CVE-2026-82527 in R2R
Summary
by MITRE • 09/03/2026
R2R through 3.6.6 contains a SQL injection vulnerability that allows unauthenticated attackers to inject SQL predicates into the chunks search query by manipulating the filter key parameter in the retrieval search endpoint. Attackers can exploit the direct interpolation of filter keys into the SQL WHERE clause without parameterization or escaping to perform time-based and boolean-based data exfiltration from the application database.
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Analysis
by VulDB Data Team • 09/03/2026
The vulnerability identified within R2R versions through 3.6.6 represents a critical security flaw rooted in improper neutralization of special elements used in an SQL command, commonly categorized under CWE-89 Improper Neutralization of Special Elements used in an SQL Command. This specific instance manifests as a classic injection vector where the application fails to properly validate or sanitize user-supplied input before incorporating it into backend database queries. The flaw is located within the retrieval search endpoint, specifically affecting the chunks search functionality which is designed to filter and retrieve data based on provided criteria. Because this component handles sensitive document retrievals in a Retrieval-Augmented Generation architecture, compromising its integrity poses significant risks to both data confidentiality and system availability.
The technical mechanism of exploitation relies on the direct interpolation of the filter key parameter into the SQL WHERE clause without the use of prepared statements or proper escaping mechanisms. In secure software development practices, user inputs should always be treated as untrusted data that requires strict validation before being used in dynamic query construction. However, in this vulnerable implementation, the application constructs SQL queries by concatenating raw input strings directly into the command structure. This allows an attacker to inject arbitrary SQL predicates by manipulating the filter key parameter. Since the vulnerability exists prior to any authentication checks, it is classified as an unauthenticated attack vector, meaning that no valid credentials are required to initiate exploitation.
From a tactical perspective, this vulnerability aligns with ATT&CK technique T1059 Command and Scripting Interpreter sub-technique SQL Injection, where adversaries use structured query language commands to interact directly with the database backend. The attacker can leverage time-based blind injection techniques by introducing delays into the SQL execution flow, such as using functions like SLEEP or WAITFOR DELAY in Microsoft SQL Server environments. By observing the response times of the application, an adversary can deduce information about the underlying data structure and content bit-by-bit. Alternatively, boolean-based inference attacks allow for data exfiltration by modifying queries to return true or false results based on specific conditions, enabling the extraction of sensitive database contents without triggering obvious error messages that might alert security monitoring systems.
The operational impact of this vulnerability is severe due to its potential for complete data compromise. An unauthenticated attacker can extract confidential information stored in the application database, including potentially proprietary documents, user metadata, or internal configuration details critical to the R2R system's operation. Beyond confidentiality breaches, successful exploitation could lead to unauthorized access control bypasses if the injected SQL alters authentication logic or retrieves administrative credentials. In a Retrieval-Augmented Generation context, this could also facilitate prompt injection attacks indirectly by allowing attackers to manipulate the source documents retrieved for generation tasks, thereby influencing AI outputs with malicious content derived from exfiltrated data.
Mitigation strategies must address both immediate remediation and long-term architectural improvements. The primary fix involves refactoring the database interaction layer to utilize parameterized queries or prepared statements exclusively. This ensures that user input is treated as literal data rather than executable code, effectively neutralizing injection attempts regardless of their content. Additionally, implementing strict input validation on all filter parameters can provide a secondary defense-in-depth measure by rejecting inputs that do not conform to expected formats or character sets. For organizations unable to immediately patch the software, deploying a Web Application Firewall with rules specifically tuned to detect SQL injection patterns in query strings may offer temporary protection against automated exploitation attempts while development teams work on releasing an updated version of R2R beyond 3.6.6 that resolves this critical flaw.