| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| In the Linux kernel, the following vulnerability has been resolved:
driver core: enforce device_lock for driver_match_device()
Currently, driver_match_device() is called from three sites. One site
(__device_attach_driver) holds device_lock(dev), but the other two
(bind_store and __driver_attach) do not. This inconsistency means that
bus match() callbacks are not guaranteed to be called with the lock
held.
Fix this by introducing driver_match_device_locked(), which guarantees
holding the device lock using a scoped guard. Replace the unlocked calls
in bind_store() and __driver_attach() with this new helper. Also add a
lock assertion to driver_match_device() to enforce this guarantee.
This consistency also fixes a known race condition. The driver_override
implementation relies on the device_lock, so the missing lock led to the
use-after-free (UAF) reported in Bugzilla for buses using this field.
Stress testing the two newly locked paths for 24 hours with
CONFIG_PROVE_LOCKING and CONFIG_LOCKDEP enabled showed no UAF recurrence
and no lockdep warnings. |
| This vulnerability exists in Quantum Networks router due to improper access control and insecure default configuration in the web-based management interface. An unauthenticated attacker could exploit this vulnerability by accessing exposed API endpoints on the targeted device.
Successful exploitation of this vulnerability could allow the attacker to access sensitive information, including internal endpoints, scripts and directories on the targeted device. |
| In the Linux kernel, the following vulnerability has been resolved:
firmware: thead: Fix buffer overflow and use standard endian macros
Addresses two issues in the TH1520 AON firmware protocol driver:
1. Fix a potential buffer overflow where the code used unsafe pointer
arithmetic to access the 'mode' field through the 'resource' pointer
with an offset. This was flagged by Smatch static checker as:
"buffer overflow 'data' 2 <= 3"
2. Replace custom RPC_SET_BE* and RPC_GET_BE* macros with standard
kernel endianness conversion macros (cpu_to_be16, etc.) for better
portability and maintainability.
The functionality was re-tested with the GPU power-up sequence,
confirming the GPU powers up correctly and the driver probes
successfully.
[ 12.702370] powervr ffef400000.gpu: [drm] loaded firmware
powervr/rogue_36.52.104.182_v1.fw
[ 12.711043] powervr ffef400000.gpu: [drm] FW version v1.0 (build
6645434 OS)
[ 12.719787] [drm] Initialized powervr 1.0.0 for ffef400000.gpu on
minor 0 |
| This vulnerability exists in Quantum Networks router due to lack of enforcement of strong password policies in the web-based management interface. An attacker on the same network could exploit this vulnerability by performing password guessing or brute-force attacks against user accounts, leading to unauthorized access to the targeted device. |
| The Log4j1XmlLayout from the Apache Log4j 1-to-Log4j 2 bridge fails to escape characters forbidden by the XML 1.0 standard, producing malformed XML output. Conforming XML parsers are required to reject documents containing such characters with a fatal error, which may cause downstream log processing systems to drop or fail to index affected records.
Two groups of users are affected:
* Those using Log4j1XmlLayout directly in a Log4j Core 2 configuration file.
* Those using the Log4j 1 configuration compatibility layer with org.apache.log4j.xml.XMLLayout specified as the layout class.
Users are advised to upgrade to Apache Log4j 1-to-Log4j 2 bridge version 2.25.4, which corrects this issue.
Note: The Apache Log4j 1-to-Log4j 2 bridge is deprecated and will not be present in Log4j 3. Users are encouraged to consult the Log4j 1 to Log4j 2 migration guide https://logging.apache.org/log4j/2.x/migrate-from-log4j1.html , and specifically the section on eliminating reliance on the bridge. |
| The WebSocket backend uses charging station identifiers to uniquely associate sessions but allows multiple endpoints to connect using the same session identifier. This implementation results in predictable session identifiers and enables session hijacking or shadowing, where the most recent connection displaces the legitimate charging station and receives backend commands intended for that station. This vulnerability may allow unauthorized users to authenticate as other users or enable a malicious actor to cause a denial-of-service condition by overwhelming the backend with valid session requests. |
| Deserialization of untrusted data in Microsoft High Performance Compute Pack (HPC) allows an authorized attacker to elevate privileges locally. |
| This vulnerability exists in Quantum Networks router due to missing rate limiting and CAPTCHA protection for failed login attempts in the web-based management interface. An attacker on the same network could exploit this vulnerability by performing brute force attacks against administrative credentials, leading to unauthorized access with root privileges on the targeted device. |
| This vulnerability exists in Quantum Networks router due to inadequate sanitization of user-supplied input in the management CLI interface. An authenticated remote attacker could exploit this vulnerability by injecting arbitrary OS commands on the targeted device.
Successful exploitation of this vulnerability could allow the attacker to perform remote code execution with root privileges on the targeted device. |
| The WebSocket Application Programming Interface lacks restrictions on the number of authentication requests. This absence of rate limiting may allow an attacker to conduct denial-of-service attacks by suppressing or mis-routing legitimate charger telemetry, or conduct brute-force attacks to gain unauthorized access. |
| OOM Denial of Service via Unbounded Array Allocation in Apache OpenNLP AbstractModelReader
Versions Affected:
before 2.5.9
before 3.0.0-M3
Description:
The AbstractModelReader methods getOutcomes(), getOutcomePatterns(), and getPredicates() each read a 32-bit signed integer count field from a binary model stream and pass that value directly to an array allocation (new String[numOutcomes], new int[numOCTypes][], new String[NUM_PREDS]) without validating that the value is non-negative or within a reasonable bound. The count is therefore fully attacker-controlled when the model file originates from an untrusted source.
A crafted .bin model file in which any of these count fields is set to Integer.MAX_VALUE (or any value large enough to exhaust the available heap) triggers an OutOfMemoryError at the array allocation itself, before the corresponding label or pattern data is consumed from the stream. The error occurs very early in deserialization: for a GIS model, getOutcomes() is reached after only the model-type string, the correction constant, and the correction parameter have been read; so the attacker pays no meaningful size cost to weaponize a payload, and a single small file can crash a JVM that loads it. Any code path that deserializes a .bin model is affected, including direct use of GenericModelReader and any higher-level component that delegates to it during model load.
The practical impact is denial of service against processes that load model files from untrusted or semi-trusted origins.
Mitigation:
* 2.x users should upgrade to 2.5.9.
* 3.x users should upgrade to 3.0.0-M3.
Note: The fix introduces an upper bound on each of the three count fields, checked before array allocation; counts that are negative or exceed the bound cause an IllegalArgumentException to be thrown and the read to fail fast with no large allocation. The default bound is 10,000,000, which is well above the entry counts of legitimate OpenNLP models but far below any value that would threaten heap exhaustion. Deployments that legitimately need to load models with more entries than the default can raise the limit at JVM startup by setting the OPENNLP_MAX_ENTRIES system property to the desired positive integer (e.g. -DOPENNLP_MAX_ENTRIES=50000000); invalid or non-positive values fall back to the default.
Users who cannot upgrade immediately should treat all .bin model files as untrusted input unless their provenance is verified, and should avoid loading models supplied by end users or fetched from third-party repositories without integrity checks. |
| n8n is an open source workflow automation platform. Prior to versions 1.123.33 and 2.17.5, the dynamic-node-parameters endpoints did not verify whether the authenticated caller was authorized to use a supplied credential reference. An authenticated user with access to a shared workflow could supply a foreign credential ID in the request body, causing the backend to decrypt and use that credential in a helper execution path where the caller also controls the destination URL. This allowed the caller to force the backend to authenticate against attacker-controlled infrastructure using a credential belonging to another user, effectively exfiltrating a reusable API key. The issue is not limited to any single node type; any node that resolves credentials dynamically through these endpoints may be affected. This issue has been patched in versions 1.123.33, 2.17.5, and 2.18.0. |
| n8n is an open source workflow automation platform. Prior to versions 1.123.32, 2.17.4, and 2.18.1, an authenticated user with permission to create or modify workflows containing a Python Code Node could escape the sandbox and achieve arbitrary code execution on the task runner container. This issue only affects instances where the Python Task Runner is enabled. This issue has been patched in versions 1.123.32, 2.17.4, and 2.18.1. |
| Improper Validation of Certificate with Host Mismatch vulnerability in Apache Thrift.
This issue affects Apache Thrift: before 0.23.0.
Users are recommended to upgrade to version 0.23.0, which fixes the issue. |
| Origin Validation Error, Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal'), Improper Neutralization of CRLF Sequences in HTTP Headers ('HTTP Request/Response Splitting'), Uncontrolled Resource Consumption vulnerability in Apache Thrift.
This issue affects Apache Thrift: before 0.23.0.
Users are recommended to upgrade to version 0.23.0, which fixes the issue. |
| Memory corruption when processing camera sensor input/output control codes with invalid output buffers. |
| Memory corruption when another driver calls an IOCTL with invalid input/output buffer. |
| Memory corruption while creating a process on the digital signal processor due to allocation failure at the kernel level. |
| OpenCode Systems OC Messaging / USSD Gateway OC Release 6.32.2 contains a broken access control vulnerability in the web-based control panel allowing authenticated low-privileged attackers to gain to access to arbitrary SMS messages via a crafted company or tenant identifier parameter. |
| A security issue was discovered in ingress-nginx where the `nginx.ingress.kubernetes.io/rewrite-target` Ingress annotation can be used to inject configuration into nginx. This can lead to arbitrary code execution in the context of the ingress-nginx controller, and disclosure of Secrets accessible to the controller. (Note that in the default installation, the controller can access all Secrets cluster-wide.) |
