Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
-
AccessDiscover internet-exposed R2R search endpoint
-
DeliveryCraft HTTP request with malicious filter key value
-
ExploitSQL predicate injected into WHERE clause without sanitization
-
ExecutionExecute time-based or boolean blind SQLi queries
-
PersistEnumerate database schema and table contents
-
ImpactExfiltrate sensitive application data
Vulnerability Assessment
| Weakness |
CWE
OWASP Top 10:2025
A05:2025 - Injection
ASVS 5.0
V1 - Encoding and Sanitization Parameterized queries, prepared statements
MITRE ATT&CK
2 techniques across 2 tactics: Initial Access, Persistence The technique list with ATT&CK links and the kill-chain view is part of the Basic plan and up. |
| Exploitation Conditions | No special conditions - remote unauthenticated exploitation against default configurations of R2R versions through 3.6.6, targeting the retrieval search endpoint's filter key parameter in the chunks search query. The affected endpoint is a core framework feature requiring no authentication in the default deployment posture. Limiting factors: the attacker must have network reachability to the R2R API port; deployments placed behind an authenticating reverse proxy or API gateway (non-default) block the PR:N attack path. Exploitation is limited to read-only data exfiltration (C:H) - no write access, privilege escalation, or denial-of-service capability is indicated by available data. Both time-based blind and boolean-based blind extraction techniques are explicitly described as viable attack methods. |
| Impact | The CVSS 4.0 vector (AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N, score 8.7) is well-calibrated to the described behavior: unauthenticated network access, no complexity prerequisites, high confidentiality impact, and no integrity or availability impact - accurately reflecting a read-only blind SQLi exfiltration path with no apparent write exploitation. The PR:N designation is explicitly supported by the description's statement of 'unauthenticated attackers.' The public PoC reported by VulnCheck significantly elevates the realistic exploitation likelihood, as it lowers the skill barrier to opportunistic scanning. EPSS data is not provided in input - exploitation probability cannot be independently quantified here. No CISA KEV listing means active widespread exploitation is not confirmed, but the combination of unauthenticated AV:N, AC:L, and a working PoC against a framework that may expose retrieval search endpoints to the internet makes this a genuine priority for any R2R deployment accessible without a preceding authentication layer. The narrow impact (C:H only, no I or A) constrains blast radius to database exfiltration, but RAG databases commonly contain sensitive ingested documents, user data, and application secrets. |
| Exploit ScenarioDerived | An unauthenticated attacker identifies an internet-exposed R2R instance and sends a crafted POST request to the retrieval search endpoint with a manipulated filter key parameter embedding a time-based SQL payload (e.g., appending a conditional SLEEP or pg_sleep call). By measuring response latency differences, the attacker confirms injection and proceeds to enumerate database schema and extract table contents - including ingested RAG document chunks, user records, or stored API credentials - using automated blind SQLi tooling. The publicly available PoC on GitHub issue #2308 confirms this attack path and provides a working reference for exploitation. |
Get an e-mail when this CVE is exploited, patched or re-scored. Free account.
Alert meAnalysisAIv1 – Sep 03, 2026
Unauthenticated SQL injection in SciPhi-AI R2R through version 3.6.6 exposes the application database to blind data exfiltration via the retrieval search endpoint's filter key parameter. The root cause is direct string interpolation of attacker-controlled filter keys into SQL WHERE clauses with no parameterization or escaping, enabling both time-based and boolean-based extraction techniques. A publicly available proof-of-concept exploit exists (VulnCheck, GitHub issue #2308), materially elevating the practical risk beyond the theoretical; no CISA KEV listing at time of analysis.
RemediationAI
Upgrade R2R beyond version 3.6.6 - consult the SciPhi-AI GitHub repository (https://github.com/SciPhi-AI/R2R/issues/2308) and the VulnCheck advisory (https://www.vulncheck.com/advisories/r2r-sql-injection-via-retrieval-search-filter-key) to confirm the specific patched release version, which is not independently confirmed from available data. If immediate upgrade is not feasible, restrict network access to the retrieval search API endpoint at the infrastructure level (firewall rules, API gateway ACLs, reverse-proxy authentication) to prevent unauthenticated external access - this eliminates the unauthenticated AV:N attack path but introduces deployment friction and may break intended public-facing use cases. As a secondary detective and blocking control, deploy a WAF rule targeting SQLi syntax patterns (time-delay keywords, boolean payloads, UNION-based markers) in the filter key parameter; note this is bypassable via obfuscation and should not be treated as a primary mitigation. Server-side, the underlying fix must replace dynamic filter key interpolation with a strict allow-list of permitted column/field names validated before query construction.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in euvd
Checking this CVE against your own stacks and servers is part of the Basic plan and up.
Technical ContextAI · show details
R2R is a Retrieval-Augmented Generation (RAG) framework developed by SciPhi-AI (CPE: cpe:2.3:a:sciphi-ai:r2r:*:*:*:*:*:*:*:*) that provides a managed pipeline for ingesting documents, chunking them, and serving semantic or keyword retrieval queries. CWE-89 (Improper Neutralization of Special Elements in SQL Commands) identifies the root cause: the retrieval search endpoint constructs dynamic SQL WHERE clauses by concatenating user-supplied filter key values directly into the query string rather than using prepared statements or allow-listed identifiers. Because SQL identifiers (column/table names) cannot be bound via standard parameterized query placeholders, frameworks that allow dynamic field selection must implement strict server-side allow-listing - the absence of either parameterization or escaping here leaves the predicate boundary fully attacker-controlled. The affected endpoint is the /chunks search query within the retrieval search surface, which is a core, publicly accessible feature of the framework.
Know when R2R gets its next vulnerability
- Watch products and get an email when something new is published
- Check this CVE against your own stack and servers
- Exploit and PoC references, threat intelligence from 22 sources
No credit card · 7-day full trial
Severity by source
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N
Unauthenticated network SQLi with read-only database exfiltration; S:U as no scope change beyond the application database, I:N and A:N per description.
Primary rating from Vendor (VulnCheck).
CVSS VectorVendor: VulnCheck
DescriptionCVE.org
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.
Technical POC Analysis
The vulnerability is an unauthenticated SQL injection (CWE-89) in SciPhi-AI R2R through 3.6.6.
Full technical POC analysis - root cause, step-by-step exploitation and patch breakdown - is part of the Pro and Business plans.
Latest POC
1 PoC candidate from github (unverified)
Sign in to open the public PoC links collected for this CVE.
Executive ViewAI
SciPhi-AI R2R deployments through version 3.6.6 are vulnerable to unauthenticated database attacks through an SQL injection flaw in the retrieval search endpoint, allowing attackers to extract sensitive data without any credentials. This vulnerability poses an immediate risk to organizations using affected versions, as publicly available exploit code exists and attackers can exfiltrate database contents at scale. Organizations must immediately audit their R2R deployments and implement protective measures to prevent unauthorized data access.
Until a vendor patch is released: deploy Web Application Firewall rules to block SQL injection patterns in the filter key parameter; implement network segmentation to restrict access to the retrieval search endpoint to internal or trusted networks only; enable comprehensive logging and real-time alerting on database query anomalies and unusual data access patterns; enforce strict input validation and prepared statements in application code if code modifications are feasible; implement a database activity monitoring (DAM) solution to detect and block attempted data exfiltration.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
SQL injection exploits the way applications construct database queries by mixing user input directly into SQL statements.
Unauthenticated stacked SQL injection in SciPhi-AI R2R through version 3.6.6 lets remote attackers execute arbitrary SQL
Unauthenticated remote attackers can exploit a server-side request forgery (SSRF) in SciPhi-AI R2R 3.6.6 and earlier by
Hard-coded JWT signing secrets in SciPhi-AI R2R through 3.6.6 can let remote unauthenticated attackers forge valid JSON
Insecure Direct Object Reference in R2R's conversation API through version 3.6.5 enables any authenticated user to modif
EUVD-2026-70701
GHSA-j3pv-p6h2-grgg
NVD
CVE.org
EPSS
Vulnrichment
Exploit-DB