CVE-2024-10835
SQLi in Dbgpt Db-Gpt 0.6.0
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-10835 is a critical-severity SQL Injection (CWE-89) vulnerability in Dbgpt Db-Gpt. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 38% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Supply Chain and Deployment risk domain.
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-2024-10835 is a critical vulnerability in eosphoros-ai/db-gpt version v0.6.0, where the web API endpoint POST /api/v1/editor/sql/run allows execution of arbitrary SQL queries without any access control. This flaw, classified under CWE-89 (SQL Injection), enables attackers to exploit DuckDB SQL functionality for arbitrary file writes to the victim's file system, potentially escalating to remote code execution (RCE). The issue carries 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), highlighting its severe impact.
Unauthenticated remote attackers can exploit this vulnerability by sending crafted requests to the affected API endpoint, requiring no privileges, low attack complexity, or user interaction. Successful exploitation grants the ability to write arbitrary files anywhere on the file system via DuckDB's SQL capabilities, which can overwrite critical files or configurations, leading to full system compromise through RCE.
Mitigation details and additional technical information are available in the advisory published on Huntr at https://huntr.com/bounties/e32fda74-ca83-431c-8de8-08274ba686c9. The vulnerability was publicly disclosed on 2025-03-20.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-7076
Vulnerability Data
In eosphoros-ai/db-gpt version v0.6.0, the web API `POST /api/v1/editor/sql/run` allows execution of arbitrary SQL queries without any access control. This vulnerability can be exploited by attackers to perform Arbitrary File Write using DuckDB SQL, enabling them to write arbitrary files…
more
to the victim's file system. This can potentially lead to Remote Code Execution (RCE).
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai, gpt
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.