| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| A message body that is deeply nested and decoded by pn_message_body() could overflow the stack and cause a crash.
This issue affects Apache Qpid Proton C: through 0.40.0.
Users are recommended to upgrade to version 0.41.1, which fixes the issue. |
| A flaw was found in FreeIPA. A low-privilege authenticated user can exploit this vulnerability by submitting an oversized One-Time Password (OTP) key value. This oversized key is then decoded and re-encoded without proper size limits, consuming excessive CPU and memory resources. This can lead to a denial of service, degrading the availability of the IPA service. |
| A stack overflow vulnerability was found in gfs2-utils. The metadata walk code in metawalk.c uses alloca() with an untrusted inode height value from on-disk metadata without bounds validation, causing stack exhaustion and a denial of service when processing crafted GFS2 filesystem images. |
| A stack overflow vulnerability was found in gfs2-utils. The hash table traversal code in metawalk.c uses alloca() with an exponentially-derived size from the untrusted on-disk di_depth field without bounds validation. A crafted GFS2 filesystem image with a large di_depth value causes stack exhaustion and a denial of service when processed by fsck.gfs2, gfs2_edit, or savemeta. |
| Sliver is a command and control framework. Prior to 1.7.6, an HTTP(S) listener using the PNG encoder accepts attacker-controlled PNG dimensions without an effective decoded-size or pixel limit in util/encoders/images.go, while the listener nonce space implemented in server/encoders/encoders.go is small enough to search remotely. An unauthenticated attacker who identifies a valid nonce can submit a highly compressed image to PNGEncoder.Decode, where it expands during png.Decode, exhausting server memory and causing a complete loss of availability. This vulnerability is fixed in 1.7.6. |
| The Model Context Protocol TypeScript SDK provides TypeScript client and server implementations of the Model Context Protocol. From 1.3.0 until 1.32.0 in @modelcontextprotocol/sdk and from 2.0.0 until 2.3.0 in @modelcontextprotocol/server, HTTP servers did not enforce a limit on the number of array elements and object keys validated in one request. The affected surface is validation of HTTP requests containing arrays or object keys. The trigger is an array-element or object-key validation workload large enough to exhaust memory while remaining within the request size limit. A single request within the default 4 MiB limit can terminate the process with JavaScript heap exhaustion. No credentials are required unless the application authenticates before SDK processing. Tools accepting arrays or records carry the greatest risk. stdio-only servers do not expose the HTTP request path. Upgrading alone does not enable the new validation bound. Operators must configure both a tool-input element bound and an appropriate request body size limit. This issue is fixed in @modelcontextprotocol/sdk 1.32.0 and @modelcontextprotocol/server 2.3.0. |
| In the Linux kernel, the following vulnerability has been resolved:
drm/amdgpu: Limit BO list entry count to prevent resource exhaustion
Userspace can pass an arbitrary number of BO list entries via the
bo_number field. Although the previous multiplication overflow check
prevents out-of-bounds allocation, a large number of entries could still
cause excessive memory allocation (up to potentially gigabytes) and
unnecessarily long list processing times.
Introduce a hard limit of 128k entries per BO list, which is more than
sufficient for any realistic use case (e.g., a single list containing all
buffers in a large scene). This prevents memory exhaustion attacks and
ensures predictable performance.
Return -EINVAL if the requested entry count exceeds the limit
(cherry picked from commit 688b87d39e0aa8135105b40dc167d74b5ada5332) |
| 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. |
| Pillow is a Python imaging library. In versions 2.3.0 through 12.3.0, EPS rendering does not validate the scaled image dimensions before invoking Ghostscript. Applications that process untrusted EPS or PostScript files using an application-selected scale greater than one can incur excessive Ghostscript CPU and temporary disk consumption. In versions with decompression-bomb protection, the scaled output is checked only after Ghostscript has completed rendering, allowing resource consumption beyond the configured pixel limit. The amplification depends on the scale selected by the application, not an attacker-controlled scale value. This issue is fixed in version 13.0.0. |
| pypdf is a free and open-source pure-python PDF library. Prior to 6.21.0, an attacker can craft a PDF containing arrays or dictionaries with many elements, causing parsing to consume large amounts of memory. This issue is fixed in version 6.21.0. |
| pypdf is a free and open-source pure-python PDF library. Prior to 6.21.0, an attacker can craft a PDF containing a content stream with many small operations, causing parsing to consume large amounts of memory. This issue is fixed in version 6.21.0. |
| 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. |
| 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. |
| 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. |
| 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. |
| 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. |
| In the Linux kernel, the following vulnerability has been resolved:
s390/entry: Mark IRQ entries to fix stack depot warnings
The stack depot filters out everything outside of the top interrupt
context as an uninteresting or irrelevant part of the stack traces. This
helps with stack trace de-duplication, avoiding an explosion of saved
stack traces that share the same IRQ context code path but originate
from different randomly interrupted points, eventually exhausting the
stack depot.
Filtering uses in_irqentry_text() to identify functions within the
.irqentry.text and .softirqentry.text sections, which then become the
last stack trace entries being saved.
While __do_softirq() is placed into the .softirqentry.text section by
common code, populating .irqentry.text is architecture-specific.
Currently, the .irqentry.text section on s390 is empty, which prevents
stack depot filtering and de-duplication and could result in warnings
like:
Stack depot reached limit capacity
WARNING: CPU: 0 PID: 286113 at lib/stackdepot.c:252 depot_alloc_stack+0x39a/0x3c8
with PREEMPT and KASAN enabled.
Fix this by moving the IO/EXT interrupt handlers from .kprobes.text into
the .irqentry.text section and updating the kprobes blacklist to include
the .irqentry.text section.
This is done only for asynchronous interrupts and explicitly not for
program checks, which are synchronous and where the context beyond the
program check is important to preserve. Despite machine checks being
somewhat in between, they are extremely rare, and preserving context
when possible is also of value.
SVCs and Restart Interrupts are not relevant, one being always at the
boundary to user space and the other being a one-time thing.
IRQ entries filtering is also optionally used in ftrace function graph,
where the same logic applies. |
| In the Linux kernel, the following vulnerability has been resolved:
io_uring/tctx: work around xa_store() allocation error issue
syzbot triggered the following WARN_ON:
WARNING: CPU: 0 PID: 16 at io_uring/tctx.c:51 __io_uring_free+0xfa/0x140 io_uring/tctx.c:51
which is the
WARN_ON_ONCE(!xa_empty(&tctx->xa));
sanity check in __io_uring_free() when a io_uring_task is going through
its final put. The syzbot test case includes injecting memory allocation
failures, and it very much looks like xa_store() can fail one of its
memory allocations and end up with ->head being non-NULL even though no
entries exist in the xarray.
Until this issue gets sorted out, work around it by attempting to
iterate entries in our xarray, and WARN_ON_ONCE() if one is found. |
