ZTE ElasticNet RNIA NGI sql injection

CVSS Meta Temp Score
CVSS is a standardized scoring system to determine possibilities of attacks. The Temp Score considers temporal factors like disclosure, exploit and countermeasures. The unique Meta Score calculates the average score of different sources to provide a normalized scoring system.
Current Exploit Price (≈)
Our analysts are monitoring exploit markets and are in contact with vulnerability brokers. The range indicates the observed or calculated exploit price to be seen on exploit markets. A good indicator to understand the monetary effort required for and the popularity of an attack.
CTI Interest Score
Our Cyber Threat Intelligence team is monitoring different web sites, mailing lists, exploit markets and social media networks. The CTI Interest Score identifies the interest of attackers and the security community for this specific vulnerability in real-time. A high score indicates an elevated risk to be targeted for this vulnerability.
6.4$0-$5k4.09

Summaryinfo

A vulnerability, which was classified as critical, has been found in ZTE ElasticNet RNIA NGI. The affected element is an unknown function. This manipulation causes sql injection. This vulnerability is tracked as CVE-2026-118871. The attack is possible to be carried out remotely. No exploit exists.

Detailsinfo

A vulnerability classified as critical was found in ZTE ElasticNet RNIA NGI (affected version unknown). Affected by this vulnerability is an unknown functionality. The manipulation with an unknown input leads to a sql injection vulnerability. The CWE definition for the vulnerability is CWE-89. The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. As an impact it is known to affect confidentiality, integrity, and availability. The summary by CVE is:

SQL injection vulnerability classified as an internal threat level.Attackers can steal database information via SQL injection while logged in.

It is possible to read the advisory at support.zte.com.cn. This vulnerability is known as CVE-2026-118871 since 10/29/2026. The exploitation appears to be easy. The attack can be launched remotely. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $0-$5k at the moment (estimation calculated on 11/02/2026). The attack technique deployed by this issue is T1505 according to MITRE ATT&CK.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

Productinfo

Vendor

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License

Website

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔒
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 6.4
VulDB Meta Temp Score: 6.4

VulDB Base Score: 6.3
VulDB Temp Score: 6.3
VulDB Vector: 🔒
VulDB Reliability: 🔍

CNA Base Score: 6.5
CNA Vector (zte): 🔒

CVSSv2info

AVACAuCIA
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VectorComplexityAuthenticationConfidentialityIntegrityAvailability
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VulDB Base Score: 🔒
VulDB Temp Score: 🔒
VulDB Reliability: 🔍

Exploitinginfo

Class: Sql injection
CWE: CWE-89 / CWE-74 / CWE-707
CAPEC: 🔒
ATT&CK: 🔒

Physical: No
Local: No
Remote: Yes

Availability: 🔒
Status: Not defined
Price Prediction: 🔍
Current Price Estimation: 🔒

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Threat Intelligenceinfo

Interest: 🔍
Active Actors: 🔍
Active APT Groups: 🔍

Countermeasuresinfo

Recommended: no mitigation known
Status: 🔍

0-Day Time: 🔒

Timelineinfo

10/29/2026 CVE reserved
11/02/2026 +4 days Advisory disclosed
11/02/2026 +0 days VulDB entry created
11/02/2026 +0 days VulDB entry last update

Sourcesinfo

Vendor: zte.com.cn

Advisory: support.zte.com.cn
Status: Confirmed

CNA: zte
CVE: CVE-2026-118871 (🔒)

GCVE (CVE): GCVE-0-2026-118871
GCVE (VulDB): GCVE-100-429787

Entryinfo

Created: 11/02/2026 10:59
Changes: 11/02/2026 10:59 (59)
Complete: 🔍
Cache ID: 216::103

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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