CVE-2018-10055 : What You Need to Know
Learn about CVE-2018-10055, a critical vulnerability in Google TensorFlow's XLA compiler before version 1.7.1, potentially leading to crashes or unauthorized memory access.
Google TensorFlow's XLA compiler before version 1.7.1 is vulnerable to a heap buffer overflow, potentially leading to crashes or unauthorized access to process memory when encountering a malicious configuration file.
Understanding CVE-2018-10055
This CVE involves a critical vulnerability in the TensorFlow XLA compiler that could be exploited by a crafted configuration file.
What is CVE-2018-10055?
The vulnerability in the TensorFlow XLA compiler could result in a crash or unintended access to other parts of the process memory due to invalid memory access and a heap buffer overflow.
The Impact of CVE-2018-10055
The impact includes the potential for a malicious actor to exploit the vulnerability by providing a specially crafted configuration file, leading to crashes or unauthorized access to sensitive process memory.
Technical Details of CVE-2018-10055
The technical details shed light on the specifics of the vulnerability and its implications.
Vulnerability Description
The vulnerability arises from invalid memory access and a heap buffer overflow in the TensorFlow XLA compiler, allowing unauthorized access to process memory.
Affected Systems and Versions
- Product: Google TensorFlow
- Versions affected: Before 1.7.1
Exploitation Mechanism
The vulnerability can be exploited by encountering a maliciously crafted configuration file, triggering the heap buffer overflow and invalid memory access.
Mitigation and Prevention
Protecting systems from CVE-2018-10055 requires immediate actions and long-term security practices.
Immediate Steps to Take
- Update Google TensorFlow to version 1.7.1 or later to mitigate the vulnerability.
- Avoid opening or processing untrusted configuration files.
Long-Term Security Practices
- Regularly update software and libraries to the latest versions.
- Implement code reviews and security testing to identify and address vulnerabilities.
Patching and Updates
- Apply patches and security updates provided by Google TensorFlow to address the vulnerability.