CVE-2026-88054: CWE-125: Out-of-bounds Read in tesseract-ocr tesseract
Tesseract is an open source OCR engine. In version 5.5.3 and earlier, Plumbing::DeSerialize in src/lstm/plumbing.cpp rejects excessively large network stacks but accepts a zero-length stack for NT_SERIES, NT_PARALLEL, or NT_REVERSED layers in a crafted .traineddata model. During LSTMRecognizer initialization in src/lstm/lstmrecognizer.cpp, CacheXScaleFactor(XScaleFactor()) reaches Series::CacheXScaleFactor in src/lstm/series.cpp, which dereferences stack_[0] on the empty vector and invokes a virtual method through an invalid Network pointer. This causes a deterministic crash and denial of service at model load. No fixed release is available as of this review.
AI Analysis
Technical Summary
Tesseract OCR versions 5.5.3 and earlier contain a vulnerability in the Plumbing::DeSerialize function where zero-length stacks for NT_SERIES, NT_PARALLEL, or NT_REVERSED layers are accepted in a crafted .traineddata model. During LSTMRecognizer initialization, the code dereferences stack_[0] on an empty vector, invoking a virtual method through an invalid Network pointer. This causes a deterministic crash and denial of service at model load time. No patched release is available as of the review date.
Potential Impact
An attacker can cause a deterministic crash of the Tesseract OCR engine by supplying a malicious .traineddata model with zero-length stacks in specific network layers. This leads to denial of service during model initialization. There is no indication of code execution or data leakage.
Mitigation Recommendations
No official fix or patch is currently available for this vulnerability. Users should avoid loading untrusted or crafted .traineddata models to prevent denial of service. Monitor vendor advisories for updates regarding a patch.
CVE-2026-88054: CWE-125: Out-of-bounds Read in tesseract-ocr tesseract
Description
Tesseract is an open source OCR engine. In version 5.5.3 and earlier, Plumbing::DeSerialize in src/lstm/plumbing.cpp rejects excessively large network stacks but accepts a zero-length stack for NT_SERIES, NT_PARALLEL, or NT_REVERSED layers in a crafted .traineddata model. During LSTMRecognizer initialization in src/lstm/lstmrecognizer.cpp, CacheXScaleFactor(XScaleFactor()) reaches Series::CacheXScaleFactor in src/lstm/series.cpp, which dereferences stack_[0] on the empty vector and invokes a virtual method through an invalid Network pointer. This causes a deterministic crash and denial of service at model load. No fixed release is available as of this review.
CVSS v4.0
Score 6.9medium
Affected software
tesseract-ocr
tesseract
pkg:github/tesseract-ocr/tesseractRun on your own infrastructure? Check whether these packages are installed with threat-finder — our free open-source scanner.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
Tesseract OCR versions 5.5.3 and earlier contain a vulnerability in the Plumbing::DeSerialize function where zero-length stacks for NT_SERIES, NT_PARALLEL, or NT_REVERSED layers are accepted in a crafted .traineddata model. During LSTMRecognizer initialization, the code dereferences stack_[0] on an empty vector, invoking a virtual method through an invalid Network pointer. This causes a deterministic crash and denial of service at model load time. No patched release is available as of the review date.
Potential Impact
An attacker can cause a deterministic crash of the Tesseract OCR engine by supplying a malicious .traineddata model with zero-length stacks in specific network layers. This leads to denial of service during model initialization. There is no indication of code execution or data leakage.
Mitigation Recommendations
No official fix or patch is currently available for this vulnerability. Users should avoid loading untrusted or crafted .traineddata models to prevent denial of service. Monitor vendor advisories for updates regarding a patch.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- GitHub_M
- Date Reserved
- 2026-09-09T21:22:45.434Z
- Cvss Version
- 4.0
- State
- PUBLISHED
Threat ID: 6aa2ee7d555a9c516207cb28
Added to database: 09/10/2026, 17:53:01 UTC
Last enriched: 09/10/2026, 18:06:49 UTC
Last updated: 09/10/2026, 18:44:06 UTC
Views: 8
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