CVE-2020-15214 Vulnerability Analysis & Exploit Details

CVE-2020-15214
Vulnerability Scoring

8.1
/10
Severe Risk

Cybersecurity professionals consider CVE-2020-15214 an immediate threat requiring urgent mitigation.

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: None
    No privileges are required for exploitation.
  • Scope: Changed
    Successful exploitation can impact components beyond the vulnerable component.
  • User Interaction: None
    No user interaction is necessary for exploitation.

CVE-2020-15214 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:N/UI:N/S:C/C:L/I:L/A:H

CVE-2020-15214 Vulnerability Summary

CVE-2020-15214: In TensorFlow Lite before versions 2.2.1 and 2.3.1, models using segment sum can trigger a write out bounds / segmentation fault if the segment ids are not sorted. Code assumes that the segment ids are in increasing order, using the last element of the tensor holding them to determine the dimensionality of output tensor. This results in allocating insufficient memory for the output tensor and in a write outside the bounds of the output array. This usually results in a segmentation fault, but depending on runtime conditions it can provide for a write gadget to be used in future memory corruption-based exploits. The issue is patched in commit 204945b19e44b57906c9344c0d00120eeeae178a and is released in TensorFlow versions 2.2.1, or 2.3.1. A potential workaround would be to add a custom `Verifier` to the model loading code to ensure that the segment ids are sorted, although this only handles the case when the segment ids are stored statically in the model. A similar validation could be done if the segment ids are generated at runtime between inference steps. If the segment ids are generated as outputs of a tensor during inference steps, then there are no possible workaround and users are advised to upgrade to patched code.

Assessing the Risk of CVE-2020-15214

Access Complexity Graph

The exploitability of CVE-2020-15214 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-2020-15214

CVE-2020-15214 presents a challenge to exploit due to its high attack complexity, but the absence of privilege requirements still makes it a viable target for skilled attackers. A thorough security review is advised.

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-2020-15214, 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-2020-15214, showing how Confidentiality, Integrity, and Availability might be affected if the vulnerability is exploited. Higher values usually signal greater potential damage.

  • Confidentiality: Low
    CVE-2020-15214 could lead to minor leaks of non-critical information without major privacy breaches.
  • Integrity: Low
    Exploiting CVE-2020-15214 may cause minor changes to data without severely impacting its accuracy.
  • Availability: High
    CVE-2020-15214 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: 0.311% (probability of exploit)

EPSS Percentile: 70.28% (lower percentile = lower relative risk)
This vulnerability is less risky than approximately 29.72% of others.

CVE-2020-15214 References

External References

CWE Common Weakness Enumeration

CWE-787

Vulnerable Configurations

  • cpe:2.3:a:google:tensorflow:2.2.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:-:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:-:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc1:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc1:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc1:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc1:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc2:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc2:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc2:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc2:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc2:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc3:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc3:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc3:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc3:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc3:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc3:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc4:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc4:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc4:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc4:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.2.0:rc4:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.2.0:rc4:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:-:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:-:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:-:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:-:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:-:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:-:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:rc0:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:rc0:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:rc0:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:rc0:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:rc0:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:rc0:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:rc1:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:rc1:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:rc1:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:rc1:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:rc1:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:rc1:*:*:lite:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:rc2:*:*:*:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:rc2:*:*:*:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:rc2:*:*:-:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:rc2:*:*:-:*:*:*
  • cpe:2.3:a:google:tensorflow:2.3.0:rc2:*:*:lite:*:*:*
    cpe:2.3:a:google:tensorflow:2.3.0:rc2:*:*:lite:*:*:*

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