CVE-2026-115924

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

HIGH
8.6
CVSS Score
Published: October 26, 2026 at 07:22 PM UTC
Updated: October 31, 2026 at 02:17 AM UTC
1 product affected across 1 vendorRembg

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Severity
HIGH8.6
Exploit prediction
EPSS 0.4%
SSVC
PoC

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.

Affected

Our own answer: ranges merged, affected separated from platform-only, with confidence and review flags.

v < 2.0.82

Remediation

No guide yet

No remediation guidance has been written for this CVE yet, and no fixed version or vendor advisory is recorded against it.

SSVC — Action Prioritization

SSVCPoCAutomatablePartial impact

SSVC signals action urgency (what to patch first), separate from CVSS which measures severity.

CVSS

8.6HIGHGitHub_M
Attack Vector
NETWORK
Complexity
LOW
Privileges
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
HIGH
Integrity
LOW
Availability
LOW
Vector?

Quick Info

StatusDEFERRED
CWE
CWE-22

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