SentencepieceApplication · Google

CVE-2026-1260

HIGH · 7.8 CVSS v3.1 Published 2026-01-22
Fix available
A fix is available. Upgrade to 0.2.1 or later.
See remediation →
80/100
Remediation priority · High
Zero-click

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
Invalid memory access in Sentencepiece versions less than 0.2.1 when using a vulnerable model file, which is not created in the normal training procedure.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · moderate confidence

A memory access vulnerability exists in Sentencepiece versions prior to 0.2.1. The flaw is triggered when parsing a specially crafted model file that cannot be generated through normal training procedures, leading to invalid memory access.

MitigationUpgrade Sentencepiece to version 0.2.1 or later. Additionally, ensure only model files from trusted, legitimate training procedures are loaded.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.

NVD · CPE data
SentencepieceApplication
Affected:< 0.2.1

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Local
Complexity
Low
Privileges
Low
User interaction
None
Scope
Unchanged
Confidentiality
High
Integrity
High
Availability
High

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

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Identify Sentencepiece library version
    Run 'pip show sentencepiece' or check your package manager for the installed sentencepiece version
    Affected if The installed version is below 0.2.1
  2. Identify Sentencepiece library version programmatically
    In Python, run 'import sentencepiece as sp; print(sp.__version__)' or check the library's version attribute
    Affected if The version returned is less than 0.2.1
  3. Determine model file source
    Review the origin of any .model files being loaded with sentencepiece.SentencePieceProcessor.Load() or LoadModel()
    Affected if The model file was obtained from an untrusted or non-standard source, or was not created through normal training procedures
  4. Inspect model loading behavior
    Monitor application logs or error output when loading model files with sentencepiece
    Affected if Loading a model file from an untrusted source triggers unexpected behavior, crashes, or memory errors

You are affected if you have sentencepiece version below 0.2.1 AND load model files from untrusted or non-standard sources that could be specifically crafted to exploit this flaw.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

dbcve · scoped
Upgrade available Upgrade to 0.2.1 or later
Fixed in 0.2.1
Interim mitigation

Upgrade Sentencepiece to version 0.2.1 or later. Additionally, ensure only model files from trusted, legitimate training procedures are loaded.

Recommended fix Moderate confidence

Sentencepiece >= 0.2.1

  1. Upgrade Sentencepiece to version 0.2.1 or later to remediate the memory buffer bounds error
  2. If using a package manager (e.g., pip, conda), run: pip install sentencepiece>=0.2.1 or conda install sentencepiece>=0.2.1
  3. After upgrading, re-validate any model files in use to ensure they were not crafted to exploit this vulnerability
  4. If using Sentencepiece in a larger project, rebuild or update dependencies to pull in the fixed version

Generated from the published advisory — verify against the referenced sources before acting.

Fix this in Sentencepiece Scoped from the published advisory
  • Consultation2.0 h
  • Implementation4.0 h
  • Testing4.0 h
  • Review / QA2.0 h
12.0 hours of engineering $2,080
Get the upgrade done

An estimate, not a bill — we confirm scope with you before any work starts. Need it this week? Rush from $3,328.

Scan for this in your stack

Free · runs locally
dbcve dependency scanner

Check whether your project pulls in CVE-2026-1260 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.

References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2026-1260 in production — separate from our analysis above.

No notes yet

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
  • No weaponised exploit code, or anything meant to cause harm
  • No spam, self-promotion, credentials, or personal data