Vulnerabilities

h3. Summary<br /> <br /> 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&amp;#39;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.  <br /> <br /> h3. Context<br /> <br /> This vulnerability allows an unauthenticated remote attacker to access specific files within the web application root directory in affected versions.<br /> <br /> h3. Details:<br /> <br /> * The vulnerability must be addressed for affected versions of:<br /> Bitbucket Data Center, introduced in version &gt;= 4.6.0, fix versions: 9.4.26, 10.2.8, 10.5.1<br /> Confluence Data Center, introduced in version &gt;= 5.10.0, fix versions 9.2.26, 10.2.19<br /> Crowd Data Center, introduced in version &gt;= 2.11.0, fix versions 6.3.7, 7.0.3, 7.1.1, 7.2.4<br /> Jira Software Data Center, introduced in version &gt;= 7.1.0, fix versions 9.12.40, 10.3.26, 11.3.12<br /> Jira Service Management Data Center, introduced in version &gt;= 3.1.0, fix versions 5.12.40, 10.3.26, 11.3.12<br /> Bamboo Data Center &gt;= 7.0.1, fix versions 10.2.24, 12.1.12<br /> Crucible, fix versions 4.9.15<br /> Fisheye, fix version 4.9.15<br /> * Exploitation requires prior knowledge of the target file&amp;#39;s exact name and path.<br /> * The vulnerability does not include the capability to enumerate or list directory contents.

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&amp;#39;s password.

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.

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

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 2.94.0 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 2.27.0 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 2.83.0 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 2.45.0 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 2.16.0 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 2.0.0 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.

In AMD Versal™ Adaptive SoC devices, insufficient boundary checks in USB boot mode—when enabled through board modifications—could allow crafted images to trigger a buffer overflow and overwrite an active function pointer, which may result in arbitrary code execution during boot process. This condition could lead to potential impacts on confidentiality, integrity, and availability.