CVE-2026-105749

MediumCVSS 6.5/10Last modified Oct 8, 2026

Description

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.

Metrics

CVSS 3.1 6.5/10CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H

Weakness enumeration

CWE-400CWE-789

Affected software

No affected versions have been published.

Timeline

Published
Oct 5, 2026
Last modified
Oct 8, 2026
NVD status
Modified

Related CVEs from 2026

CVE-2026-105758.8IBM MQ could allow an authenticated attacker to cause a denial of service or potentially escalate privileges due to a heap buffer overflow wCVE-2026-1057507.5Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.82.0 uCVE-2026-1057517.5Docling simplifies document processing by parsing diverse formats and providing integrations with the generative AI ecosystem. From 2.107.0 CVE-2026-1057523.1vLLM is an inference and serving engine for large language models. Prior to 0.30.0, Harmony tool continuations submitted through "POST /v1/rCVE-2026-1057536.5vLLM is an inference and serving engine for large language models. Prior to 0.28.0, the default mirrored multimodal LRU cache can commit a mCVE-2026-1057546.5vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the /inference/v1/generate endpoint in the disaggregatedCVE-2026-1057554.2vLLM is an inference and serving engine for large language models. Prior to 0.30.0, flash late-interaction scoring at the /score and /rerankCVE-2026-1057566.5vLLM is an inference and serving engine for large language models. Prior to 0.30.0, OpenAI-compatible request models accept a non-empty cachCVE-2026-1057576.5vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scCVE-2026-1057585.3vLLM is an inference and serving engine for large language models. From 0.24.0 until 0.30.0, the Qwen2VLVideoBackend and Qwen3VLVideoBackendCVE-2026-1057597.5vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the Rust frontend's track_http_metrics middleware recordCVE-2026-1057605.3vLLM is an inference and serving engine for large language models. Prior to 0.30.0, a caller can use the request-level media_io_kwargs field