RHSA-2026:7545
Vulnerability from csaf_redhat - Published: 2026-04-10 21:56 - Updated: 2026-09-08 01:11Summary
Red Hat Security Advisory: Red Hat Hardened Images RPMs bug fix and enhancement update
Severity
Moderate
Notes
Topic: An update for Red Hat Hardened Images RPMs is now available.
Details: This update includes the following RPMs:
oniguruma:
* oniguruma-6.9.10-4.1.hum1 (aarch64, x86_64)
* oniguruma-devel-6.9.10-4.1.hum1 (aarch64, x86_64)
* oniguruma-6.9.10-4.1.hum1.src (src)
Terms of Use: This content is licensed under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). If you distribute this content, or a modified version of it, you must provide attribution to Red Hat Inc. and provide a link to the original.
An issue was discovered in Oniguruma 6.2.0, as used in Oniguruma-mod in Ruby through 2.4.1 and mbstring in PHP through 7.1.5. A stack out-of-bounds write in onigenc_unicode_get_case_fold_codes_by_str() occurs during regular expression compilation. Code point 0xFFFFFFFF is not properly handled in unicode_unfold_key(). A malformed regular expression could result in 4 bytes being written off the end of a stack buffer of expand_case_fold_string() during the call to onigenc_unicode_get_case_fold_codes_by_str(), a typical stack buffer overflow.
5.9 (Medium)
Affected products
Fixed
3 products
Threats
Impact
Moderate
An issue was discovered in Oniguruma 6.2.0, as used in Oniguruma-mod in Ruby through 2.4.1 and mbstring in PHP through 7.1.5. A SIGSEGV occurs in left_adjust_char_head() during regular expression compilation. Invalid handling of reg->dmax in forward_search_range() could result in an invalid pointer dereference, normally as an immediate denial-of-service condition.
6.5 (Medium)
Affected products
Fixed
3 products, the same list as for
CVE-2017-9225
Threats
Impact
Moderate
References
14 references
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"text": "This update includes the following RPMs:\n\noniguruma:\n * oniguruma-6.9.10-4.1.hum1 (aarch64, x86_64)\n * oniguruma-devel-6.9.10-4.1.hum1 (aarch64, x86_64)\n * oniguruma-6.9.10-4.1.hum1.src (src)",
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{
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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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