FKIE_CVE-2017-12598
Vulnerability from fkie_nvd - Published: 2017-08-07 01:29 - Updated: 2026-06-17 01:03
Severity
Summary
OpenCV (Open Source Computer Vision Library) through 3.3 has an out-of-bounds read error in the cv::RBaseStream::readBlock function in modules/imgcodecs/src/bitstrm.cpp when reading an image file by using cv::imread, as demonstrated by the 8-opencv-invalid-read-fread test case.
References
Impacted products
| Vendor | Product | Version | |
|---|---|---|---|
| opencv | opencv | * | |
| debian | debian_linux | 8.0 | |
| debian | debian_linux | 9.0 |
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"lastModified": "2026-06-17T01:03:35.677",
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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- Not confirmed: The user expressed doubt about the validity of the vulnerability.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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Related by attack behaviour
Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.
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