CVE-2005-2875 (GCVE-0-2005-2875)
Vulnerability from cvelistv5 – Published: 2005-09-13 04:00 – Updated: 2024-08-07 22:53
VLAI
EPSS
VEX
Summary
Py2Play allows remote attackers to execute arbitrary Python code via pickled objects, which Py2Play unpickles and executes.
Severity
No CVSS data available.
CWE
- n/a
Assigner
References
8 references
| URL | Tags |
|---|---|
| http://secunia.com/advisories/16855 | third-party-advisoryx_refsource_SECUNIA |
| http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=326976 | x_refsource_CONFIRM |
| http://www.debian.org/security/2005/dsa-856 | vendor-advisoryx_refsource_DEBIAN |
| http://www.securityfocus.com/bid/14864 | vdb-entryx_refsource_BID |
| http://secunia.com/advisories/17106 | third-party-advisoryx_refsource_SECUNIA |
| http://soya.literati.org/ | x_refsource_MISC |
| http://www.gentoo.org/security/en/glsa/glsa-20050… | vendor-advisoryx_refsource_GENTOO |
| https://bugs.gentoo.org/show_bug.cgi?id=103524 | x_refsource_CONFIRM |
Date Public
2005-09-13 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.
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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