Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:H/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:XSummary
CVE-2026-34576 is a high-severity SSRF (CWE-918) vulnerability in Gitroom Postiz. Its CVSS base score is 8.3 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 19th 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 Other 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-2026-34576 is a Server-Side Request Forgery (SSRF) vulnerability, classified under CWE-918, affecting Postiz, an AI-powered social media scheduling tool. In versions prior to 2.21.3, the POST /public/v1/upload-from-url endpoint allows authenticated users to supply a URL that the server fetches via axios.get() without any SSRF protections. The sole validation—a check for image file extensions like .png or .jpg—is easily bypassed by appending such an extension to any URL path.
An authenticated API user with low privileges (PR:L) can exploit this vulnerability remotely (AV:N) with low complexity (AC:L) and no user interaction (UI:N). Successful exploitation enables the attacker to fetch internal network resources, cloud instance metadata, and other internal services. The fetched response data is then uploaded to storage and returned directly to the attacker, resulting in high confidentiality impact (C:H) with a changed scope (S:C), as reflected in the CVSS v3.1 base score of 7.7.
The vulnerability has been patched in Postiz version 2.21.3. Security practitioners should upgrade to this version immediately. Additional details are available in the GitHub security advisory at https://github.com/gitroomhq/postiz-app/security/advisories/GHSA-89vp-m2qw-7v34 and the release notes at https://github.com/gitroomhq/postiz-app/releases/tag/v2.21.3.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-18446
Vulnerability Data
Postiz is an AI social media scheduling tool. Prior to version 2.21.3, the POST /public/v1/upload-from-url endpoint accepts a user-supplied URL and fetches it server-side using axios.get() with no SSRF protections. The only validation is a file extension check (.png, .jpg,…
more
etc.) which is trivially bypassed by appending an image extension to any URL path. An authenticated API user can fetch internal network resources, cloud instance metadata, and other internal services, with the response data uploaded to storage and returned to the attacker. This issue has been patched in version 2.21.3.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other 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.