CVE-2024-47074
Published: 11 October 2024
Summary
CVE-2024-47074 is a critical-severity Deserialization of Untrusted Data (CWE-502) vulnerability in Dataease Dataease. Its CVSS base score is 9.3 (Critical).
Operationally, ranked in the top 22.7% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-42262
Vulnerability details
DataEase is an open source data visualization analysis tool. In Dataease, the PostgreSQL data source in the data source function can customize the JDBC connection parameters and the PG server target to be connected. In backend/src/main/java/io/dataease/provider/datasource/JdbcProvider.java, PgConfiguration class don't filter…
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any parameters, directly concat user input. So, if the attacker adds some parameters in JDBC url, and connect to evil PG server, the attacker can trigger the PG jdbc deserialization vulnerability, and eventually the attacker can execute through the deserialization vulnerability system commands and obtain server privileges. The vulnerability has been fixed in v1.18.25.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
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.