TorchServe is a tool for serving and scaling PyTorch models in production. TorchServe default configuration lacks proper input validation, enabling third parties to invoke remote HTTP download requests and write files to the disk. This issue could be taken advantage of to compromise the integrity of the system and sensitive data. This issue is present in versions 0.1.0 to 0.8.1. A user is able to load the model of their choice from any URL that they would like to use. The user of TorchServe is responsible for configuring both the allowed_urls and specifying the model URL to be used. A pull request to warn the user when the default value for allowed_urls is used has been merged in PR #2534. TorchServe release 0.8.2 includes this change. Users are advised to upgrade. There are no known workarounds for this issue.
Vulnerable Product | Search on Vulmon | Subscribe to Product |
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pytorch torchserve |
Topics Security Off-Prem On-Prem Software Offbeat Special Features Vendor Voice Vendor Voice Resources Meta, the project's maintainer, shrugs
A trio of now-patched security issues in TorchServe, an open-source tool for scaling PyTorch machine-learning models in production, could lead to server takeover and remote code execution (RCE), according to security researchers. The three CVEs, collectively dubbed "ShellTorch," rendered "tens of thousands of exposed instances" vulnerable, wrote software bill of material management firm Oligo Security's Idan Levcovich, Guy Kaplan, and Gal Elbaz in a report published on Tuesday. Meta, which along...