CVE-2016-6580 (GCVE-0-2016-6580)
Vulnerability from cvelistv5 – Published: 2017-01-10 15:00 – Updated: 2024-08-06 01:36
VLAI
EPSS
VEX
Summary
A HTTP/2 implementation built using any version of the Python priority library prior to version 1.2.0 could be targeted by a malicious peer by having that peer assign priority information for every possible HTTP/2 stream ID. The priority tree would happily continue to store the priority information for each stream, and would therefore allocate unbounded amounts of memory. Attempting to actually use a tree like this would also cause extremely high CPU usage to maintain the tree.
Severity
7.5 (High)
CWE
- n/a
Assigner
References
2 references
| URL | Tags |
|---|---|
| http://www.securityfocus.com/bid/92311 | vdb-entryx_refsource_BID |
| https://python-hyper.org/priority/en/latest/secur… | x_refsource_CONFIRM |
Date Public
2016-08-04 00:00
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Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
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Vulnerability timeline
Sightings and recorded dates, grouped by day · UTC
How durations are calculated
Following the VTEM framework (Black Hat USA 2015), time to patch starts when the vendor or a coordinator was informed, total time to patch at discovery, and disclosure to patch at public disclosure; vendor response time runs from the report to its acknowledgement. Time to exploit and time unpatched start at the earliest discovery or report, falling back to public disclosure. Unpatched time ends at the first recorded patch, or the calculation time when no patch is recorded. Exploitation to patch shows the interval between those two events; a published proof of concept is a public exploit, not exploitation.
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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.