CVE-2018-10055 Vulnerability Analysis & Exploit Details

CVE-2018-10055
Vulnerability Scoring

8.1
/10
Severe Risk

Cybersecurity professionals consider CVE-2018-10055 an immediate threat requiring urgent mitigation.

Attack Complexity Details

  • Attack Complexity: Low
    Exploits can be performed without significant complexity or special conditions.
  • Attack Vector: Network
    Vulnerability is exploitable over a network without physical access.
  • Privileges Required: None
    No privileges are required for exploitation.
  • Scope: Unchanged
    Exploit remains within the originally vulnerable component.
  • User Interaction: Required
    User interaction is necessary for successful exploitation.

CVE-2018-10055 Details

Status: Modified

Last updated: 🕞 21 Nov 2024, 03:40 UTC
Originally published on: 🕔 24 Apr 2019, 17:29 UTC

Time between publication and last update: 2037 days

CVSS Release: version 3

CVSS3 Source

nvd@nist.gov

CVSS3 Type

Primary

CVSS3 Vector

CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:H

CVE-2018-10055 Vulnerability Summary

CVE-2018-10055: Invalid memory access and/or a heap buffer overflow in the TensorFlow XLA compiler in Google TensorFlow before 1.7.1 could cause a crash or read from other parts of process memory via a crafted configuration file.

Assessing the Risk of CVE-2018-10055

Access Complexity Graph

The exploitability of CVE-2018-10055 depends on two key factors: attack complexity (the level of effort required to execute an exploit) and privileges required (the access level an attacker needs).

Exploitability Analysis for CVE-2018-10055

With low attack complexity and no required privileges, CVE-2018-10055 is an easy target for cybercriminals. Organizations should prioritize immediate mitigation measures to prevent unauthorized access and data breaches.

Understanding AC and PR

A lower complexity and fewer privilege requirements make exploitation easier. Security teams should evaluate these aspects to determine the urgency of mitigation strategies, such as patch management and access control policies.

Attack Complexity (AC) measures the difficulty in executing an exploit. A high AC means that specific conditions must be met, making an attack more challenging, while a low AC means the vulnerability can be exploited with minimal effort.

Privileges Required (PR) determine the level of system access necessary for an attack. Vulnerabilities requiring no privileges are more accessible to attackers, whereas high privilege requirements limit exploitation to authorized users with elevated access.

CVSS Score Breakdown Chart

Above is the CVSS Sub-score Breakdown for CVE-2018-10055, illustrating how Base, Impact, and Exploitability factors combine to form the overall severity rating. A higher sub-score typically indicates a more severe or easier-to-exploit vulnerability.

CIA Impact Analysis

Below is the Impact Analysis for CVE-2018-10055, showing how Confidentiality, Integrity, and Availability might be affected if the vulnerability is exploited. Higher values usually signal greater potential damage.

  • Confidentiality: High
    Exploiting CVE-2018-10055 can result in unauthorized access to sensitive data, severely compromising data privacy.
  • Integrity: None
    CVE-2018-10055 poses no threat to data integrity.
  • Availability: High
    CVE-2018-10055 can disrupt system operations, potentially causing complete denial of service (DoS).

Exploit Prediction Scoring System (EPSS)

The EPSS score estimates the probability that this vulnerability will be exploited in the near future.

EPSS Score: 0.127% (probability of exploit)

EPSS Percentile: 48.82% (lower percentile = lower relative risk)
This vulnerability is less risky than approximately 51.18% of others.

CVE-2018-10055 References

External References

CWE Common Weakness Enumeration

CWE-119

CAPEC Common Attack Pattern Enumeration and Classification

  • Buffer Overflow via Environment Variables CAPEC-10 This attack pattern involves causing a buffer overflow through manipulation of environment variables. Once the adversary finds that they can modify an environment variable, they may try to overflow associated buffers. This attack leverages implicit trust often placed in environment variables.
  • Overflow Buffers CAPEC-100 Buffer Overflow attacks target improper or missing bounds checking on buffer operations, typically triggered by input injected by an adversary. As a consequence, an adversary is able to write past the boundaries of allocated buffer regions in memory, causing a program crash or potentially redirection of execution as per the adversaries' choice.
  • Buffer Manipulation CAPEC-123 An adversary manipulates an application's interaction with a buffer in an attempt to read or modify data they shouldn't have access to. Buffer attacks are distinguished in that it is the buffer space itself that is the target of the attack rather than any code responsible for interpreting the content of the buffer. In virtually all buffer attacks the content that is placed in the buffer is immaterial. Instead, most buffer attacks involve retrieving or providing more input than can be stored in the allocated buffer, resulting in the reading or overwriting of other unintended program memory.
  • Client-side Injection-induced Buffer Overflow CAPEC-14 This type of attack exploits a buffer overflow vulnerability in targeted client software through injection of malicious content from a custom-built hostile service. This hostile service is created to deliver the correct content to the client software. For example, if the client-side application is a browser, the service will host a webpage that the browser loads.
  • Filter Failure through Buffer Overflow CAPEC-24 In this attack, the idea is to cause an active filter to fail by causing an oversized transaction. An attacker may try to feed overly long input strings to the program in an attempt to overwhelm the filter (by causing a buffer overflow) and hoping that the filter does not fail securely (i.e. the user input is let into the system unfiltered).
  • MIME Conversion CAPEC-42 An attacker exploits a weakness in the MIME conversion routine to cause a buffer overflow and gain control over the mail server machine. The MIME system is designed to allow various different information formats to be interpreted and sent via e-mail. Attack points exist when data are converted to MIME compatible format and back.
  • Overflow Binary Resource File CAPEC-44 An attack of this type exploits a buffer overflow vulnerability in the handling of binary resources. Binary resources may include music files like MP3, image files like JPEG files, and any other binary file. These attacks may pass unnoticed to the client machine through normal usage of files, such as a browser loading a seemingly innocent JPEG file. This can allow the adversary access to the execution stack and execute arbitrary code in the target process.
  • Buffer Overflow via Symbolic Links CAPEC-45 This type of attack leverages the use of symbolic links to cause buffer overflows. An adversary can try to create or manipulate a symbolic link file such that its contents result in out of bounds data. When the target software processes the symbolic link file, it could potentially overflow internal buffers with insufficient bounds checking.
  • Overflow Variables and Tags CAPEC-46 This type of attack leverages the use of tags or variables from a formatted configuration data to cause buffer overflow. The adversary crafts a malicious HTML page or configuration file that includes oversized strings, thus causing an overflow.
  • Buffer Overflow via Parameter Expansion CAPEC-47 In this attack, the target software is given input that the adversary knows will be modified and expanded in size during processing. This attack relies on the target software failing to anticipate that the expanded data may exceed some internal limit, thereby creating a buffer overflow.
  • Buffer Overflow in an API Call CAPEC-8 This attack targets libraries or shared code modules which are vulnerable to buffer overflow attacks. An adversary who has knowledge of known vulnerable libraries or shared code can easily target software that makes use of these libraries. All clients that make use of the code library thus become vulnerable by association. This has a very broad effect on security across a system, usually affecting more than one software process.
  • Buffer Overflow in Local Command-Line Utilities CAPEC-9 This attack targets command-line utilities available in a number of shells. An adversary can leverage a vulnerability found in a command-line utility to escalate privilege to root.

Vulnerable Configurations

  • cpe:2.3:a:google:tensorflow:-:*:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:-:*:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:-:*:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:-:*:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.1.7:*:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.1.7:*:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.5.0:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.5.0:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.5.0:*:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.5.0:*:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.5.0:*:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.5.0:*:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.6.0:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.6.0:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.6.0:*:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.6.0:*:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.6.0:*:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.6.0:*:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.7.0:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.7.0:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.7.0:*:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.7.0:*:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.7.0:*:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.7.0:*:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.7.1:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.7.1:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.7.1:*:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.7.1:*:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.7.1:*:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.7.1:*:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.8.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.8.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.8.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.8.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.8.0:-:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.8.0:-:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.8.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.8.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.8.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.8.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.8.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.8.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.9.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.9.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.9.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.9.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.9.0:-:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.9.0:-:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.9.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.9.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.9.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.9.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.9.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.9.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.10.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.10.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.10.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.10.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.10.0:-:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.10.0:-:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.10.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.10.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.10.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.10.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.10.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.10.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:-:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:-:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:rc1:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:rc1:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:rc1:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:rc1:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:rc2:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:rc2:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:rc2:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.11.0:rc2:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.11.0:rc2:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.0:*:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.0:*:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.0:rc1:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.0:rc1:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.1:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.1:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.1:*:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.1:*:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:0.12.1:*:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:0.12.1:*:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:-:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:-:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:rc1:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:rc1:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:rc1:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:rc1:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:rc2:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:rc2:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:rc2:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:rc2:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:rc2:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:alpha:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:alpha:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:alpha:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:alpha:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.0:alpha:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.0:alpha:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.1:*:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.1:*:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.1:*:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.1:*:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.0.1:*:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.0.1:*:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:-:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:-:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:rc1:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:rc1:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:rc1:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:rc1:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:rc2:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:rc2:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:rc2:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.1.0:rc2:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.1.0:rc2:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:-:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:-:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:rc1:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:rc1:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:rc1:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:rc1:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:rc2:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:rc2:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:rc2:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:1.2.0:rc2:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:1.2.0:rc2:*:*:lite:*:*:*
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  • cpe:2.3:a:google:tensorflow:1.3.0:rc2:*:*:*:*:*:*
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  • cpe:2.3:a:google:tensorflow:1.7.0:-:*:*:*:*:*:*
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    cpe:2.3:a:google:tensorflow:1.7.0:rc1:*:*:lite:*:*:*

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