Answer in brief
CVE-2026-115924 records a High severity (CVSS 8.6) vulnerability in Rembg: Unauthenticated SAM model injection permits local-file disclosure through malicious ONNX graphs. The current sources do not mark it as known exploited. The current feed maps danielgatis/rembg (generic). Check affected ranges and fixed versions before updating.
Analysis pending evidence review
HOL Guard separates source facts from reviewed analysis. See the methodology.
CVSS is 8.6. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.
Analysis status
Analysis pending evidence review
Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.
The current feed maps danielgatis/rembg (generic). Check affected ranges and fixed versions before updating.
| Package | Affected range | Fixed version |
|---|---|---|
| danielgatis/rembggeneric | <2.0.82 | 2.0.82 |
Published upstream
Oct 26, 2026
Evidence: source:cvelist:source_dates:source-dates:recordSource modified
Oct 26, 2026
Evidence: source:cvelist:source_dates:source-dates:recordFirst seen by HOL
Oct 26, 2026
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.
Quoted source text, attributed separately from HOL analysis.