CVE-2020-15197 Vulnerability Analysis & Exploit Details

CVE-2020-15197
Vulnerability Scoring

6.3
/10
High Risk

If left unpatched, CVE-2020-15197 could lead to major system disruptions or data loss.

Attack Complexity Details

  • Attack Complexity: High
    Exploits require significant effort and special conditions.
  • Attack Vector: Network
    Vulnerability is exploitable over a network without physical access.
  • Privileges Required: Low
    Some privileges are necessary to exploit the vulnerability.
  • Scope: Changed
    Successful exploitation can impact components beyond the vulnerable component.
  • User Interaction: None
    No user interaction is necessary for exploitation.

CVE-2020-15197 Details

Status: Analyzed

Last updated: 🕐 17 Aug 2021, 13:21 UTC
Originally published on: 🕖 25 Sep 2020, 19:15 UTC

Time between publication and last update: 325 days

CVSS Release: version 3

CVSS3 Source

nvd@nist.gov

CVSS3 Type

Primary

CVSS3 Vector

CVSS:3.1/AV:N/AC:H/PR:L/UI:N/S:C/C:N/I:N/A:H

CVE-2020-15197 Vulnerability Summary

CVE-2020-15197: In Tensorflow before version 2.3.1, the `SparseCountSparseOutput` implementation does not validate that the input arguments form a valid sparse tensor. In particular, there is no validation that the `indices` tensor has rank 2. This tensor must be a matrix because code assumes its elements are accessed as elements of a matrix. However, malicious users can pass in tensors of different rank, resulting in a `CHECK` assertion failure and a crash. This can be used to cause denial of service in serving installations, if users are allowed to control the components of the input sparse tensor. The issue is patched in commit 3cbb917b4714766030b28eba9fb41bb97ce9ee02 and is released in TensorFlow version 2.3.1.

Assessing the Risk of CVE-2020-15197

Access Complexity Graph

The exploitability of CVE-2020-15197 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-2020-15197

This vulnerability, CVE-2020-15197, requires a high level of attack complexity and low privileges, making it difficult but not impossible to exploit. Organizations should ensure robust security configurations to mitigate risks.

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-2020-15197, 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-2020-15197, showing how Confidentiality, Integrity, and Availability might be affected if the vulnerability is exploited. Higher values usually signal greater potential damage.

  • Confidentiality: None
    CVE-2020-15197 has no significant impact on data confidentiality.
  • Integrity: None
    CVE-2020-15197 poses no threat to data integrity.
  • Availability: High
    CVE-2020-15197 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: 0.135% (probability of exploit)

EPSS Percentile: 50.27% (lower percentile = lower relative risk)
This vulnerability is less risky than approximately 49.73% of others.

CVE-2020-15197 References

External References

CWE Common Weakness Enumeration

CWE-617

Vulnerable Configurations

  • cpe:2.3:a:google:tensorflow:2.3.0:*:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:*:*:*:-:*:*:*

Protect Your Infrastructure against CVE-2020-15197: Combat Critical CVE Threats

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