Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:HSummary
CVE-2025-22952 is a critical-severity SSRF (CWE-918) vulnerability in Usememos Memos. Its CVSS base score is 9.8 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked in the top 15% of CVEs by exploit likelihood; 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.
elestio memos v0.23.0 is vulnerable to server-side request forgery because of insufficient validation of user-supplied URLs. The affected component is the open-source memos application hosted at elest.io and maintained in the usememos/memos GitHub repository, and the flaw is tracked as CWE-918 with a CVSS 3.1 score of 9.8.
An unauthenticated remote attacker can supply crafted URLs to trigger SSRF requests, enabling arbitrary interaction with internal or external resources and resulting in high impact to confidentiality, integrity, and availability. The published EPSS score stands at 0.2794 with a recorded peak of 0.3498.
References point to the project repository, an open issue, and a pull request that address the flaw, though no explicit mitigation guidance is provided in the available sources.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-5566
Vulnerability Data
elestio memos v0.23.0 is vulnerable to Server-Side Request Forgery (SSRF) due to insufficient validation of user-supplied URLs, which can be exploited to perform SSRF attacks.
- 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.
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.