CVE-2025-53641
Published: 11 July 2025
Summary
CVE-2025-53641 is a high-severity SSRF (CWE-918) vulnerability. Its CVSS base score is 8.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 49.4th 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.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-21168
Vulnerability details
Postiz is an AI social media scheduling tool. From 1.45.1 to 1.62.3, the Postiz frontend application allows an attacker to inject arbitrary HTTP headers into the middleware pipeline. This flaw enables a server-side request forgery (SSRF) condition, which can be…
more
exploited to initiate unauthorized outbound requests from the server hosting the Postiz application. This vulnerability is fixed in 1.62.3.
- 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 TechniquesAI
Why these techniques?
The SSRF vulnerability in the public-facing Postiz frontend via HTTP header injection enables exploitation of public-facing applications (T1190) and facilitates network service discovery (T1046) through unauthorized outbound requests to internal network resources.
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Penetration testing attempts server-side requests to internal resources, identifying SSRF weaknesses for remediation.
Outbound connections to external resources can be monitored and limited at the boundary, reducing SSRF impact.
Validates server-side URLs and resource references to block SSRF attempts.
Detects server-side request forgery through monitoring of unexpected outbound connections.