[ CVE-2026-115924 · Published 26 Oct 2026 ]
Rembg: Unauthenticated SAM model injection permits local-file disclosure through malicious ONNX graphs
[ Why it matters ]Priority signals
- Public proof-of-concept exploit exists (CISA SSVC)
[ Description ]Official 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.
[ Fixes ]Fixes and patches
- rembg 2.0.82Fixed version · GitHub Advisories · pip package rembg: upgrade to 2.0.82 or later (affected < 2.0.82)
[ Packages ]Affected open-source packages
- rembg pipAffected < 2.0.82 · fixed in 2.0.82 · GHSA-qr6x-7v33-6qmg