Cyber Resilience

CVE-2025-23320

High

Published: 06 August 2025

Published
06 August 2025
Modified
12 August 2025
KEV Added
Patch
CVSS Score v3.1 7.5 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N
EPSS Score 0.0027 50.5th percentile
Risk Priority 15 60% EPSS · 20% KEV · 20% CVSS

Summary

CVE-2025-23320 is a high-severity Generation of Error Message Containing Sensitive Information (CWE-209) vulnerability in Nvidia Triton Inference Server. Its CVSS base score is 7.5 (High).

Operationally, ranked in the top 49.5% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.

EU & UK References

Vulnerability details

NVIDIA Triton Inference Server for Windows and Linux contains a vulnerability in the Python backend, where an attacker could cause the shared memory limit to be exceeded by sending a very large request. A successful exploit of this vulnerability might…

more

lead to information disclosure.

CWE(s)

Related Threats

No named actor attribution yet. ATT&CK technique mapping in progress for this CVE.

Affected Assets

nvidia
triton inference server
≤ 25.07

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.

addresses: CWE-209

Detects error messages that leak sensitive information as evidence of disclosure.

addresses: CWE-209

The control directly mitigates generation of error messages containing sensitive authentication details by requiring obscured feedback instead of verbose responses.

addresses: CWE-209

Misdirection allows generation of misleading error messages that withhold or falsify sensitive details.

addresses: CWE-209

Explicitly requires error messages to avoid including sensitive or exploitable details while still supporting corrective action.

addresses: CWE-209

Validation ensures error messages contain only expected, non-sensitive content and blocks leakage via verbose errors.

addresses: CWE-209

Fail-safe procedures can be defined to suppress or sanitize error output, reducing generation of messages that contain sensitive information.

References