Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-3789 is a medium-severity SSRF (CWE-918) vulnerability in Bytedesk Bytedesk. Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 35th 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-2026-3789 is a server-side request forgery (SSRF) vulnerability, classified as CWE-918, affecting Bytedesk versions up to 1.3.9. The flaw exists in the getModels function of the file source-code/src/main/java/com/bytedesk/ai/springai/providers/gitee/SpringAIGiteeRestService.java within the SpringAIGiteeRestController component. Published on 2026-03-09, it carries a CVSS v3.1 base score of 6.3 (AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:L/A:L).
The vulnerability enables remote exploitation through manipulation of the apiUrl argument. Low-privileged remote attackers (PR:L) can trigger SSRF without user interaction, potentially achieving low-level impacts on confidentiality, integrity, and availability.
Advisories recommend upgrading to Bytedesk version 1.4.5.4, which resolves the issue via patch commit 975e39e4dd527596987559f56c5f9f973f64eff7. Upgrading the affected component is advised, as the exploit is now public and may be used.
The vulnerable component relates to Bytedesk's AI integration using SpringAI and the Gitee provider, with details available in the project's GitHub repository, including issues #21 and the referenced commit.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-10279
Vulnerability Data
A vulnerability was detected in Bytedesk up to 1.3.9. Affected is the function getModels of the file source-code/src/main/java/com/bytedesk/ai/springai/providers/gitee/SpringAIGiteeRestService.java of the component SpringAIGiteeRestController. Performing a manipulation of the argument apiUrl results in server-side request forgery. Remote exploitation of the attack is…
more
possible. The exploit is now public and may be used. Upgrading to version 1.4.5.4 is able to address this issue. The patch is named 975e39e4dd527596987559f56c5f9f973f64eff7. Upgrading the affected component is advised.
- 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: ai
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.