CVE-2026-0772
Published: 23 January 2026
Summary
CVE-2026-0772 is a high-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Langflow Langflow. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 18.3% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Supply Chain and Deployment risk domain.
Deeper analysis
Langflow contains a deserialization of untrusted data vulnerability in its disk cache service that permits remote code execution on affected installations. The flaw stems from insufficient validation of user-supplied data and is tracked as CWE-502; successful exploitation allows code to run in the context of the service account. Authentication is required, and the issue carries a CVSS 3.0 score of 7.5 with network attack vector and high complexity.
An authenticated remote attacker can supply crafted data to the disk cache component, triggering deserialization that leads to arbitrary code execution. The vulnerability was originally reported as ZDI-CAN-27919.
The issue is described in Zero Day Initiative advisory ZDI-26-038. Exploitation probability remains low, with an EPSS score of 0.0153 and a peak of only 0.0168.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-4467
Vulnerability details
Langflow Disk Cache Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Langflow. Authentication is required to exploit this vulnerability. The specific flaw exists within the disk cache…
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service. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the service account. Was ZDI-CAN-27919.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: langflow
Related Threats
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Validates or rejects untrusted serialized data before deserialization occurs.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.