CVE-2022-40619 (GCVE-0-2022-40619)

Vulnerability from cvelistv5 – Published: 2026-01-28 00:00 – Updated: 2026-01-29 18:52
VLAI Previdian
Summary
FunJSQ, a third-party module integrated on some NETGEAR routers and Orbi WiFi Systems, exposes an HTTP server over the LAN interface of affected devices. This interface is vulnerable to unauthenticated arbitrary command injection through the funjsq_access_token parameter. This affects R6230 before 1.1.0.112, R6260 before 1.1.0.88, R7000 before 1.0.11.134, R8900 before 1.0.5.42, R9000 before 1.0.5.42, and XR300 before 1.0.3.72 and Orbi RBR20 before 2.7.2.26, RBR50 before 2.7.4.26, RBS20 before 2.7.2.26, and RBS50 before 2.7.4.26.
Severity
7.7 (High)
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:L
SSVC
Exploitation: none Automatable: no Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-01-29 18:51 UTC
CWE
  • n/a
  • CWE-77 - Improper Neutralization of Special Elements used in a Command ('Command Injection')
Assigner
References
Previdian
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: 140aeed8-fc3d-40db-9194-52e666aeb77f

Vulnerability ID: CVE-2022-40619

Status: Confirmed

Status Updated: 2026-01-28 01:00 CET

Exploited: Yes

Timestamps
First Seen: 2026-01-28
Asserted: 2026-01-28
Scope
Notes: FunJSQ, a third-party module integrated on some NETGEAR routers and Orbi WiFi Systems, exposes an HTTP server over the LAN interface of affected... | Affected: NETGEAR / Routers and Orbi WiFi Systems | CVSS: 7.7 (HIGH) | EPSS: 0.02538 | Used in malware: unknown | Not yet in CISA KEV: True
Evidence

Type: Public Report

Signal: Successful Exploitation

Confidence: 70%

Source: previdian

Details
Feed Previdian (previdian.com)
Title FunJSQ, a third-party module integrated on some NETGEAR routers and Orbi WiFi Systems, exposes an HTTP server over the LAN interface of affected...
Cve Id CVE-2022-40619
Vendor NETGEAR
Ghsa Id None
Product Routers and Orbi WiFi Systems
Added Date 2026-01-28T00:00:00.000Z
Cvss Score 7.7
Epss Score 0.02538
Previous Ids
Cvss Severity HIGH
Virtual Patch False
Cvss Estimated False
Epss Percentile 0.84402
Used In Malware unknown
Vulnerability Id CVE-2022-40619
Ahead Of Cisa Kev None
Not Yet In Cisa Kev True
References
Created: 2026-10-02 09:10 CEST | Updated: 2026-10-02 09:10 CEST
Show details on NVD website
To clipboard 

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              "url": "https://www.onekey.com/resource/security-advisory-netgear-routers-funjsq-vulnerabilities"
            }
          ]
        }
      },
      "cveMetadata": {
        "assignerOrgId": "8254265b-2729-46b6-b9e3-3dfca2d5bfca",
        "assignerShortName": "mitre",
        "cveId": "CVE-2022-40619",
        "datePublished": "2026-01-28T00:00:00.000Z",
        "dateReserved": "2022-09-12T00:00:00.000Z",
        "dateUpdated": "2026-01-29T18:52:26.839Z",
        "state": "PUBLISHED"
      },
      "dataType": "CVE_RECORD",
      "dataVersion": "5.2"
    }
  }
}



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Tags
Taxonomy of the tags.





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.



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.