Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/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:XSummary
CVE-2026-7223 is a medium-severity SSRF (CWE-918) vulnerability. Its CVSS base score is 5.5 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 20th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
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-2026-7223 is a server-side request forgery (SSRF) vulnerability, classified as CWE-918, affecting BigSweetPotatoStudio HyperChat versions up to 2.0.0-alpha.63. The flaw exists in the fetch function of the file packages/core/src/http/aiProxyMiddleware.mts within the AI Proxy Middleware component, where manipulation of the baseurl argument enables the issue. Published on 2026-04-28, it carries a CVSS v3.1 base score of 7.3 (AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:L), indicating high severity due to its network accessibility and low complexity.
The vulnerability can be exploited remotely by unauthenticated attackers with no user interaction required. By supplying a malicious baseurl argument, attackers can trick the server into initiating arbitrary requests, potentially compromising low levels of confidentiality, integrity, and availability as scored by CVSS.
Advisories note that the project was informed early via GitHub issue #142 (https://github.com/BigSweetPotatoStudio/HyperChat/issues/142) but has not responded. No patches or mitigations are available yet; practitioners should review the repository (https://github.com/BigSweetPotatoStudio/HyperChat/) and VulDB entries (https://vuldb.com/vuln/359823) for updates.
The exploit is publicly available and might be used. The involvement of the AI Proxy Middleware component suggests relevance to AI-integrated chat applications.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-25980
Vulnerability Data
A vulnerability was identified in BigSweetPotatoStudio HyperChat up to 2.0.0-alpha.63. Affected by this issue is the function fetch of the file packages/core/src/http/aiProxyMiddleware.mts of the component AI Proxy Middleware. Such manipulation of the argument baseurl leads to server-side request forgery. The…
more
attack can be launched remotely. The exploit is publicly available and might be used. The project was informed of the problem early through an issue report but has not responded yet.
- 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
—
—
—
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.