Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N/E:X/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-2026-26286 is a high-severity SSRF (CWE-918) vulnerability in Sillytavern Sillytavern. Its CVSS base score is 7.1 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 27th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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-2026-26286 is a Server-Side Request Forgery (SSRF) vulnerability, classified under CWE-918, affecting SillyTavern, a locally installed user interface for interacting with text generation large language models, image generation engines, and text-to-speech voice models. The issue resides in the asset download endpoint in versions prior to 1.16.0, where insufficient validation allows authenticated users to trigger arbitrary HTTP requests from the server and retrieve the full response body.
An authenticated user with low privileges (PR:L) can exploit this vulnerability remotely (AV:N) with low complexity (AC:L) and no user interaction (UI:N), achieving high confidentiality impact (C:H) through changed scope (S:C) and low integrity impact (I:L), as reflected in its CVSS v3.1 base score of 8.5. Attackers can leverage the SSRF to access internal services, cloud metadata endpoints, and private network resources by crafting malicious requests via the asset download functionality.
The vulnerability was addressed in SillyTavern version 1.16.0 through the addition of a whitelist domain check for asset download requests, which can be reviewed and customized by editing the `whitelistImportDomains` array in the `config.yaml` file. Details are available in the GitHub Security Advisory at https://github.com/SillyTavern/SillyTavern/security/advisories/GHSA-cccp-94vg-j92r.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-8305
Vulnerability Data
SillyTavern is a locally installed user interface that allows users to interact with text generation large language models, image generation engines, and text-to-speech voice models. In versions prior to 1.16.0, a Server-Side Request Forgery (SSRF) vulnerability in the asset download…
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endpoint allows authenticated users to make arbitrary HTTP requests from the server and read the full response body, enabling access to internal services, cloud metadata, and private network resources. The vulnerability has been patched in the version 1.16.0 by introducing a whitelist domain check for asset download requests. It can be reviewed and customized by editing the `whitelistImportDomains` array in the `config.yaml` file.
- CWE(s)
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.