CVE-2025-14177 (GCVE-0-2025-14177)

Vulnerability from cvelistv5 – Published: 2025-12-27 19:33 – Updated: 2025-12-29 16:01
VLAI
Title
Information Leak of Memory in getimagesize
Summary
In PHP versions:8.1.* before 8.1.34, 8.2.* before 8.2.30, 8.3.* before 8.3.29, 8.4.* before 8.4.16, 8.5.* before 8.5.1, the getimagesize() function may leak uninitialized heap memory into the APPn segments (e.g., APP1) when reading images in multi-chunk mode (such as via php://filter). This occurs due to a bug in php_read_stream_all_chunks() that overwrites the buffer without advancing the pointer, leaving tail bytes uninitialized. This may lead to information disclosure of sensitive heap data and affect the confidentiality of the target server.
Severity
6.3 (Medium)
CVSS:4.0/AV:N/AC:H/AT:P/PR:N/UI:N/VC:L/VI:N/VA:N/SC:L/SI:N/SA:N
SSVC
Exploitation: poc Automatable: no Technical Impact: partial
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-12-29 16:01 UTC
CWE
Assigner
References
Impacted products
Vendor Product Version
PHP Group PHP Affected: 8.1.* , < 8.1.34 (semver)
Affected: 8.2.* , < 8.2.30 (semver)
Affected: 8.3.* , < 8.3.29 (semver)
Affected: 8.4.* , < 8.4.16 (semver)
Affected: 8.5.* , < 8.5.1 (semver)
Create a notification for this product.
Date Public
2025-12-18 00:00
Credits
Nikita Sveshnikov (Positive Technologies)
Show details on NVD website
To clipboard 

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Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.

Sightings

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Nomenclature

  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.


Detection rules are retrieved from Rulezet.


Related by attack behaviour

Vulnerabilities whose description is nearest to this one in the vector space of the CIRCL/vulnerability-attack-technique-biencoder model. This is a similarity search over the bi-encoder space (plain cosine), not a classification, and it has no measured accuracy.