Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:NSummary
CVE-2026-34577 is a high-severity SSRF (CWE-918) vulnerability in Gitroom Postiz. Its CVSS base score is 8.6 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 39th 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 Privacy and Disclosure 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-2026-34577 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 unauthenticated GET /public/stream endpoint in the PublicController accepts a user-supplied "url" query parameter and proxies the full HTTP response back to the caller. The sole validation checks if the URL ends with ".mp4", which can be easily bypassed by appending ".mp4" to the query parameter value or as a URL fragment.
Unauthenticated attackers can exploit this vulnerability remotely with low complexity and no privileges required, as indicated by the CVSS v3.1 base score of 8.6 (AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N). By crafting a malicious URL that passes the weak validation, attackers can force the server to make requests to arbitrary internal services, cloud metadata endpoints like those on localhost or private IPs, and other network-internal resources, potentially leaking sensitive data through the proxied responses.
The vulnerability has been patched in Postiz version 2.21.3. Security practitioners should upgrade to this version or later. Additional details are available in the GitHub security advisory at https://github.com/gitroomhq/postiz-app/security/advisories/GHSA-mv6h-v3jg-g539 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-2026-18448
Vulnerability Data
Postiz is an AI social media scheduling tool. Prior to version 2.21.3, the GET /public/stream endpoint in PublicController accepts a user-supplied url query parameter and proxies the full HTTP response back to the caller. The only validation is url.endsWith('mp4'), which…
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is trivially bypassable by appending .mp4 as a query parameter value or URL fragment. The endpoint requires no authentication and has no SSRF protections, allowing an unauthenticated attacker to read responses from internal services, cloud metadata endpoints, and other network-internal resources. This issue has been patched in version 2.21.3.
- CWE(s)
AI Security AnalysisAI
- AI Category
- LLM Application Platforms
- Risk Domain
- Privacy and Disclosure
- 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.