| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| MIME::Words versions before 5.521 for Perl allow memory exhaustion via repeated "=?" sequences in decode_mimewords.
For each "=?" that does not start a complete encoded word, decode_mimewords appends an error message containing the whole input string to $@. A boundary of 8,000 "=?" pairs (16,000 bytes) adds 8,000 copies of itself to $@, about 128 MB.
From version 5.518, MIME::Parser decodes every multipart boundary this way, so a remote sender can exhaust the memory of the parsing process with one Content-Type header. |
| MIME::Parser versions before 5.521 for Perl allow memory exhaustion via indented error messages from a truncated, deeply nested message.
Each stored parser diagnostic is indented by three spaces per nesting level. When a message nested N levels deep ends without its closing boundaries, every level logs an error at its own depth, so the stored diagnostics grow with the square of N. The defaults place no limit on nesting depth. |
| Vulnerability in the Oracle Solaris product of Oracle Systems (component: Services). The supported version that is affected is 11.4. Difficult to exploit vulnerability allows unauthenticated attacker with logon to the infrastructure where Oracle Solaris executes to compromise Oracle Solaris. Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of Oracle Solaris. CVSS 3.1 Base Score 5.1 (Availability impacts). CVSS Vector: (CVSS:3.1/AV:L/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H). |
| A vulnerability was found in a2ui-project a2ui up to 0.10.6. This affects the function DataContext.resolveSignal of the file renderers/web_core/src/v0_9/rendering/data-context.ts of the component Resolver. The manipulation results in resource consumption. The attack can be launched remotely. The exploit has been made public and could be used. The patch is identified as c76e17272e52c12c6dcf68905b1df978c39e9aa5. It is advisable to implement a patch to correct this issue. |
| A security flaw has been discovered in a2aproject a2a-java up to 1.2.0.Final. The impacted element is the function queue.offer of the component ChildQueue. Performing a manipulation results in resource consumption. The attack can be initiated remotely. Upgrading to version 1.3.0.Final is sufficient to resolve this issue. The patch is named be663f806efcfdddd2805d214fae4998379ac5f2. It is advisable to upgrade the affected component. |
| russh is a Rust SSH client and server library that includes an SSH agent protocol implementation. From 0.60.0 until 0.65.0, channel-open parsing accepts a peer-declared maximum_packet_size of zero and passes it into ChannelTx::poll_writable in russh/src/channels/io/tx.rs. The Channel::data, Channel::make_writer, and Channel::into_stream asynchronous write paths then calculate a writable size of zero and remain pending forever because window adjustments cannot satisfy a static zero packet maximum. An authenticated client can strand server writes, and a malicious server can strand client writes, allowing affected tasks, channels, and connections to accumulate without surfacing an error. This issue is fixed in version 0.65.0. |
| 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. |
| markdown-it is a Markdown parser. From versions 14.1.0 to before 14.3.3, and 15.0.0 to before 15.0.3, a link reference definition whose label or title is never closed is O(n²) with default options. Continuation lines are pulled lazily with str += lineContent in src/rules_block/reference.ts, and the subsequent charCodeAt and slice calls flatten the V8 cons-string, copying everything collected so far; this runs before the rule decides the definition is invalid. No options are required to trigger it. This issue has been patched in versions 14.3.3 and 15.0.3. |
| HTTP::Body versions before 1.23_01 for Perl allow CPU exhaustion via quadratic rescanning of a multipart body with a missing or malformed boundary.
Before the first part, and between parts, the multipart parser searches the whole buffered body for the next boundary. On a miss it keeps everything and searches again from the start when the next chunk arrives. A body with no boundary, or with a delimiter followed by neither CRLF nor "--", is therefore rescanned on every chunk, taking time quadratic in its size.
A remote attacker can exhaust worker CPU with a few such requests. |
| RE2JS is the JavaScript port of RE2, a regular expression engine that provides linear time matching. From 2.2.0 until 2.8.7, enabling LOOKBEHINDS and using repeated matching through matcher().find(), matchAll(), split(), or matcher().replaceAll() can cause quadratic total work. Machine.match restarts lookbehind scanning from offset zero for each requested start position, while Matcher-based APIs request capture slots that prevent the early exit used for captureless matching. Dense matches therefore repeatedly rescan the input, allowing attacker-influenced text to monopolize a single-threaded worker and deny service. This issue is fixed in version 2.8.7. |
| A user with the Viewer role in Grafana can crash the server by submitting a crafted server-side math expression (uncontrolled recursion). A user with permission to provision alert rules can make the outage persist across restarts. |
| When a broker decodes a compressed record batch, the per-record decoder reads a declared body size from the decompressed stream and allocates a buffer of that size before validating it against the bytes available or any configured limit. The size is attacker-controlled, and the batch CRC does not constrain it, so a small (around 90-byte), CRC-valid compressed produce request can declare a body size of up to about 2 GiB and force the broker to attempt that allocation, raising OutOfMemoryError. The record size limit (max.message.bytes), the request size limit, and client/broker quotas bound only the compressed wire size, not the declared decompressed size.
Impact:
An authenticated principal with Write on a topic can crash broker request-handler threads (reached when a batch's codec differs from the topic's compression.type and records are re-encoded) and any consumer that fetches the record, denying service. On brokers started with -XX:+ExitOnOutOfMemoryError, a common hardening, a single crafted request terminates the broker JVM. More seriously, a crafted record is accepted at ingest and written to disk; when the log-cleaner later reads it on a compacted topic, the OutOfMemoryError (an Error, not an Exception) terminates the cleaner thread, which is not restarted. With the default of a single cleaner thread, log compaction then stops for the entire broker, including the internal __consumer_offsets and __transaction_state topics, and the condition persists across restarts until the offending record is removed. The impact is availability only; no data is disclosed or altered.
Mitigation:
Upgrade to Apache Kafka 4.2.2, 4.3.2, or 4.4.0, and set max.decompressed.message.bytes (at the broker and/or topic level) to a bounded value appropriate for your workload. Upgrading alone is not sufficient: for backward compatibility this configuration defaults to an effectively unlimited value (about 2 GiB), so a broker remains exposed until the limit is set. Choose a value at or slightly above the largest legitimate decompressed record your applications produce, and comfortably below the broker heap divided by the number of request-handler and cleaner threads. Until you can upgrade and configure the limit, restrict Write access to trusted producers; quotas and max.message.bytes do not mitigate this issue.
Resolution:
From Apache Kafka 4.2.2, 4.3.2, and 4.4.0: the broker validates a record's declared decompressed body size against max.decompressed.message.bytes before allocating, on the produce-validation, log-compaction, and timestamp-lookup paths, and rejects oversized or negative sizes with InvalidRecordException. Operators must set this configuration to a bounded value to be protected, as its default is effectively unlimited. |
| Several Kafka deserialization paths read a size or count field from input data and use it directly to allocate an array, collection, or byte buffer, with no check against the bytes actually available. A small crafted input can therefore declare a very large size and force a multi-gigabyte allocation. The affected paths are, in Kafka Streams, ProcessorRecordContext (header count), ChangedDeserializer (varint value length), CombinedKeySchema (foreign-key length, which could also produce a negative size), ProcessorMetadata (key length), and AssignmentInfo group-assignment decoding; and, in the clients library, ListDeserializer (used by ListSerde).
Impact:
An attacker can trigger the oversized allocation and raise an OutOfMemoryError that crashes the affected consumer or Kafka Streams thread; the broker and the rest of the cluster are unaffected. The reachable surface depends on the path: writing a crafted record to a Streams application's internal changelog or repartition topics, or committing crafted offset metadata to its consumer group (Streams internal paths); writing a crafted record to any topic that a consumer reads with ListSerde (ListDeserializer); or, as a member of a Streams consumer group, returning crafted assignment data when elected leader (AssignmentInfo). Because a crafted record remains in its topic, the error can recur on restart. The record size limit (max.message.bytes) does not help, because the allocation is driven by a size field rather than by the input's length.
Mitigation:
Upgrade to Apache Kafka 4.2.2, 4.3.2, or 4.4.0. Where authorization is enabled, restrict write access to each application's internal topics and consumer group to its own principal, and restrict who can produce to topics that are consumed with ListSerde.
Resolution:
From Apache Kafka 4.2.2, 4.3.2, and 4.4.0: these deserialization paths validate the declared size against the remaining input before allocating and reject input that fails the check. |
| 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. |
| In Progress® Telerik® Document Processing Libraries prior to version 2026.3.1027, uncontrolled recursion, inefficient algorithmic complexity and infinite loop vulnerabilities in RadWordsProcessing allow an unauthenticated attacker to terminate or hang the host process via a crafted DOCX, DOC, RTF or HTML document. |
| 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. |
| In the Linux kernel, the following vulnerability has been resolved:
perf: Fix perf_pmu_migrate_context() leaving events behind
__perf_pmu_remove() walks the group leaders of a CPU and PMU with
perf_event_groups_for_cpu_pmu(), removing each one as it goes.
perf_remove_from_context() takes the leader out of the groups rbtree,
after which rb_next() on that node returns NULL, prematurely ending the
walk. Other groups stay behind in the source context.
On CPU hotplug, they are then torn down with the dying CPU. They keep
running until teardown, while the PMU's interrupt and migrated events
are on a new CPU, which drivers rely on never happening.
Walk ctx->event_list instead and pick out the PMU's events by their
pmu_ctx. |
| In the Linux kernel, the following vulnerability has been resolved:
gpiolib: fix memory leak in gpiod_set_array_value_complex() on error paths
A drive-by review by Sashiko reports that, after a failed call to
gpiochip_set_multiple(), gpiod_set_array_value() returns abruptly,
bypassing the freeing of possibly alloced bitmaps, potentially leaking
memory. It is an unlikely error path, but is possible.
Defer the return code check until after the bitmap_free() block. |
| 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. |
