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| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2026-44272 | 2026-06-22 | 8.8 High | ||
| Dell Wyse Management Suite (WMS), versions prior to WMS 2605, contain an Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') vulnerability. A low privileged attacker with remote access could potentially exploit this vulnerability, leading to Unauthorized access. | ||||
| CVE-2026-47155 | 2026-06-22 | 6.5 Medium | ||
| vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, vLLM's revision pinning controls do not consistently apply to all artifacts loaded for a model. A deployment that supplies --revision or --code-revision can still load dynamic code, GGUF files, image processors, retrieval side weights, or same-repository subfolder weights/config from an unpinned/default revision. This is a supply-chain integrity issue for pinned vLLM deployments. Operators can believe they are serving a reviewed model revision while vLLM resolves behavior-affecting nested or sibling artifacts outside that reviewed revision. This vulnerability is fixed in 0.22.0. | ||||
| CVE-2026-41523 | 2026-06-22 | 7.5 High | ||
| vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, an assert-based security check in vLLM's activation function loading allows any unauthenticated attacker to achieve arbitrary code execution on the server by publishing a malicious HuggingFace model, when vLLM runs in Python optimized mode (python -O or PYTHONOPTIMIZE=1). This vulnerability is fixed in 0.22.0. | ||||
| CVE-2026-54232 | 2026-06-22 | 8.8 High | ||
| vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.1, the vLLM Dockerfile is vulnerable to a dependency confusion attack through the flashinfer-jit-cache package. The package is installed from a custom index (flashinfer.ai/whl/) using --extra-index-url, but the package name was not registered on PyPI, and UV_INDEX_STRATEGY="unsafe-best-match" is set globally. An attacker who registers flashinfer-jit-cache on PyPI with version 0.6.11.post2 can execute arbitrary code as root during the Docker build and backdoor every resulting container image, enabling exfiltration of all user prompts, API credentials, and model data from production vLLM deployments This vulnerability is fixed in 0.22.1. | ||||
| CVE-2026-54233 | 2026-06-22 | 6.5 Medium | ||
| vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, vLLM's /v1/audio/transcriptions endpoint limits compressed upload size but not decoded PCM output. A 25MB OPUS file expands to ~14.9GB of float32 PCM at decode time. This vulnerability is fixed in 0.23.1rc0. | ||||
| CVE-2026-54236 | 2026-06-22 | 5.3 Medium | ||
| vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, the fix for CVE-2026-22778, which introduced a sanitize_message helper that strips object-repr memory addresses from error messages before they reach the client, is incomplete: several response paths echo str(exc) directly to clients without calling sanitize_message. The unsanitized sites include the Anthropic API router in vllm/entrypoints/anthropic/api_router.py (the POST /v1/messages and POST /v1/messages/count_tokens handlers), the Server-Sent Events streaming converter in vllm/entrypoints/anthropic/serving.py, and the realtime speech-to-text WebSocket in vllm/entrypoints/speech_to_text/realtime/connection.py. These paths catch the exception inside the route coroutine and construct the JSONResponse themselves, bypassing the sanitizing global FastAPI exception handler, and WebSocket frames do not traverse that handler chain at all. Using the same primitive as the parent issue, an unauthenticated attacker can send malformed image bytes through the Anthropic Messages API image content parts so that PIL.Image.open raises an UnidentifiedImageError whose message contains the BytesIO object repr, leaking the heap memory address verbatim in the error.message field of the response body. This vulnerability is fixed in 0.23.1rc0. | ||||
| CVE-2026-54235 | 2026-06-22 | N/A | ||
| vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0. | ||||
| CVE-2026-48746 | 2026-06-22 | 9.1 Critical | ||
| vLLM is an inference and serving engine for large language models (LLMs). From 0.3.0 until 0.22.0, a vulnerability in ASGI web servers and starlette's trust on those web servers enables an authentication bypass of the OpenAI API AuthenticationMiddleware. It allows to use the API without providing the configured VLLM_API_KEY or --api-key. This vulnerability is fixed in 0.22.0. | ||||
| CVE-2026-53923 | 2026-06-22 | N/A | ||
| vLLM is an inference and serving engine for large language models (LLMs). From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels (csrc/quantization/gguf/gguf_kernel.cu) causes partial tensor processing. The output tensor is allocated at full size via torch::empty (uninitialized memory), but the dequantize CUDA kernel processes only a truncated number of elements. The unfilled portion of the output tensor retains whatever was previously in GPU memory. In multi-tenant inference deployments, this residual GPU memory may contain tensor data from other users' inference requests, constituting information disclosure. This vulnerability is fixed in 0.23.1rc0. | ||||
| CVE-2026-44223 | 2 Vllm, Vllm-project | 2 Vllm, Vllm | 2026-06-22 | 6.5 Medium |
| vLLM is an inference and serving engine for large language models (LLMs). From 0.18.0 to before 0.20.0, the extract_hidden_states speculative decoding proposer in vLLM returns a tensor with an incorrect shape after the first decode step, causing a RuntimeError that crashes the EngineCore process. The crash is triggered when any request in the batch uses sampling penalty parameters (repetition_penalty, frequency_penalty, or presence_penalty). A single request with a penalty parameter (e.g., "repetition_penalty": 1.1) is sufficient to crash the server. This vulnerability is fixed in 0.20.0. | ||||
| CVE-2026-55409 | 2026-06-22 | 7.6 High | ||
| Filament is a collection of full-stack components for accelerated Laravel development. From 3.0.0 until 3.3.53, a disabled RichEditor field rendered its raw state without sanitizing HTML. Where the data stored in this field's state isn't sanitized already when the form state was filled, an attacker could plant malicious HTML or JavaScript and achieve XSS that executes for users who view the form. This vulnerability is fixed in 3.3.53. | ||||
| CVE-2026-48067 | 2026-06-22 | 6.5 Medium | ||
| Filament is a collection of full-stack components for accelerated Laravel development. From filament/actions 4.0.0 until 4.11.4 and 5.6.4 and from filament/tables 3.0.0 until 3.3.51, the recordSelectOptionsQuery() method may be used to scope the options available in the Select field for AttachAction and AssociateAction. However, the built-in validation rule for these fields did not apply the same scope. As a result, a user who can trigger these actions could tamper with the Livewire component's state and submit an out-of-scope value. This vulnerability is fixed in filament/actions 4.11.4 and 5.6.4 and filament/tables 3.3.51. | ||||
| CVE-2026-48167 | 2026-06-22 | 6.4 Medium | ||
| Filament is a collection of full-stack components for accelerated Laravel development. From 4.0.0 until 4.11.5 and 5.6.5, the ImageColumn and ImageEntry components render raw database values without escaping HTML. Where the data passed to these components isn't validated, an attacker could plant malicious HTML or JavaScript and achieve stored XSS that executes for users who view the table or schema. This vulnerability is fixed in 4.11.5 and 5.6.5. | ||||
| CVE-2026-48166 | 2026-06-22 | 5.3 Medium | ||
| Filament is a collection of full-stack components for accelerated Laravel development. From 4.0.0 until 4.11.5 and 5.6.5, the login page has an observable timing discrepancy that allows unauthenticated attackers to enumerate registered email addresses. The impact is limited to disclosing whether an account exists for a given email. This vulnerability is fixed in 4.11.5 and 5.6.5. | ||||
| CVE-2026-48505 | 2026-06-22 | 7.4 High | ||
| Filament is a collection of full-stack components for accelerated Laravel development. From 4.0.0 until 4.11.5 and 5.6.5, a flaw in the handling of recovery codes for app-based multi-factor authentication allows the same recovery code to be reused via concurrent submission. This issue does not affect email-based MFA. It also only applies when recovery codes are enabled. If an attacker gains access to both the user's password and their recovery codes, they get two authenticated sessions per recovery code burned instead of one, or more if they batch the parallel submissions wider, materially extending the attacker's window of access compared to what the single-use guarantee implies. This vulnerability is fixed in 4.11.5 and 5.6.5. | ||||
| CVE-2026-48500 | 2026-06-22 | 6.5 Medium | ||
| Filament is a collection of full-stack components for accelerated Laravel development. From 3.0.0 until 3.3.52, 4.11.5, and 5.6.5, any schema can contain a file upload form field, so Filament applies Livewire's WithFileUploads trait to the Livewire component the schema is embedded in. However, some schemas, such as the panel login form, do not require file uploads, and exposing unauthenticated temporary file uploads on these components is not an acceptable risk. On these components, an unauthenticated attacker could upload arbitrary files to the application's temporary storage, which could be abused to exhaust disk space or inflate storage costs. This vulnerability is fixed in 3.3.52, 4.11.5, and 5.6.5. | ||||
| CVE-2026-44889 | 2026-06-22 | 6.1 Medium | ||
| WebOb provides objects for HTTP requests and responses. Prior to 1.8.10, the normalization of the HTTP Location header during a redirect is vulnerable to an open redirect: WebOb joins the redirect target to the request URI using Python's urljoin, and since Python 3.10 the underlying urlsplit strips ASCII tab, carriage return, and newline characters before parsing, so a redirect target containing such characters can be reinterpreted as a protocol-relative URL whose authority is an attacker-controlled host. This bypasses the CVE-2024-42353 fix that escaped a leading double slash, allowing an attacker who influences the redirect location to send users to an arbitrary external site instead of the intended one. This vulnerability is fixed in 1.8.10. | ||||
| CVE-2026-51844 | 2026-06-22 | 9.8 Critical | ||
| Tenda AC7 v15.03.06.44 contains a stack buffer overflow vulnerability in the /goform/AdvSetMacMtuWan interface via the cloneType parameter. | ||||
| CVE-2026-51846 | 1 Tenda | 1 Ac7 | 2026-06-22 | 9.8 Critical |
| In Tenda AC7 v15.03.06.44, the wanSpeed parameter of the route /goform/AdvSetMacMtuWan has a stack buffer overflow vulnerability that can lead to remote arbitrary code execution. | ||||
| CVE-2026-44274 | 2026-06-22 | 7.8 High | ||
| Dell Wyse Management Suite (WMS), versions prior to WMS 2605, contain an Improper Link Resolution Before File Access vulnerability. A low privileged attacker with local access could potentially exploit this vulnerability, leading to Unauthorized access. | ||||