๐Ÿ” CVE Alert

CVE-2026-115924

HIGH 8.6

Rembg: Unauthenticated SAM model injection permits local-file disclosure through malicious ONNX graphs

CVSS Score
8.6
EPSS Score
0.0%
EPSS Percentile
0th

Rembg is a tool to remove images background. Prior to 2.0.82, the public /api/remove endpoint passes attacker-controlled extras.sam_model through rembg/commands/s_command.py to rembg/sessions/sam.py, where it is interpolated into SAM filenames and GitHub download URLs passed to pooch.retrieve() without a pinned hash. An unauthenticated attacker can supply a sam_model value combining path traversal with URL fragment syntax to exploit the HTTP request discarding the fragment while the local POSIX path retains it. The first request primes the attacker-selected path tree, and an identical repeated request downloads malicious ONNX encoder and decoder files beside a readable target file. The graphs can load the target through ONNX external data and encode its bytes into the returned PNG mask, disclosing complete files accessible to the rembg process and allowing arbitrary ONNX computation. This issue is fixed in version 2.0.82.

CWE CWE-22
Vendor danielgatis
Product rembg
Published Oct 26, 2026
Stay Ahead of the Next One

Get instant alerts for danielgatis rembg

Be the first to know when new high vulnerabilities affecting danielgatis rembg are published โ€” delivered to Slack, Telegram or Discord.

Get Free Alerts โ†’ Free ยท No credit card ยท 60 sec setup

CVSS v3 Breakdown

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L
Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
Low
Availability
Low

Affected Versions

danielgatis / rembg
< 2.0.82

References

NVD โ†— CVE.org โ†— EPSS Data โ†—
github.com: https://github.com/danielgatis/rembg/security/advisories/GHSA-qr6x-7v33-6qmg github.com: https://github.com/danielgatis/rembg/commit/b2758c6b39bb2b02df90a03128110339476984d3 github.com: https://github.com/danielgatis/rembg/releases/tag/v2.0.82