High severity · published Oct 26, 2026
CVE-2026-115924
Rembg: Unauthenticated SAM model injection permits local-file disclosure through malicious ONNX graphs
New
8.6
CVSS
0.4%
EPSS
No
On KEV
Description
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.
CVSS vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
None
Confidentiality
High
Integrity
Low
Availability
Low
Scope
Unchanged
Exploitation
Is it being used?
Exploit prediction (EPSS)0.4% · higher than 33% of CVEs
Exploited in the wildNo evidence yet
CISA KEVNot listed
Ransomware campaign useNot known
Affected products
Which versions
RE
rembg · danielgatis
< 2.0.82 · source: vendor
References
NVD
https://nvd.nist.gov/vuln/detail/CVE-2026-115924
CVE.org
https://www.cve.org/CVERecord?id=CVE-2026-115924
github.com
https://github.com/danielgatis/rembg/commit/b2758c6b39bb2b02df90a03128110339476984d3
github.com
https://github.com/danielgatis/rembg/releases/tag/v2.0.82
github.com
https://github.com/danielgatis/rembg/security/advisories/GHSA-qr6x-7v33-6qmg
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Rembg has a Path Traversal via Custom Model Loading
