CVE-2020-8203 (GCVE-0-2020-8203)
Vulnerability from cvelistv5 – Published: 2020-07-15 16:10 – Updated: 2024-08-04 09:56
VLAI
EPSS
VEX
Summary
Prototype pollution attack when using _.zipObjectDeep in lodash before 4.17.20.
Severity
7.4 (High)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling (CWE-770)
Assigner
References
8 references
| URL | Tags |
|---|---|
| https://hackerone.com/reports/712065 | x_refsource_MISC |
| https://www.oracle.com/security-alerts/cpuApr2021.html | x_refsource_MISC |
| https://security.netapp.com/advisory/ntap-2020072… | x_refsource_CONFIRM |
| https://github.com/lodash/lodash/issues/4874 | x_refsource_MISC |
| https://www.oracle.com//security-alerts/cpujul2021.html | x_refsource_MISC |
| https://www.oracle.com/security-alerts/cpuoct2021.html | x_refsource_MISC |
| https://www.oracle.com/security-alerts/cpujan2022.html | x_refsource_MISC |
| https://www.oracle.com/security-alerts/cpuapr2022.html | x_refsource_MISC |
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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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