CVE-2019-1010246 (GCVE-0-2019-1010246)
Vulnerability from cvelistv5 – Published: 2019-07-18 18:04 – Updated: 2024-08-05 03:07
VLAI
EPSS
VEX
Summary
MailCleaner before c888fbb6aaa7c5f8400f637bcf1cbb844de46cd9 is affected by: Unauthenticated MySQL database password information disclosure. The impact is: MySQL database content disclosure (e.g. username, password). The component is: The API call in the function allowAction() in NewslettersController.php. The attack vector is: HTTP Get request. The fixed version is: c888fbb6aaa7c5f8400f637bcf1cbb844de46cd9.
Severity
7.5 (High)
CWE
- Unauthenticated MySQL database password information disclosure
Assigner
References
1 reference
| URL | Tags |
|---|---|
| https://github.com/MailCleaner/MailCleaner/commit… | x_refsource_MISC |
Impacted products
1 product
| Vendor | Product | Version | CPE status | |
|---|---|---|---|---|
| MailCleaner | MailCleaner |
Affected:
before c888fbb6aaa7c5f8400f637bcf1cbb844de46cd9 [fixed: c888fbb6aaa7c5f8400f637bcf1cbb844de46cd9]
|
guessed |
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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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