CVE-2025-0851
published 2025-01-29CVE-2025-0851: A path traversal issue in ZipUtils.unzip and TarUtils.untar in Deep Java Library (DJL) on all platforms allows a bad actor to write files to arbitrary…
PriorityP268critical9.8CVSS 3.1
AVNACLPRNUINSUCHIHAH
EPSS
23.08%
97.5th percentile
A path traversal issue in ZipUtils.unzip and TarUtils.untar in Deep Java Library (DJL) on all platforms allows a bad actor to write files to arbitrary locations.
Affected
1 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| aws | deepjavalibrary | >= 0.1.0 < 0.31.1 | 0.31.1 |
CVSS provenance
nvdv3.19.8CRITICALCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
nvdv4.09.3CRITICALCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
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OSV
Deep Java Library path traversal issue
osv·2025-01-29
CVE-2025-0851 [CRITICAL] Deep Java Library path traversal issue
Deep Java Library path traversal issue
## Summary
[Deep Java Library (DJL)](https://docs.djl.ai/master/index.html) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides a native Java development experience and functions like any other regular Java library.
DJL provides utilities for extracting tar and zip model archives that are used when loading models for use with DJL. These utilities were found to contain issues that do not protect against absolute path traversal during the extraction process.
## Impact
An issue exists with DJL's untar and unzip functionalities. Specifically, it is possible to create an archive on a Windows system, and when extracted on a Ma
GHSA
Deep Java Library path traversal issue
ghsa·2025-01-29
CVE-2025-0851 [CRITICAL] CWE-22 Deep Java Library path traversal issue
Deep Java Library path traversal issue
## Summary
[Deep Java Library (DJL)](https://docs.djl.ai/master/index.html) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides a native Java development experience and functions like any other regular Java library.
DJL provides utilities for extracting tar and zip model archives that are used when loading models for use with DJL. These utilities were found to contain issues that do not protect against absolute path traversal during the extraction process.
## Impact
An issue exists with DJL's untar and unzip functionalities. Specifically, it is possible to create an archive on a Windows system, and when extracted on a Ma
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
2025-01-29
Published