Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:L/A:LSummary
CVE-2024-48988 is a high-severity SQL Injection: Hibernate (CWE-564) vulnerability in Apache Streampark. Its CVSS base score is 7.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 45th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-54906
Vulnerability Data
SQL Injection vulnerability in Apache StreamPark. This issue affects Apache StreamPark: from 2.1.4 before 2.1.6. Users are recommended to upgrade to version 2.1.6, which fixes the issue. This vulnerability is present only in the distribution package (SpringBoot platform) and does…
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not involve Maven artifacts. It can only be exploited after a user has successfully logged into the platform (implying that the attacker would first need to compromise the login authentication). As a result, the associated risk is considered relatively low.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V6.2.5
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and static analysis can discover dynamic-query construction flaws before deployment.
Input validation directly stops untrusted data from being concatenated into dynamic Hibernate queries.
Requiring documented secure-development standards and tools reduces use of unsafe dynamic SQL patterns.
Secure engineering principles require parameterized queries or ORM-safe APIs instead of string-built SQL.
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 prevent dynamic SQL construction from untrusted input.
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 can detect injection flaws but does not prevent them at design time.
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.
Secure SDLC mandates input validation and ORM usage that reduce dynamic SQL injection risk.
Application security requirements include secure query construction and ORM parameter binding.
Secure architecture principles discourage dynamic SQL but do not directly address Hibernate misuse.