CVHub520 X-AnyLabeling Model Downloader model.py download_with_retry certificate validation

Summaryinfo

A vulnerability marked as problematic has been reported in CVHub520 X-AnyLabeling. Affected is the function download_with_retry of the file anylabeling/services/auto_labeling/model.py of the component Model Downloader. This manipulation causes certificate validation. The identification of this vulnerability is CVE-2026-79785. It is possible to initiate the attack remotely. There is no exploit available.

Detailsinfo

A vulnerability classified as problematic was found in CVHub520 X-AnyLabeling (the affected version is unknown). Affected by this vulnerability is the function download_with_retry of the file anylabeling/services/auto_labeling/model.py of the component Model Downloader. The manipulation with an unknown input leads to a certificate validation vulnerability. The CWE definition for the vulnerability is CWE-295. The product does not validate, or incorrectly validates, a certificate. As an impact it is known to affect integrity. The summary by CVE is:

X-AnyLabeling's model downloader disabled TLS certificate verification. download_with_retry in anylabeling/services/auto_labeling/model.py built a context with ssl._create_unverified_context() and passed it to urllib.request.urlopen, so neither the certificate chain nor the hostname was checked on any model download, and models are fetched over HTTPS from the project's release host. Any party positioned to intercept that connection could therefore answer it with content of their own choosing. The response is written to a .part file and moved into place with os.replace, and the only post-download check, safe_check_model, validates the file's format rather than its provenance: no hash or signature is compared against an expected value. For an ONNX target the substituted file passes onnx.checker.check_model and is then used for inference, so the attacker chooses the model that produces the application's annotations. For a .pth or .pt target, which the shipped SAM2 video, YOLOE, UPN and open_vision configurations use, the check worker calls torch.load without weights_only, so a substituted file is unpickled and executes code of the attacker's choosing on PyTorch releases predating the weights_only default.

It is possible to read the advisory at github.com. This vulnerability is known as CVE-2026-79785 since 08/25/2026. The exploitation appears to be difficult. The attack can be launched remotely. The exploitation doesn't need any form of authentication. Technical details of the vulnerability are known, but there is no available exploit. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 08/25/2026). The attack technique deployed by this issue is T1587.003 according to MITRE ATT&CK.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

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• CVHub520

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• X-AnyLabeling

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CPE 2.2info

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