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VAR-201809-0080

Vulnerability from variot - Updated: 2025-01-30 19:52

An exploitable buffer overflow vulnerability exists in the DDNS client used by the Foscam C1 Indoor HD Camera running application firmware 2.52.2.43. On devices with DDNS enabled, an attacker who is able to intercept HTTP connections will be able to fully compromise the device by creating a rogue HTTP server. FoscamC1IndoorHDCamera is a wireless HD IP camera from China Foscam. DDNSclient is one of the dynamic domain name service clients

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CVE-2017-2855 (GCVE-0-2017-2855)

Vulnerability from cvelistv5 – Published: 2018-09-19 16:00 – Updated: 2024-09-16 18:02

Summary

Severity

8.1 (High)


                        
                          CVSS:3.0/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H

CWE

Buffer Overflow

Assigner

talos CNA under the mitre root

CNA scorecard – unranked: 8 records in the last 180 days, 10 needed details

References

1 reference

URL	Tags
https://talosintelligence.com/vulnerability_repor…	x_refsource_MISC

Impacted products

1 product

Vendor	Product	Version
Foscam	Foscam C1 Indoor HD Camera	Affected: Foscam Indoor IP Camera C1 Series,System Firmware Version: 1.9.3.18,Application Firmware Version: 2.52.2.43,Plug-In Version: 3.3.0.26

Date Public

2017-11-13 00:00

Show details on NVD website

JSON

To clipboard

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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.

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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.
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