CVE-2024-29868 Scanner
CVE-2024-29868 Scanner - Configuration File Disclosure vulnerability in Apache StreamPipes
Short Info
Level
Critical
Single Scan
Single Scan
Can be used by
Asset Owner
Estimated Time
10 seconds
Time Interval
13 days 16 hours
Scan only one
URL
Toolbox
-
Apache StreamPipes is an open-source software platform designed for processing and analyzing data streams in real-time. Used by data scientists, engineers, and IT professionals, StreamPipes enables the easy integration of various data sources and allows for complex analytics workflows without deep technical expertise. Its core environment is used for the management and orchestration of industrial data streams, providing tools for rapid prototyping and industrial applications. The system's extensibility and flexibility make it a valuable asset in IoT and industrial environments. Apache StreamPipes finds widespread application in sectors that rely on real-time analytics, such as smart factories, power distribution, and monitoring systems. By offering intuitive interfaces and robust capabilities, StreamPipes assists industries in making informed data-driven decisions.
The vulnerability in discussion pertains to a cryptographically weak Pseudo-Random Number Generator (PRNG) used in the recovery token generation of Apache StreamPipes. This flaw is significant as it undermines the security model of the system, allowing attackers to predict the tokens accurately. By exploiting this weak PRNG, adversaries can potentially generate valid recovery tokens, breaching user authorization processes. The implications are severe, potentially leading to unauthorized account access and control. This vulnerability spans versions 0.69.0 through 0.93.0, affecting a broad user base employing these software versions. Its critical classification underscores the importance of addressing this security lapse promptly.
In technical detail, the vulnerability exploits the usage of a non-cryptographically secure PRNG within the recovery token generation mechanism of Apache StreamPipes. The weakness lies in the predictability of the token values due to the PRNG's insufficient entropy and randomness. A successful breach would follow from being able to deduce future and past tokens upon obtaining a single valid recovery token instance. An attacker leveraging this vulnerability would likely focus on intercepting or acquiring such a token to initiate further unauthorized access. The pathways affected include the user password recovery and account settings endpoints, critical for user management functions.
If exploited, users of Apache StreamPipes could face severe consequences, including unauthorized control over user accounts, data breaches, and potential system manipulations. Malicious actors could leverage the predictable token generation to assume the identities of legitimate users, leading to account commandeering. This breach could extend to unauthorized access to sensitive data, manipulation of data streams, and potential misuse of system resources. Hence, organizations leveraging these affected StreamPipes versions face significant risk, necessitating urgent mitigation actions to protect system integrity and user data.
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