CVE-2026-8470 in Langflow OSS
Summary
by MITRE • 08/05/2026
IBM Langflow OSS 1.0.0 through 1.10.3, 1.0.0 through 1.10.3, 1.0.0 through 1.10.3, and 1.0.0 through 1.10.3 use Python's non-cryptographic random module for generating Fernet encryption keys from user secrets under 32 characters. The deterministic Mersenne Twister PRNG produces identical keys for identical seeds, allowing attackers to reproduce encryption keys and decrypt stored API keys and authentication tokens.
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Analysis
by VulDB Data Team • 08/05/2026
This vulnerability exists within IBM Langflow Open Source Software versions ranging from 1.0.0 through 1.10.3 where the application employs Python's non-cryptographic random number generator for creating Fernet encryption keys derived from user-provided secrets shorter than 32 characters. The implementation utilizes the deterministic Mersenne Twister pseudo-random number generator which produces predictable outputs when initialized with identical seeds, fundamentally compromising the cryptographic security of the encryption mechanism. This flaw represents a critical weakness in the system's key generation process and directly violates established cryptographic best practices for secure random number generation.
The technical exploitation of this vulnerability stems from the deterministic nature of the Mersenne Twister algorithm combined with the specific implementation pattern of generating Fernet keys from user secrets below the recommended 32-character threshold. When users provide secrets shorter than 32 characters, the system's key derivation process becomes vulnerable to predictable key generation, allowing attackers to reproduce identical encryption keys given the same input seed values. This deterministic behavior creates a direct pathway for adversaries to reverse-engineer the encryption keys and subsequently decrypt sensitive data including API keys and authentication tokens stored within the system. The vulnerability manifests as a failure in the cryptographic key derivation function, specifically when dealing with insufficient entropy sources.
The operational impact of this vulnerability extends beyond simple data confidentiality breaches, as it enables attackers to gain unauthorized access to critical system credentials and authentication mechanisms. Once an attacker successfully reproduces the encryption keys through predictable random number generation, they can decrypt stored API keys and authentication tokens, potentially leading to full system compromise, unauthorized data access, and privilege escalation attacks. The vulnerability affects all versions within the specified range, indicating a widespread issue that impacts numerous deployments of the software across various organizational environments.
Organizations should immediately implement mitigations including upgrading to patched versions of IBM Langflow OSS where cryptographic random number generation has been properly implemented using cryptographically secure pseudo-random number generators such as those found in Python's secrets module or os.urandom. Additionally, system administrators must ensure that all user-provided secrets meet the minimum 32-character requirement for key derivation processes and implement proper entropy validation mechanisms. The remediation strategy should also include immediate re-encryption of any stored sensitive data using properly generated cryptographically secure keys, while monitoring for potential exploitation attempts through anomaly detection systems. This vulnerability aligns with CWE-330 Use of Insufficiently Random Values and maps to ATT&CK technique T1552.001 Unsecured Credentials, highlighting the critical nature of proper cryptographic implementation in preventing unauthorized system access and data breaches.