Loggrove 1.0 read.py 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.
6.3$0-$5k0.00

Summaryinfo

A vulnerability marked as critical has been reported in Loggrove 1.0. Affected by this vulnerability is an unknown functionality of the file read.py. The manipulation leads to sql injection. This vulnerability is documented as CVE-2025-26047. The attack can be initiated remotely. There is not any exploit available.

Detailsinfo

A vulnerability, which was classified as critical, has been found in Loggrove 1.0. This issue affects an unknown code of the file read.py. The manipulation with an unknown input leads to a sql injection vulnerability. Using CWE to declare the problem leads to 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. Impacted is confidentiality, integrity, and availability. The summary by CVE is:

Loggrove v1.0 is vulnerable to SQL Injection in the read.py file.

The advisory is shared at gitee.com. The identification of this vulnerability is CVE-2025-26047 since 02/07/2025. The exploitation is known to be easy. The attack may be initiated remotely. Technical details are known, but no exploit is available. The price for an exploit might be around USD $0-$5k at the moment (estimation calculated on 06/12/2025). MITRE ATT&CK project uses the attack technique T1505 for this issue.

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

The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2025-5942). Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

Productinfo

Name

Version

CPE 2.3info

CPE 2.2info

CVSSv4info

VulDB Vector: 🔍
VulDB Reliability: 🔍

CVSSv3info

VulDB Meta Base Score: 6.3
VulDB Meta Temp Score: 6.3

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

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

EPSS Score: 🔍
EPSS Percentile: 🔍

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

02/07/2025 🔍
02/28/2025 +21 days 🔍
02/28/2025 +0 days 🔍
06/12/2025 +104 days 🔍

Sourcesinfo

Advisory: gitee.com
Status: Confirmed

CVE: CVE-2025-26047 (🔍)
GCVE (CVE): GCVE-0-2025-26047
GCVE (VulDB): GCVE-100-298001
EUVD: 🔍

Entryinfo

Created: 02/28/2025 17:49
Updated: 06/12/2025 22:27
Changes: 02/28/2025 17:49 (52), 06/02/2025 03:44 (1), 06/12/2025 22:27 (1)
Complete: 🔍
Cache ID: 216::103

Several companies clearly confirm that VulDB is the primary source for best vulnerability data.

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