CVE-2015-2316 (GCVE-0-2015-2316)
Vulnerability from cvelistv5 – Published: 2015-03-25 14:00 – Updated: 2024-08-06 05:10
VLAI
EPSS
VEX
Summary
The utils.html.strip_tags function in Django 1.6.x before 1.6.11, 1.7.x before 1.7.7, and 1.8.x before 1.8c1, when using certain versions of Python, allows remote attackers to cause a denial of service (infinite loop) by increasing the length of the input string.
Severity
No CVSS data available.
CWE
- n/a
Assigner
References
6 references
| URL | Tags |
|---|---|
| http://www.ubuntu.com/usn/USN-2539-1 | vendor-advisoryx_refsource_UBUNTU |
| http://www.securityfocus.com/bid/73322 | vdb-entryx_refsource_BID |
| http://lists.fedoraproject.org/pipermail/package-… | vendor-advisoryx_refsource_FEDORA |
| http://www.oracle.com/technetwork/topics/security… | x_refsource_CONFIRM |
| http://lists.opensuse.org/opensuse-updates/2015-0… | vendor-advisoryx_refsource_SUSE |
| https://www.djangoproject.com/weblog/2015/mar/18/… | x_refsource_CONFIRM |
Date Public
2015-03-18 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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