Langflow: Deserialization of Untrusted Data
CVE-2026-0772 is a high-severity deserialization of untrusted data vulnerability in Langflow, with a CVSS 3.0 base score of 7.5 out of 10. It can be exploited remotely over the network by an attacker with a low-privileged account, without any action from a user. Affected Langflow versions: 1.5.0.post2. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 1.24% chance of exploitation within 30 days, higher than 70% of scored CVEs.
High severity with no evidence of exploitation so far.
What to do
- Check which version of Langflow you run against the affected versions below, and install the vendor's latest release.
Affected products and versions
Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.
How the severity score breaks down
- Attack vector
- NetworkCan be exploited remotely over a network, including the internet.
- Attack complexity
- HighSuccess depends on conditions outside the attacker's control.
- Privileges required
- LowA basic user account is enough.
- User interaction
- NoneNo action by a victim is required.
- Scope
- UnchangedImpact stays within the vulnerable component.
- Confidentiality
- HighAll data handled by the component can be read.
- Integrity
- HighData or code can be modified at will.
- Availability
- HighThe component can be taken down completely.
Vector: CVSS:3.0/AV:N/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H. Scored by CNA (trendmicro.com).
Official description
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 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.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Deserialization of Untrusted Data
The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.
How developers prevent this class of flaw
- If available, use the signing/sealing features of the programming language to assure that deserialized data has not been tainted. For example, a hash-based message authentication code (HMAC) could be used to ensure that data has not been modified.
- When deserializing data, populate a new object rather than just deserializing. The result is that the data flows through safe input validation and that the functions are safe.
- Explicitly define a final object() to prevent deserialization.
More Deserialization of Untrusted Data vulnerabilities (CWE-502)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: none, automatable: no, technical impact: total).
- Record last changed materially (score, affected products, status or references).
References
Third-party and government advisories
- zerodayinitiative.com/advisories/ZDI-26-038/Third Party Advisory
Other vulnerabilities in Langflow
- 8.1 High severity
- 9.8 Critical severity
- 8.8 High severity
- 8.8 High severity
- 8.8 High severity
- 8.8 High severity
Recent Deserialization of Untrusted Data vulnerabilities
- 9.8 Critical severity
- 9.8 Critical severity
- 9.8 Critical severity
- 8.1 High severity
- 9.8 Critical severity
- 7.8 High severity
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