent.
When Antigravity AI involves model files, script entry points, virtual environments, or extension modules, this consistency becomes critical. Many SIGILL failures do not come from the main program binary itself. Instead, an indirectly loaded .so, cached file, or intermediate artifact often comes from the wrong platform.
Enable Samba sharing on the RDK X board
First, prepare the shared directory on the board and make sure the Samba service is installed and reachable.
sudo apt update
sudo apt install -y samba # Install the Samba service
sudo mkdir -p /data/antigravity
sudo chown -R $USER:$USER /data/antigravity # Grant the current user access to the directoryThe goal of this step is to expose a stable project-specific shared directory on the board.
Then edit the Samba configuration.
[antigravity]
path = /data/antigravity
browseable = yes
read only = no
guest ok = no
create mask = 0755
directory mask = 0755
valid users = youruserThis configuration defines a writable share and helps prevent cache or dependency generation failures caused by insufficient permissions in AI projects.
Performing a local mount on Windows or Linux is more reliable
If the development machine runs Windows, you can map a network drive directly. If it runs Linux, you can mount the share through CIFS. The key point is this: after that, operate on the project from the mounted directory whenever possible instead of opening the remote directory directly through Remote-SSH.
sudo mkdir -p /mnt/rdkx
sudo mount -t cifs //RDKX_IP/antigravity /mnt/rdkx \
-o username=youruser,password=yourpass,iocharset=utf8,vers=3.0 # Mount the shared directoryThis command maps the project directory on the board to a local path so that the IDE, interpreter, and build scripts can all use a consistent location.
The recommended workflow is “edit in the mounted directory, execute in the board terminal”
A safer practice is to expose the source code through the Samba share, work from the locally mounted directory in the editor, and still execute the program from a native terminal on the RDK X board. This preserves the native ARM runtime environment while reducing interference from Remote-SSH in path resolution and extension behavior.
cd /data/antigravity
python3 main.py # Run the AI project entry point in the board's native terminalThis approach provides the best chance of keeping the runtime interpreter, shared libraries, and CPU instruction set aligned with the target device.
You should clean caches and bad artifacts before changing code
Many SIGILL fixes fail because developers change the access method but do not remove previously generated invalid caches. This is especially common in Python AI projects, Node native extensions, or C++ plugin-based projects, where mixed local and remote workflows easily leave behind files built for the wrong architecture.
Run a minimal cleanup first
find . -name "__pycache__" -type d -exec rm -rf {} + # Remove Python caches
find . -name "*.so" -delete # Delete suspicious native extensions
find . -name "build" -type d -exec rm -rf {} + # Remove build directoriesThis cleanup prevents the system from continuing to reuse compiled binaries that do not match the target architecture.
The page images and decorative elements do not provide reusable technical evidence
The original Markdown includes many CSDN decorative assets, avatars, ads, and site logos. These are not technical evidence related to the issue itself and should not be part of the core analysis.
 AI Visual Insight: This image is actually an ad slot or site promotional asset rather than a crash log, terminal output, architecture diagram, or mount flow illustration. It provides no valid technical evidence about the SIGILL root cause, ARM instruction-set compatibility, or Samba mount paths.
This approach works by separating the editing path from the execution path
On ARM boards like RDK X, the biggest risk is that the host-side toolchain quietly leaks into runtime behavior. The Samba mount strategy works because it makes file synchronization more transparent while leaving execution responsibility on the target device itself. That helps prevent x86-generated artifacts, IDE extension agents, or the wrong interpreter from contaminating the ARM runtime environment.
If the issue still persists, continue checking these three areas: whether the target program downloaded a precompiled package for the wrong architecture, whether the model inference framework pulled in an x86 .so, and whether environment variables such as PATH, LD_LIBRARY_PATH, or PYTHONPATH were rewritten by Remote-SSH.
FAQ answers are structured below
Q1: Why does the same code crash under Remote-SSH but run normally in the board’s local terminal?
A: The difference is usually not in the source code. It is typically in interpreter selection, dynamic library search order, extension agents, and cache directories. Remote-SSH changes these contexts and may cause the ARM process to load the wrong binary dependencies.
Q2: Why can a Samba mount fix SIGILL instead of only affecting transfer speed?
A: It fixes file access semantics and build artifact consistency. With a local mount, project reads, writes, caches, indexing, and tool access paths become more stable, which reduces the chance of consuming heterogeneous artifacts by mistake.
Q3: If SIGILL still happens after mounting, what should I check next?
A: Start with the outputs of uname -m, file, and ldd to confirm the architecture of the main program and .so files. Then clear caches. Finally, verify that the Python virtual environment, precompiled wheels, environment variables, and extensions are not still pointing to the wrong platform.
[AI Readability Summary]
This article reconstructs the SIGILL crash issue that occurs when running Antigravity AI through VS Code Remote-SSH on an RDK X board with an ARM architecture. It presents a stable fix path based on a locally mounted Samba network share, and explains the mechanism, configuration steps, validation process, and common pitfalls.