CWE-1023

Incomplete Comparison with Missing Factors

The product performs a comparison between entities that must consider multiple factors or characteristics of each entity, but the comparison does not include one or more of these factors.

CVE-2021-23146 (GCVE-0-2021-23146)
Vulnerability from cvelistv5
Published
2021-11-18 17:59
Modified
2024-09-17 02:41
CWE
Summary
An Incomplete Comparison with Missing Factors vulnerability in the Gallagher Controller allows an attacker to bypass PIV verification. This issue affects: Gallagher Command Centre 8.40 versions prior to 8.40.1888 (MR3); 8.30 versions prior to 8.30.1359 (MR3); 8.20 versions prior to 8.20.1259 (MR5); 8.10 versions prior to 8.10.1284 (MR7); version 8.00 and prior versions.
Impacted products
Vendor Product Version
Gallagher Command Center Version: 8.40 prior to 8.40.1888 (MR3)
Version: 8.30 prior to 8.30.1359 (MR3)
Version: 8.20 prior to 8.20.1259 (MR5)
Version: 8.10 prior to 8.10.1284 (MR7)
Version: 8.00 and prior
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Show details on NVD website


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CVE-2024-5528 (GCVE-0-2024-5528)
Vulnerability from cvelistv5
Published
2025-02-05 10:31
Modified
2025-02-05 20:13
CWE
  • CWE-1023 - Incomplete Comparison with Missing Factors
Summary
An issue was discovered in GitLab CE/EE affecting all versions prior to 16.11.6, starting from 17.0 prior to 17.0.4, and starting from 17.1 prior to 17.1.2, which allows a subdomain takeover in GitLab Pages.
References
https://gitlab.com/gitlab-org/gitlab/-/issues/464558 issue-tracking, permissions-required
https://hackerone.com/reports/2523654 technical-description, exploit, permissions-required
Impacted products
Vendor Product Version
GitLab GitLab Version: 0.0   
Version: 17.0   
Version: 17.1   
    cpe:2.3:a:gitlab:gitlab:*:*:*:*:*:*:*:*
Create a notification for this product.
Show details on NVD website


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CVE-2025-46722 (GCVE-0-2025-46722)
Vulnerability from cvelistv5
Published
2025-05-29 16:36
Modified
2025-05-29 18:13
CWE
  • CWE-1288 - Improper Validation of Consistency within Input
  • CWE-1023 - Incomplete Comparison with Missing Factors
Summary
vLLM is an inference and serving engine for large language models (LLMs). In versions starting from 0.7.0 to before 0.9.0, in the file vllm/multimodal/hasher.py, the MultiModalHasher class has a security and data integrity issue in its image hashing method. Currently, it serializes PIL.Image.Image objects using only obj.tobytes(), which returns only the raw pixel data, without including metadata such as the image’s shape (width, height, mode). As a result, two images of different sizes (e.g., 30x100 and 100x30) with the same pixel byte sequence could generate the same hash value. This may lead to hash collisions, incorrect cache hits, and even data leakage or security risks. This issue has been patched in version 0.9.0.
Impacted products
Vendor Product Version
vllm-project vllm Version: >= 0.7.0, < 0.9.0
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Mitigation

Phase: Testing

Description:

  • Thoroughly test the comparison scheme before deploying code into production. Perform positive testing as well as negative testing.

No CAPEC attack patterns related to this CWE.

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