CVE-2025-34021
Published: 20 June 2025
Summary
CVE-2025-34021 is a high-severity Improper Input Validation (CWE-20) vulnerability in Cxsecurity (inferred from references). Its CVSS base score is 7.8 (High).
Operationally, ranked in the top 47.6% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-18779
Vulnerability details
A server-side request forgery (SSRF) vulnerability exists in multiple Selea Targa IP OCR-ANPR camera models, including iZero, Targa 512, Targa 504, Targa Semplice, Targa 704 TKM, Targa 805, Targa 710 INOX, Targa 750, and Targa 704 ILB. The application fails…
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to validate user-supplied input in JSON POST parameters such as ipnotify_address and url, which are used by internal mechanisms to perform image fetch and DNS lookups. This allows remote unauthenticated attackers to induce the system to make arbitrary HTTP requests to internal or external systems, potentially bypassing firewall policies or conducting internal service enumeration. Exploitation evidence was observed by the Shadowserver Foundation on 2025-01-25 UTC.
- CWE(s)
Related Threats
No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.
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.
Directly implements checks on information inputs to reject invalid data before processing.
Penetration testing attempts server-side requests to internal resources, identifying SSRF weaknesses for remediation.
Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.
Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.
Outbound connections to external resources can be monitored and limited at the boundary, reducing SSRF impact.
Detects server-side request forgery through monitoring of unexpected outbound connections.
Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.