CVE-2022-22970 (GCVE-0-2022-22970)
Vulnerability from cvelistv5 – Published: 2022-05-12 19:28 – Updated: 2024-08-03 03:28
VLAI
EPSS
VEX
Summary
In spring framework versions prior to 5.3.20+ , 5.2.22+ and old unsupported versions, applications that handle file uploads are vulnerable to DoS attack if they rely on data binding to set a MultipartFile or javax.servlet.Part to a field in a model object.
Severity
5.3 (Medium)
CWE
- CWE-770 - Allocation of Resources Without Limits or Throttling
Assigner
References
3 references
| URL | Tags |
|---|---|
| https://tanzu.vmware.com/security/cve-2022-22970 | x_refsource_MISC |
| https://www.oracle.com/security-alerts/cpujul2022.html | x_refsource_MISC |
| https://security.netapp.com/advisory/ntap-2022061… | x_refsource_CONFIRM |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| n/a | Spring Framework |
Affected:
Spring Framework versions 5.3.x prior to 5.3.20, 5.2.x prior to 5.2.22 and all old and unsupported versions
|
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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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