CVE-2016-5636 (GCVE-0-2016-5636)
Vulnerability from cvelistv5 – Published: 2016-09-02 14:00 – Updated: 2024-08-06 01:07
VLAI
EPSS
VEX
Summary
Integer overflow in the get_data function in zipimport.c in CPython (aka Python) before 2.7.12, 3.x before 3.4.5, and 3.5.x before 3.5.2 allows remote attackers to have unspecified impact via a negative data size value, which triggers a heap-based buffer overflow.
Severity
9.8 (Critical)
CWE
- n/a
Assigner
References
15 references
Date Public
2016-01-21 00:00
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"redhat_vex": {
"aggregate_severity": "Low",
"current_release_date": "2026-06-27T06:35:19+00:00",
"cve": "CVE-2016-5636",
"id": "CVE-2016-5636",
"initial_release_date": "2016-01-21T00:00:00+00:00",
"product_status:fixed": "88",
"product_status:known_affected": "40",
"product_status:known_not_affected": "4",
"source": "Red Hat CSAF VEX",
"status": "final",
"title": "python: Heap overflow in zipimporter module",
"url": "https://security.access.redhat.com/data/csaf/v2/vex/2016/cve-2016-5636.json",
"version": "3"
}
}
}
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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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