CVE Database

Color Notes 1.4 contains a denial of service vulnerability that allows attackers to crash the application by pasting excessively long character strings into note fields. Attackers can generate a payload containing 350,000 repeated characters and paste it twice into a new note to cause the application to stop responding.

Nerdbank.MessagePack is a NativeAOT-compatible MessagePack serialization library. Prior to 1.1.62, Nerdbank.MessagePack contains an uncontrolled stack allocation vulnerability in DateTime decoding. A malicious MessagePack payload can declare an oversized timestamp extension length, causing the reader to allocate an attacker-controlled number of bytes on the stack. This can trigger a StackOverflowException, which is not catchable by user code and terminates the process. This vulnerability is fixed in 1.1.62.

A vulnerability exists in the ngx_http_scgi_module and ngx_http_uwsgi_module modules that may result in excessive memory allocation or an over-read of data. When scgi_pass or uwsgi_pass is configured, an unauthenticated attacker with man-in-the-middle (MITM) ability to control responses from an upstream server may be able to read the memory of the NGINX worker process or restart it.  Note: Software versions which have reached End of Technical Support (EoTS) are not evaluated.

OpenTelemetry.OpAmp.Client is the OpAMP client for OpenTelemetry .NET. Prior to 0.2.0-alpha.1, when receiving responses from the OpAMP server over HTTP, the OpAMP client allocates an unbounded buffer to read all bytes from the server, with no upper-bound on the number of bytes consumed. This could cause memory exhaustion in the consuming application if the configured OpAMP server is attacker-controlled (or a network attacker can MitM the connection) and an extremely large body is returned in the response. This vulnerability is fixed in 0.2.0-alpha.1.

memono Notepad 4.2 contains a denial of service vulnerability that allows attackers to crash the application by pasting excessively long character buffers into note fields. Attackers can generate a payload containing 350000 repeated characters and paste it twice into a new note to trigger an application crash on iOS devices.

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.

Zserio is a framework for serializing structured data with a compact and efficient way with low overhead. Prior to 2.18.1, a crafted payload as small as 4-5 bytes can force memory allocations of up to 16 GB, crashing any process with an OOM error (Denial of Service). This vulnerability is fixed in 2.18.1.

Wasmtime is a runtime for WebAssembly. From 25.0.0 to before 36.0.7, 42.0.2, and 43.0.1, Wasmtime's Winch compiler backend contains a bug where translating the table.grow operator causes the result to be incorrectly typed. For 32-bit tables this means that the result of the operator, internally in Winch, is tagged as a 64-bit value instead of a 32-bit value. This invalid internal representation of Winch's compiler state compounds into further issues depending on how the value is consumed. The primary consequence of this bug is that bytes in the host's address space can be stored/read from. This is only applicable to the 16 bytes before linear memory, however, as the only significant return value of table.grow that can be misinterpreted is -1. The bytes before linear memory are, by default, unmapped memory. Wasmtime will detect this fault and abort the process, however, because wasm should not be able to access these bytes. Overall this this bug in Winch represents a DoS vector by crashing the host process, a correctness issue within Winch, and a possible leak of up to 16-bytes before linear memory. Wasmtime's default compiler is Cranelift, not Winch, and Wasmtime's default settings are to place guard pages before linear memory. This means that Wasmtime's default configuration is not affected by this issue, and when explicitly choosing Winch Wasmtime's otherwise default configuration leads to a DoS. Disabling guard pages before linear memory is required to possibly leak up to 16-bytes of host data. This vulnerability is fixed in 36.0.7, 42.0.2, and 43.0.1.

NVIDIA Triton Inference Server contains a vulnerability where insufficient input validation and a large number of outputs could cause a server crash. A successful exploit of this vulnerability might lead to denial of service.

SoftEtherVPN is a an open-source cross-platform multi-protocol VPN Program. In 5.2.5188 and earlier, a pre-authentication denial-of-service vulnerability exists in SoftEther VPN Developer Edition 5.2.5188 (and likely earlier versions of Developer Edition). An unauthenticated remote attacker can crash the vpnserver process by sending a single malformed EAP-TLS packet over raw L2TP (UDP/1701), terminating all active VPN sessions.

An attacker might be able to trick DNSdist into allocating too much memory while processing DNS over QUIC or DNS over HTTP/3 payloads, resulting in a denial of service. In setups with a large quantity of memory available this usually results in an exception and the QUIC connection is properly closed, but in some cases the system might enter an out-of-memory state instead and terminate the process.

NVIDIA Triton Inference Server contains a vulnerability in the HTTP endpoint where an attacker may cause a denial of service by providing a large compressed payload. A successful exploit of this vulnerability may lead to denial of service.