| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Vulnerability in the PeopleSoft Enterprise HCM Global Payroll Switzerland product of Oracle PeopleSoft (component: Global Payroll for Switzerland). The supported version that is affected is 9.2. Easily exploitable vulnerability allows high privileged attacker with logon to the infrastructure where PeopleSoft Enterprise HCM Global Payroll Switzerland executes to compromise PeopleSoft Enterprise HCM Global Payroll Switzerland. Successful attacks of this vulnerability can result in unauthorized update, insert or delete access to some of PeopleSoft Enterprise HCM Global Payroll Switzerland accessible data as well as unauthorized read access to a subset of PeopleSoft Enterprise HCM Global Payroll Switzerland accessible data and unauthorized ability to cause a partial denial of service (partial DOS) of PeopleSoft Enterprise HCM Global Payroll Switzerland. CVSS 3.1 Base Score 4.2 (Confidentiality, Integrity and Availability impacts). CVSS Vector: (CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:L/I:L/A:L). |
| MIME::Parser versions before 5.521 for Perl set no limit on the number of message parts by default, allowing memory exhaustion.
The max_parts option defaulted to -1, which disables the limit, so a parser created with default settings builds an entity for every part however many a message has.
Version 5.521 sets max_parts to 1000 and max_depth to 64 by default. Setting either to -1 still removes the limit. |
| OpenTelemetry Python provides the Python API and SDK for OpenTelemetry. Prior to 1.45.0, JaegerPropagator.extract() in opentelemetry-propagator-jaeger processes inbound uberctx-* baggage values without entry, per-entry byte, or total-byte limits. Services that enable the optional Jaeger propagator can perform unnecessary CPU work and short-lived heap allocations when an untrusted carrier supplies numerous or oversized values, contributing to denial of service when transport-level limits do not constrain the input. Common default Python HTTP server limits reduce the practical impact, while custom getters, non-HTTP transports, or raised header limits increase exposure. This issue is fixed in version 1.45.0. |
| pypdf is a free and open-source pure-python PDF library. Prior to 6.21.0, an attacker can craft a PDF that causes large memory usage or long runtimes when an application retrieves the document's form fields. This issue is fixed in version 6.21.0. |
| HTTP::Body versions before 1.24_01 for Perl allow memory exhaustion via unbounded buffering of chunked request bodies.
In chunked mode, used when no content length is given, add() holds each chunk in memory until all of it has arrived. A line that is not a chunk-size line, a size line without CRLF, or a size too large to fit an integer leaves the parser waiting forever, and every later add() grows the buffer.
A remote attacker can exhaust memory in applications that pass chunked request bodies to HTTP::Body. |
| HTTP::Body versions before 1.23_01 for Perl allow memory exhaustion via an unbounded multipart part header block.
The multipart parser takes everything up to the first blank line after a boundary as the part's header block, with no limit on its size or number of lines. Every line is stored in the part's header hash, so a block of short lines costs about 60 bytes of memory per input byte.
A remote attacker can exhaust worker memory with a single request. |
| HTTP::Body versions before 1.23_01 for Perl allow memory and temporary file exhaustion via an unlimited number of form fields and multipart parts.
The urlencoded parser splits the whole body on its separators at once, creating one scalar per separator before any field is stored. This costs about 90 bytes of memory per separator byte. The multipart parser creates a temporary file for every part that carries a filename. Neither parser limits how many fields or parts a body may hold.
A remote attacker can exhaust worker memory with a body made of separators, or create thousands of temporary files with one request of small file parts. |
| Allocation of resources without limits or throttling in Windows SMB Server allows an unauthorized attacker to deny service over a network. |
| Apache Kafka's code-generated protocol readers pre-size an array's collection from the element count declared by the sender. That count is checked only against the bytes remaining in the request buffer, which assumes about one byte per element; because most elements need several bytes, a request can declare far more elements than the buffer holds and still pass. For a keyed array the reader then allocates an ImplicitLinkedHashCollection of capacity (2 * count +1), so a request of a few tens of megabytes can force a heap allocation several times larger before any element is read. The pattern is emitted into every generated reader, so it affects all Kafka API types with an array field.
Impact:
Request parsing happens before any authorization check. On a listener that does not require authentication (for example PLAINTEXT), an unauthenticated attacker can send a few concurrent requests that each declare a very large=
array length and allocate many times their wire size in broker heap, crashing the broker with an OutOfMemoryError. The reporter demonstrated three concurrent ~90 MB ProduceRequest (v3) connections exhausting a 1 GB heap (~8x amplification). On listeners that require authentication, the attacker needs valid credentials but no specific ACL, since parsing precedes authorization..
Mitigation:
Upgrade to Apache Kafka 4.2.2, 4.3.2, or 4.4.0. Until then, lowering socket.request.max.bytes and restricting network access to broker listeners reduces, but does not remove, exposure.
Resolution:
From Apache Kafka 4.2.2, 4.3.2, and 4.4.0: generated readers cap the initial array pre-allocation at MessageUtil.MAX_PREALLOCATED_ARRAY_CAPACITY (1000) and grow it on demand, and reject a declared array length above MessageUtil.MAX_ARRAY_LENGTH (1,000,000). |
| The broker-side PushTelemetry API (KIP-714) validates only the compressed size of a client's metrics payload against telemetry.max.bytes (default 1 MB) before decompressing it. ClientTelemetryUtils.decompress() then decompresses the payload with no limit on the decompressed output size, growing a heap buffer until the compressed input is exhausted. A small, highly compressible payload (for example gzip-compressed zeros) can therefore expand to hundreds of megabytes of broker heap.
Impact:
An authenticated client can send a PushTelemetry request with a small compressed payload that decompresses to a very large size, consuming broker heap out of proportion to the request size. Repeated or concurrent requests can exhaust the broker heap and cause an OutOfMemoryError, degrading or crashing the broker; a client that targets multiple brokers can affect cluster availability. PushTelemetry is available to any authenticated client and is not gated by an ACL.
Mitigation:
Upgrade to Apache Kafka 4.2.2, 4.3.1, or 4.4.0. On affected versions there is no configuration that fully prevents the amplification, because telemetry.max.bytes bounds only the compressed size; lowering telemetry.max.bytes reduces the worst-case decompressed size proportionally and is a partial mitigation.
Resolution:
- From Apache Kafka 4.2.2, 4.3.1, and 4.4.0: ClientTelemetryUtils.decompress() enforces a maximum decompressed size equal to telemetry.max.bytes (default 1 MB). Decompression reads in bounded chunks and aborts with a TelemetryTooLargeException once the decompressed total exceeds the limit, so an over-large or highly compressible payload is rejected instead of being fully expanded in heap. The decompressed size is therefore bounded by default. |
| Allocation of resources without limits or throttling in Windows Netlogon allows an authorized attacker to deny service over a network. |
| Pillow is a Python imaging library. From 8.1.0 until 13.0.0, Pillow can allocate an APNG disposal background at the full canvas size before applying the decompression-bomb check. A crafted APNG with a small first frame, a very large declared canvas, and background disposal or first-frame OP_PREVIOUS reaches PngImageFile._seek while Image.open() positions frame zero. The full-canvas allocation occurs inside Image.open() without requiring pixel loading or frame iteration. This can exhaust memory and deny service. This issue is fixed in version 13.0.0. |
| AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. Prior to 3.14.4, keepalive timeout handling is absent during the initial portion of a request. An attacker can keep an idle connection open indefinitely before sending any request data, consuming server connection capacity. This issue is fixed in version 3.14.4. |
| In Progress® Telerik® Document Processing Libraries prior to version 2026.3.1027, uncontrolled recursion, infinite loop, inefficient algorithmic complexity and resource allocation vulnerabilities in RadPdfProcessing and AI document summarization and question answering allow an unauthenticated attacker to terminate or hang the host process via a crafted PDF document or document text submitted for summarization or question answering. |
| vLLM is an inference and serving engine for large language models. From 0.19.0 until 0.32.0, authenticated callers can supply a request chat template when no server-side --chat-template is configured, or a malicious model repository can provide a template that is compiled and rendered by tokenizer.apply_chat_template() without a wall-clock timeout, output-size limit, or iteration bound. Rendering runs in a ThreadPoolExecutor with one worker by default, so a nonterminating render can block /v1/responses and other chat-template users after the request ends, while an output-expanding render can exhaust server memory. Harmony models are not affected because they do not use this Jinja path. This issue is fixed in version 0.32.0. |
| vLLM is an inference and serving engine for large language models. Prior to 0.32.0, the Phi-4 multimodal audio encoder in phi4mm_audio.py and phi4mm_utils.py uses eager attention by default, allowing a remote client to submit one legal long audio clip that causes MultiHeadedAttention.forward_attention to materialize and retain full attention matrices in self.attn. The scaled dot-product attention branch does not materialize these matrices. The resulting quadratic GPU-memory use can cause an out-of-memory condition and terminate EngineCore for all users. This issue is fixed in version 0.32.0. |
| vLLM is an inference and serving engine for large language models. From 0.16.0 until 0.32.0, the /v1/responses endpoint allows an authenticated caller to place an attacker-controlled template in chat_template_kwargs[chat_template] when no server template is configured. ChatParams.get_apply_chat_template_kwargs() preserves that value without enforcing trust_request_chat_template, so the request can bypass the intended trust policy and cause CPU or memory exhaustion through Jinja rendering. This issue is fixed in version 0.32.0. |
| Allocation of resources without limits in password-based private-key decryption (PbeUtilities.GenerateCipherParameters) in Legion of the Bouncy Castle Inc. bc-csharp before 2.7.0 allows an attacker who can supply an encrypted private key, such as a PKCS#8 EncryptedPrivateKeyInfo or "ENCRYPTED PRIVATE KEY" PEM file, to cause a denial of service through CPU exhaustion via an iteration count close to 2^31, because the count is taken from the unauthenticated algorithm parameters without an upper bound and the key derivation runs before the password or the data can be checked. PKCS#5 PBES1 and PBES2 (PBKDF2), the PKCS#12 PBE algorithms and CMS password recipients (CmsPbeKey) are affected. Loading PKCS#12 files with Pkcs12Store is covered by CVE-2026-63572, and a zero or negative count with the PKCS#12 algorithms by CVE-2026-63575. |
| Allocation of Resources Without Limits or Throttling vulnerability in the HTTP/2 request body reader of mtrudel bandit allows an unauthenticated remote attacker to exhaust server memory via a request body sent as many 1-byte DATA frames.
do_read_data/5 in lib/bandit/http2/stream.ex keeps every DATA frame payload as its own list element until the read returns. The :length option of read_body/2 counts body bytes, not frames, so a body of 1-byte frames costs a list cell and a binary term per byte. Interleaving the frames across up to 500 concurrent streams per connection keeps each stream consuming its frames as they arrive; in the reporter's test, 100 streams held 25 to 40 MiB of stream process memory for 5 MB sent. Only routes whose Plug reads the request body are affected, which includes any route behind Plug.Parsers.
This issue affects bandit: from 0.3.1 before 1.14.1. |
| Allocation of resources without limits or throttling in OpenSSH for Windows allows an unauthorized attacker to deny service over a network. |
