Base de CVEs

In the Linux kernel, the following vulnerability has been resolved: mptcp: allow subflow rcv wnd to shrink In MPTCP connection, the `window` field in the TCP header refers to the MPTCP-level rcv_nxt and it's right edge should not move backward. Such constraint is enforced at DSS option generation time. At the same time, the TCP stack ensures independently that the TCP-level rcv wnd right's edge does not move backward. That in turn causes artificial inflating of the MPTCP rcv window when the incoming data is acked at the TCP level and is OoO in the MPTCP sequence space (or lands in the backlog). As a consequence, the incoming traffic can exceed the receiver rcvbuf size even when the sender is not misbehaving. Prevent such scenario forcibly allowing the TCP subflow to shrink the TCP-level rcv wnd regardless of the current netns setting.

AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. In versions prior to 0.6.52, the Fill Text Template block is vulnerable to a Denial of Service (DoS) attack. While the backend implements a SandboxedEnvironment to prevent unauthorized attribute access (e.g., blocking __class__), it fails to limit the computational complexity or execution time of the expressions. An attacker can input computationally expensive Python/Jinja2 expressions that consume the server's CPU and memory, leading to a complete system hang or crash. In multi-tenant or self-hosted environments, this results in a complete service outage and "noisy neighbor" effects that require manual administrative intervention to recover. This issue has been fixed in version 0.6.52.

Mistune is a Python Markdown parser with renderers and plugins. Prior to 3.3.0, Mistune is vulnerable to a CPU exhaustion DoS due to superlinear (approximately O(n²)) behavior in parse_link_text. When parsing Markdown containing many consecutive [ characters, parse_link_text repeatedly scans the input using a regex search inside a loop. Each iteration re-scans a large portion of the remaining string, resulting in quadratic-time behavior. An attacker-controlled Markdown input can therefore trigger excessive CPU usage with a very small payload. This vulnerability is fixed in 3.3.0.

jackson-databind contains the general-purpose data-binding functionality and tree-model for Jackson Data Processor. From 2.13.0 until 2.14.0, a potential Denial-of-Service exists when attacker sends deeply nested JSON if (and only if) the service reads deeply nested (1000s of levels) JSON as JsonNode (ObjectMapper.readTree()) and writes out same (or modifided) node using JsonNode.toString(). This can consume significant amount of resources with concurrent relatively small requests (1000 nested arrays is 2kB). This vulnerability is fixed in 2.14.0.

Langflow is a tool for building and deploying AI-powered agents and workflows. Prior to 1.0.19, an attacker can send a /api/v1/files/upload/ request without any authentication token/cookies and abuse a very long multipart form boundary to make the langflow app unusable for all users for an indefinite amount of time. This vulnerability is fixed in 1.0.19.

Cap-go capgo (capgo-backend) before 12.128.12 contains an unauthenticated denial-of-service vulnerability arising from the audit_logs table's Row-Level Security (RLS) policy when accessed via the Supabase PostgREST API. Because the PostgreSQL query planner executes costly logic before RLS rejection, unfiltered queries to the public.audit_logs endpoint using the public anon key consistently trigger statement timeouts (PostgREST error 57014). Under concurrency, this exhausts database resources and causes cascading HTTP 500 failures on unrelated endpoints (e.g. /orgs), resulting in an application-layer denial of service.

Traefik before 2.10.5 and 3.0.0-beta4 is affected by a denial-of-service vulnerability in HTTP/2 request handling inherited from the Go standard library's HTTP/2 implementation (CVE-2023-44487 / CVE-2023-39325, the 'Rapid Reset' technique). A remote attacker can rapidly create and cancel HTTP/2 streams to exhaust server resources and cause service unavailability.

Python-Multipart is a streaming multipart parser for Python. Prior to 0.0.30, when parsing application/x-www-form-urlencoded bodies, QuerystringParser located the field separator with a two step lookup: it first scanned the entire remaining buffer for &, and only when no & existed anywhere ahead did it fall back to scanning for ;. For a body that uses ; as the separator and contains no &, every field iteration performed a full failed & scan over the entire remaining buffer before locating the nearby ;. With N semicolon separated fields in a chunk of size B, this yields O(B^2) byte comparisons per chunk. An attacker can submit a small crafted body of the form a;a;a;... and cause the parser to spend seconds of CPU per request. A handful of concurrent requests can exhaust worker processes. This vulnerability is fixed in 0.0.30.

The public dashboard query endpoint does not limit request body size before processing, allowing unauthenticated attackers to trigger excessive memory allocation by sending arbitrarily large JSON payloads. This can lead to denial of service through memory exhaustion. No valid dashboard access token or authentication is required to exploit this vulnerability.

IBM WebSphere Application Server 9.0, and 8.5 and IBM WebSphere Application Server - Liberty 17.0.0.3 through 26.0.0.6 are vulnerable to a denial of service, caused by sending a specially-crafted request. A remote attacker could exploit this vulnerability to cause the server to consume memory resources.

IBM WebSphere Application Server 9.0, and 8.5 and IBM WebSphere Application Server - Liberty 17.0.0.3 through 26.0.0.6 are vulnerable to a denial of service, caused by sending a specially-crafted request. A remote attacker could exploit this vulnerability to cause the server to consume memory resources.

Angular is a development platform for building mobile and desktop web applications using TypeScript/JavaScript and other languages. Prior to 22.0.1, 21.2.17, and 20.3.25, a Denial of Service (DoS) vulnerability exists in the @angular/common package of the Angular framework. The formatDate function, which is also utilized by the standard Angular DatePipe, does not properly limit or validate the length of the format parameter. When parsing a maliciously crafted, excessively long date format string (e.g., a repeating pattern or very large string), the internal parser splits the string iteratively using a regular expression loop. This results in uncontrolled resource consumption (high CPU utilization and excessive memory allocations), leading to a Denial of Service (DoS). This vulnerability is fixed in 22.0.1, 21.2.17, and 20.3.25.

js-toml is a TOML parser for JavaScript, fully compliant with the TOML 1.0.0 Spec. Versions up to and including 1.1.0 parse hexadecimal / octal / binary integer literals via a hand-written `parseBigInt` loop that multiplies a `BigInt` accumulator by the radix once per input digit. Each iteration performs a `BigInt * BigInt` operation on an accumulator that grows linearly with the number of digits already consumed, so the whole loop is O(n²) in the literal length. The lexer regex places no upper bound on the literal length, so a single TOML document containing one ~500 kB hex literal pins one CPU core for ~40 seconds on a modern laptop (Apple M-series, Node v22). Memory amplification is bounded but CPU amplification is severe and grows quadratically: doubling the literal length quadruples the work. A caller that invokes `load()` on attacker-controlled TOML (configuration upload endpoints, CI/CD systems ingesting third-party `*.toml`, IDE plugins, build tools) is exposed to a single-request CPU exhaustion DoS. Version 1.1.1 fixes the issue.

A flaw in Node.js HTTP/2 server API can cause servers to keep accepting data even after sending a `GOAWAY` frame. This vulnerability affects two supported release lines: **Node.js 22** and **Node.js 24**.

CometD is a scalable comet implementation for web messaging. In versions 5.0.0 through 5.0.22, 6.0.0 through 6.0.18, 7.0.0 through 7.0.18, and 8.0.0 through 8.0.8, bad clients that always send a fixed batch value when the server is using the acknowledgement extension may cause the unacknowledged message queue to grow indefinitely, eventually causing an `OutOfMemoryError`. Versions 5.0.23, 6.0.19, 7.0.19, and 8.0.9 patch the issue. As a workaround, disable the acknowledgement extension.

AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Prior to 0.6.63, `MediaDurationBlock` will download and store the video in a temporary directory without deleting before all noded are done. `StepThroughItemsBlock` can be used to iterate `MediaDurationBlock` multiple times. `StepThroughItemsBlock` does not limit the number of loops. In addition, `MediaDurationBlock ` does not limit the amount of disk space consumed in the current working directory and does not delete the video after outputing the result. When a malicious user chooses to screen shot many web pages, the disk space will eventually run out, causing a DoS. Version 0.6.63 patches the issue.

AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Prior to 0.6.63, `AddAudioToVideoBlock` will download and store the video and audio in a temporary directory without deleting before all noded are done. `StepThroughItemsBlock` can be used to iterate `MediaDurationBlock` multiple times. `StepThroughItemsBlock` does not limit the number of loops. In addition, `AddAudioToVideoBlock` does not limit the amount of disk space consumed in the current working directory and does not delete the video after outputing the result. When a malicious user chooses to screen shot many web pages, the disk space will eventually run out, causing a DoS. Version 0.6.63 patches the issue.

AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Prior to 0.6.63, ScreenshotWebPageBlock will store the captured screenshots in a temporary directory. `StepThroughItemsBlock` can be used to iterate `ScreenshotWebPageBlock` multiple times. `StepThroughItemsBlock` does not limit the number of loops. In addition, `ScreenshotWebPageBlock` does not limit the amount of disk space consumed in the current working directory. When a malicious user chooses to screen shot many web pages, the disk space will eventually run out, causing a DoS. Version 0.6.63 patches the issue.

AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Prior to 0.6.63, `StepThroughItemsBlock` can iterate all the contents in a list and send them to `FileStoreBlock` for downloading one by one. Although `FileStoreBlock` has access time limits for downloading files, `StepThroughItemsBlock` can be used to slowly iterate and download relatively small files (e.g., 100M) multiple times. `StepThroughItemsBlock` does not limit the number of loops. In addition, `FileStoreBlock` does not limit the amount of disk space consumed in the current working directory. When a malicious user chooses to download too many videos, the disk space will eventually run out, causing a DoS. Version 0.6.63 patches the issue.

AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Prior to 0.6.63, AutoGPT's LoopVideoBLock allows users to input a video file and process the video, such as looping it 5 times or extending the time, and finally writing it to disk. However, there is no limit on the resources that can be allocated during execution. For example, the number of loops is user-controllable and unlimited. When a malicious attacker loops too many times, the generated video is too large, and after writing it to disk, the disk space is exhausted, eventually causing DoS. Version 0.6.63 patches the issue.

LiquidJS is a Shopify/GitHub Pages compatible template engine written in pure JavaScript. In versions 10.25.7 and below, the date filter's strftime implementation parses width specifiers like %9999999d and forwards the captured width unchecked into pad()/padStart(), leading to memory and render limit bypass. In src/util/underscore.ts, the pad loop performs unbounded string concatenation without consulting the Context's memoryLimit or renderLimit, so a single small template ({{ x | date: '%5000000d' }}) produces megabytes of output and unbounded CPU. The memoryLimit and renderLimit options the docs (src/liquid-options.ts:87-92) advertise as DoS controls — and which the docstring explicitly mentions for strftime — are entirely bypassed. Exploitation can cause large memory allocations, high CPU usage, or OOM crashes per render. This issue has been fixed in version 10.26.0.