CVE-2018-6000 (GCVE-0-2018-6000)

Vulnerability from cvelistv5 – Published: 2018-01-22 20:00 – Updated: 2024-08-05 05:47
VLAI Shadowserver
Summary
An issue was discovered in AsusWRT before 3.0.0.4.384_10007. The do_vpnupload_post function in router/httpd/web.c in vpnupload.cgi provides functionality for setting NVRAM configuration values, which allows attackers to set the admin password and launch an SSH daemon (or enable infosvr command mode), and consequently obtain remote administrative access, via a crafted request. This is available to unauthenticated attackers in conjunction with CVE-2018-5999.
Severity
9.8 (Critical)
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
CWE
  • n/a
Assigner
mitre CNA under the mitre root
CNA scorecard E 29/100 over 2193 records in the last 180 days details
References
Date Public
2018-01-22 00:00
Shadowserver
Known Exploited Vulnerability - GCVE BCP-07 Compliant
KEV entry ID: f7e1179e-9ded-410b-b2a3-fefd0f7e3b3e

Vulnerability ID: CVE-2018-6000

Status: Confirmed

Status Updated: 2026-10-03 00:00 UTC

Exploited: Yes

Characteristics
Severity: 98.0
Timestamps
First Seen: 2026-09-29
Asserted: 2026-09-29
Last Seen: 2026-10-03
Scope
Asset Exposure: ['internet-facing']
Notes: Affected: ASUS / ASUSWRT | Class: router | Severity: Critical (CVSS 9.8) | IoT: yes | In CISA KEV: no | Honeypot connections on 2026-10-03: 4
Evidence

Type: Honeypot

Signal: In The Wild Attempts

Confidence: 70%

Source: shadowserver

Details
1D 1
Iot yes
Feed Shadowserver Foundation honeypot/exploited-vulnerabilities
Type http-scan
Class router
7D Avg 0
Vendor ASUS
30D Avg 0
90D Avg 0
Product ASUSWRT
Cisa Kev no
Connections 4
Observation Date 2026-10-03
Vulnerability Class CVSS
Vulnerability Score 9.8
Vulnerability Severity Critical
References
Created: 2026-10-21 09:03 UTC | Updated: 2026-10-21 09:03 UTC
Show details on NVD website
To clipboard 

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}



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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.