RLSA-2024:4720 Important: httpd:2.4 security update

The httpd packages provide the Apache HTTP Server, a powerful, efficient, and extensible web server. Security Fixes: httpd: Encoding problem in modproxy CVE-2024-38473 httpd: Substitution encoding issue in modrewrite CVE-2024-38474 httpd: Improper escaping of output in modrewrite CVE-2024-38475...

PT-2025-20383

Name of the Vulnerable Software and Affected Versions PostgreSQL versions prior to 17.5, 16.9, 15.13, 14.18, and 13.21 Description The vulnerability is related to a buffer over-read in PostgreSQL's GB18030 encoding validation. This issue allows a database input provider to achieve temporary denia...

CVE-2025-21469

Memory corruption while processing image encoding, when input buffer length is 0 in IOCTL call...

CVE-2025-21470

Memory corruption while processing image encoding, when configuration is NULL in IOCTL parameter...

CVE-2025-21470

Memory corruption while processing image encoding, when configuration is NULL in IOCTL parameter...

CVE-2025-21469

Memory corruption while processing image encoding, when input buffer length is 0 in IOCTL call...

CVE-2024-45567

Memory corruption while encoding JPEG format...

CVE-2024-45567

Memory corruption while encoding JPEG format...

CVE-2025-21470 Improper Access Control in Camera Driver

Memory corruption while processing image encoding, when configuration is NULL in IOCTL parameter...

CVE-2025-21470 Improper Access Control in Camera Driver

Memory corruption while processing image encoding, when configuration is NULL in IOCTL parameter...

CVE-2025-21470

CVE-2025-21470 concerns memory corruption in Qualcomm chipsets during image encoding when the IOCTL configuration is NULL, attributed to a camera driver issue. The vulnerability affects the image-encoding path (memory corruption via NULL config in IOCTL) and is rated high severity (CVSS: Local ac...

CVE-2025-21469 Improper Access Control in Camera Driver

Memory corruption while processing image encoding, when input buffer length is 0 in IOCTL call...

CVE-2025-21469

CVE-2025-21469 concerns memory corruption in Qualcomm chipsets’ camera driver during image encoding when the IOCTL input buffer length is 0. The issue is reported as a local, low-privilege condition with high impact to confidentiality, integrity and availability. Public details consistently cite ...

CVE-2024-45567 Use After Free in Camera Driver

Memory corruption while encoding JPEG format...

CVE-2024-45567 Use After Free in Camera Driver

Memory corruption while encoding JPEG format...

CVE-2024-45567

CVE-2024-45567 describes a memory corruption issue in Qualcomm camera driver related to JPEG encoding. The CVE is tied to Qualcomm chipsets and affects the JPEG encoding path, with root cause identified as memory corruption during the encoding process. Documented impact is high (CVSS 3.1: AV=L, A...

Allocation of Resources Without Limits or Throttling

Overview Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling through the handling of incoming HTTP requests with Transfer-Encoding: chunked or without a Content-Length header. An attacker can cause uncontrolled memory allocation on the server b...

PT-2025-19848 · Qualcomm · Snapdragon +14

Name of the Vulnerable Software and Affected Versions: The product name cannot be determined. Description: The issue involves memory corruption that occurs while encoding JPEG format. This problem is related to the process of handling JPEG encoding, which can lead to memory corruption...

CVE-2025-46728: Uncontrolled Resource Consumption

cpp-httplib is a C++ header-only HTTP/HTTPS server and client library. Prior to version 0.20.1, the library fails to enforce configured size limits on incoming request bodies when Transfer-Encoding: chunked is used or when no Content-Length header is provided. A remote attacker can send a chunked...

The Steganographic Potentials of Language Models

The potential for large language models LLMs to hide messages within plain text steganography poses a challenge to detection and thwarting of unaligned AI agents, and undermines faithfulness of LLMs reasoning. We explore the steganographic capabilities of LLMs fine-tuned via reinforcement learnin...