RHSA-2025:19107
Vulnerability from csaf_opensuse - Published: 2025-10-27 00:00 - Updated: 2026-09-20 11:49Summary
security update for libecap
Severity
Important
Notes
Title of the patch: security update for libecap
Description of the patch: This security update provides a functional equivalent of RHSA-2025:19107.
The original Red Hat(R) advisory is available from the Red Hat web site at
https://access.redhat.com/errata/RHSA-2025:19107.
Patchnames: RHSA-2025:19107
Terms of use: CSAF 2.0 data is provided by SUSE under the Creative Commons License 4.0 with Attribution (CC-BY-4.0).
8.6 (High)
Affected products
Recommended
3 products
| Product | Identifier | Version | Remediation |
|---|---|---|---|
| Unresolved product id: SUSE Liberty Linux 8:libecap-0:1.0.1-2.module+el8.9.0+19703+a1da7223.x86_64::squid:4 | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Liberty Linux 8:libecap-devel-0:1.0.1-2.module+el8.9.0+19703+a1da7223.x86_64::squid:4 | — |
Vendor Fix
|
|
| Unresolved product id: SUSE Liberty Linux 8:squid-7:4.15-10.module+el8.10.0+23592+d564ec65.9.x86_64::squid:4 | — |
Vendor Fix
|
Threats
Impact
important
References
7 references
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"ids": [
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"notes": [
{
"category": "general",
"text": "Squid is a caching proxy for the Web. In Squid versions prior to 7.2, a failure to redact HTTP authentication credentials in error handling allows information disclosure. The vulnerability allows a script to bypass browser security protections and learn the credentials a trusted client uses to authenticate. This potentially allows a remote client to identify security tokens or credentials used internally by a web application using Squid for backend load balancing. These attacks do not require Squid to be configured with HTTP authentication. The vulnerability is fixed in version 7.2. As a workaround, disable debug information in administrator mailto links generated by Squid by configuring squid.conf with email_err_data off.",
"title": "CVE description"
}
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"details": "To install this SUSE Security Update use the SUSE recommended installation methods like YaST online_update or \"zypper patch\".\n",
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}
]
}
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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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