Answer in brief
CVE-2026-79785 records a Unknown severity vulnerability in X-AnyLabeling before 4.0.0-beta.9 Improper Certificate Validation in Model Downloads. The current sources do not mark it as known exploited. The current feed maps CVHub520/X-AnyLabeling (generic), CVHub520/X-AnyLabeling (generic). Check affected ranges and fixed versions before updating.
Analysis pending evidence review
HOL Guard separates source facts from reviewed analysis. See the methodology.
A CVSS score is not reported in the current record. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.
Analysis status
Analysis pending evidence review
Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.
The current feed maps CVHub520/X-AnyLabeling (generic), CVHub520/X-AnyLabeling (generic). Check affected ranges and fixed versions before updating.
| Package | Affected range | Fixed version |
|---|---|---|
| CVHub520/X-AnyLabelinggeneric | >=0 <4.0.0-beta.9 | 4.0.0-beta.9 |
| CVHub520/X-AnyLabelinggeneric | >=0 <4.0.0b9 | 4.0.0b9 |
Published upstream
Aug 25, 2026
Evidence: source:cvelist:source_dates:source-dates:recordSource modified
Aug 25, 2026
Evidence: source:cvelist:source_dates:source-dates:recordFirst seen by HOL
Aug 25, 2026
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.
Quoted source text, attributed separately from HOL analysis.