Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XSummary
CVE-2026-5322 is a medium-severity Injection (CWE-74) vulnerability. Its CVSS base score is 6.9 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 18th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as AI Agent Protocols and Integrations; in the Data-Related Vulnerabilities risk domain.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-5322 is a SQL injection vulnerability (CWE-74, CWE-89) affecting the Request function in the file src/servers/database/server.js of the MCP Handler component within AlejandroArciniegas mcp-data-vis at commit bc597e391f184d2187062fd567599a3cb72adf51/de5a51525a69822290eaee569a1ab447b490746d. The software follows a rolling release model, so specific version information for affected or patched releases is unavailable.
The vulnerability is remotely exploitable by unauthenticated attackers with low complexity and no user interaction required, earning a CVSS 3.1 base score of 7.3 (AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L). Exploitation via SQL injection manipulation can result in limited impacts to confidentiality, integrity, and availability.
Advisories from VulDB and a GitHub issue in wing3e/public_exp detail the vulnerability and disclose a public exploit. The vendor was contacted early but provided no response, with no patches or mitigations specified. The exploit has been made publicly available for potential use.
Notable context includes the public disclosure of the exploit, increasing the risk of active exploitation, particularly given the lack of vendor response.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-18126
Vulnerability Data
A vulnerability has been found in AlejandroArciniegas mcp-data-vis bc597e391f184d2187062fd567599a3cb72adf51/de5a51525a69822290eaee569a1ab447b490746d. This affects the function Request of the file src/servers/database/server.js of the component MCP Handler. The manipulation leads to sql injection. The attack may be initiated remotely. The exploit has been disclosed…
more
to the public and may be used. This product uses a rolling release model to deliver continuous updates. As a result, specific version information for affected or updated releases is not available. The vendor was contacted early about this disclosure but did not respond in any way.
- CWE(s)
AI Security AnalysisAI
- AI Category
- AI Agent Protocols and Integrations
- Risk Domain
- Data-Related Vulnerabilities
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: mcp
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover SQLi flaws before deployment but does not stop their introduction.
SI-10 directly requires validation of information inputs to reject malformed or special-element content before it reaches downstream parsers.
Secure engineering principles require parameterized queries and input sanitization that structurally eliminate SQLi.
System monitoring can identify attempted SQLi exploitation via anomalous queries after the weakness exists.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly require input validation and output encoding that prevent injection flaws.
Training raises developer awareness of SQLi risks and can reduce introduction likelihood (partial) but removes none of the actual coding flaw's risk by itself since technical neutralization is still required.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development catches injection vulnerabilities before release.
Early warnings and shared best-practice information help organizations apply the latest remediation techniques against SQL-injection vulnerabilities.
Threat-intelligence feeds that surface new SQL-injection campaigns enable rapid updates to query-construction defenses and detection signatures before exploitation occurs.
Logging supports detection of injection attempts but does not prevent the weakness.
Monitoring activities can identify active injection attacks after they occur.
Secure development life cycle mandates input validation and output encoding that directly prevent injection flaws.