EUVD-2026-83796
GHSA-jf58-7v68-wxqh
Severity by source
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/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
Pickle deserialization via torch.load yields full code execution (C/I/A:H); exploitation needs a victim to load an untrusted file, so AV:L and UI:R with no prior authentication (PR:N).
Primary rating from Vendor (VulDB).
CVSS VectorVendor: VulDB
Lifecycle Timeline
5DescriptionCVE.org
A vulnerability was detected in dmlc dgl up to 2.1.0. This impacts the function load_info/_read_torch_data of the file utils.py. Performing a manipulation of the argument path results in deserialization. The attack can be initiated remotely. The exploit is now public and may be used. The project was informed of the problem early through an issue report but has not responded yet.
AnalysisAI
Unsafe deserialization in dmlc DGL (Deep Graph Library) up to and including 2.1.0 allows arbitrary code execution when a victim loads a crafted DGL graph info artifact through the load_info / _read_torch_data path in utils.py, which hands an attacker-influenced 'path' to torch.load and therefore to Python's pickle machinery. Per the authoritative assessment this is an untrusted-input/supply-chain scenario rather than a network-service exploit: no memory-safety trigger exists and DGL exposes no network-facing listener by default, so the attacker must deliver a malicious serialized file (shared dataset, model artifact, or downloaded graph) and induce the user to open it, which is why the assessed vector requires user interaction. …
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Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata
Vulnerability AssessmentAI
| Exploitation | Exploitation requires a victim to load an attacker-controlled or untrusted serialized file (a DGL graph/info artifact) through the load_info / _read_torch_data code path, which calls torch.load (pickle) without safe-loading. … Additional conditions and limiting factors are described in the full assessment. |
| Risk Assessment | This is CWE-502 unsafe deserialization in dmlc DGL (Deep Graph Library) up to 2.1.0: load_info/_read_torch_data in utils.py deserializes an attacker-influenced 'path' via torch.load, which is a pickle-based loader that executes arbitrary code embedded in the serialized object. … 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 | No vendor-released patch was identified at time of analysis: the maintainers were notified via GitHub issue dmlc/dgl#7932 and had not responded, and no fixed version is documented in the references, so the primary action is monitoring https://github.com/dmlc/dgl/ for a patched release or commit. … Detailed patch versions, workarounds, and compensating controls in full report. |
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Same weakness CWE-502 – Deserialization of Untrusted Data
View allSame technique Deserialization
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External POC / Exploit Code
Leaving vuln.today