Intelligence
Explorer.

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. A per-request backend mismatch can re-raise a grammar compilation exception, padding produced by the ngram_gpu speculative-decoding mode can pass a negative token to guidance validation, and the Rust frontend can admit empty structured-output values that the Python frontend rejects, allowing ordinary constrained-generation requests to terminate the shared engine. This issue is fixed in version 0.30.0.

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, OpenAI-compatible request models accept a non-empty cache_salt value without enforcing the character and length restrictions required by the IPCCacheServerKey consumer in LMCache-MP. On deployments using the LMCache-MP connector, a salt that contains a forbidden character or exceeds the permitted length can raise an uncaught ValueError during scheduler cache lookup, causing EngineCore to terminate and denying service to all concurrent users. This issue is fixed in version 0.30.0.

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, flash late-interaction scoring at the /score and /rerank endpoints derives each worker's query_key value from the caller-controlled X-Request-Id header. A concurrent request that reuses a victim's identifier can overwrite the cached query embedding so the victim's documents are scored against the attacker's query, and shared use counters can also cause a late-interaction cache-miss error. This issue is fixed in version 0.30.0.

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the /inference/v1/generate endpoint in the disaggregated scale-out path accepts caller-supplied tensors in the features.kwargs_data field, cache identifiers in the features.mm_hashes field, ranges in the features.mm_placeholders field, and wire-selected multimodal field processors without rebinding them to the active model renderer contract. Forged grid geometry, field types, or non-positive placeholder lengths can terminate the shared EngineCore; when an attacker knows or can induce a victim's content hash, forged cache hashes can poison or retrieve cross-request encoder-cache state; and dropped sparse placeholder masks can alter replayed transport semantics. This issue is fixed in version 0.30.0.

vLLM is an inference and serving engine for large language models. Prior to 0.28.0, the default mirrored multimodal LRU cache can commit a media hash in the frontend sender cache during multimodal rendering and before engine admission, while the engine receiver cache never receives the payload if that request is rejected. A later request reusing the same media hash causes MultiModalProcessorSenderCache to send no payload and MultiModalReceiverCache to reach an assertion with the message "Expected a cached item," producing a shared-service availability failure. This issue is fixed in version 0.28.0.

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, Harmony tool continuations submitted through "POST /v1/responses" requests rebuild the next-turn engine input without preserving the cache_salt value, placing the continuation prefix in the global unsalted cache namespace even when the caller enabled salting. On deployments with prefix caching enabled, which is the default, an authenticated tenant who can reconstruct a victim's low-entropy post-tool history can submit the same continuation and use the cached_tokens_per_turn count to determine whether the prefix was previously processed, defeating the intended tenant isolation of salted prefix caching. This issue is fixed in version 0.30.0.

A vulnerability was identified in girishsaraf Online-Appointment-Booking-System up to f427b4757128ca253d33d0cc4e87bbb9c999a4d5. This issue affects the function mysqli_query of the file locateus.php of the component Doctor Search Endpoint. The manipulation of the argument doctorname leads to sql injection. Remote exploitation of the attack is possible. The exploit is publicly available and might be used. This product follows a rolling release approach for continuous delivery, so version details for affected or updated releases are not provided. The project was informed of the problem early through an issue report but has not responded yet.

A vulnerability was determined in girishsaraf Online-Appointment-Booking-System up to f427b4757128ca253d33d0cc4e87bbb9c999a4d5. This vulnerability affects unknown code of the file get_town.php of the component AJAX Endpoint. Executing a manipulation of the argument countryid/townid/cid/didval/cidval can lead to sql injection. The attack may be launched remotely. The exploit has been publicly disclosed and may be utilized. This product operates on a rolling release basis, ensuring continuous delivery. Consequently, there are no version details for either affected or updated releases. The project was informed of the problem early through an issue report but has not responded yet.

GraphQL Tools provides utilities for building, stitching, and mocking GraphQL schemas. Prior to 12.0.1, the GraphQL Tools utils package's mergeDeep function follows inherited properties while recursively merging source objects and does not exclude __proto__, constructor, or prototype keys. An unauthenticated GraphQL client can alias fields to those names so responses from two subgraphs collide during ordinary supergraph result merging, causing mergeDeep to traverse Object and Function prototypes and overwrite Function.prototype.call with a subgraph-supplied value. This breaks subsequent requests in the process until restart. This issue is fixed in version 12.0.1.

A malicious frontend can submit an LLB definition that causes buildkitd to panic and terminate, interrupting all builds running on that daemon.

When proxy networking with CA injection is enabled, a build can modify its CA bundle before cleanup. This may cause cleanup to block, operate outside the build rootfs, or fail without failing the build.

openSIS Classic 9.3 allows an authenticated user with the built-in teacher role can select an arbitrary staff record through staff_id and cause the School Information update path to reset that selected account's password.

h3. Summary This is a vulnerability in Bitbucket Data Center, Confluence Data Center, Jira Service Management Data Center, Jira Software Data Center, Bamboo Data Center. Crowd Data Center, Crucible and Fisheye. This Arbitrary File Access vulnerability allows an unauthenticated attacker to access specific files within the web application root directory in affected versions. Exploitation requires prior knowledge of the target file's exact name and path; this vulnerability does not allow attackers to enumerate or list directory contents. In some configurations, there may be some sensitive files that make this highly severe.   h3. Context This vulnerability allows an unauthenticated remote attacker to access specific files within the web application root directory in affected versions. h3. Details: * The vulnerability must be addressed for affected versions of: Bitbucket Data Center, introduced in version >= 4.6.0, fix versions: 9.4.26, 10.2.8, 10.5.1 Confluence Data Center, introduced in version >= 5.10.0, fix versions 9.2.26, 10.2.19 Crowd Data Center, introduced in version >= 2.11.0, fix versions 6.3.7, 7.0.3, 7.1.1, 7.2.4 Jira Software Data Center, introduced in version >= 7.1.0, fix versions 9.12.40, 10.3.26, 11.3.12 Jira Service Management Data Center, introduced in version >= 3.1.0, fix versions 5.12.40, 10.3.26, 11.3.12 Bamboo Data Center >= 7.0.1, fix versions 10.2.24, 12.1.12 Crucible, fix versions 4.9.15 Fisheye, fix version 4.9.15 * Exploitation requires prior knowledge of the target file's exact name and path. * The vulnerability does not include the capability to enumerate or list directory contents.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.107.0 until 2.120.3, docling/backend/opendocument_backend.py uses the xlink:href attribute value of a draw:image element as a filesystem path when the referenced part is not found in the document archive. The _image_ref_from_odf_image function reads that attacker-controlled path without a scheme check, extraction-directory confinement, or the enable_local_fetch setting used by other backends. Readable files that Pillow can decode as images are embedded in converted output, and other existing paths can be distinguished through the attempted read. This issue is fixed in 2.120.3.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.82.0 until 2.118.1, HTMLBackendOptions(render_page=True) permits file URLs because HTMLDocumentBackend._get_browser_request_block_reason does not enforce the enable_local_fetch setting or confine local requests to the source document directory. Crafted path-backed HTML can embed a readable local text file in a browser-rendered page image when Playwright is installed. Only filesystem Path inputs are affected because stream inputs use an opaque origin, and the default configuration, command-line interface, docling-serve, and non-rendering backends are not affected. This issue is fixed in 2.118.1.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.0.0 until 2.131.0, the HTML, JATS, OpenDocument spreadsheet, and BoxNote backends, including docling/backend/html_backend.py, docling/backend/jats_backend.py, and docling/backend/boxnote_backend.py, accept the rowspan and colspan attribute values without an upper bound and execute loops or allocate a table grid proportional to the declared span. A very small document can therefore cause sustained CPU use or multi-gigabyte memory allocation, and the document_timeout setting does not interrupt the single backend conversion call. Export through the TableData.grid property can further materialize the oversized grid. This issue is fixed in 2.131.0.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.16.0 until 2.131.0, the InputFormat.JSON_DOCLING backend in docling/backend/json/docling_json_backend.py validates serialized DoclingDocument input without rejecting picture image references that contain local paths or file URIs. When the document is enriched or exported with ImageRefMode.EMBEDDED, the DoclingDocument._with_embedded_pictures and ImageRef.pil_image methods can open those references and place readable image bytes in Markdown or HTML output. Disclosure is limited to files Pillow can decode as images, while differing decode behavior can also reveal whether a path exists. Direct untrusted loading through docling-core is outside this Docling fix. This issue is fixed in 2.131.0.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.45.0 until 2.131.0, METS-GBS format detection in docling/datamodel/document.py and the backend in docling/backend/mets_gbs_backend.py call tarfile.TarFile.getmembers() before enforcing the max_member_count limit, causing the full archive member list to be allocated before the limit can stop processing. A small gzip-compressed tar archive with a very large number of empty members can therefore consume memory proportional to the declared member count, including during format detection before the allowed_formats restriction is applied. This issue is a residual weakness in the member-count protection added for CVE-2026-44018. This issue is fixed in 2.131.0.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.83.0 until 2.131.0, the KServeV2OcrModel class defined in docling/models/stages/ocr/kserve_v2_ocr_model.py sends page images to its configured endpoint without checking the pipeline_options.enable_remote_services setting, even when the caller sets that policy control to false. The StandardPdfPipeline._make_ocr_model method also fails to pass the flag into the OCR factory, allowing remote OCR processing in configurations that rely on remote services being disabled. The destination is configured by the caller rather than selected by an attacker. This issue is fixed in 2.131.0.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.27.0 until 2.131.0, Docling plugin factories in docling/models/factories/base_factory.py call load_setuptools_entrypoints() before applying the allow_external_plugins setting, so every module registered in the Docling entry-point group is imported even when external plugins are disabled. An installed third-party or compromised package can therefore execute import-time code when Docling starts, while the subsequent namespace filter misleadingly reports that the plugin was not loaded. This issue is fixed in 2.131.0.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.94.0 until 2.132.0, callers that opt into LatexBackendOptions(tikz_engine="tectonic") invoke docling/backend/latex/engines/tectonic.py to compile an untrusted TikZ body and document preamble without restricting TeX file primitives including \openin and \openout. Crafted input can read files available to the converter and create or overwrite writable files, and enabling the tikz_engine_allow_shell_escape option additionally permits shell commands through TeX. The default configuration, which does not enable Tectonic rendering, is not affected. This vulnerability is fixed in 2.132.0.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.91.0 until 2.132.0, validate_url_safety in docling/backend/utils/image_resource_loader.py validates a hostname with a single IPv4 lookup and then allows the HTTP client to resolve and parse the original URL again, permitting DNS rebinding, mixed public and internal address records, and backslash authority parser disagreement to reach internal services. HTMLBackendOptions(render_page=True) also allows HTTP and HTTPS browser requests without validating their resolved destination. Exploitation requires remote fetching to be enabled, and response content is exposed only when it is decoded as an image or passively rendered in a page screenshot. This issue is fixed in 2.132.0.

Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.95.0 until 2.132.0, the HTML image resource loader in docling/backend/utils/image_resource_loader.py forwards headers configured through the HTMLBackendOptions.headers setting to every remote image URL named by an untrusted document when enable_remote_fetch=True and fetch_images=True. The loader does not restrict those credentials to the source document's origin, allowing requests that carry custom headers such as API keys and cookies to follow cross-origin redirects and expose the caller's configured credentials to a document author. The default configuration is not affected because remote fetching and configured headers are required. This issue is fixed in 2.132.0.

A vulnerability was found in girishsaraf Online-Appointment-Booking-System up to f427b4757128ca253d33d0cc4e87bbb9c999a4d5. This affects the function mysqli_query of the file Admin/mlogin.php of the component Login Handler. Performing a manipulation of the argument uname/pass results in sql injection. The attack may be initiated remotely. The exploit has been made public and could be used. This product uses a rolling release model to deliver continuous updates. As a result, specific version information for affected or updated releases is not available. The project was informed of the problem early through an issue report but has not responded yet.