CVE-2026-115924highCWE-22

CVE-2026-115924: high-severity vulnerability in danielgatis rembg

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

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21Vexday Risk Score

No sign of exploitation. No public exploitation artifact known so far.

ssvc Trackcvss 8.6epss 0.4%
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:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L
Affected products
danielgatis · rembg