CVE-2017-12598: High severity OpenCV Opencv vulnerability

Published Aug 7, 2017
·
Updated

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.

Affected Software

3 affected components
OpenCV Opencv<=3.3.0
Debian Debian Linux=8.0
Debian Debian Linux=9.0

Event History

Aug 7, 2017
CVE Published
via MITRE·01:00 AM
Data Sourced
via MITRE·01:00 AM
Description
Free Weekly Intel

Don't miss critical vulnerabilities

Join thousands of security professionals who receive our weekly digest of trending CVEs, zero-days, and exploited vulnerabilities.

No spam. Unsubscribe anytime.

Frequently Asked Questions

1

What is the severity of CVE-2017-12598?

CVE-2017-12598 is classified as a medium severity vulnerability due to its potential for causing out-of-bounds read errors.

2

How do I fix CVE-2017-12598?

To fix CVE-2017-12598, update OpenCV to version 3.4.0 or later which includes the necessary patches.

3

What systems are affected by CVE-2017-12598?

CVE-2017-12598 affects OpenCV versions up to and including 3.3.0 and also impacts Debian versions 8.0 and 9.0.

4

What type of vulnerability is CVE-2017-12598?

CVE-2017-12598 is an out-of-bounds read vulnerability found in the cv::RBaseStream::readBlock function.

5

Can CVE-2017-12598 be exploited remotely?

CVE-2017-12598 can be exploited if an attacker can provide a specially crafted image file to the cv::imread function.

Contact

SecAlerts Pty Ltd.
132 Wickham Terrace
Fortitude Valley,
QLD 4006, Australia
info@secalerts.co
By using SecAlerts services, you agree to our services end-user license agreement. This website is safeguarded by reCAPTCHA and governed by the Google Privacy Policy and Terms of Service. All names, logos, and brands of products are owned by their respective owners, and any usage of these names, logos, and brands for identification purposes only does not imply endorsement. If you possess any content that requires removal, please get in touch with us.
© 2026 SecAlerts Pty Ltd.
ABN: 70 645 966 203, ACN: 645 966 203