CVE-2025-6199 is a vulnerability identified in the GIF image parser component of GdkPixbuf's LZW decoder, which is used in Red Hat Enterprise Linux 10. The flaw arises when the decoder encounters an invalid symbol during the decompression process of GIF images. Instead of correctly reporting the actual number of bytes written to the output buffer, the decoder erroneously reports the output size as the full buffer length. This logic error causes uninitialized memory sections within the buffer to be included in the output image data. Consequently, this can lead to the exposure of arbitrary memory contents, potentially leaking sensitive information from the system's memory to an unauthorized actor. The vulnerability is classified as an information disclosure issue and does not affect the integrity or availability of the system. Exploitation requires a local vector (AV:L), low attack complexity (AC:L), no privileges required (PR:N), but user interaction is necessary (UI:R), such as opening or processing a crafted GIF image. The scope is unchanged (S:U), and the impact is limited to confidentiality (C:L) with no impact on integrity or availability. The CVSS v3.1 base score is 3.3, indicating a low severity level. No known exploits are currently in the wild, and no patches or mitigations have been explicitly linked yet. The vulnerability affects Red Hat Enterprise Linux 10, which is widely used in enterprise environments, including in Europe. The flaw could be exploited by an attacker who can trick a user into opening a maliciously crafted GIF image, potentially leaking sensitive memory information from the affected system.

For European organizations, the primary impact of CVE-2025-6199 is the potential leakage of sensitive information from system memory when processing malicious GIF images. Although the severity is low and the confidentiality impact is limited, the exposure of arbitrary memory contents could include sensitive data such as cryptographic keys, passwords, or other confidential information depending on what resides in the uninitialized memory. This could facilitate further attacks or data breaches. The requirement for user interaction (opening a crafted image) limits the attack vector primarily to phishing or social engineering campaigns. Organizations handling sensitive or regulated data, such as financial institutions, healthcare providers, and government agencies, may be more concerned about any information leakage. Additionally, since Red Hat Enterprise Linux 10 is commonly used in server and workstation environments, the vulnerability could affect critical infrastructure if exploited. However, the lack of known exploits and the low CVSS score suggest the immediate risk is limited. Still, European organizations should remain vigilant, especially those with high compliance requirements under GDPR or other data protection laws, as any leakage of personal or sensitive data could have regulatory consequences.

1. Monitor Red Hat and GdkPixbuf project advisories closely for official patches or updates addressing CVE-2025-6199 and apply them promptly once available. 2. Implement strict email and web filtering to block or quarantine suspicious image files, particularly GIFs from untrusted sources, to reduce the risk of users opening malicious images. 3. Educate users about the risks of opening unsolicited or unexpected image attachments, emphasizing caution with GIF files. 4. Employ application whitelisting and sandboxing techniques for image processing applications to limit the impact of potential exploitation. 5. Use memory protection and address space layout randomization (ASLR) features available in Red Hat Enterprise Linux 10 to reduce the likelihood of successful exploitation of memory disclosure vulnerabilities. 6. Conduct regular security audits and vulnerability scans focusing on image processing libraries and related components. 7. Consider disabling or restricting the use of GIF image processing in environments where it is not necessary, or use alternative safer image formats if feasible. 8. Implement network segmentation and least privilege principles to limit access to critical systems that might be targeted using this vulnerability.