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Security Fix for Arbitrary Code Execution - huntr.dev (#1672)

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* fixed arbitary code execution

* Update train.py

* Full to Safe

Co-authored-by: Asjid Kalam <asjid.kalam@gmail.com>
Co-authored-by: Jamie Slome <jamie@418sec.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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huntr.dev | the place to protect open source 2021-01-25 17:39:34 +00:00 committed by GitHub
parent 9f4e853c60
commit cf5db95953
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1 changed files with 3 additions and 3 deletions
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train.py
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@ -59,7 +59,7 @@ def train(hyp, opt, device, tb_writer=None, wandb=None):
cuda = device.type != 'cpu' cuda = device.type != 'cpu'
init_seeds(2 + rank) init_seeds(2 + rank)
with open(opt.data) as f: with open(opt.data) as f:
data_dict = yaml.load(f, Loader=yaml.FullLoader) # data dict data_dict = yaml.load(f, Loader=yaml.SafeLoader) # data dict
with torch_distributed_zero_first(rank): with torch_distributed_zero_first(rank):
check_dataset(data_dict) # check check_dataset(data_dict) # check
train_path = data_dict['train'] train_path = data_dict['train']
@ -476,7 +476,7 @@ if __name__ == '__main__':
assert os.path.isfile(ckpt), 'ERROR: --resume checkpoint does not exist' assert os.path.isfile(ckpt), 'ERROR: --resume checkpoint does not exist'
apriori = opt.global_rank, opt.local_rank apriori = opt.global_rank, opt.local_rank
with open(Path(ckpt).parent.parent / 'opt.yaml') as f: with open(Path(ckpt).parent.parent / 'opt.yaml') as f:
opt = argparse.Namespace(**yaml.load(f, Loader=yaml.FullLoader)) # replace opt = argparse.Namespace(**yaml.load(f, Loader=yaml.SafeLoader)) # replace
opt.cfg, opt.weights, opt.resume, opt.global_rank, opt.local_rank = '', ckpt, True, *apriori # reinstate opt.cfg, opt.weights, opt.resume, opt.global_rank, opt.local_rank = '', ckpt, True, *apriori # reinstate
logger.info('Resuming training from %s' % ckpt) logger.info('Resuming training from %s' % ckpt)
else: else:
@ -500,7 +500,7 @@ if __name__ == '__main__':
# Hyperparameters # Hyperparameters
with open(opt.hyp) as f: with open(opt.hyp) as f:
hyp = yaml.load(f, Loader=yaml.FullLoader) # load hyps hyp = yaml.load(f, Loader=yaml.SafeLoader) # load hyps
# Train # Train
logger.info(opt) logger.info(opt)