The Visualizer – Tables & Charts Manager with Built-in AI Generator plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the 'backend-title' parameter in all versions up to, and including, 4.0.5 due to insufficient input sanitization and output escaping. This makes it possible for authenticated attackers, with contributor-level access and above, to inject arbitrary web scripts in pages that will execute whenever a user accesses an injected page.

Exposure of sensitive information to an unauthorized actor in Microsoft Graph allows an authorized attacker to disclose information over a network.

Hulumi is an open-source toolkit that ships secure-by-default cloud and platform infrastructure components for Pulumi. Prior to version 1.4.0, IAM-role policy checks can be bypassed when the role trusts multiple OIDC providers. This issue has been patched in version 1.4.0.

In the Linux kernel, the following vulnerability has been resolved: net/mlx5e: xsk: Fix unlocked writing to ICOSQ During napi poll, when the affinity changes and there's still XSK work to be done, we trigger an ICOSQ interrupt on the new CPU. However, this triggering on the ICOSQ is done unprotected. There are 2 such races: A) mlx5e_trigger_irq() is called while mlx5e_xsk_alloc_rx_mpwqe() is running from a different CPU due to affinity change. This can happen because IRQ triggering is done after napi_complete_done(). At this point the NAPI can be scheduled on a different CPU. Like this: CPU A (old affinity, NAPI tail) CPU B (new affinity, fresh NAPI) ------------------------------- -------------------------------- napi_complete_done() clears SCHED mlx5e_cq_arm(...) napi_schedule_prep() sets SCHED mlx5e_napi_poll() mlx5e_xsk_alloc_rx_mpwqe() mlx5e_icosq_sync_lock() // noop memcpy 640 B UMR body advance sq->pc by 10 mlx5e_trigger_irq(&c->icosq) wqe_info[pi] = {NOP, 1} mlx5e_post_nop() advances sq->pc B) mlx5e_trigger_irq() is called on the ICOSQ when mlx5e_trigger_napi_icosq() is running. The obvious fix would be to lock the ICOSQ. But ICOSQ has an optimized locking scheme that doesn't work for this scenario. Kick the async ICOSQ instead which is always locked. This issue was noticed in the wild with the following splat: netdevice: ge-0-0-1: Bad OP in ICOSQ CQE: 0xd WARNING: drivers/net/ethernet/mellanox/mlx5/core/en_rx.c:826 [...] [...] Call Trace: <IRQ> mlx5e_napi_poll+0x11d/0x7f0 [mlx5_core] __napi_poll+0x30/0x200 ? skb_defer_free_flush+0x9c/0xc0 net_rx_action+0x2fe/0x3f0 handle_softirqs+0xd8/0x340 __irq_exit_rcu+0xbc/0xe0 common_interrupt+0x85/0xa0 </IRQ> <TASK> asm_common_interrupt+0x26/0x40 [...] ---[ end trace 0000000000000000 ]--- mlx5_core 0000:08:00.0 ge-0-0-1: Error cqe on cqn 0x548, ci 0x2022, qn 0x8f4, opcode 0xd, syndrome 0x2, vendor syndrome 0x68 00000000: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00000010: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00000020: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00000030: 00 00 00 00 01 00 68 02 01 00 08 f4 de 14 59 d2 WQE DUMP: WQ size 16384 WQ cur size 0, WQE index 0x1e14, len: 64 00000000: 00 00 00 01 d9 ed 80 02 00 00 00 01 d9 ed 90 02 00000010: 00 00 00 01 d9 ed a0 02 00 00 00 01 d9 ed b0 02 00000020: 00 00 00 01 d9 ed c0 02 00 00 00 01 d9 ed d0 02 00000030: 00 00 00 01 d9 ed e0 02 00 00 00 01 d9 ed f0 02 mlx5_core 0000:08:00.0 ge-0-0-1: Error cqe on cqn 0x548, ci 0x2023, qn 0x8f4, opcode 0xd, syndrome 0x5, vendor syndrome 0xf9 00000000: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00000010: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00000020: 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00000030: 00 00 00 00 01 00 f9 05 01 00 08 f4 de 15 cf d2

Server-side request forgery (ssrf) in Azure AI Search allows an authorized attacker to elevate privileges over a network.

Missing authentication for critical function in Microsoft Azure Kubernetes Service allows an unauthorized attacker to elevate privileges over a network.

The Paid Membership Plugin, Ecommerce, User Registration Form, Login Form, User Profile & Restrict Content WordPress plugin before 4.16.18 does not consistently enforce the role restriction configured on its front-end registration role-selection field. The set of roles offered to the visitor and the set of roles the registration handler accepts are derived by two different parsers, and for some valid ways of configuring the offered roles the handler ignores the restriction and falls back to accepting any non-administrator role. Combined with the absence of a nonce on the public registration handler, this allows an unauthenticated visitor to register an account with a higher role, such as Editor or Author, than the form was configured to offer.

Kernel software installed and running inside a Guest VM may post improper commands to the GPU Firmware to trigger a write of data outside the Guest's virtualised GPU memory. Out of bounds accesses triggered by malware introduced to a Guest KMD could allow privilege escalation which escapes virtualization boundaries.

Arbitrary Class Instantiation via XML Feature Generator Descriptor and Format Name in Apache OpenNLP Versions Affected: - before 2.5.10 - before 3.0.0-M5 Description: Three code paths in Apache OpenNLP load a class by its fully-qualified name via Class.forName() and invoke its no-arg constructor without any prior validation of the class name or its type.  The affected paths are: (1) GeneratorFactory, which reads the class attribute of generator elements in an XML feature generator descriptor; such descriptors are embedded as artifacts in model archives (e.g. TokenNameFinder and POSTagger models) and are parsed during model loading, so an attacker who can supply a crafted model archive controls the class name directly. (2) StreamFactoryRegistry.getFactory(Class, String), which falls back to interpreting an unregistered format name as the fully-qualified class name of an ObjectStreamFactory; this is exploitable in applications that pass untrusted format names (e.g. exposing the -format parameter of the command-line tooling to external input). (3) StringInterners, which instantiates the interner implementation named by the opennlp.interner.class system property; this value is normally deployer-controlled, so it is hardened as defense in depth rather than being independently attacker-reachable. Exploitation requires a class with attacker-useful side effects in its static initializer or no-arg constructor (JNDI lookup, outbound network I/O, filesystem access) to be present on the classpath, so this is not drop-in remote code execution. T Mitigation: Upgrade to a fixed release. The fix routes all three paths through ExtensionLoader.instantiateExtension(...), which consults a package-prefix allowlist before Class.forName() is invoked, so a disallowed class is never loaded, initialized, or constructed. Classes under the opennlp. prefix remain permitted by default. Deployments that load models referencing feature generator factories, object stream factories, or string interners outside opennlp.* must opt those packages in, either programmatically via ExtensionLoader.registerAllowedPackage(String) before the first model load, or by setting the OPENNLP_EXT_ALLOWED_PACKAGES system property to a comma-separated list of allowed package prefixes. Users who cannot upgrade immediately should ensure all model files and format names are sourced from trusted origins and should audit their classpath for classes with side-effecting static initializers or constructors.

Weintek cMT3092X HMI allows a non-privileged user to modify tokens to escalate privileges.