Base de CVEs

Vulnerabilities in HPE Networking EdgeConnect SD-WAN Gateways could allow an unauthenticated adjacent attacker to conduct denial-of-service attacks. Successful exploitation could allow an attacker to crash the system, preventing it from rebooting without manual intervention and disrupting network operations.

Vulnerability in the PeopleSoft Enterprise PeopleTools product of Oracle PeopleSoft (component: Ren Server). Supported versions that are affected are 8.61-8.63. Easily exploitable vulnerability allows unauthenticated attacker with network access via HTTP to compromise PeopleSoft Enterprise PeopleTools. Successful attacks of this vulnerability can result in unauthorized ability to cause a hang or frequently repeatable crash (complete DOS) of PeopleSoft Enterprise PeopleTools. CVSS 3.1 Base Score 7.5 (Availability impacts). CVSS Vector: (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H).

Http4s is a Scala interface for HTTP services. Prior to 0.23.35 and 1.0.0-M47, An Ember server with HTTP/2 enabled through withHttp2 does not enforce SETTINGS_MAX_CONCURRENT_STREAMS for peer-created streams. One unauthenticated connection can open an unbounded number of streams, each retaining per-stream state until heap exhaustion. The same unchecked allocation is reachable in an ember-client through server-initiated PUSH_PROMISE frames because enablePush is not enforced. This issue is fixed in versions 0.23.35 and 1.0.0-M47.

Http4s is a Scala interface for HTTP services. Prior to 0.23.35 and 1.0.0-M47, Ember’s HTTP/2 flow-control window is replenished according to bytes received from the network rather than bytes consumed by the application, while each stream stores DATA in an unbounded channel. A hostile peer can therefore send a body faster than a slow or non-draining application consumes it, retaining payloads in heap on an ember-server or ember-client configured with withHttp2. The patch bounds the per-stream H2Connection body channel so application consumption applies backpressure. This issue is fixed in versions 0.23.35 and 1.0.0-M47.

Http4s is a Scala interface for HTTP services. Prior to 0.23.35 and 1.0.0-M47, Ember HTTP/2 serializes outbound frames through one unbounded queue consumed by writeLoop. When the peer stops reading, an unauthenticated HTTP/2 client can continue sending PING, SETTINGS, or DATA frames that cause Ember to enqueue acknowledgments or WINDOW_UPDATE frames faster than the writer drains them, exhausting heap memory on a server built with withHttp2. The shared behavior also affects an ember-client connected to a hostile HTTP/2 server, and the patch replaces the unbounded path with bounded, backpressured outbound queues. This issue is fixed in versions 0.23.35 and 1.0.0-M47.

Http4s is a Scala interface for HTTP services. Prior to 0.23.35 and 1.0.0-M47, The shared WebSocket decoder permits unbounded message buffering because defragmentation accumulates fragments without a limit and FrameTranscoder accepts declared lengths up to Int.MaxValue. A remote client that completes a WebSocket handshake against an http4s-blaze-server or http4s-ember-server endpoint can exhaust server memory with oversized frames or fragmented messages. The patched decoder applies a configurable 64 MiB default limit to individual frames and defragmented messages through EmberServerBuilder.withMaxWebSocketMessageSize. This issue is fixed in versions 0.23.35 and 1.0.0-M47.

Http4s is a Scala interface for HTTP services. Prior to 0.23.35 and 1.0.0-M47, the DigestAuth server middleware removes fresh nonces and stops eviction at the first stale nonce because its stale-nonce comparison is inverted. On an application that protects at least one route with DigestAuth, an unauthenticated attacker can repeatedly trigger authentication challenges, causing the persistent nonce map to grow until the JVM exhausts heap memory. This issue is fixed in versions 0.23.35 and 1.0.0-M47.

mcp-searxng is a Model Context Protocol server that gives AI assistants web search and URL-reading capabilities through SearXNG. Prior to 1.7.1, web_url_read in src/index.ts passes a caller-supplied URL to readUrlContent() in src/url-reader.ts, where checkContentLength() treats a missing Content-Length header as an inconclusive preflight and the normal and error paths then consume the complete body with response.text(). A server that omits Content-Length can therefore bypass URL_READ_MAX_CONTENT_LENGTH_BYTES and force unbounded memory use. The resulting string is also processed by NodeHtmlMarkdown.translate(), increasing CPU consumption and allowing an unauthenticated HTTP client to cause denial of service. This issue is fixed in version 1.7.1.

IBM Verify Identity Access could allow a remote attacker to cause a denial of service due to insufficient validation of incoming request resources.

This High severity DoS (Denial of Service) vulnerability was introduced in versions 8.9.0, 9.0.1, 9.1.0, 9.2.0, 9.3.1, 9.4.0, 9.5.1, 10.0.2, 10.1.0, and 10.2.0 of Confluence Data Center. This DoS (Denial of Service) vulnerability, with a CVSS Score of 7.1, allows an authenticated attacker to cause a resource to be unavailable for its intended users by temporarily or indefinitely disrupting services of a host connected to a network. Atlassian recommends that Confluence Data Center customers upgrade to latest version, if you are unable to do so, upgrade your instance to one of the specified supported fixed versions: Confluence Data Center 9.2: Upgrade to a release greater than or equal to 9.2.24 Confluence Data Center 10.2: Upgrade to a release greater than or equal to 10.2.17 See the release notes ([https://confluence.atlassian.com/doc/confluence-release-notes-327.html]). You can download the latest version of Confluence Data Center from the download center ([https://www.atlassian.com/software/confluence/download-archives]). This vulnerability was reported via our Penetration Testing program.

Crawl4AI before 0.9.3 contains an uncontrolled resource consumption vulnerability in PDFContentScrapingStrategy that allows untrusted clients to cause denial of service. Attackers can select the PDF scraping strategy in POST requests to download large remote PDFs without size or page limits, exhausting disk, CPU, and bandwidth on shared workers.

A resource exhaustion issue was addressed with improved input validation. This issue is fixed in macOS Golden Gate 27, macOS Sequoia 15.8, macOS Tahoe 26.7. A remote attacker may be able to cause a denial-of-service.