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RedHat Linux
RedHat Linux
•added 2026/09/24 2:13 p.m.•11 views

tesseract: Tesseract: Heap out-of-bounds write via crafted .traineddata

A flaw was found in Tesseract, an open-source Optical Character Recognition OCR engine. A remote attacker could exploit this by providing a specially crafted .traineddata LSTM model component. When Tesseract's deserializer processes this component during OCR recognition, an unchecked integer...

6.8CVSS6.7AI score0.00126EPSS
SaveExploits0References8
CVE
CVE
•added 2026/09/10 5:39 p.m.•36 views

CVE-2026-88054

Tesseract is an open-source OCR engine affected in version 5.5.3 and earlier by a denial-of-service flaw. The root cause is in Plumbing::DeSerialize (src/lstm/plumbing.cpp), which rejects excessively large network stacks but accepts a zero-length stack for NT_SERIES, NT_PARALLEL, or NT_REVERSED l...

6.9CVSS5.8AI score0.00153EPSS
SaveExploits1References2Affected Software1
Positive Technologies
Positive Technologies
•added 2026/09/10 12:00 a.m.•23 views

PT-2026-89520

Name of the Vulnerable Software and Affected Versions Tesseract versions prior to 5.5.4 Description A flaw exists in the Plumbing::DeSerialize function within src/lstm/plumbing.cpp that allows a crafted .traineddata model to contain a zero-length stack for NT SERIES, NT PARALLEL, or NT REVERSED...

6.9CVSS5.7AI score0.00153EPSS
SaveExploits1References31
NVD
NVD
•added 2026/08/11 3:17 p.m.•20 views

CVE-2026-73066

Tesseract is an open source OCR engine. Prior to 5.5.3, a crafted .traineddata LSTM model component loaded through Tesseract's deserializer can cause an unchecked signed integer multiplication in Convolve::DeSerialize in src/lstm/convolve.cpp to wrap the convolution output-channel count,...

6.8CVSS0.00126EPSS
SaveExploits0References4
UbuntuCve
UbuntuCve
•added 2026/08/11 3:17 p.m.•17 views

CVE-2026-73066

Tesseract is an open source OCR engine. Prior to 5.5.3, a crafted .traineddata LSTM model component loaded through Tesseract's deserializer can cause an unchecked signed integer multiplication in Convolve::DeSerialize in src/lstm/convolve.cpp to wrap the convolution output-channel count,...

6.8CVSS6.2AI score0.00126EPSS
SaveExploits0References5
EUVD
EUVD
•added 2026/08/11 2:49 p.m.•22 views

EUVD-2026-56181

Tesseract is an open source OCR engine. Prior to 5.5.3, a crafted .traineddata LSTM model component loaded through Tesseract's deserializer can cause an unchecked signed integer multiplication in Convolve::DeSerialize in src/lstm/convolve.cpp to wrap the convolution output-channel count,...

6.8CVSS6.2AI score0.00126EPSS
SaveExploits0References4
Positive Technologies
Positive Technologies
•added 2026/08/11 12:00 a.m.•9 views

PT-2026-70224

Name of the Vulnerable Software and Affected Versions Tesseract versions prior to 5.5.3 Description A heap out-of-bounds write can occur during OCR recognition when a crafted .traineddata LSTM model component is loaded through the deserializer. This happens because an unchecked signed integer...

6.8CVSS5.9AI score0.00126EPSS
SaveExploits0References36
Packet Storm News
Packet Storm News
•added 2026/03/11 12:00 a.m.•14 views

Incremental Federated Learning for Intrusion Detection in IoT Networks under Evolving Threat Landscape

The expansion of Internet of Things IoT devices has increased the attack surface of networks, necessitating a robust and adaptive intrusion detection systems. Machine learning based systems have been considered promising in enhancing the detection performance. Federated learning settings enabled ...

5.8AI score
SaveExploits0
Packet Storm News
Packet Storm News
•added 2025/10/09 12:00 a.m.•15 views

New Machine Learning Approaches for Intrusion Detection in ADS-B

With the growing reliance on the vulnerable Automatic Dependent Surveillance-Broadcast ADS-B protocol in air traffic management ATM, ensuring security is critical. This study investigates emerging machine learning models and training strategies to improve AI-based intrusion detection systems IDS...

6.9AI score
SaveExploits0
Packet Storm News
Packet Storm News
•added 2025/06/09 12:00 a.m.•16 views

Evaluating Explainable AI for Deep Learning-Based Network Intrusion Detection System Alert Classification

A Network Intrusion Detection System NIDS monitors networks for cyber attacks and other unwanted activities. However, NIDS solutions often generate an overwhelming number of alerts daily, making it challenging for analysts to prioritize high-priority threats. While deep learning models promise to...

6.9AI score
SaveExploits0
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