serve: Exposure of Resource to Wrong Sphere
CVE-2024-35199 is a high-severity exposure of resource to wrong sphere vulnerability in serve from PyTorch, with a CVSS 3.1 base score of 8.2 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, without any action from a user. Affected serve versions: >= 0.3.0, < 0.11.0. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 0.64% chance of exploitation within 30 days, higher than 51% of scored CVEs.
High severity with no evidence of exploitation so far.
What to do
- Update torchserve to 0.11.0 or a later version.
- Read the advisory on github.com for workarounds and exact fixed builds.
- Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| Pytorch | serve | >= 0.3.0, < 0.11.0 | Not stated |
| Pytorch | torchserve | 0.3.0 up to, but not including, 0.11.0 | 0.11.0 |
Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.
How the severity score breaks down
- Attack vector
- NetworkCan be exploited remotely over a network, including the internet.
- Attack complexity
- LowNo special conditions are needed; the attack works reliably.
- Privileges required
- NoneNo account or login is needed.
- User interaction
- NoneNo action by a victim is required.
- Scope
- UnchangedImpact stays within the vulnerable component.
- Confidentiality
- LowSome restricted data can be read.
- Integrity
- NoneNothing can be modified.
- Availability
- HighThe component can be taken down completely.
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:H. Scored by CNA (github.com).
Official description
TorchServe is a flexible and easy-to-use tool for serving and scaling PyTorch models in production. In affected versions the two gRPC ports 7070 and 7071, are not bound to [localhost](http://localhost/) by default, so when TorchServe is launched, these two interfaces are bound to all interfaces. Customers using PyTorch inference Deep Learning Containers (DLC) through Amazon SageMaker and EKS are not affected. This issue in TorchServe has been fixed in PR #3083. TorchServe release 0.11.0 includes the fix to address this vulnerability. Users are advised to upgrade. There are no known workarounds for this vulnerability.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Exposure of Resource to Wrong Sphere
The product exposes a resource to the wrong control sphere, providing unintended actors with inappropriate access to the resource.
More Exposure of Resource to Wrong Sphere vulnerabilities (CWE-668)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: none, automatable: yes, technical impact: partial).
- Record last changed materially (score, affected products, status or references).
References
Advisories
- github.com/pytorch/serve/security/advisories/GHSA-hhpg-v63p-wp7wThird Party Advisory
Patches and release notes
Other vulnerabilities in serve
- 9.8 Critical severity
- 9.8 Critical severity
Recent Exposure of Resource to Wrong Sphere vulnerabilities
- 7.1 High severity
- 9.3 Critical severity
- 7.1 High severity
- 7.8 High severity
- 7.1 High severity
- 7.1 High severity
Spotted an error? Tell us.