EUVD-2025-16327

Comprehensive Technical Analysis of EUVD-2025-16327

1. Vulnerability Assessment and Severity Evaluation

The vulnerability EUVD-2025-16327, also known as CVE-2025-27528, pertains to a Deserialization of Untrusted Data issue in Apache InLong. This vulnerability allows attackers to bypass security mechanisms in InLong JDBC, leading to arbitrary file reading. The CVSS (Common Vulnerability Scoring System) base score of 9.1 indicates a critical severity level. The CVSS vector CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N breaks down as follows:

• AV:N (Attack Vector: Network): The vulnerability is exploitable over the network.
• AC:L (Attack Complexity: Low): The attack requires minimal skill or resources.
• PR:N (Privileges Required: None): No privileges are required to exploit the vulnerability.
• UI:N (User Interaction: None): No user interaction is required.
• S:U (Scope: Unchanged): The vulnerability does not change the security scope.
• C:H (Confidentiality: High): The vulnerability has a high impact on confidentiality.
• I:H (Integrity: High): The vulnerability has a high impact on integrity.
• A:N (Availability: None): The vulnerability does not impact availability.

2. Potential Attack Vectors and Exploitation Methods

The primary attack vector involves sending specially crafted data to the Apache InLong system, which is then deserialized without proper validation. This can lead to:

• Arbitrary File Reading: Attackers can read sensitive files on the system, potentially exposing configuration files, credentials, or other sensitive data.
• Bypassing Security Mechanisms: The vulnerability allows attackers to circumvent existing security controls, making it easier to execute further attacks.

Exploitation methods may include:

• Network-Based Attacks: Exploiting the vulnerability over the network by sending malicious data packets.
• Phishing and Social Engineering: Tricking users into interacting with malicious content that exploits the vulnerability.

3. Affected Systems and Software Versions

The vulnerability affects Apache InLong versions from 1.13.0 through 2.1.0. Organizations using these versions are at risk and should take immediate action to mitigate the threat.

4. Recommended Mitigation Strategies

To mitigate the risk associated with this vulnerability, the following actions are recommended:

• Upgrade to Version 2.2.0: Users should upgrade to Apache InLong version 2.2.0, which includes the necessary security patches.
• Cherry-Pick the Fix: For organizations unable to upgrade immediately, cherry-picking the fix from the provided GitHub pull request (https://github.com/apache/inlong/pull/11747) is a viable alternative.
• Implement Network Security Measures: Use firewalls and intrusion detection systems (IDS) to monitor and block suspicious network traffic.
• Regular Security Audits: Conduct regular security audits and vulnerability assessments to identify and address potential security issues.
• User Education: Educate users about the risks of phishing and social engineering attacks to reduce the likelihood of exploitation.

5. Impact on European Cybersecurity Landscape

The vulnerability poses a significant risk to organizations within the European Union that rely on Apache InLong for data integration and processing. Given the critical nature of the vulnerability, it could lead to data breaches, loss of sensitive information, and potential regulatory non-compliance under GDPR (General Data Protection Regulation). Organizations must prioritize patching and mitigation efforts to protect their data and maintain compliance.

6. Technical Details for Security Professionals

• Deserialization Issue: The vulnerability stems from the deserialization of untrusted data without proper validation, allowing attackers to manipulate the data and bypass security controls.
• JDBC Component: The issue specifically affects the InLong JDBC component, which is used for database connectivity and data processing.
• Exploit Code: While no public exploit code is available at the time of writing, security professionals should be vigilant for any emerging threats and monitor relevant security forums and databases.
• Patch Details: The patch provided in the GitHub pull request (https://github.com/apache/inlong/pull/11747) addresses the deserialization issue by implementing proper validation and sanitization of input data.

In conclusion, EUVD-2025-16327 is a critical vulnerability that requires immediate attention from organizations using Apache InLong. By following the recommended mitigation strategies and staying informed about emerging threats, organizations can protect their systems and data from potential exploitation.