CVE-2026-15053

DoS vulnerability in the vibration service. Impact: Successful exploitation of this vulnerability may affect availability.

Memory Allocation with Excessive Size Value vulnerability in Apache HTTP Server's mod_http leads to denial of service via malicious HTTP requests. This issue affects Apache HTTP Server: from 2.4.17 through 2.4.67.

Memory allocation with excessive size value in Windows Local Security Authority Subsystem Service (LSASS) allows an unauthorized attacker to deny service over a network.

Memory Allocation with Excessive Size Value 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.

OOM Denial of Service via Unbounded Array Allocation in Apache OpenNLP AbstractModelReader  Versions Affected:  before 1.9.5 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.

Coder allows organizations to provision remote development environments via Terraform. Starting in version 2.24.0 and prior to versions 2.29.7, 2.32.7, 2.33.8, and 2.34.2, `NewDataBuilder` in `provisionersdk/proto/dataupload.go` allocated a byte slice using the client-supplied `FileSize` from a `DataUpload` message without an upper-bound check. Although the DRPC wire limit is 4 MiB, the `FileSize` value itself was unconstrained. The fix in versions 2.29.7, 2.32.7, 2.33.8, and 2.34.2 validates `FileSize` against an upper bound (`MaxFileSize = 100 MiB`) before allocation. As a workaround, restrict access to the provisioner daemon serve endpoint to trusted provisioner daemon service accounts.