CVE-2026-115924 (GCVE-0-2026-115924)
Vulnerability from cvelistv5 – Published: 2026-10-26 19:22 – Updated: 2026-10-26 19:22
VLAI
EPSS
VEX
Title
Rembg: Unauthenticated SAM model injection permits local-file disclosure through malicious ONNX graphs
Summary
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.
Severity
8.6 (High)
CWE
- CWE-22 - Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://github.com/danielgatis/rembg/security/adv… | x_refsource_CONFIRM |
| https://github.com/danielgatis/rembg/commit/b2758… | x_refsource_MISC |
| https://github.com/danielgatis/rembg/releases/tag… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| danielgatis | rembg |
Affected:
< 2.0.82
|
guessed |
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"title": "Rembg: Unauthenticated SAM model injection permits local-file disclosure through malicious ONNX graphs"
}
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"datePublished": "2026-10-26T19:22:52.720Z",
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"cveTags": [],
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{
"lang": "en",
"value": "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."
}
],
"id": "CVE-2026-115924",
"lastModified": "2026-10-27T16:04:22.707",
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"scope": "UNCHANGED",
"userInteraction": "NONE",
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"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/danielgatis/rembg/commit/b2758c6b39bb2b02df90a03128110339476984d3"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/danielgatis/rembg/releases/tag/v2.0.82"
},
{
"source": "security-advisories@github.com",
"url": "https://github.com/danielgatis/rembg/security/advisories/GHSA-qr6x-7v33-6qmg"
}
],
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"type": "Primary"
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]
}
}
}
}
FKIE_CVE-2026-115924
Vulnerability from fkie_nvd - Published: 2026-10-26 20:17 - Updated: 2026-10-27 16:04
Severity
Summary
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.
References
Impacted products
| Vendor | Product | Version |
|---|
{
"affected": [
{
"affectedData": [
{
"product": "rembg",
"vendor": "danielgatis",
"versions": [
{
"status": "affected",
"version": "\u003c 2.0.82"
}
]
}
],
"source": "security-advisories@github.com"
}
],
"cveTags": [],
"descriptions": [
{
"lang": "en",
"value": "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."
}
],
"id": "CVE-2026-115924",
"lastModified": "2026-10-27T16:04:22.707",
"metrics": {
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"confidentialityImpact": "HIGH",
"integrityImpact": "LOW",
"privilegesRequired": "NONE",
"scope": "UNCHANGED",
"userInteraction": "NONE",
"vectorString": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L",
"version": "3.1"
},
"exploitabilityScore": 3.9,
"impactScore": 4.7,
"source": "security-advisories@github.com",
"type": "Secondary"
}
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"published": "2026-10-26T20:17:52.250",
"references": [
{
"source": "security-advisories@github.com",
"url": "https://github.com/danielgatis/rembg/commit/b2758c6b39bb2b02df90a03128110339476984d3"
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"source": "security-advisories@github.com",
"url": "https://github.com/danielgatis/rembg/releases/tag/v2.0.82"
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"source": "security-advisories@github.com",
"url": "https://github.com/danielgatis/rembg/security/advisories/GHSA-qr6x-7v33-6qmg"
}
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"sourceIdentifier": "security-advisories@github.com",
"vulnStatus": "Deferred",
"weaknesses": [
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"value": "CWE-22"
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"type": "Primary"
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]
}
GHSA-QR6X-7V33-6QMG
Vulnerability from github – Published: 2026-10-27 14:45 – Updated: 2026-10-27 14:45
VLAI
Summary
Rembg: Unauthenticated SAM model injection permits local-file disclosure through malicious ONNX graphs
Details
The public /api/remove endpoint uses attacker-controlled extras.sam_model in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.
This issue affects SAM's sam_model in 2.0.81 and returns complete file contents.
Screenshot 1 — First unauthenticated request primes the path and returns HTTP 500.
Technical details
rembg/commands/s_command.py:188-223,384-397 accepts public extras JSON and passes it to new_session(). rembg/sessions/sam.py:313-355 inserts sam_model into encoder/decoder filenames and fixed GitHub URLs, then invokes pooch.retrieve() without a pinned hash.
Requests removes the URL #fragment; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.
The graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.
Screenshot 2 — The identical second request returns HTTP 200 with an encoded PNG.
Proof of concept
The attached loopback-only PoC produced:
VULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag
first-http=500 second-http=200
decoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28
The /etc/passwd variant produced:
VULNERABLE: disclosed /etc/passwd (839 bytes)
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin
...
nobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin
The decoded contents matched /etc/passwd inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.
Screenshot 3 — The decoder reconstructs all 839 bytes of /etc/passwd.
Impact
An unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both /flag and /etc/passwd.
Remediation
Allow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.
decode_samfragment_png.py samfragment_04.py samfragment_etc_passwd_lab.py
Severity
8.6 (High)
{
"affected": [
{
"package": {
"ecosystem": "PyPI",
"name": "rembg"
},
"ranges": [
{
"events": [
{
"introduced": "0"
},
{
"fixed": "2.0.82"
}
],
"type": "ECOSYSTEM"
}
]
}
],
"aliases": [
"CVE-2026-115924"
],
"database_specific": {
"cwe_ids": [
"CWE-22"
],
"github_reviewed": true,
"github_reviewed_at": "2026-10-27T14:45:36Z",
"nvd_published_at": "2026-10-26T20:17:52Z",
"severity": "HIGH"
},
"details": "The public `/api/remove` endpoint uses attacker-controlled `extras.sam_model` in both SAM filenames and GitHub download URLs. Path traversal plus a URL fragment lets an unauthenticated attacker place malicious ONNX models beside a target file. The models read the file as ONNX external data and encode its bytes into the returned PNG.\n\n This issue affects SAM\u0027s `sam_model` in 2.0.81 and returns complete file contents.\n\n\n\u003cimg width=\"2172\" height=\"1182\" alt=\"image\" src=\"https://github.com/user-attachments/assets/70aacab1-5ef8-4aad-b30e-e3780adef4d2\" /\u003e\n\n *Screenshot 1 \u2014 First unauthenticated request primes the path and returns HTTP 500.*\n\n\n### Technical details\n\n`rembg/commands/s_command.py:188-223,384-397` accepts public `extras` JSON and passes it to `new_session()`. `rembg/sessions/sam.py:313-355` inserts `sam_model` into encoder/decoder filenames and fixed GitHub URLs, then invokes `pooch.retrieve()` without a pinned hash.\n\nRequests removes the URL `#fragment`; the local POSIX path retains it. Pooch creates attacker-selected parent directories without enforcing cache containment. The first request creates the path tree and returns HTTP 500. The identical second request downloads the attacker asset twice and stores it as both SAM models beside the target.\n\nThe graph uses a relative external tensor to read the target and maps every byte to mask pixels. rembg returns the mask as a PNG, which the attacker decodes back into the original bytes.\n\n\n\u003cimg width=\"2432\" height=\"1254\" alt=\"image\" src=\"https://github.com/user-attachments/assets/99215c39-3619-4952-8f41-5ef2034f7499\" /\u003e\n\n *Screenshot 2 \u2014 The identical second request returns HTTP 200 with an encoded PNG.*\n \n\u003cimg width=\"2858\" height=\"1548\" alt=\"image\" src=\"https://github.com/user-attachments/assets/26322071-101c-41aa-a356-08a4969ef475\" /\u003e\n\n\n### Proof of concept\n\nThe attached loopback-only PoC produced:\n\n```text\nVULNERABLE: unauthenticated SAM model injection disclosed the synthetic /flag\nfirst-http=500 second-http=200\ndecoded-value=REMBG_AUDIT_SYNTHETIC_FLAG_2026_08_28\n```\n\nThe `/etc/passwd` variant produced:\n\n```text\nVULNERABLE: disclosed /etc/passwd (839 bytes)\nroot:x:0:0:root:/root:/bin/bash\ndaemon:x:1:1:daemon:/usr/sbin:/usr/sbin/nologin\n...\nnobody:x:65534:65534:nobody:/nonexistent:/usr/sbin/nologin\n```\n\nThe decoded contents matched `/etc/passwd` inside the owned container. Testing used a local TLS stand-in for GitHub; no public target was contacted.\n\n\n\u003cimg width=\"1816\" height=\"1146\" alt=\"image\" src=\"https://github.com/user-attachments/assets/664eaf25-5963-4ca6-b7eb-3e198499194a\" /\u003e\n\n *Screenshot 3 \u2014 The decoder reconstructs all 839 bytes of `/etc/passwd`.*\n\n### Impact\n\nAn unauthenticated attacker can execute arbitrary ONNX computation and disclose complete files that rembg can reach under the required filesystem permissions. The supplied root-running container exposed both `/flag` and `/etc/passwd`.\n\n### Remediation\n\nAllow only fixed SAM identifiers mapped server-side to fixed filenames, URLs, and pinned hashes. Reject path and URL syntax; canonicalize destinations and enforce cache containment before creating directories. Run the container as a non-root user with a read-only root filesystem.\n\n[decode_samfragment_png.py](https://github.com/user-attachments/files/31601255/decode_samfragment_png.py)\n[samfragment_04.py](https://github.com/user-attachments/files/31601256/samfragment_04.py)\n[samfragment_etc_passwd_lab.py](https://github.com/user-attachments/files/31601258/samfragment_etc_passwd_lab.py)",
"id": "GHSA-qr6x-7v33-6qmg",
"modified": "2026-10-27T14:45:36Z",
"published": "2026-10-27T14:45:36Z",
"references": [
{
"type": "WEB",
"url": "https://github.com/danielgatis/rembg/security/advisories/GHSA-qr6x-7v33-6qmg"
},
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-115924"
},
{
"type": "WEB",
"url": "https://github.com/danielgatis/rembg/commit/b2758c6b39bb2b02df90a03128110339476984d3"
},
{
"type": "PACKAGE",
"url": "https://github.com/danielgatis/rembg"
},
{
"type": "WEB",
"url": "https://github.com/danielgatis/rembg/releases/tag/v2.0.82"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:L/A:L",
"type": "CVSS_V3"
}
],
"summary": "Rembg: Unauthenticated SAM model injection permits local-file disclosure through malicious ONNX graphs"
}
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Nomenclature
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
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Browse all ATT&CK techniques and the vulnerabilities related to each.
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