Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:HSummary
CVE-2025-23317 is a critical-severity Heap-based Buffer Overflow (CWE-122) vulnerability in Nvidia Triton Inference Server. Its CVSS base score is 9.1 (Critical).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked in the top 22% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) 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.
NVIDIA Triton Inference Server is affected by a vulnerability in its HTTP server component, tracked as CVE-2025-23317 and assigned CWE-122. The flaw permits an attacker to initiate a reverse shell through a specially crafted HTTP request, which can result in remote code execution, denial of service, data tampering, or information disclosure. The issue carries a CVSS v3.1 score of 9.1, reflecting network attack vector, low complexity, and no required privileges or user interaction.
Unauthenticated remote attackers can exploit the vulnerability over the network by submitting the malicious request to the HTTP server interface. Successful exploitation grants the ability to execute arbitrary code, disrupt service availability, modify data, or access sensitive information on the affected inference server instance.
The EPSS score has remained low, moving only from 0.0488 currently to a peak of 0.0572 with no indication of significant exploitation interest after disclosure.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-23839
Vulnerability Data
NVIDIA Triton Inference Server contains a vulnerability in the HTTP server, where an attacker could start a reverse shell by sending a specially crafted HTTP request. A successful exploit of this vulnerability might lead to remote code execution, denial of…
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service, data tampering, or information disclosure.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.4.1
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation (including fuzzing and memory-error detectors) can discover heap overflows after they have been coded.
Input validation enforces bounds checking on data written to heap buffers, directly stopping the overflow condition from being introduced.
Security engineering principles require use of memory-safe constructs and bounds-checked allocation routines that avoid introducing heap overflows.
Memory-protection mechanisms limit the ability of a heap overflow to execute attacker-controlled code or corrupt adjacent structures.
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 require bounds checking and safe memory handling that prevent heap overflows.
Vulnerability scanning and recording can discover heap-overflow flaws but does not prevent their introduction in code.
Timely patching removes known heap-overflow instances after they exist.
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.
Security testing in development and acceptance can detect heap overflows before release.
Secure development lifecycle mandates practices that reduce the likelihood of introducing heap overflows.
Application security requirements can specify bounds-checking and safe memory APIs that mitigate heap overflows.
Secure architecture and engineering principles include memory-safety and input-validation controls that address heap overflows.
Secure coding standards directly prescribe techniques (safe functions, bounds checks) that prevent heap-based buffer overflows.
Change management ensures controlled deployment of fixes for discovered heap-overflow vulnerabilities.