CVE-2023-6857 (GCVE-0-2023-6857)
Vulnerability from cvelistv5 – Published: 2023-12-19 13:38 – Updated: 2025-02-13 17:26
VLAI
EPSS
VEX
Summary
When resolving a symlink, a race may occur where the buffer passed to `readlink` may actually be smaller than necessary.
*This bug only affects Firefox on Unix-based operating systems (Android, Linux, MacOS). Windows is unaffected.* This vulnerability affects Firefox ESR < 115.6, Thunderbird < 115.6, and Firefox < 121.
Severity
5.3 (Medium)
CWE
- Symlinks may resolve to smaller than expected buffers
Assigner
References
9 references
Impacted products
3 products
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| Mozilla | Firefox ESR |
Affected:
unspecified , < 115.6
(custom)
|
guessed | |
| Mozilla | Thunderbird |
Affected:
unspecified , < 115.6
(custom)
|
guessed | |
| Mozilla | Firefox |
Affected:
unspecified , < 121
(custom)
|
guessed |
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"sourceIdentifier": "security@mozilla.org",
"vulnStatus": "Modified",
"weaknesses": [
{
"description": [
{
"lang": "en",
"value": "CWE-362"
}
],
"source": "nvd@nist.gov",
"type": "Primary"
}
]
}
},
"redhat_vex": {
"aggregate_severity": "Moderate",
"current_release_date": "2025-11-21T14:56:43+00:00",
"cve": "CVE-2023-6857",
"id": "CVE-2023-6857",
"initial_release_date": "2023-12-19T00:00:00+00:00",
"product_status:fixed": "311",
"product_status:known_affected": "4",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "Mozilla: Symlinks may resolve to smaller than expected buffers",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2023/cve-2023-6857.json",
"version": "3"
},
"suse_vex": {
"aggregate_severity": "important",
"current_release_date": "2026-08-31T01:15:15Z",
"cve": "CVE-2023-6857",
"id": "CVE-2023-6857",
"initial_release_date": "2023-12-20T02:09:29Z",
"product_status:known_affected": "36",
"product_status:recommended": "258",
"source": "SUSE CSAF VEX",
"status": "interim",
"title": "SUSE CVE CVE-2023-6857",
"url": "https://ftp.suse.com/pub/projects/security/csaf-vex/cve-2023-6857.json",
"version": "31"
}
}
}
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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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