GHSA-99RJ-3595-5FRJ
Vulnerability from github – Published: 2025-06-13 18:30 – Updated: 2026-06-02 15:31
VLAI
Details
A flaw was found in how GLib’s GString manages memory when adding data to strings. If a string is already very large, combining it with more input can cause a hidden overflow in the size calculation. This makes the system think it has enough memory when it doesn’t. As a result, data may be written past the end of the allocated memory, leading to crashes or memory corruption.
Severity
{
"affected": [],
"aliases": [
"CVE-2025-6052"
],
"database_specific": {
"cwe_ids": [
"CWE-190"
],
"github_reviewed": false,
"github_reviewed_at": null,
"nvd_published_at": "2025-06-13T16:15:28Z",
"severity": "LOW"
},
"details": "A flaw was found in how GLib\u2019s GString manages memory when adding data to strings. If a string is already very large, combining it with more input can cause a hidden overflow in the size calculation. This makes the system think it has enough memory when it doesn\u2019t. As a result, data may be written past the end of the allocated memory, leading to crashes or memory corruption.",
"id": "GHSA-99rj-3595-5frj",
"modified": "2026-06-02T15:31:48Z",
"published": "2025-06-13T18:30:35Z",
"references": [
{
"type": "ADVISORY",
"url": "https://nvd.nist.gov/vuln/detail/CVE-2025-6052"
},
{
"type": "WEB",
"url": "https://access.redhat.com/security/cve/CVE-2025-6052"
},
{
"type": "WEB",
"url": "https://bugzilla.redhat.com/show_bug.cgi?id=2372666"
},
{
"type": "WEB",
"url": "https://cert-portal.siemens.com/productcert/html/ssa-032379.html"
},
{
"type": "WEB",
"url": "https://cert-portal.siemens.com/productcert/html/ssa-253495.html"
}
],
"schema_version": "1.4.0",
"severity": [
{
"score": "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:L",
"type": "CVSS_V3"
}
]
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
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
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
Browse all ATT&CK techniques and the vulnerabilities related to each.
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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.
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