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Tesseract OCR EUVDEUVD-2026-75591

| CVE-2026-88048 HIGH
Out-of-bounds Read (CWE-125)
2026-09-10 GitHub_M
8.6
CVSS 4.0 · Vendor: GitHub_M
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Vendor (GitHub_M) PRIMARY
8.6 HIGH
CVSS:4.0/AV:L/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
vuln.today AI
8.4 HIGH

Attacker needs only to supply a malicious traineddata file (local vector); no privileges or user interaction required beyond normal application execution; all three impact pillars apply.

3.1 AV:L/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
4.0 AV:L/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

Primary rating from Vendor (GitHub_M).

CVSS VectorVendor: GitHub_M

Attack Vector
Local
Attack Complexity
Low
Privileges Required
None
User Interaction
None
Scope
X

Lifecycle Timeline

4
POC Analysis Generated
Sep 10, 2026 - 19:24 vuln.today
Source Code Evidence Fetched
Sep 10, 2026 - 17:06 vuln.today
Analysis Generated
Sep 10, 2026 - 17:06 vuln.today
CVE Published
Sep 10, 2026 - 16:21 cve.org
HIGH 8.6

DescriptionCVE.org

Tesseract is an open source OCR engine. In version 5.5.3 and earlier, FullyConnected::DeSerialize in src/lstm/fullyconnected.cpp does not validate the deserialized layer scalars ni_ and no_ against the weight-matrix dimensions. During FullyConnected::Forward, MatrixDotVector in src/lstm/weightmatrix.cpp writes w.dim1() results into temp_line, which is sized from no_, and reads w.dim2() minus one inputs from curr_input, which is sized from ni_. A crafted .traineddata NT_SOFTMAX layer can therefore use inconsistent dimensions to cause a heap out-of-bounds write and read on the default LSTM engine, resulting in heap corruption, a crash, information disclosure, or potentially controlled corruption. No fixed release is available as of this review.

AnalysisAI

Heap out-of-bounds write and read in Tesseract OCR Engine 5.5.3 and earlier allows an attacker who can supply a crafted .traineddata model file to corrupt heap memory during LSTM inference, potentially achieving information disclosure, a crash, or controlled heap corruption leading to code execution. The flaw lies in FullyConnected::DeSerialize, which loads layer dimension scalars ni_ and no_ without cross-validating them against the actual weight matrix dimensions; when Forward is subsequently called, MatrixDotVector writes into a scratch buffer sized by no_ but indexed by the actual matrix row count, and reads from a buffer sized by ni_ but indexed by column count minus one. …

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Attack ChainAIDerived

Hypothetical attack flow derived from CVE metadata

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Vulnerability AssessmentAI

Exploitation The vulnerability is triggered when Tesseract loads a crafted `.traineddata` file containing an `NT_SOFTMAX` layer with a weight matrix whose dimensions do not match the declared `ni_`/`no_` scalars, and then performs at least one recognition pass (calls `Forward`). … Additional conditions and limiting factors are described in the full assessment.
Risk Assessment The CVSS 4.0 score of 8.6 with vector AV:L/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H accurately reflects a straightforward local exploitation path once the attacker controls which `.traineddata` file an application loads. … Full risk analysis with EPSS, KEV, and SSVC signal comparison available after sign-in.
Exploit Scenario Full exploit scenario with step-by-step reproduction available after sign-in.
Remediation Upstream fix available via commit 103dc134eb36411ddc6833ec20aa2c76795bd0ff (not yet in a tagged release); organisations should apply this patch from source and rebuild Tesseract until an official release ships. … Detailed patch versions, workarounds, and compensating controls in full report.

Recommended ActionAI

Within 24 hours, identify and inventory all systems running Tesseract OCR Engine 5.5.3 or earlier, particularly those processing model files from external or untrusted sources. …

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EUVD-2026-75591 vulnerability details – vuln.today

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