| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| A security vulnerability has been detected in nipy nibabel up to 5.4.2. The affected element is the function array_from_file of the file nibabel/volumeutils.py of the component Header Handler. The manipulation leads to uncontrolled memory allocation. The attack is possible to be carried out remotely. The pull request to fix this issue awaits acceptance. |
| A flaw was found in openstack-network-exporter. The HTTP server within the component is configured without essential timeout settings, such as ReadHeaderTimeout. This vulnerability allows an unauthenticated, remote attacker to initiate multiple slow HTTP header connections. By trickling header bytes, the attacker can exhaust server resources, specifically file descriptors, leading to a Denial of Service (DoS) that prevents legitimate Prometheus metric scraping and alerting. |
| 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. |
| 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). |
| Apache Kafka's code-generated readers for flexible protocol versions read a tagged-field count declared by the sender and retain a RawTaggedField object for each unknown field. That count was bounded only by the outer request frame size (socket.request.max.bytes); it was not checked against the remaining buffer bytes or capped. Because each entry can be encoded in as little as two bytes (unknown tag 0, size 0), a modest request can declare tens of millions of tagged fields and force one object allocation per declared field. Flexible request headers (header version 2, used by flexible APIs such as ApiVersions v3) are parsed this way, so the amplification applies to the request header itself.
Impact:
The flexible request header is parsed on the network thread before authorization, request dispatch, and request-time quota accounting. A client can send a request of a few tens of megabytes whose header declares about 20 million tagged fields, forcing roughly that many RawTaggedField allocations and exhausting broker heap or inducing process-wide GC stalls, denying broker service. Because the header is parsed for pre-authentication APIs such as ApiVersions (v3), the allocation can occur before authentication; no Kafka resource ACL or quota is required.
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 bounds-check the tagged-field count for flexible-versioned messages, rejecting a negative count, a count exceeding the remaining buffer bytes, or a count exceeding a fixed maximum (10,000), before any per-field allocation. |
| 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. |
| Tanium addressed an infinite loop vulnerability in Threat Response Client Extension. |
| Vulnerability in the Oracle Outside In Technology product of Oracle Fusion Middleware (component: Outside In Clean Content SDK). The supported version that is affected is 8.5.8. Easily exploitable vulnerability allows unauthenticated attacker with network access via HTTP to compromise Oracle Outside In Technology. Successful attacks of this vulnerability can result in unauthorized creation, deletion or modification access to critical data or all Oracle Outside In Technology accessible data and unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of Oracle Outside In Technology. CVSS 3.1 Base Score 9.1 (Integrity and Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:H). |
| Echo is a Go web framework. From 4.0.0 until 4.16.1, Echo v4's opt-in BodyDump middleware reads complete request bodies into memory before handlers run and retains complete response bodies for the dump callback without capture limits. An unauthenticated client that can reach a route using BodyDump can submit large bodies or influence large responses, causing repeated or concurrent allocations that exhaust process memory. BodyDump is not enabled by default, and external request limits may reduce request-side exposure but do not bound response capture. This issue is fixed in 4.16.1. |
| Echo is a Go web framework. From 4.0.0 until 4.16.1, Echo v4's opt-in Decompress middleware exposes a gzip-decoded request stream without limiting its expanded size. A small compressed request can expand into a very large body when a handler reads or binds it, consuming excessive memory or CPU and allowing repeated or concurrent requests to cause denial of service. The middleware is not enabled by default, and limiting only the compressed request size does not bound the decoded size. This issue is fixed in 4.16.1. |
| 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. |
| Pillow is a Python imaging library. From 9.1.0 until 13.0.0, BmpRleDecoder.decode() in src/PIL/BmpImagePlugin.py permits crafted RLE BMP delta escapes and absolute-mode runs to append beyond the remaining dest_length without a per-branch cap. A delta can add roughly 255 image rows in one iteration, so a kilobyte-sized file with a large but permitted width can expand the data bytearray to hundreds of megabytes or more, causing memory-exhaustion denial of service. This issue is fixed in version 13.0.0. |
| 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. |
| 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. 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. |
