Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:NSummary
CVE-2026-54350 is a critical-severity SQL Injection (CWE-89) vulnerability in Budibase Budibase. Its CVSS base score is 10.0 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 38th percentile by exploit likelihood (below the median); 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.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-39914
Vulnerability Data
Budibase is an open-source low-code platform. Prior to 3.39.12, an unauthenticated visitor of any published Budibase app reads every document of the backing MongoDB, CouchDB, Elasticsearch, DynamoDB-PartiQL, or REST-with-JSON-body collection and, where the builder has published a PUBLIC write query,…
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modifies every document of that collection with one HTTP request. enrichContext at packages/server/src/sdk/workspace/queries/queries.ts:121-138 substitutes parameter values into the raw JSON body of a query, then JSON.parses the result. The validator validateQueryInputs at packages/server/src/api/controllers/query/index.ts:61-71 rejects only Handlebars markers ({{, }}) in user input and does not escape JSON metacharacters (", \, }). A parameter value containing a closing quote and additional keys lifts attacker-controlled fields into the parsed filter object. For Mongo find, the parsed filter passes directly to collection.find() (packages/server/src/integrations/mongodb.ts:506-510). Duplicate-key JSON parsing overrides the builder's {name: "..."} with {name: {$exists: true}} and returns every document. The same primitive against an updateMany query (mongodb.ts:577-585) widens the filter scope to the full collection while the builder-controlled $set body runs against every matched document. The authorized middleware at packages/server/src/middleware/authorized.ts:141-148 short-circuits when the query's role is PUBLIC. CSRF is not enforced on this path. POST /api/v2/queries/:queryId (packages/server/src/api/routes/query.ts:63) accepts the call with no session, only an x-budibase-app-id header that is public from the published-app URL. This vulnerability is fixed in 3.39.12.
- 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.
Application security requirements explicitly call for controls against injection and improper query construction.
Secure architecture principles reduce the likelihood of query-logic flaws but do not prescribe the specific coding practice.