CVE-2025-62593
Published: 26 November 2025
Summary
CVE-2025-62593 is a critical-severity Code Injection (CWE-94) vulnerability. Its CVSS base score is 9.4 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Drive-by Compromise (T1189); ranked at the 2.0th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Deep Learning Frameworks; in the Supply Chain and Deployment risk domain.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-199754
Vulnerability details
Ray is an AI compute engine. Prior to version 2.52.0, developers working with Ray as a development tool can be exploited via a critical RCE vulnerability exploitable via Firefox and Safari. This vulnerability is due to an insufficient guard against…
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browser-based attacks, as the current defense uses the User-Agent header starting with the string "Mozilla" as a defense mechanism. This defense is insufficient as the fetch specification allows the User-Agent header to be modified. Combined with a DNS rebinding attack against the browser, and this vulnerability is exploitable against a developer running Ray who inadvertently visits a malicious website, or is served a malicious advertisement (malvertising). This issue has been patched in version 2.52.0.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Deep Learning Frameworks
- 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 RCE vulnerability enables drive-by compromise (T1189) via malicious websites or malvertising using DNS rebinding and User-Agent spoofing, exploiting the Ray development tool through browser interactions for client execution (T1203).
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.
Awareness training educates users on avoiding untrusted links and actions that can be exploited via CSRF.
Requiring user re-entry of credentials for sensitive actions prevents automated forgery of requests without active user participation.
Security testing regimens explicitly include checks for missing or ineffective anti-CSRF protections in web applications.
Makes persistent code injection into loaded programs impossible when the executable image itself resides on hardware-protected read-only media.
Dynamically generated code can be produced and executed inside the isolated chamber, preventing host compromise from code-injection payloads.
Validates inputs used in dynamic code generation to block injected directives.
Directly prevents execution of attacker-supplied code written into data memory regions.
Detects anomalous request patterns consistent with cross-site request forgery.