CVE-2026-35549

An issue was discovered in MariaDB Server before 11.4.10, 11.5.x through 11.8.x before 11.8.6, and 12.x before 12.2.2. If the cachingsha2password authentication plugin is installed, and some user accounts are configured to use it, a large packet can crash the server because sha256cryptr uses allo...

CVE-2026-35549

An issue was discovered in MariaDB Server before 11.4.10, 11.5.x through 11.8.x before 11.8.6, and 12.x before 12.2.2. If the cachingsha2password authentication plugin is installed, and some user accounts are configured to use it, a large packet can crash the server because sha256cryptr uses allo...

CVE-2026-35549

Disclaimer: This data contains information about vulnerable...

CVE-2026-35549

An issue was discovered in MariaDB Server before 11.4.10, 11.5.x through 11.8.x before 11.8.6, and 12.x before 12.2.2. If the cachingsha2password authentication plugin is installed, and some user accounts are configured to use it, a large packet can crash the server because sha256cryptr uses allo...

CVE-2026-35549

Summary: CVE-2026-35549 affects MariaDB Server before 11.4.10, 11.5.x through 11.8.x before 11.8.6, and 12.x before 12.2.2. If the caching_sha2_password plugin is installed and some accounts use it, a large packet can crash the server because sha256_crypt_r uses alloca. Impact: Availability is HI...

PT-2026-29985

Name of the Vulnerable Software and Affected Versions MariaDB Server versions prior to 11.4.10 MariaDB Server versions 11.5.0 through 11.8.5 MariaDB Server versions prior to 12.2.2 Description MariaDB Server is susceptible to a crash when using the caching sha2 password authentication plugin with...

PYSEC-2026-2299

vLLM is an inference and serving engine for large language models LLMs. From version 0.5.5 to before version 0.18.0, Librosa defaults to using numpy.mean for mono downmixing tomono, while the international standard ITU-R BS.775-4 specifies a weighted downmixing algorithm. This discrepancy results...

libpng: LIBPNG has a heap buffer overflow in png_set_quantize

A heap based buffer overflow flaw has been discovered in LibPNG. Prior to version 1.6.55, an out-of-bounds read vulnerability exists in the pngsetquantize API function. When the function is called with no histogram and the number of colors in the palette is more than twice the maximum supported b...

CVE-2026-32145 Multipart form body parser bypasses body size limits in wisp

Allocation of Resources Without Limits or Throttling vulnerability in gleam-wisp wisp allows a denial of service via multipart form body parsing. The multipartbody function bypasses configured maxbodysize and maxfilessize limits. When a multipart boundary is not present in a chunk, the parser tak...

CVE-2026-32145 Multipart form body parser bypasses body size limits in wisp

Allocation of Resources Without Limits or Throttling vulnerability in gleam-wisp wisp allows a denial of service via multipart form body parsing. The multipartbody function bypasses configured maxbodysize and maxfilessize limits. When a multipart boundary is not present in a chunk, the parser tak...

AgentWatcher: A Rule-Based Prompt Injection Monitor

Large language models LLMs and their applications, such as agents, are highly vulnerable to prompt injection attacks. State-of-the-art prompt injection detection methods have the following limitations: 1 their effectiveness degrades significantly as context length increases, and 2 they lack...

PT-2026-29877

Name of the Vulnerable Software and Affected Versions vLLM versions 0.5.5 through 0.17.999 Description vLLM, an inference and serving engine for large language models LLMs, exhibits an inconsistency in audio processing. Versions 0.5.5 through 0.17.999 utilize numpy.mean for mono downmixing via...

vLLM 输入验证错误漏洞

vLLM is an open-source LLM-based inference and service engine that features high throughput and efficient memory usage. Versions of vLLM prior to 0.5.5 and 0.18.0 contained a vulnerability related to input validation errors. This vulnerability stemmed from inconsistencies in the audio mono downmi...

Combating Data Laundering in LLM Training

Data rights owners can detect unauthorized data use in large language model LLM training by querying with proprietary samples. Often, superior performance e.g., higher confidence or lower loss on a sample relative to the untrained data implies it was part of the training corpus, as LLMs tend to...

UBUNTU-CVE-2026-34159

llama.cpp is an inference of several LLM models in C/C++. Prior to version b8492, the RPC backend's deserializetensor skips all bounds validation when a tensor's buffer field is 0. An unauthenticated attacker can read and write arbitrary process memory via crafted GRAPHCOMPUTE messages. Combined...

Automated Framework to Evaluate and Harden LLM System Instructions against Encoding Attacks

System Instructions in Large Language Models LLMs are commonly used to enforce safety policies, define agent behavior, and protect sensitive operational context in agentic AI applications. These instructions may contain sensitive information such as API credentials, internal policies, and...

Important: python-tornado

Issue Overview: Tornado is a Python web framework and asynchronous networking library. In versions of Tornado prior to 6.5.5, the only limit on the number of parts in multipart/form-data is the maxbodysize setting default 100MB. Since parsing occurs synchronously on the main thread, this creates...

Security update for python-tornado

This update for python-tornado fixes the following issues: CVE-2025-67724: missing validation of the supplied reason phrase bsc1254903. CVE-2025-67725: Denial of Service DoS via maliciously crafted HTTP request caused by the HTTPHeaders.add method bsc1254905. CVE-2026-31958: parsing large multipa...

SUSE-SU-2026:1162-1 Security update for python-tornado

This update for python-tornado fixes the following issues: - CVE-2025-67724: missing validation of the supplied reason phrase bsc1254903. - CVE-2025-67725: Denial of Service DoS via maliciously crafted HTTP request caused by the HTTPHeaders.add method bsc1254905. - CVE-2026-31958: parsing large...

DEBIAN-CVE-2026-34155

RAUC controls the update process on embedded Linux systems. Prior to version 1.15.2, RAUC bundles using the 'plain' format exceeding a payload size of 2 GiB cause an integer overflow which results in a signature which covers only the first few bytes of the payload. Given such a bundle with a...