Raw vector
CVSS:3.1/AV:N/AC:H/PR:H/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2023-37941 is a medium-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Apache Superset. Its CVSS base score is 6.6 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 2% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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-2023-37941 is a deserialization vulnerability affecting Apache Superset versions 1.5.0 through 2.1.0. An attacker who obtains write access to the Superset metadata database can store a crafted Python object that triggers remote code execution on the web backend when deserialized by the application.
The metadata database is described as an internal component normally reachable only by the system administrator or the Superset process itself, so successful exploitation requires significant prior privileges. The CVSS 6.6 score reflects the high attack complexity and administrative access needed, yet successful attacks can result in full confidentiality, integrity, and availability impact on the Superset instance.
Advisories from the Apache project recommend upgrading to version 2.1.1 or later to address the issue. Public references include exploit code posted to Packet Storm and security announcements on the Apache mailing lists that reiterate the upgrade guidance.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-2493
Vulnerability Data
If an attacker gains write access to the Apache Superset metadata database, they could persist a specifically crafted Python object that may lead to remote code execution on Superset's web backend. The Superset metadata db is an 'internal' component that…
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is typically only accessible directly by the system administrator and the superset process itself. Gaining access to that database should be difficult and require significant privileges. This vulnerability impacts Apache Superset versions 1.5.0 up to and including 2.1.0. Users are recommended to upgrade to version 2.1.1 or later.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
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.
Penetration testing supplies malicious serialized objects, detecting unsafe deserialization and supporting corrective actions.
Evaluation of untrusted data handling (deserialization testing) reveals unsafe processing, which the required remediation process addresses.
Untrusted serialized data can be deserialized and observed inside the chamber, blocking gadget-chain exploitation outside the sandbox.
Validates or rejects untrusted serialized data before deserialization occurs.
Identifies and blocks malicious code introduced through deserialization of untrusted data at system boundaries.
Integrity verification of serialized information can detect tampering before deserialization occurs.
Provenance of associated data allows detection of untrusted sources before deserialization or processing occurs.
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.
PR.PS-02 addresses only post-deployment updates/patching and cannot prevent introduction of unsafe deserialization code, yet it can remediate some instances when the flaw exists in outdated libraries or components.
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 includes validation of deserialization routines and the use of untrusted data, reducing the likelihood that unsafe object reconstruction will be deployed.
Requiring vetted libraries, regular updates and SAST before release reduces the likelihood that deserialization logic will accept and act on attacker-controlled serialized objects.
Regular scanning of third-party libraries and timely patching reduce the likelihood that unsafe deserialization vulnerabilities remain active.
Mandatory malware scanning of data received over networks or storage media intercepts malicious serialized payloads before they are deserialized by the target application.