CVE-2025-27522 is a vulnerability classified under CWE-502, which pertains to the deserialization of untrusted data within the Apache Software Foundation's Apache InLong project. Apache InLong is a distributed data integration framework designed to collect, aggregate, and transmit massive amounts of data efficiently. This vulnerability affects versions from 1.13.0 through 2.1.0. The core issue arises when the software deserializes data from untrusted sources without proper validation or sanitization, potentially allowing an attacker to manipulate the deserialization process. This can lead to unauthorized information disclosure or integrity violations. Notably, this vulnerability is described as a secondary mining bypass related to a previously identified vulnerability, CVE-2024-26579, indicating it may be used in conjunction with or as a follow-up exploit to bypass security controls established in the earlier CVE. The vulnerability has a CVSS v3.1 base score of 6.5, indicating a medium severity level. The vector string (AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N) reveals that the attack can be executed remotely over the network without requiring authentication or user interaction, with low attack complexity. The impact affects confidentiality and integrity but does not affect availability. Users of Apache InLong are advised to upgrade to version 2.2.0 or apply the specific patch referenced in the Apache GitHub pull request #11732 to remediate the vulnerability. There are no known exploits in the wild at the time of publication, but the nature of deserialization vulnerabilities often makes them attractive targets for attackers seeking to compromise data integrity or confidentiality in distributed data systems.

For European organizations, the impact of CVE-2025-27522 can be significant, especially for those relying on Apache InLong for data integration and processing tasks. The vulnerability allows remote attackers to potentially access or manipulate sensitive data streams without authentication, posing risks to data confidentiality and integrity. This could lead to unauthorized data exposure, tampering with data pipelines, or undermining trust in data analytics and decision-making processes. Given the increasing regulatory scrutiny in Europe, including GDPR requirements for data protection and breach notification, exploitation of this vulnerability could result in compliance violations, financial penalties, and reputational damage. Additionally, organizations in sectors such as finance, telecommunications, healthcare, and critical infrastructure that utilize Apache InLong for real-time data processing may face operational risks if data integrity is compromised. Although availability is not directly impacted, the indirect consequences of data manipulation could disrupt business operations or lead to erroneous automated decisions. The lack of required authentication and user interaction increases the risk profile, as attackers can exploit the vulnerability remotely without needing prior access or user involvement.

To mitigate CVE-2025-27522 effectively, European organizations should: 1) Immediately upgrade Apache InLong installations to version 2.2.0, which contains the official fix for this vulnerability. 2) If upgrading is not immediately feasible, apply the specific patch referenced in the Apache GitHub pull request #11732 to address the deserialization flaw. 3) Implement network-level controls such as firewall rules and segmentation to restrict access to Apache InLong services, limiting exposure to trusted networks and known IP addresses. 4) Monitor logs and network traffic for unusual deserialization activities or anomalous data flows that could indicate exploitation attempts. 5) Conduct code reviews and security assessments of any custom extensions or integrations with Apache InLong to ensure they do not introduce additional deserialization risks. 6) Employ runtime application self-protection (RASP) or application-layer firewalls capable of detecting and blocking malicious serialized payloads. 7) Maintain an incident response plan that includes procedures for handling potential data integrity or confidentiality breaches stemming from this vulnerability. These measures go beyond generic patching by emphasizing proactive monitoring, network defense, and secure development practices tailored to the nature of the vulnerability.