Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/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-2025-54379 is a high-severity SQL Injection (CWE-89) vulnerability in Lfedge Ekuiper. Its CVSS base score is 8.9 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 48% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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-2025-54379 is a critical SQL injection vulnerability (CWE-89) affecting LF Edge eKuiper, a lightweight IoT data analytics and stream processing engine designed for resource-constrained edge devices. The flaw exists in the getLast API functionality in versions prior to 2.2.1, where attackers can manipulate the table name input in an API request to execute arbitrary SQL statements on the underlying SQLite database. Assigned a CVSS v3.1 base score of 9.8 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H), it was published on 2025-07-24.
Unauthenticated remote attackers can exploit this vulnerability over the network with low complexity and no user interaction required. By crafting malicious requests to the getLast API endpoint, they can inject SQL payloads, potentially leading to data theft, corruption, deletion, or full compromise of the SQLite database storing eKuiper's data.
The vulnerability is fixed in eKuiper version 2.2.1, as detailed in the project's GitHub security advisory (GHSA-526j-mv3p-f4vv) and the corresponding patch commit (72c4918744934deebf04e324ae66933ec089ebd3). Security practitioners should upgrade to 2.2.1 or later and review API exposures on edge deployments.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-22548
Vulnerability Data
LF Edge eKuiper is a lightweight IoT data analytics and stream processing engine running on resource-constraint edge devices. In versions before 2.2.1, there is a critical SQL Injection vulnerability in the getLast API functionality of the eKuiper project. This flaw…
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allows unauthenticated remote attackers to execute arbitrary SQL statements on the underlying SQLite database by manipulating the table name input in an API request. Exploitation can lead to data theft, corruption, or deletion, and full database compromise. This is fixed in version 2.2.1.
- 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 evaluation can discover SQLi flaws before deployment but does not stop their introduction.
Input validation directly stops untrusted data from reaching SQL query construction without neutralization.
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 target injection flaws during coding and review so largely prevent CWE-89 introduction, yet the single broad outcome leaves residual risk from incomplete neutralization techniques or missed edge cases.
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.
The same secure-coding and static-analysis activities surface missing neutralization of SQL metacharacters before the system is accepted.
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-coding rules and security testing phases mandate the use of parameterized queries or equivalent escaping, preventing the construction of dynamic SQL statements from untrusted input.
Language-specific secure coding rules, peer review and SAST together prevent the construction of SQL statements from untrusted data without proper parameterization or escaping.