CVE-2013-10061 (GCVE-0-2013-10061)
Vulnerability from cvelistv5 – Published: 2025-08-01 20:45 – Updated: 2026-04-07 14:03
VLAI
EPSS
VEX
Title
Netgear Routers setup.cgi RCE
Summary
An authenticated OS command injection vulnerability exists in Netgear routers (tested on the DGN1000B model firmware versions 1.1.00.24 and 1.1.00.45) via the TimeToLive parameter in the setup.cgi endpoint. The vulnerability arises from improper input neutralization, enabling command injection through crafted POST requests. This flaw enables remote attackers to deploy payloads or manipulate system state post-authentication.
Severity
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2025-08-06 14:15 UTC
CWE
- CWE-78 - Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://raw.githubusercontent.com/rapid7/metasplo… | exploit |
| https://www.exploit-db.com/exploits/24464 | exploit |
| https://www.exploit-db.com/exploits/24931 | exploit |
| https://web.archive.org/web/20150218074318/http:/… | technical-descriptionexploit |
| https://www.vulncheck.com/advisories/netgear-lega… | third-party-advisory |
Impacted products
Date Public
2013-02-07 00:00
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Nomenclature
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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.