| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.0.26 to before 1.56.0, aServer-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials. This vulnerability only affects applications that accept message history from external users. This vulnerability is fixed in 1.56.0. |
| IBM DB2 Merge Backup for Linux, UNIX and Windows 12.1.0.0 could allow an authenticated user to cause the program to crash due to a buffer being overwritten when it is allocated on the stack. |
| IBM DB2 Merge Backup for Linux, UNIX and Windows 12.1.0.0 could allow an authenticated user to cause the program to crash due to the incorrect calculation of a buffer size. |
| JinJava is a Java-based template engine based on django template syntax, adapted to render jinja templates. Prior to versions 2.7.6 and 2.8.3, JinJava is vulnerable to arbitrary Java execution via bypass through ForTag. This allows arbitrary Java class instantiation and file access bypassing built-in sandbox restrictions. This issue has been patched in versions 2.7.6 and 2.8.3. |
| Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 1.34.0 to before 1.51.0, a path traversal vulnerability in the Pydantic AI web UI allows an attacker to serve arbitrary JavaScript in the context of the application by crafting a malicious URL. In affected versions, the CDN URL is constructed using a version query parameter from the request URL. This parameter is not validated, allowing path traversal sequences that cause the server to fetch and serve attacker-controlled HTML/JavaScript from an arbitrary source on the same CDN, instead of the legitimate chat UI package. If a victim clicks the link or visits it via an iframe, attacker-controlled code executes in their browser, enabling theft of chat history and other client-side data. This vulnerability only affects applications that use Agent.to_web to serve a chat interface and clai web to serve a chat interface from the CLI. These are typically run locally (on localhost), but may also be deployed on a remote server. This vulnerability is fixed in 1.51.0. |
| Dell Unisphere for PowerMax, version(s) 10.2, contain(s) an External Control of File Name or Path vulnerability. A low privileged attacker with remote access could potentially exploit this vulnerability, leading to Information disclosure. |
| Dell Unisphere for PowerMax, version(s) 10.2, contain(s) an External Control of File Name or Path vulnerability. A low privileged attacker with remote access could potentially exploit this vulnerability to delete arbitrary files. |
| Dell Unisphere for PowerMax, version(s) 10.2, contain(s) an External Control of File Name or Path vulnerability. A low privileged attacker with remote access could potentially exploit this vulnerability, leading to the ability to overwrite arbitrary files. |
| Dell Unisphere for PowerMax, version(s) 10.2, contain(s) a Missing Authorization vulnerability. A low privileged attacker with remote access could potentially exploit this vulnerability, leading to Unauthorized access. |
| TrustTunnel is an open-source VPN protocol with a rule bypass issue in versions prior to 0.9.115. In `tls_listener.rs`, `TlsListener::listen()` peeks 1024 bytes and calls `extract_client_random(...)`. If `parse_tls_plaintext` fails (for example, a fragmented/partial ClientHello split across TCP writes), `extract_client_random` returns `None`. In `rules.rs`, `RulesEngine::evaluate` only evaluates `client_random_prefix` when `client_random` is `Some(...)`. As a result, when extraction fails (`client_random == None`), any rule that relies on `client_random_prefix` matching is skipped and evaluation falls through to later rules. As an important semantics note: `client_random_prefix` is a match condition only. It does not mean "block non-matching prefixes" by itself. A rule with `client_random_prefix = ...` triggers its `action` only when the prefix matches (and the field is available to evaluate). Non-matches (or `None`) simply do not match that rule and continue to fall through. The vulnerability is fixed in version 0.9.115. |
| An unauthenticated stack-based buffer overflow vulnerability exists in the HTTP API endpoint /cgi-bin/api.values.get. A remote attacker can leverage this vulnerability to achieve unauthenticated remote code execution (RCE) with root privileges on a target device. The vulnerability affects all six device models in the series: GXP1610, GXP1615, GXP1620, GXP1625, GXP1628, and GXP1630. |
| Magento-lts is a long-term support alternative to Magento Community Edition (CE). Prior to version 20.16.1, the admin url can be discovered without prior knowledge of it's location by exploiting the X-Original-Url header on some configurations. This issue has been patched in version 20.16.1. |
| TrustTunnel is an open-source VPN protocol with a server-side request forgery and and private network restriction bypass in versions prior to 0.9.114. In `tcp_forwarder.rs`, SSRF protection for `allow_private_network_connections = false` was only applied in the `TcpDestination::HostName(peer)` path. The `TcpDestination::Address(peer) => peer` path proceeded to `TcpStream::connect()` without equivalent checks (for example `is_global_ip`, `is_loopback`), allowing loopback/private targets to be reached by supplying a numeric IP. The vulnerability is fixed in version 0.9.114. |
| Jenkins 2.550 and earlier, LTS 2.541.1 and earlier accepts Run Parameter values that refer to builds the user submitting the build does not have access to, allowing attackers with Item/Build and Item/Configure permission to obtain information about the existence of jobs, the existence of builds, and if a specified build exists, its display name. |
| Jenkins 2.483 through 2.550 (both inclusive), LTS 2.492.1 through 2.541.1 (both inclusive) does not escape the user-provided description of the "Mark temporarily offline" offline cause, resulting in a stored cross-site scripting (XSS) vulnerability exploitable by attackers with Agent/Configure or Agent/Disconnect permission. |
| Sensitive data disclosure and manipulation due to improper authentication. The following products are affected: Acronis Cyber Protect 16 (Linux, Windows) before build 39938, Acronis Cyber Protect 15 (Linux, Windows) before build 41800. |
| A weakness has been identified in huggingface smolagents 1.24.0. Impacted is the function requests.get/requests.post of the component LocalPythonExecutor. Executing a manipulation can lead to server-side request forgery. It is possible to launch the attack remotely. The exploit has been made available to the public and could be used for attacks. The vendor was contacted early about this disclosure but did not respond in any way. |
| Sensitive data disclosure and manipulation due to improper authentication. The following products are affected: Acronis Cyber Protect 16 (Linux, Windows) before build 39938, Acronis Cyber Protect 15 (Linux, Windows) before build 41800. |
| Sensitive data disclosure and manipulation due to missing authentication. The following products are affected: Acronis Cyber Protect Cloud Agent (Linux, macOS, Windows) before build 39870, Acronis Cyber Protect 16 (Linux, macOS, Windows) before build 39938, Acronis Cyber Protect 15 (Linux, macOS, Windows) before build 41800. |
| PolarLearn is a free and open-source learning program. In 0-PRERELEASE-15 and earlier, a timing attack vulnerability in the sign-in process allows unauthenticated attackers to determine if a specific email address is registered on the platform. By measuring the response time of the login endpoint, an attacker can distinguish between valid and invalid email addresses. This occurs because the server only performs the computationally expensive Argon2 password hashing if the user exists in the database. Requests for existing users take significantly longer (~650ms) than requests for non-existent users (~160ms). |
