mirror of
https://github.com/THU-MIG/yolov10.git
synced 2025-05-23 21:44:22 +08:00
Command injection and Path traversal security fixes (#888)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
parent
365c2ef481
commit
a5a3ce88b3
@ -54,7 +54,7 @@ for orientation in ExifTags.TAGS.keys():
|
|||||||
def get_hash(paths):
|
def get_hash(paths):
|
||||||
# Returns a single hash value of a list of paths (files or dirs)
|
# Returns a single hash value of a list of paths (files or dirs)
|
||||||
size = sum(os.path.getsize(p) for p in paths if os.path.exists(p)) # sizes
|
size = sum(os.path.getsize(p) for p in paths if os.path.exists(p)) # sizes
|
||||||
h = hashlib.md5(str(size).encode()) # hash sizes
|
h = hashlib.sha256(str(size).encode()) # hash sizes
|
||||||
h.update(''.join(paths).encode()) # hash paths
|
h.update(''.join(paths).encode()) # hash paths
|
||||||
return h.hexdigest() # return hash
|
return h.hexdigest() # return hash
|
||||||
|
|
||||||
|
@ -44,7 +44,7 @@ def img2label_paths(img_paths):
|
|||||||
def get_hash(paths):
|
def get_hash(paths):
|
||||||
# Returns a single hash value of a list of paths (files or dirs)
|
# Returns a single hash value of a list of paths (files or dirs)
|
||||||
size = sum(os.path.getsize(p) for p in paths if os.path.exists(p)) # sizes
|
size = sum(os.path.getsize(p) for p in paths if os.path.exists(p)) # sizes
|
||||||
h = hashlib.md5(str(size).encode()) # hash sizes
|
h = hashlib.sha256(str(size).encode()) # hash sizes
|
||||||
h.update("".join(paths).encode()) # hash paths
|
h.update("".join(paths).encode()) # hash paths
|
||||||
return h.hexdigest() # return hash
|
return h.hexdigest() # return hash
|
||||||
|
|
||||||
|
@ -5,6 +5,7 @@ Simple training loop; Boilerplate that could apply to any arbitrary neural netwo
|
|||||||
|
|
||||||
import os
|
import os
|
||||||
import subprocess
|
import subprocess
|
||||||
|
import sys
|
||||||
import time
|
import time
|
||||||
from collections import defaultdict
|
from collections import defaultdict
|
||||||
from copy import deepcopy
|
from copy import deepcopy
|
||||||
@ -28,10 +29,10 @@ from ultralytics.yolo.utils import (DEFAULT_CFG, LOGGER, RANK, SETTINGS, TQDM_BA
|
|||||||
yaml_save)
|
yaml_save)
|
||||||
from ultralytics.yolo.utils.autobatch import check_train_batch_size
|
from ultralytics.yolo.utils.autobatch import check_train_batch_size
|
||||||
from ultralytics.yolo.utils.checks import check_file, check_imgsz, print_args
|
from ultralytics.yolo.utils.checks import check_file, check_imgsz, print_args
|
||||||
from ultralytics.yolo.utils.dist import ddp_cleanup, generate_ddp_command
|
from ultralytics.yolo.utils.dist import ddp_cleanup, generate_ddp_file, find_free_network_port
|
||||||
from ultralytics.yolo.utils.files import get_latest_run, increment_path
|
from ultralytics.yolo.utils.files import get_latest_run, increment_path
|
||||||
from ultralytics.yolo.utils.torch_utils import (EarlyStopping, ModelEMA, de_parallel, init_seeds, one_cycle,
|
from ultralytics.yolo.utils.torch_utils import (EarlyStopping, ModelEMA, de_parallel, init_seeds, one_cycle,
|
||||||
select_device, strip_optimizer)
|
select_device, strip_optimizer, TORCH_1_9)
|
||||||
|
|
||||||
|
|
||||||
class BaseTrainer:
|
class BaseTrainer:
|
||||||
@ -174,13 +175,18 @@ class BaseTrainer:
|
|||||||
|
|
||||||
# Run subprocess if DDP training, else train normally
|
# Run subprocess if DDP training, else train normally
|
||||||
if world_size > 1 and "LOCAL_RANK" not in os.environ:
|
if world_size > 1 and "LOCAL_RANK" not in os.environ:
|
||||||
command = generate_ddp_command(world_size, self)
|
# cmd, file = generate_ddp_command(world_size, self) # security vulnerability in Snyk scans
|
||||||
|
file = generate_ddp_file(self) if sys.argv[0].endswith('yolo') else os.path.abspath(sys.argv[0])
|
||||||
|
torch_distributed_cmd = "torch.distributed.run" if TORCH_1_9 else "torch.distributed.launch"
|
||||||
|
cmd = [
|
||||||
|
sys.executable, "-m", torch_distributed_cmd, "--nproc_per_node", f"{world_size}", "--master_port",
|
||||||
|
f"{find_free_network_port()}", file] + sys.argv[1:]
|
||||||
try:
|
try:
|
||||||
subprocess.run(command)
|
subprocess.run(cmd, check=True)
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
self.console(e)
|
self.console.warning(e)
|
||||||
finally:
|
finally:
|
||||||
ddp_cleanup(command, self)
|
ddp_cleanup(self, file)
|
||||||
else:
|
else:
|
||||||
self._do_train(int(os.getenv("RANK", -1)), world_size)
|
self._do_train(int(os.getenv("RANK", -1)), world_size)
|
||||||
|
|
||||||
|
@ -44,21 +44,15 @@ def generate_ddp_file(trainer):
|
|||||||
|
|
||||||
def generate_ddp_command(world_size, trainer):
|
def generate_ddp_command(world_size, trainer):
|
||||||
import __main__ # noqa local import to avoid https://github.com/Lightning-AI/lightning/issues/15218
|
import __main__ # noqa local import to avoid https://github.com/Lightning-AI/lightning/issues/15218
|
||||||
file_name = os.path.abspath(sys.argv[0])
|
file = generate_ddp_file(trainer) if sys.argv[0].endswith('yolo') else os.path.abspath(sys.argv[0])
|
||||||
using_cli = not file_name.endswith(".py")
|
|
||||||
if using_cli:
|
|
||||||
file_name = generate_ddp_file(trainer)
|
|
||||||
torch_distributed_cmd = "torch.distributed.run" if TORCH_1_9 else "torch.distributed.launch"
|
torch_distributed_cmd = "torch.distributed.run" if TORCH_1_9 else "torch.distributed.launch"
|
||||||
return [
|
cmd = [
|
||||||
sys.executable, "-m", torch_distributed_cmd, "--nproc_per_node", f"{world_size}", "--master_port",
|
sys.executable, "-m", torch_distributed_cmd, "--nproc_per_node", f"{world_size}", "--master_port",
|
||||||
f"{find_free_network_port()}", file_name] + sys.argv[1:]
|
f"{find_free_network_port()}", file] + sys.argv[1:]
|
||||||
|
return cmd, file
|
||||||
|
|
||||||
|
|
||||||
def ddp_cleanup(command, trainer):
|
def ddp_cleanup(trainer, file):
|
||||||
# delete temp file if created
|
# delete temp file if created
|
||||||
tempfile_suffix = f"{id(trainer)}.py"
|
if f"{id(trainer)}.py" in file: # if temp_file suffix in file
|
||||||
if tempfile_suffix in "".join(command):
|
os.remove(file)
|
||||||
for chunk in command:
|
|
||||||
if tempfile_suffix in chunk:
|
|
||||||
os.remove(chunk)
|
|
||||||
break
|
|
||||||
|
Loading…
x
Reference in New Issue
Block a user