Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:NCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-30247 is a medium-severity SSRF (CWE-918) vulnerability in Tencent Weknora. Its CVSS base score is 5.9 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 32th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
This vulnerability is AI-related — categorised as LLM Application Platforms; in the Supply Chain and Deployment risk domain.
The strongest mitigations our analysis identified map to AC-4 (Information Flow Enforcement) 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.
CVE-2026-30247 is a Server-Side Request Forgery (SSRF) vulnerability (CWE-918) affecting WeKnora, an LLM-powered framework for deep document understanding and semantic retrieval, in versions prior to 0.2.12. The issue resides in the "Import document via URL" feature, where the backend performs URL validation to block private IPs, loopback addresses, reserved hostnames, and cloud metadata endpoints, but neglects to validate HTTP redirect targets. This allows bypass via redirect chains, and Docker-specific addresses like host.docker.internal are also unblocked. The vulnerability carries a CVSS v3.1 base score of 5.9 (AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:N/A:N).
Any unauthenticated attacker with network access can exploit this by submitting a malicious URL to the import feature that initiates a redirect chain leading to internal services. Exploitation requires high complexity due to crafting effective redirects, but successful attacks enable the server to fetch sensitive internal resources, resulting in high confidentiality impact through unauthorized data access, with no integrity or availability disruption.
The GitHub Security Advisory (GHSA-595m-wc8g-6qgc) confirms the issue has been patched in WeKnora version 0.2.12, recommending immediate upgrades for affected deployments.
As an LLM-powered framework, this SSRF vulnerability highlights risks in AI/ML pipelines where external document ingestion could expose backend infrastructure. No real-world exploitation has been reported.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-10106
Vulnerability Data
WeKnora is an LLM-powered framework designed for deep document understanding and semantic retrieval. Prior to version 0.2.12, the application's "Import document via URL" feature is vulnerable to Server-Side Request Forgery (SSRF) through HTTP redirects. While the backend implements comprehensive URL…
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validation (blocking private IPs, loopback addresses, reserved hostnames, and cloud metadata endpoints), it fails to validate redirect targets. An attacker can bypass all protections by using a redirect chain, forcing the server to access internal services. Additionally, Docker-specific internal addresses like host.docker.internal are not blocked. This issue has been patched in version 0.2.12.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: llm
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.6V1.5.3V5.3.2V10.4.7
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.
Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.
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 development practices directly include input validation and destination allow-listing that prevent SSRF.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
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.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.