How severe is CVE-2026-105749?

CVE-2026-105749 has a CVSS score of 6.5/10, rated MEDIUM. Review your exposure and patch according to your risk tolerance.

Which packages are affected by CVE-2026-105749?

CVE-2026-105749 affects the following packages: docling (PyPI), docling-slim (PyPI). Ecosystems affected: PyPI.

How do I fix CVE-2026-105749?

Update docling to 2.131.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-105749 is resolved across your whole dependency graph.

How do I detect CVE-2026-105749 in my PyPI dependencies?

Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for docling, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

How do I mitigate CVE-2026-105749 if there is no patch (or I can't update yet)?

Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Is CVE-2026-105749 actively exploited in the wild?

No public exploit code has been indexed for CVE-2026-105749 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for CVE-2026-105749?

CVE-2026-105749 has an EPSS (Exploit Prediction Scoring System) score of 0.3%, placing it in the 18th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is CVE-2026-105749?

CVE-2026-105749 is classified as Uncontrolled Resource Consumption (CWE-400), CWE-789 (CWE-789). These weakness types describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation.

When was CVE-2026-105749 published, and has it been updated?

CVE-2026-105749 was published on October 5, 2026 and was last updated on October 21, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍

🐍 PyPI

Not in CISA KEV

MEDIUM severity

CVE-2026-105749 — docling

MEDIUMFix: docling-project/docling@c5b4429

CVE-2026-105749 is a medium-severity (CVSS 6.5) Uncontrolled Resource Consumption vulnerability in docling. A fix is available for docling — see the affected versions and patch details below.

Docling: Unbounded table rowspan/colspan in HTML, JATS, ODS and BoxNote backends causes CPU/memory exhaustion

Also known asGHSA-cgc7-9qp3-86m3PYSEC-2026-4195PYSEC-2026-4211

Published

Oct 5, 2026

Updated

Oct 21, 2026

Affected

2 pkgs

Patched

2 / 2

Exploits

None indexed

Exploitation data as of Oct 22, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

Proof-of-concept exploit code exists

CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.

Exploitation and automatability from CISA’s SSVC triage for CVE-2026-105749.

EPSS Exploitation Probability

via FIRST.org ↗

0.3%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs18th percentile — riskier than 18% of all scored CVEsHighest risk

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

How urgent is this, really

CVE-2026-105749 by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.

Where this sits among everything scored

Of 394,803 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.

Real-World Exposure

2 pkgs affected

🐍docling🐍docling-slim

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

Summary

The HTML, JATS, ODS (OpenDocument spreadsheet) and BoxNote backends accept table rowspan / colspan values without an upper bound. A few bytes of input, such as <td rowspan="100000000">, make docling run loops proportional to the declared span and allocate a table grid of the declared size. The result is CPU and memory exhaustion.

Details

docling/backend/html_backend.py (_get_cell_spans) parses span attributes with no upper limit. The cell-filling loop then iterates row_span × col_span times.
docling/backend/jats_backend.py and docling/backend/boxnote_backend.py fill their tables the same way.
The OpenDocument spreadsheet path scans the declared span range.
Export (for example export_to_markdown()) materialises the full grid through TableData.grid in docling-core.

document_timeout does not bound this. It is checked between pipeline stages, and these backends convert the whole document in a single call. max_file_size and max_num_pages do not help because the payload is tiny.

Measured on 2.130.0: a 54-byte HTML file with rowspan="1e8" takes about 4.4 s of CPU, and the time grows linearly with the value. A 52-byte file with colspan="3000000" takes about 23 s and reaches 4.5 GB peak memory during Markdown export.

Impact

Denial of service of the converting process from a very small input document. Confidentiality and integrity are not affected.

Proof of concept

<table><tr><td colspan="3000000">x</td></tr></table>

from docling.document_converter import DocumentConverter
DocumentConverter().convert("span.html").document.export_to_markdown()

Patches

Fixed in docling 2.131.0 by #4414. Table spans are clamped to the HTML limits (colspan 1000, rowspan 65534) and to the actual size of the table in the HTML, JATS, BoxNote and OpenDocument spreadsheet backends, so conversion time and memory grow with the real table only.

Workarounds

Upgrade to 2.131.0. For older versions:

Run conversions of untrusted documents in a separate process with memory and CPU-time limits, or restrict allowed_formats to formats that are not affected.

Affected Packages

2 total 2 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`docling`	≥ 2.0.0&&< 2.131.0	2.131.0`pip install --upgrade 'docling==2.131.0'`
🐍PyPI	`docling-slim`	≥ 2.92.0&&< 2.131.0	2.131.0`pip install --upgrade 'docling-slim==2.131.0'`

Affected Products

1 product · 1 configurations

Application

doclingdocling

≥ 2.0.0 && < 2.131.0

range

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for docling, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update docling to 2.131.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-105749 is resolved across your whole dependency graph.
Workarounds
Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Fixing This On Your OS

If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.

Red HatModerate

Red Hat rates this docling flaw as having MODERATE security impact (CVSS 3.1 score 6.5, AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:N/A:H), consistent with the upstream assessment. A denial of service flaw was found in the docling document conversion library, which Red Hat ships bundled in Red Hat OpenShift AI (RHOAI) and…

Workaround published by Red Hat

Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base, or stability. In particular, the docling document_timeout setting does not interrupt the vulnerable backend conversion call and therefore does not prevent the resource exhaustion. The upstream docling project has fixed this issue in version 2.131.0.

Source: Red Hat security advisory for CVE-2026-105749 (CC BY 4.0)

Frequently Asked Questions

### Summary The HTML, JATS, ODS (OpenDocument spreadsheet) and BoxNote backends accept table `rowspan` / `colspan` values without an upper bound. A few bytes of input, such as `<td rowspan="100000000">`, make docling run loops proportional to the declared span and allocate a table grid of the declared size. The result is CPU and memory exhaustion. ### Details - `docling/backend/html_backend.py` (`_get_cell_spans`) parses span attributes with no upper limit. The cell-filling loop then iterates `row_span × col_span` times. - `docling/backend/jats_backend.py` and `docling/backend/boxnote_backe