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License: Apache License 2.0

Starlark 4.57% C++ 82.29% Shell 0.02% Java 2.76% Python 10.30% Rust 0.06%

federated-compute's Introduction

Federated Compute Platform

This repository hosts code for executing federated programs and computations.

Definitions

A federated computation is a set of processing steps that run on a server and set of clients, where each step is either

local processing of values on the client or server or
transport which moves values via
- broadcast (server-to-clients)
- select (client-server response)
- aggregate (clients-to-server). A federated computation invoked by a central coordinator returns one or more aggregates.

A federated program is a set of processing steps run by a central coordinator that include one or more invocations of federated computation, transformations of computation results, and releases of aggregate values to the engineer/analyst who invoked the program.

To learn more about these concepts, check out:

Infrastructure

At Google, federated programs and computations are authored in TensorFlow Federated, compiled to deployable artifacts, and run in a distributed system consisting of a central coordinator, and a set of devices such as phones. The TFF repository contains infrastructure for authoring and simulating federated programs and computations.

This repository hosts infrastructure for compiling and running federated programs and computations in the cross-device setting. We are actively working on open sourcing the core components of our production infrastructure, with a focus on privacy-sensitive code-paths such as the pipeline for compiling deployable artifacts from TFF computations, client-side processing, and server-side aggregation logic.

As of 12/7/2022, parts of the repository - in particular, code in the client/ directory, and the service & data format definitions in proto/ - are used in production in Google's federated learning infrastructure. Other parts - notably, production server side infrastructure - have not yet been open sourced due to its dependencies on proprietary infrastructure, and we instead provide a reference / example server implementation in demo/ for demonstration purposes.

The best way to get started is to run the end-to-end demo //fcp/demo:federated_program_test, which will spin up example services, clients, and run a federated program; this test will cover the majority of the code in this repository.

Remote attestation of server-side, TEE-hosted applications

As described in the Confidential Federated Computations paper, this repository hosts a client-side implementation of the ConfidentialAggregations protocol, which uses remotely attested server-side applications that run in a Trusted Execution Environment (TEE).

Clients using this library and which participate in this protocol will verify attestation evidence for the ledger application hosted in the Confidential Federated Compute repository. They will also verify the data access policy that the ledger will enforce, which will specify one or more allowed data transformation applications which are built from that same repository.

Please see fcp/client/attestation/README.md for more details on this process.

Getting Started

Please refer to the instructions in GETTING_STARTED.md.

Disclaimer

This is not an officially supported Google product.

federated-compute's People

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cyberflamego test-mass-forker-org-1 bairuowen aishpattabi jiang-zl lakshaygujjar isabella232 pinkdiamond1 shotsan macasieb doug-leith yuangu002 q-sudhirdeshmukh michalprussak reakkae thecodeofmontecristo

federated-compute's Issues

Demo test failed due to `OSError: read-only filesystem`

I followed the GETTING_STARTED guide and got a successful build.

But the demo test (bazelisk //fcp/demo:federated_program_test --config=clang) failed locally. The test log is pasted as following:

exec ${PAGER:-/usr/bin/less} "$0" || exit 1
Executing tests from //fcp/demo:federated_program_test
-----------------------------------------------------------------------------
2023-04-07 17:14:13.652917: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2023-04-07 17:14:13.690128: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2023-04-07 17:14:13.690429: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-04-07 17:14:14.381273: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
WARNING:tensorflow:From /usr/local/google/home/ryangu/venv/lib/python3.10/site-packages/tensorflow/python/util/deprecation.py:576: calling function (from tensorflow.python.eager.polymorphic_function.polymorphic_function) with experimental_relax_shapes is deprecated and will be removed in a future version.
Instructions for updating:
experimental_relax_shapes is deprecated, use reduce_retracing instead
WARNING:tensorflow:From /usr/local/google/home/ryangu/venv/lib/python3.10/site-packages/tensorflow/python/util/deprecation.py:576: calling function (from tensorflow.python.eager.polymorphic_function.polymorphic_function) with experimental_relax_shapes is deprecated and will be removed in a future version.
Instructions for updating:
experimental_relax_shapes is deprecated, use reduce_retracing instead
Traceback (most recent call last):
  File "/usr/local/google/home/ryangu/.cache/bazel/_bazel_ryangu/6e3f6b9903df237029824c625696458e/sandbox/linux-sandbox/12836/execroot/com_google_fcp/bazel-out/k8-opt/bin/fcp/demo/federated_program_test.runfiles/com_google_fcp/fcp/demo/federated_program_test.py", line 24, in <module>
    import tensorflow_federated as tff
  File "/usr/local/google/home/ryangu/venv/lib/python3.10/site-packages/tensorflow_federated/__init__.py", line 78, in <module>
    backends.native.set_sync_local_cpp_execution_context()
  File "/usr/local/google/home/ryangu/venv/lib/python3.10/site-packages/tensorflow_federated/python/core/backends/native/execution_contexts.py", line 164, in set_sync_local_cpp_execution_context
    context = create_sync_local_cpp_execution_context(
  File "/usr/local/google/home/ryangu/venv/lib/python3.10/site-packages/tensorflow_federated/python/core/backends/native/execution_contexts.py", line 148, in create_sync_local_cpp_execution_context
    factory = executor_factory.local_cpp_executor_factory(
  File "/usr/local/google/home/ryangu/venv/lib/python3.10/site-packages/tensorflow_federated/python/core/impl/executor_stacks/executor_factory.py", line 103, in local_cpp_executor_factory
    _decompress_file(compressed_path, binary_path)
  File "/usr/local/google/home/ryangu/venv/lib/python3.10/site-packages/tensorflow_federated/python/core/impl/executor_stacks/executor_factory.py", line 55, in _decompress_file
    with open(output_path, 'wb') as binary_file:
OSError: [Errno 30] Read-only file system: '/usr/local/google/home/ryangu/venv/lib/python3.10/site-packages/tensorflow_federated/python/core/impl/executor_stacks/../../../../data/worker_binary'

I only used sudo on two apt install commands, as instructed:
sudo apt install -y git gcc python3 python3-dev python3-venv and
sudo apt install -y clang lld libc++-dev libc++abi-dev

Cannot install from pip due to conflicting absl-py dependency

Hi folks!

When installing the latest available commit in this repository (8d4b013673f87ccd35c9ec95a97749a5ff83f467), I get the following dependency conflict error:

ERROR: Cannot install -r requirements.txt (line 27), -r requirements.txt (line 28) and absl-py==2.* and >=2.0 because these package versions have conflicting dependencies.

The conflict is caused by:
    The user requested absl-py==2.* and >=2.0
    tensorflow 2.14.0 depends on absl-py>=1.0.0
    tensorflow-federated 0.68.0 depends on absl-py==1.* and >=1.0

To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip attempt to solve the dependency conflict

ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts

This happens both on a x86_64 Linux with Ubuntu 22.04, and on a M1 macOS

To reproduce, from your shell (I tested with Docker):

Run a container to isolate the environment: docker run --rm -it ubuntu:22.04
Update package repo: apt update
Install build dependencies and cURL: apt install -y git gcc python3 python3-dev python3-venv curl
Install bazelisk: curl --output /usr/local/bin/bazelisk-linux-amd64 https://github.com/bazelbuild/bazelisk/releases/download/v1.19.0/bazelisk-linux-amd64
Make bazelisk executable: chmod a+x /usr/local/bin/bazelisk-linux-amd64
Create a venv: python3 -m venv venv
Activate the venv: source venv/bin/activate
Update pip: pip install --upgrade pip
Clone the federated-compute repository: git clone https://github.com/google/federated-compute.git
Change the working directory: cd federated-compute
Install federated-compute: pip install -r requirements.txt

Thanks for your support!

request: include gRPC demo server

The demo uses an http federated compute protocol. There is also a gRPC federated API that the client supports. It would be good to also include a demo server that supports a gRPC client.

Missing README.md file

There is no README file in the following folder
https://github.com/tensorflow/federated/blob/main/tensorflow_federated/python/program
so the link to the Federated Program API in TFF
404's

where can i find the Class which name is fcp.client.tasks.Task？

`bazel build //fcp/artifact_building:federated_compute_plan_builder` fails with compile error

Following the GETTING_STARTED guide, I successfully installed all dependencies in requirements.txt and verified with python3 -c "import tensorflow_federated":

2023-10-20 23:47:49.801507: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2023-10-20 23:47:49.862608: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2023-10-20 23:47:49.863466: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-10-20 23:47:51.225016: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT

Then, I run bazel build //fcp/artifact_building:federated_compute_plan_builder and got the following build error:

INFO: Analyzed target //fcp/artifact_building:federated_compute_plan_builder (181 packages loaded, 15873 targets configured).
INFO: Found 1 target...
ERROR: /usr/local/google/home/ryangu/.cache/bazel/_bazel_ryangu/15955890b671f3e842c09329bd3a9df5/external/org_tensorflow/tensorflow/tsl/lib/io/BUILD:204:11: Compiling tensorflow/tsl/lib/io/cache.cc [for tool] failed: (Exit 1): gcc failed: error executing command (from target @org_tensorflow//tensorflow/tsl/lib/io:cache) /usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections ... (remaining 49 arguments skipped)

Use --sandbox_debug to see verbose messages from the sandbox and retain the sandbox build root for debugging
In file included from external/org_tensorflow/tensorflow/tsl/lib/io/cache.cc:16:
external/org_tensorflow/tensorflow/tsl/lib/io/cache.h:99:11: error: 'uint64_t' does not name a type
   99 |   virtual uint64_t NewId() = 0;
      |           ^~~~~~~~
external/org_tensorflow/tensorflow/tsl/lib/io/cache.h:20:1: note: 'uint64_t' is defined in header '<cstdint>'; did you forget to '#include <cstdint>'?
   19 | #include "tensorflow/tsl/platform/stringpiece.h"
  +++ |+#include <cstdint>
   20 | 
external/org_tensorflow/tensorflow/tsl/lib/io/cache.cc:391:12: error: 'uint64_t tsl::table::{anonymous}::ShardedLRUCache::NewId()' marked 'override', but does not override
  391 |   uint64_t NewId() override {
      |            ^~~~~
Target //fcp/artifact_building:federated_compute_plan_builder failed to build

Note:

Python version: 3.9.17
Run at commit: 15379115139fca22e6c2ea1e047826ca2e3f3fa5

linker error

I commented out the Werror flag in the make files to get past the last issue, but now compilation fails with a linker error:

bazel-out/k8-opt/bin/fcp/client/cache/_objs/file_backed_resource_cache/file_backed_resource_cache.o:file_backed_resource_cache.cc:function fcp::client::cache::FileBackedResourceCache::CleanUp(std::optional, fcp::client::cache::CacheManifest&): error: undefined reference to 'std::filesystem::file_size(std::filesystem::__cxx11::path const&, std::error_code&)'

bazel-out/k8-opt/bin/fcp/client/opstats/_objs/pds_backed_opstats_db/pds_backed_opstats_db.o:pds_backed_opstats_db.cc:function fcp::client::opstats::PdsBackedOpStatsDb::Create(std::__cxx11::basic_string<char, std::char_traits, std::allocator > const&, absl::lts_20220623::Duration, fcp::client::LogManager&, long): error: undefined reference to 'std::filesystem::__cxx11::path::has_filename() const'

(and many similar errors). looks like the c++ std lib need to be added to the linker options for file_backed_resource_cache.o and pds_backed_opstats_db.o?

Build error: `use of undeclared identifier 'ABSL_INTERNAL_ASSUME'`

Follow the GETTING_STARTED guide to run the test with Clang.

The full error output is:

Compiling fcp/tensorflow/delete_file_op.cc failed: (Exit 1): clang failed: error executing command (from target //fcp/tensorflow:_delete_file_op.so_lib) /usr/lib/llvm-14/bin/clang -U_FORTIFY_SOURCE -fstack-protector -Wall -Wthread-safety -Wself-assign -Wunused-but-set-parameter -Wno-free-nonheap-object -fcolor-diagnostics -fno-omit-frame-pointer -g0 ... (remaining 48 arguments skipped)

Use --sandbox_debug to see verbose messages from the sandbox and retain the sandbox build root for debugging
In file included from fcp/tensorflow/delete_file_op.cc:16:
In file included from external/system_provided_tf/headers/tensorflow/core/framework/op_kernel.h:26:
In file included from external/system_provided_tf/headers/tensorflow/core/framework/allocator.h:26:
In file included from external/system_provided_tf/headers/tensorflow/core/framework/numeric_types.h:27:
In file included from external/system_provided_tf/headers/tensorflow/core/platform/types.h:23:
In file included from external/system_provided_tf/headers/tensorflow/core/platform/tstring.h:24:
In file included from external/system_provided_tf/headers/tensorflow/core/platform/cord.h:25:
In file included from external/system_provided_tf/headers/tensorflow/core/platform/default/cord.h:22:
In file included from external/system_provided_tf/headers/absl/strings/cord.h:82:
external/system_provided_tf/headers/absl/strings/internal/cord_rep_btree.h:734:5: error: use of undeclared identifier 'ABSL_INTERNAL_ASSUME'
    ABSL_INTERNAL_ASSUME(new_end <= kMaxCapacity);

My configs:
Python: Python 3.10.9
Clang:

Debian clang version 14.0.6
Target: x86_64-pc-linux-gnu
Thread model: posix
InstalledDir: /usr/bin

Bazelisk: bazel 6.1.1
tensorflow & tensorflow_federated are installed via requirements.txt

Platform doesn't support GCC 11

When trying to build the platform from Ubuntu 22.04 LTS, the build fails. It's due to different versions of GCC. In Debian, we have access to GCC 10, but in Ubuntu, we have access to GCC 11.

Here is the stacktrace I get when I try to build the platform on ubuntu:

==> googlecompute.federated-compute-platform: ERROR: /home/packer/.cache/bazel/_bazel_packer/ca0f3d8f2b007992a7f5dcb18911d5f2/external/boringssl/BUILD:130:11: Compiling src/third_party/fiat/curve25519.c failed: (Exit 1): gcc failed: error executing command /usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections ... (remaining 36 arguments skipped)
==> googlecompute.federated-compute-platform:
==> googlecompute.federated-compute-platform: Use --sandbox_debug to see verbose messages from the sandbox and retain the sandbox build root for debugging
==> googlecompute.federated-compute-platform: external/boringssl/src/third_party/fiat/curve25519.c:511:57: error: argument 2 of type 'const uint8_t[32]' {aka 'const unsigned char[32]'} with mismatched bound [-Werror=array-parameter=]
==> googlecompute.federated-compute-platform:   511 | int x25519_ge_frombytes_vartime(ge_p3 *h, const uint8_t s[32]) {
==> googlecompute.federated-compute-platform:       |                                           ~~~~~~~~~~~~~~^~~~~
==> googlecompute.federated-compute-platform: In file included from external/boringssl/src/third_party/fiat/curve25519.c:41:
==> googlecompute.federated-compute-platform: external/boringssl/src/third_party/fiat/internal.h:117:58: note: previously declared as 'const uint8_t *' {aka 'const unsigned char *'}
==> googlecompute.federated-compute-platform:   117 | int x25519_ge_frombytes_vartime(ge_p3 *h, const uint8_t *s);
==> googlecompute.federated-compute-platform:       |                                           ~~~~~~~~~~~~~~~^
==> googlecompute.federated-compute-platform: external/boringssl/src/third_party/fiat/curve25519.c:831:57: error: argument 2 of type 'const uint8_t *' {aka 'const unsigned char *'} declared as a pointer [-Werror=array-parameter=]
==> googlecompute.federated-compute-platform:   831 | void x25519_ge_scalarmult_base(ge_p3 *h, const uint8_t *a) {
==> googlecompute.federated-compute-platform:       |                                          ~~~~~~~~~~~~~~~^
==> googlecompute.federated-compute-platform: In file included from external/boringssl/src/third_party/fiat/curve25519.c:41:
==> googlecompute.federated-compute-platform: external/boringssl/src/third_party/fiat/internal.h:125:56: note: previously declared as an array 'const uint8_t[32]' {aka 'const unsigned char[32]'}
==> googlecompute.federated-compute-platform:   125 | void x25519_ge_scalarmult_base(ge_p3 *h, const uint8_t a[32]);
==> googlecompute.federated-compute-platform:       |                                          ~~~~~~~~~~~~~~^~~~~
==> googlecompute.federated-compute-platform: cc1: all warnings being treated as errors

How to use android PCS(Private compute service) as client with FCP?

How to combine PCS (Private-compute-services) and FCP effectively for federated learning and analytics? could you please share any helpful blogs or resources on this topic?

build error

When building the compiler exits with error:

In member function 'const void* fcp::aggregation::VectorData::data() const':
./fcp/aggregation/core/vector_data.h:39:52: error: 'const fcp::aggregation::VectorData::vector' has not been declared

full output is:

ERROR: /home/doug/federated-compute/fcp/aggregation/core/BUILD:150:11: Compiling fcp/aggregation/core/federated_sum.cc failed: (Exit 1): gcc failed: error executing command
(cd /root/.cache/bazel/bazel_root/a2d1cfe108fb6ecf8584c66084ab27f5/sandbox/processwrapper-sandbox/11649/execroot/com_google_fcp &&
exec env -
PATH=/root/.cache/bazelisk/downloads/bazelbuild/bazel-5.3.0-linux-x86_64/bin:/home/doug/federated-compute/venv/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
PWD=/proc/self/cwd
TF2_BEHAVIOR=1
/usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections -fdata-sections '-std=c++0x' -MD -MF bazel-out/k8-opt/bin/fcp/aggregation/core/objs/federated_sum/federated_sum.pic.d '-frandom-seed=bazel-out/k8-opt/bin/fcp/aggregation/core/objs/federated_sum/federated_sum.pic.o' -fPIC -iquote . -iquote bazel-out/k8-opt/bin -iquote external/com_google_protobuf -iquote bazel-out/k8-opt/bin/external/com_google_protobuf -iquote external/zlib -iquote bazel-out/k8-opt/bin/external/zlib -iquote external/com_google_absl -iquote bazel-out/k8-opt/bin/external/com_google_absl -isystem external/com_google_protobuf/src -isystem bazel-out/k8-opt/bin/external/com_google_protobuf/src -isystem external/zlib -isystem bazel-out/k8-opt/bin/external/zlib '-std=c++17' -fno-canonical-system-headers -Wno-builtin-macro-redefined '-D__DATE="redacted"' '-D__TIMESTAMP_="redacted"' '-D__TIME__="redacted"' -c fcp/aggregation/core/federated_sum.cc -o bazel-out/k8-opt/bin/fcp/aggregation/core/_objs/federated_sum/federated_sum.pic.o)

Configuration: 049f85fc0d6dedd96dfa70b148f22be32341167164f149dfc9688cc225c2af15

Execution platform: @local_execution_config_platform//:platform

Use --sandbox_debug to see verbose messages from the sandbox and retain the sandbox build root for debugging
In file included from ./fcp/aggregation/core/agg_vector_aggregator.h:26,
from fcp/aggregation/core/federated_sum.cc:20:
./fcp/aggregation/core/vector_data.h: In member function 'const void* fcp::aggregation::VectorData::data() const':
./fcp/aggregation/core/vector_data.h:39:52: error: 'const fcp::aggregation::VectorData::vector' has not been declared
const void* data() const override { return this->vector::data(); }
^~~~~~
Target //fcp/demo:federated_program_test failed to build

start test demo failed with errors

System

win11

python

3.10

submitted command

bazelisk test //fcp/demo:federated_program_test

error messages

Repository rule http_archive defined at:
  C:/users/corgi/_bazel_corgi/hiuillts/external/bazel_tools/tools/build_defs/repo/http.bzl:372:31: in <toplevel>
INFO: repository @org_tensorflow' used the following cache hits instead of downloading the corresponding file.
 * Hash '99c732b92b1b37fc243a559e02f9aef5671771e272758aa4aec7f34dc92dac48' for https://github.com/tensorflow/tensorflow/archive/v2.11.0.tar.gz
If the definition of 'repository @org_tensorflow' was updated, verify that the hashes were also updated.
ERROR: An error occurred during the fetch of repository 'org_tensorflow':
   Traceback (most recent call last):
        File "C:/users/corgi/_bazel_corgi/hiuillts/external/bazel_tools/tools/build_defs/repo/http.bzl", line 143, column 10, in _http_archive_impl
                patch(ctx, auth = auth)
        File "C:/users/corgi/_bazel_corgi/hiuillts/external/bazel_tools/tools/build_defs/repo/utils.bzl", line 180, column 21, in patch
                fail("Error applying patch %s:\n%s%s" %
Error in fail: Error applying patch @//fcp/patches:tensorflow_googletest.patch:
The system cannot find the path specified.

ERROR: E:/workspace/repo/federated-compute/WORKSPACE:147:13: fetching http_archive rule //external:org_tensorflow: Traceback (most recent call last):
        File "C:/users/corgi/_bazel_corgi/hiuillts/external/bazel_tools/tools/build_defs/repo/http.bzl", line 143, column 10, in _http_archive_impl
                patch(ctx, auth = auth)
        File "C:/users/corgi/_bazel_corgi/hiuillts/external/bazel_tools/tools/build_defs/repo/utils.bzl", line 180, column 21, in patch
                fail("Error applying patch %s:\n%s%s" %
Error in fail: Error applying patch @//fcp/patches:tensorflow_googletest.patch:
The system cannot find the path specified.

ERROR: Error computing the main repository mapping: no such package '@org_tensorflow//tensorflow': Error applying patch @//fcp/patches:tensorflow_googletest.patch:
The system cannot find the path specified.

Loading:

E:\WorkSpace\repo\federated-compute>

related screenshot

any ideas?😁

compile error

build exits with errors:

ERROR: /root/.cache/bazel/_bazel_root/a2d1cfe108fb6ecf8584c66084ab27f5/external/boringssl/BUILD:161:11: Compiling src/crypto/evp/p_x25519.c failed: (Exit 1): gcc failed: error executing command /usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections ... (remaining 40 arguments skipped)

Use --sandbox_debug to see verbose messages from the sandbox and retain the sandbox build root for debugging
cc1: error: command line option '-std=c++17' is valid for C++/ObjC++ but not for C [-Werror]
cc1: all warnings being treated as errors
ERROR: /root/.cache/bazel/_bazel_root/a2d1cfe108fb6ecf8584c66084ab27f5/external/boringssl/BUILD:161:11: Compiling src/crypto/asn1/a_mbstr.c failed: (Exit 1): gcc failed: error executing command /usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections ... (remaining 40 arguments skipped)

looks like an easy fix.