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ESPnet CVE-2026-90777

| EUVDEUVD-2026-77001 HIGH
Deserialization of Untrusted Data (CWE-502)
2026-09-13 VulnCheck GHSA-r7rw-fc94-3p58
8.7
CVSS 4.0 · Vendor: VulnCheck
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Vendor (VulnCheck) PRIMARY
8.7 HIGH
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
vuln.today AI
8.8 HIGH

Attacker delivers malicious checkpoint remotely; victim must load it (UI:R); successful deserialization yields full code execution (C/I/A:H); scope unchanged.

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

Primary rating from Vendor (VulnCheck).

CVSS VectorVendor: VulnCheck

Attack Vector
Network
Attack Complexity
Low
Privileges Required
None
User Interaction
P
Scope
X

Lifecycle Timeline

4
POC Analysis Generated
Sep 13, 2026 - 15:20 vuln.today
Source Code Evidence Fetched
Sep 13, 2026 - 12:01 vuln.today
Analysis Generated
Sep 13, 2026 - 12:01 vuln.today
CVE Published
Sep 13, 2026 - 11:42 cve.org
HIGH 8.7

DescriptionCVE.org

ESPnet before 202609 deserializes pretrained model checkpoints using torch.load with weights_only=False, allowing arbitrary code execution from attacker-supplied files. Attackers can craft malicious checkpoint files that execute code during deserialization when loaded through the initialization or fine-tuning path.

AnalysisAI

Arbitrary code execution in ESPnet before v.202609 is triggered when a user loads an attacker-crafted PyTorch checkpoint through any of the framework's model initialization, fine-tuning, or averaging pipelines. The root cause is CWE-502 (Deserialization of Untrusted Data): ESPnet called torch.load with weights_only=False across at least four distinct code paths, allowing pickle-embedded payloads to execute arbitrary commands with the privileges of the ESPnet process. …

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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata

Access
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Delivery
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Exploit
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Execution
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Persist
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Impact
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Vulnerability AssessmentAI

Exploitation The victim must load an attacker-supplied PyTorch checkpoint file through one of ESPnet's four vulnerable code paths: (1) pretrained model loading via espnet2/torch_utils/load_pretrained_model.py (used during initialization and transfer learning), (2) model build and fine-tuning via espnet2/tasks/abs_task.py, (3) N-best model averaging via espnet2/main_funcs/average_nbest_models.py, or (4) speech LM inference via espnet2/speechlm/bin/inference.py. … Additional conditions and limiting factors are described in the full assessment.
Risk Assessment The CVSS 4.0 score of 8.7 (AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N) is broadly sound but requires contextual framing. … Full risk analysis with EPSS, KEV, and SSVC signal comparison available after sign-in.
Exploit Scenario Full exploit scenario with step-by-step reproduction available after sign-in.
Remediation Upgrade ESPnet to v.202609 or later, available at https://github.com/espnet/espnet/releases/tag/v.202609. … Detailed patch versions, workarounds, and compensating controls in full report.

Recommended ActionAI

Within 24 hours, audit all ESPnet instances and versions in use, and suspend loading of any checkpoints from external or untrusted sources pending verification. …

Sign in for detailed remediation steps and compensating controls.

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

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CVE-2026-90777 vulnerability details – vuln.today

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