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Llama Factory CVE-2025-46567

MEDIUM
Deserialization of Untrusted Data (CWE-502)
2025-05-01 security-advisories@github.com
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:L/UI:R/S:U/C:H/I:L/A:L

Primary rating from GitHub Advisory · only source for this CVE.

CVSS VectorGitHub Advisory

CVSS:3.1/AV:L/AC:L/PR:L/UI:R/S:U/C:H/I:L/A:L
Attack Vector
Local
Attack Complexity
Low
Privileges Required
Low
User Interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
Low
Availability
Low

Lifecycle Timeline

4
Analysis Generated
Mar 28, 2026 - 18:39 vuln.today
Patch released
Mar 28, 2026 - 18:39 nvd
Patch available
PoC Detected
Jun 17, 2025 - 14:19 vuln.today
Public exploit code
CVE Published
May 01, 2025 - 18:15 nvd
MEDIUM 6.1

Blast Radius

ecosystem impact
† from your stack dependencies † transitive graph · vuln.today resolves 4-path depth
  • 1 pypi packages depend on llamafactory (1 direct, 0 indirect)

Ecosystem-wide dependent count for version 0.9.3.

DescriptionGitHub Advisory

LLama Factory enables fine-tuning of large language models. Prior to version 1.0.0, a critical vulnerability exists in the llamafy_baichuan2.py script of the LLaMA-Factory project. The script performs insecure deserialization using torch.load() on user-supplied .bin files from an input directory. An attacker can exploit this behavior by crafting a malicious .bin file that executes arbitrary commands during deserialization. This issue has been patched in version 1.0.0.

AnalysisAI

LLama Factory enables fine-tuning of large language models. Rated medium severity (CVSS 6.1), this vulnerability is low attack complexity. Public exploit code available.

Technical ContextAI

This vulnerability is classified as Deserialization of Untrusted Data (CWE-502), which allows attackers to execute arbitrary code through malicious serialized objects. LLama Factory enables fine-tuning of large language models. Prior to version 1.0.0, a critical vulnerability exists in the llamafy_baichuan2.py script of the LLaMA-Factory project. The script performs insecure deserialization using torch.load() on user-supplied .bin files from an input directory. An attacker can exploit this behavior by crafting a malicious .bin file that executes arbitrary commands during deserialization. This issue has been patched in version 1.0.0. Affected products include: Hiyouga Llama-Factory. Version information: version 1.0.0.

RemediationAI

A vendor patch is available. Apply the latest security update as soon as possible. Avoid deserializing untrusted data. Use safe serialization formats (JSON). Implement integrity checks and type allowlists.

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CVE-2025-46567 vulnerability details – vuln.today

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