CVE-2015-5276 (GCVE-0-2015-5276)
Vulnerability from cvelistv5 – Published: 2015-11-17 15:00 – Updated: 2024-08-06 06:41
VLAI
EPSS
VEX
Summary
The std::random_device class in libstdc++ in the GNU Compiler Collection (aka GCC) before 4.9.4 does not properly handle short reads from blocking sources, which makes it easier for context-dependent attackers to predict the random values via unspecified vectors.
Severity
No CVSS data available.
CWE
- n/a
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://gcc.gnu.org/bugzilla/show_bug.cgi?id=65142 | x_refsource_CONFIRM |
| https://bugzilla.redhat.com/show_bug.cgi?id=1262846 | x_refsource_CONFIRM |
| http://lists.opensuse.org/opensuse-updates/2015-1… | vendor-advisoryx_refsource_SUSE |
| http://www.securitytracker.com/id/1034375 | vdb-entryx_refsource_SECTRACK |
| http://lists.opensuse.org/opensuse-updates/2016-0… | vendor-advisoryx_refsource_SUSE |
Date Public
2015-11-10 00:00
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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.
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.
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