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-2026-3788 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 NLP and Transformers; 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-2026-3788 is a server-side request forgery (SSRF) vulnerability affecting Bytedesk versions up to 1.3.9. The issue resides in the getModels function within the file source-code/src/main/java/com/bytedesk/ai/springai/providers/openrouter/SpringAIOpenrouterRestService.java, part of the SpringAIOpenrouterRestController component. It allows manipulation of the apiUrl argument, enabling unauthorized requests from the server.
Attackers with low privileges (PR:L) can exploit this remotely (AV:N) with low complexity (AC:L) and no user interaction (UI:N), achieving low impacts on confidentiality, integrity, and availability (C:L/I:L/A:L), for an overall CVSS v3.1 score of 6.3. The vulnerability is associated with CWE-918 and has been publicly disclosed with an exploit available for use.
Mitigation involves upgrading to Bytedesk version 1.4.5.4, which includes the patch commit 975e39e4dd527596987559f56c5f9f973f64eff7. GitHub references, including the Bytedesk repository, the patch commit, and related issues (#20 and comments), provide further details on the fix.
The vulnerability occurs in an AI-related component integrating with OpenRouter via Spring AI, highlighting potential risks in AI service integrations within open-source customer support platforms like Bytedesk. No real-world exploitation in the wild is reported.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-10278
Vulnerability Data
A security vulnerability has been detected in Bytedesk up to 1.3.9. This impacts the function getModels of the file source-code/src/main/java/com/bytedesk/ai/springai/providers/openrouter/SpringAIOpenrouterRestService.java of the component SpringAIOpenrouterRestController. Such manipulation of the argument apiUrl leads to server-side request forgery. The attack may be launched…
more
remotely. The exploit has been disclosed publicly and may be used. Upgrading to version 1.4.5.4 will fix this issue. The name of the patch is 975e39e4dd527596987559f56c5f9f973f64eff7. It is recommended to upgrade the affected component.
- CWE(s)
AI Security AnalysisAI
- AI Category
- NLP and Transformers
- 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.