Vulnerability-Lookup

VAR-201709-0480

Vulnerability from variot - Updated: 2023-12-18 12:51

Server-side request forgery (SSRF) vulnerability in file_upload.php in Synology Photo Station before 6.7.4-3433 and 6.3-2968 allows remote authenticated users to download arbitrary local files via the url parameter. Synology Photo Station is a set of solutions from Synology for sharing pictures, videos and blogs on the Internet

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CVE-2017-12071 (GCVE-0-2017-12071)

Vulnerability from cvelistv5 – Published: 2017-09-08 14:00 – Updated: 2024-09-17 02:15

Summary

Severity

No CVSS data available.

CWE

CWE-918 - Server-Side Request Forgery (CWE-918)

Assigner

synology mitre root

References

1 reference

URL	Tags
https://www.synology.com/en-global/support/securi…	x_refsource_CONFIRM

Impacted products

1 product

Vendor	Product	Version
Synology	Synology Photo Station	Affected: before 6.7.4-3433 and 6.3-2968

Date Public

2017-09-08 00:00

Show details on NVD website

JSON

To clipboard

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          "url": "https://www.synology.com/en-global/support/security/Synology_SA_17_35_PhotoStation"
        }
      ],
      "x_legacyV4Record": {
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        },
        "affects": {
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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.

Detection rules are retrieved from Rulezet.

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.

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.