Huawei UMA V200R001C00 Maintenance HTTP Requests sql injection

| CVSS Meta Temp Score | Current Exploit Price (≈) | CTI Interest Score |
|---|---|---|
| 7.5 | $5k-$25k | 0.00 |
Summary
A vulnerability marked as critical has been reported in Huawei UMA V200R001C00. Affected by this vulnerability is an unknown functionality of the component Maintenance Module. Performing a manipulation as part of HTTP Requests results in sql injection. This vulnerability is known as CVE-2017-15329. Remote exploitation of the attack is possible. No exploit is available.
Details
A vulnerability classified as critical has been found in Huawei UMA V200R001C00. This affects an unknown code of the component Maintenance Module. The manipulation as part of a HTTP Requests leads to a sql injection vulnerability. CWE is classifying the issue as 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. This is going to have an impact on confidentiality, integrity, and availability. The summary by CVE is:
Huawei UMA V200R001C00 has a SQL injection vulnerability in the operation and maintenance module. An attacker logs in to the system as a common user and sends crafted HTTP requests that contain malicious SQL statements to the affected system. Due to a lack of input validation on HTTP requests that contain user-supplied input, successful exploitation may allow the attacker to execute arbitrary SQL queries.
The bug was discovered 11/10/2017. The weakness was published 02/15/2018 (Website). It is possible to read the advisory at huawei.com. This vulnerability is uniquely identified as CVE-2017-15329 since 10/14/2017. The exploitability is told to be easy. It is possible to initiate the attack remotely. A authentication is needed for exploitation. The technical details are unknown and an exploit is not publicly available. The pricing for an exploit might be around USD $5k-$25k at the moment (estimation calculated on 02/06/2023). The attack technique deployed by this issue is T1505 according to MITRE ATT&CK.
The vulnerability was handled as a non-public zero-day exploit for at least 97 days. During that time the estimated underground price was around $5k-$25k.
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.
Product
Vendor
Name
Version
License
Website
- Vendor: https://www.huawei.com/
CPE 2.3
CPE 2.2
CVSSv4
VulDB Vector: 🔍VulDB Reliability: 🔍
CVSSv3
VulDB Meta Base Score: 7.6VulDB Meta Temp Score: 7.6
VulDB Base Score: 6.3
VulDB Temp Score: 6.3
VulDB Vector: 🔍
VulDB Reliability: 🔍
NVD Base Score: 8.8
NVD Vector: 🔍
CVSSv2
| AV | AC | Au | C | I | A |
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| 💳 | 💳 | 💳 | 💳 | 💳 | 💳 |
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| Vector | Complexity | Authentication | Confidentiality | Integrity | Availability |
|---|---|---|---|---|---|
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VulDB Base Score: 🔍
VulDB Temp Score: 🔍
VulDB Reliability: 🔍
NVD Base Score: 🔍
Exploiting
Class: Sql injectionCWE: CWE-89 / CWE-74 / CWE-707
CAPEC: 🔍
ATT&CK: 🔍
Physical: No
Local: No
Remote: Yes
Availability: 🔍
Status: Not defined
EPSS Score: 🔍
EPSS Percentile: 🔍
Price Prediction: 🔍
Current Price Estimation: 🔍
| 0-Day | Unlock | Unlock | Unlock | Unlock |
|---|---|---|---|---|
| Today | Unlock | Unlock | Unlock | Unlock |
Threat Intelligence
Interest: 🔍Active Actors: 🔍
Active APT Groups: 🔍
Countermeasures
Recommended: no mitigation knownStatus: 🔍
0-Day Time: 🔍
Timeline
10/14/2017 🔍11/10/2017 🔍
02/15/2018 🔍
02/15/2018 🔍
02/16/2018 🔍
02/06/2023 🔍
Sources
Vendor: huawei.comAdvisory: sa-20171116-01
Status: Not defined
Confirmation: 🔍
CVE: CVE-2017-15329 (🔍)
GCVE (CVE): GCVE-0-2017-15329
GCVE (VulDB): GCVE-100-113355
Entry
Created: 02/16/2018 08:38Updated: 02/06/2023 16:52
Changes: 02/16/2018 08:38 (57), 01/05/2020 13:24 (2), 02/06/2023 16:52 (3)
Complete: 🔍
Cache ID: 216::103
Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.
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