Cyber Resilience

CVE-2023-49795

Medium

Published: 11 December 2023

Published
11 December 2023
Modified
21 November 2024
KEV Added
—
Patch
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CVSS Score v3.1 6.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N
EPSS Score 0.0035 58.1th percentile
Risk Priority 13 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2023-49795 is a medium-severity SSRF (CWE-918) vulnerability in Mindsdb Mindsdb. Its CVSS base score is 6.5 (Medium).

Operationally, exploitation aligns with the MITRE ATT&CK technique Data from Local System (T1005); ranked in the top 41.9% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as Enterprise AI Assistants; in the Privacy and Disclosure risk domain; MITRE ATLAS techniques in scope: Discover AI Model Ontology (AML.T0013), Discover AI Model Family (AML.T0014), Obtain Capabilities (AML.T0016).

EU & UK References

Vulnerability details

MindsDB connects artificial intelligence models to real time data. Versions prior to 23.11.4.1 contain a server-side request forgery vulnerability in `file.py`. This can lead to limited information disclosure. Users should use MindsDB's `staging` branch or v23.11.4.1, which contain a fix…

more

for the issue.

CWE(s)
CWE-918

AI Security AnalysisAI

AI Category
Enterprise AI Assistants
Risk Domain
Privacy and Disclosure
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
MindsDB is an enterprise platform that integrates AI/ML models with databases for real-time predictions and data querying, fitting the Enterprise AI Assistants category.

Related Threats

MITRE ATT&CK Enterprise TechniquesAI

T1005 Data from Local System Collection
Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration.
attack.mitre.org →
T1046 Network Service Discovery Discovery
Adversaries may attempt to get a listing of services running on remote hosts and local network infrastructure devices, including those that may be vulnerable to remote software exploitation.
attack.mitre.org →
T1083 File and Directory Discovery Discovery
Adversaries may enumerate files and directories or may search in specific locations of a host or network share for certain information within a file system.
attack.mitre.org →
T1190 Exploit Public-Facing Application Initial Access
Adversaries may attempt to exploit a weakness in an Internet-facing host or system to initially access a network.
attack.mitre.org →
Why these techniques?

SSRF vulnerability (CVE-2023-49795) in MindsDB's file.py enables exploitation of public-facing application (T1190), facilitating data from local system (T1005), file and directory discovery (T1083), and network service discovery (T1046) through forged server-side requests leading to limited information disclosure.

MITRE ATLAS TechniquesAI

MITRE ATLAS techniques

AML.T0013: Discover AI Model OntologyAML.T0014: Discover AI Model FamilyAML.T0016: Obtain CapabilitiesAML.T0032AML.T0036: Data from Information RepositoriesAML.T0037: Data from Local System

Affected Assets

mindsdb
mindsdb
≤ 23.11.4.1

Mitigating Controls

Likely Mitigating Controls AI

Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.

CA-8 Penetration Testing
addresses: CWE-918

Penetration testing attempts server-side requests to internal resources, identifying SSRF weaknesses for remediation.

SC-7 Boundary Protection
addresses: CWE-918

Outbound connections to external resources can be monitored and limited at the boundary, reducing SSRF impact.

SI-10 Information Input Validation
addresses: CWE-918

Validates server-side URLs and resource references to block SSRF attempts.

SI-4 System Monitoring
addresses: CWE-918

Detects server-side request forgery through monitoring of unexpected outbound connections.

References