| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Out of bounds read in GPU in Google Chrome on Mac and Windows prior to 148.0.7778.168 allowed a remote attacker who had compromised the renderer process to obtain potentially sensitive information from process memory via a crafted HTML page. (Chromium security severity: High) |
| Heap buffer overflow in GPU in Google Chrome on Android prior to 148.0.7778.168 allowed a remote attacker to perform an out of bounds memory write via a crafted HTML page. (Chromium security severity: High) |
| Use after free in GPU in Google Chrome prior to 148.0.7778.168 allowed a remote attacker who had compromised the renderer process to perform an out of bounds memory write via a crafted HTML page. (Chromium security severity: High) |
| Integer overflow in Internationalization in Google Chrome on Windows prior to 148.0.7778.168 allowed a remote attacker to perform an out of bounds memory write via a crafted HTML page. (Chromium security severity: High) |
| In the Linux kernel, the following vulnerability has been resolved:
mm/vmalloc: prevent RCU stalls in kasan_release_vmalloc_node
When CONFIG_PAGE_OWNER is enabled, freeing KASAN shadow pages during
vmalloc cleanup triggers expensive stack unwinding that acquires RCU read
locks. Processing a large purge_list without rescheduling can cause the
task to hold CPU for extended periods (10+ seconds), leading to RCU stalls
and potential OOM conditions.
The issue manifests in purge_vmap_node() -> kasan_release_vmalloc_node()
where iterating through hundreds or thousands of vmap_area entries and
freeing their associated shadow pages causes:
rcu: INFO: rcu_preempt detected stalls on CPUs/tasks:
rcu: Tasks blocked on level-0 rcu_node (CPUs 0-1): P6229/1:b..l
...
task:kworker/0:17 state:R running task stack:28840 pid:6229
...
kasan_release_vmalloc_node+0x1ba/0xad0 mm/vmalloc.c:2299
purge_vmap_node+0x1ba/0xad0 mm/vmalloc.c:2299
Each call to kasan_release_vmalloc() can free many pages, and with
page_owner tracking, each free triggers save_stack() which performs stack
unwinding under RCU read lock. Without yielding, this creates an
unbounded RCU critical section.
Add periodic cond_resched() calls within the loop to allow:
- RCU grace periods to complete
- Other tasks to run
- Scheduler to preempt when needed
The fix uses need_resched() for immediate response under load, with a
batch count of 32 as a guaranteed upper bound to prevent worst-case stalls
even under light load. |
| Side-channel information leakage in Navigation in Google Chrome prior to 148.0.7778.168 allowed a remote attacker to leak cross-origin data via a crafted HTML page. (Chromium security severity: Medium) |
| The llm CLI tool thru 0.27.1 contains a critical code injection vulnerability via its --functions command-line argument. This argument is intended to allow users to provide custom Python function definitions. However, the tool directly executes the provided code using the unsafe exec() function without any sanitization, sandboxing, or security restrictions. An attacker can exploit this by crafting a malicious llm command with arbitrary Python code in the --functions argument and using social engineering to trick a victim into running it. This leads to arbitrary code execution on the victim's system, potentially granting the attacker full control. |
| The Ludwig framework thru 0.10.4 is vulnerable to insecure deserialization (CWE-502) in its model serving component. When starting a model server with the ludwig serve command, the framework loads model weight files using torch.load() without enabling the security-restrictive weights_only=True parameter. This default behavior allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by providing a maliciously crafted PyTorch model file, leading to arbitrary code execution on the system hosting the Ludwig model server. |
| The mamba language model framework thru 2.2.6 is vulnerable to insecure deserialization (CWE-502) when loading pre-trained models from HuggingFace Hub. The MambaLMHeadModel.from_pretrained() method uses torch.load() to load the pytorch_model.bin weight file without enabling the security-restrictive weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the pickle module. An attacker can exploit this by publishing a malicious model repository on HuggingFace Hub. When a victim loads a model from this repository, arbitrary code is executed on the victim's system in the context of the mamba process. |
| Sandbox escape in the Profile Backup component. This vulnerability was fixed in Firefox 150.0.3. |
| An arbitrary file upload vulnerability in the ShopOrderImportController.java component of qihang-wms commit 75c15a allows attackers to execute arbitrary code via uploading a crafted file. |
| Insufficient validation of untrusted input in SiteIsolation in Google Chrome prior to 148.0.7778.168 allowed a remote attacker who had compromised the renderer process to bypass Site Isolation via a crafted HTML page. (Chromium security severity: High) |
| Stack exhaustion vulnerability in the MongoDB PHP driver can cause application crashes when processing deeply nested BSON documents in unusual circumstances when the source of these BSON documents is not MongoDB Server. |
| A flaw was found in gnutls. This vulnerability occurs because permitted name constraints were incorrectly ignored when previous Certificate Authorities (CAs) only had excluded name constraints. A remote attacker could exploit this to bypass critical name constraint checks during certificate validation. This bypass could lead to the acceptance of invalid certificates, potentially enabling spoofing or man-in-the-middle attacks against affected systems. |
| A flaw was found in libarchive. On 32-bit systems, an integer overflow vulnerability exists in the zisofs block pointer allocation logic. A remote attacker can exploit this by providing a specially crafted ISO9660 image, which can lead to a heap buffer overflow. This could potentially allow for arbitrary code execution on the affected system. |
| A flaw was found in GnuTLS. This vulnerability allows a denial of service (DoS) by excessive CPU (Central Processing Unit) and memory consumption via specially crafted malicious certificates containing a large number of name constraints and subject alternative names (SANs). |
| External Control of File Name or Path in the Mail feature of Zoom Workplace for Windows before 6.6.0 may allow an unauthenticated user to conduct an escalation of privilege via network access. |
| In the Linux kernel, the following vulnerability has been resolved:
drm/tests: shmem: Hold reservation lock around madvise
Acquire and release the GEM object's reservation lock around calls
to the object's madvide operation. The tests use
drm_gem_shmem_madvise_locked(), which led to errors such as show below.
[ 58.339389] WARNING: CPU: 1 PID: 1352 at drivers/gpu/drm/drm_gem_shmem_helper.c:499 drm_gem_shmem_madvise_locked+0xde/0x140
Only export the new helper drm_gem_shmem_madvise() for Kunit tests.
This is not an interface for regular drivers. |
| The CosyVoice project thru commit 6e01309e01bc93bbeb83bdd996b1182a81aaf11e (2025-30-21) contains an insecure deserialization vulnerability (CWE-502) in its model loading process. When loading model files (.pt) from a user-specified directory (via the --model_dir argument), the code uses torch.load() without the security-restrictive weights_only=True parameter. This allows the deserialization of arbitrary Python objects via the Pickle module. An attacker can exploit this by providing a maliciously crafted model directory containing .pt files with embedded pickle payloads. When a victim loads this directory using CosyVoice's web interface, the malicious payload is executed, leading to remote code execution on the victim's system. |
| Guardrails AI thru 0.6.7 contains a code injection vulnerability (CWE-94) in its Hub package installation mechanism. When installing validator packages via guardrails hub install, the system retrieves a manifest from the Guardrails Hub and dynamically executes a script specified in the post_install field. The script path is constructed from untrusted manifest data and executed without proper validation or sanitization, allowing remote code execution. An attacker who can publish malicious packages to the Hub can inject arbitrary code that will be executed on any system where a victim installs the malicious package. |
