Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2024-1601 is a critical-severity SQL Injection (CWE-89) vulnerability in Lollms Lollms-Webui. 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 1% 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.
An SQL injection vulnerability exists in the delete_discussion() function of the parisneo/lollms-webui application. The flaw stems from improper neutralization of special elements in SQL commands and is reachable via the /delete_discussion HTTP endpoint, where an attacker-controlled "id" parameter is used directly in database queries against the discussion and message tables.
An unauthenticated remote attacker can submit a crafted POST request containing a malicious payload in the id field. Successful exploitation deletes all records from the discussion and message tables, resulting in complete loss of conversation history and associated data. The issue carries a CVSS 3.1 score of 9.8, reflecting network attack vector, low complexity, and no required privileges or user interaction.
Public references point to a fix merged in commit f0bc8f2babdfd4770a5adbf3b60ec612e4f1db46 on the upstream repository, along with a detailed report published on huntr.com that describes the same injection vector and remediation.
EPSS scores have remained low and stable near 0.05 with no material increase after disclosure.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2024-17342
Vulnerability Data
An SQL injection vulnerability exists in the `delete_discussion()` function of the parisneo/lollms-webui application, allowing an attacker to delete all discussions and message data. The vulnerability is exploitable via a crafted HTTP POST request to the `/delete_discussion` endpoint, which internally calls…
more
the vulnerable `delete_discussion()` function. By sending a specially crafted payload in the 'id' parameter, an attacker can manipulate SQL queries to delete all records from the 'discussion' and 'message' tables. This issue is due to improper neutralization of special elements used in an SQL command.
- 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.