GSD-2022-31140
Vulnerability from gsd - Updated: 2023-12-13 01:19Details
Valinor is a PHP library that helps to map any input into a strongly-typed value object structure. Prior to version 0.12.0, Valinor can use `Throwable#getMessage()` when it should not have permission to do so. This is a problem with cases such as an SQL exception showing an SQL snippet, a database connection exception showing database IP address/username/password, or a timeout detail / out of memory detail. Attackers could use this information for potential data exfiltration, denial of service attacks, enumeration attacks, etc. Version 0.12.0 contains a patch for this vulnerability.
Aliases
Aliases
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"alias": "CVE-2022-31140",
"description": "Valinor is a PHP library that helps to map any input into a strongly-typed value object structure. Prior to version 0.12.0, Valinor can use `Throwable#getMessage()` when it should not have permission to do so. This is a problem with cases such as an SQL exception showing an SQL snippet, a database connection exception showing database IP address/username/password, or a timeout detail / out of memory detail. Attackers could use this information for potential data exfiltration, denial of service attacks, enumeration attacks, etc. Version 0.12.0 contains a patch for this vulnerability.",
"id": "GSD-2022-31140"
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"id": "GSD-2022-31140",
"modified": "2023-12-13T01:19:17.944705Z",
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"description": "Valinor is a PHP library that helps to map any input into a strongly-typed value object structure. Prior to version 0.12.0, Valinor can use `Throwable#getMessage()` when it should not have permission to do so. This is a problem with cases such as an SQL exception showing an SQL snippet, a database connection exception showing database IP address/username/password, or a timeout detail / out of memory detail. Attackers could use this information for potential data exfiltration, denial of service attacks, enumeration attacks, etc. Version 0.12.0 contains a patch for this vulnerability.",
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"package_slug": "packagist/cuyz/valinor",
"pubdate": "2022-07-12",
"solution": "Upgrade to version 0.12.0 or above.",
"title": "Generation of Error Message Containing Sensitive Information",
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"lastModifiedDate": "2022-07-16T13:40Z",
"publishedDate": "2022-07-11T20:15Z"
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}
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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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