CVE-2026-104324 in Langflow OSS
Summary
by MITRE • 10/29/2026
IBM Langflow OSS 1.0.0 through 1.12.3 could allow a remote authenticated attacker to execute arbitrary code due to deserialization of untrusted data.
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Analysis
by VulDB Data Team • 10/29/2026
The vulnerability identified in IBM Langflow versions 1.0.0 through 1.12.3 represents a critical security flaw rooted in the improper handling of serialized objects, specifically classified under CWE-502 as Deserialization of Untrusted Data. This issue arises when the application accepts data from external sources and processes it without sufficient validation or sanitization before passing it to deserialization routines. In many modern software architectures, particularly those involving complex workflows like Langflow which facilitates large language model integration, applications frequently exchange structured data formats such as JSON, YAML, or Python pickle objects between components. When these inputs are directly fed into a deserializer that can instantiate arbitrary classes from the payload, an attacker who has successfully authenticated to the system can exploit this mechanism to achieve remote code execution.
The technical mechanics of this vulnerability rely on the inherent dangers associated with certain serialization libraries, most notably in Python environments where pickle is commonly used for its flexibility but lacks security safeguards against malicious payloads. An authenticated user constructs a specially crafted serialized object that contains a sequence of operations designed to be executed upon deserialization rather than merely representing data structure. When Langflow processes this input, the underlying library instantiates classes defined by the attacker, allowing them to invoke methods or access resources within the context of the application server. This bypasses standard security controls because the execution occurs internally after authentication has been verified, effectively granting the attacker a foothold inside the system boundary with the privileges associated with the Langflow service account.
From an operational perspective, this vulnerability poses severe risks including full compromise of the underlying infrastructure hosting IBM Langflow. An adversary could leverage remote code execution to install malware, exfiltrate sensitive data processed by the language models, pivot into internal networks, or disrupt availability through resource exhaustion. The presence of authentication requirements limits the attack surface compared to unauthenticated variants but does not mitigate the severity for any legitimate user whose credentials may be compromised via phishing, credential stuffing, or other identity-based attacks. Furthermore, since Langflow is often used in development and prototyping environments where security postures might be relaxed, the risk of exploitation increases significantly if proper network segmentation and access controls are not enforced around these instances.
Mitigation strategies must focus on immediate remediation through version updates as well as architectural hardening measures. The primary defense is to upgrade IBM Langflow to a version beyond 1.12.3 where this deserialization flaw has been addressed by the vendor, typically involving the replacement of unsafe serialization methods with safer alternatives or strict allow-listing of permissible classes during deserialization processes. In addition to patching, organizations should implement network-level controls such as firewalls and intrusion detection systems that monitor for anomalous traffic patterns indicative of exploitation attempts. Access control policies must be strictly enforced using multi-factor authentication and least privilege principles to reduce the likelihood of an attacker obtaining valid credentials capable of triggering the vulnerability. Regular security assessments and code reviews focusing on input validation and serialization practices are essential to prevent similar issues in future iterations or related components within the broader application ecosystem aligned with MITRE ATT&CK techniques involving command injection via deserialization vectors.