CVE-2026-82527 (GCVE-0-2026-82527)
Vulnerability from cvelistv5 – Published: 2026-09-03 19:24 – Updated: 2026-09-03 19:24 X_Open Source
VLAI
EPSS
VEX
Title
R2R 3.6.6 SQL Injection via Retrieval Search Filter Key
Summary
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.
Severity
CWE
- CWE-89 - Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')
Assigner
References
2 references
| URL | Tags |
|---|---|
| https://github.com/SciPhi-AI/R2R/issues/2308 | technical-descriptionexploit |
| https://www.vulncheck.com/advisories/r2r-sql-inje… | third-party-advisory |
Impacted products
Date Public
2026-09-01 00:00
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}
}
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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