Cyber Resilience

CVE-2025-32392

DoS

Published
18 June 2026
Modified
06 October 2026
CVSS Score v4 8.7
Click a component to see what it means
Raw vectorCVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
EPSS Score 0.0043 35th percentile
Risk Priority 45 floored blend · peak EPSS

CVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.

Summary

CVE-2025-32392 is a high-severity Uncontrolled Resource Consumption (CWE-400) vulnerability. Its CVSS base score is 8.7 (High).

Operationally, ranked at the 35th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.

This vulnerability is AI-related — categorised as LLM Application Platforms.

The strongest mitigations our analysis identified map to SC-5 (Denial-of-service Protection) and SC-6 (Resource Availability) — see the control section below for these in your framework.

EU & UK References

Vulnerability Data

AutoGPT is a workflow automation platform for creating, deploying, and managing continuous artificial intelligence agents. Prior to 0.6.63, AutoGPT's LoopVideoBLock allows users to input a video file and process the video, such as looping it 5 times or extending the…

more

time, and finally writing it to disk. However, there is no limit on the resources that can be allocated during execution. For example, the number of loops is user-controllable and unlimited. When a malicious attacker loops too many times, the generated video is too large, and after writing it to disk, the disk space is exhausted, eventually causing DoS. Version 0.6.63 patches the issue.

CWE(s)

AI Security AnalysisAI

AI Category
LLM Application Platforms
Risk Domain
N/A
OWASP Top 10 for LLMs 2025
None mapped
Classification Reason
Matched keywords: artificial intelligence

Related Threats

CVEs Like This One

CVE-2024-1569Shared CWE-400
CVE-2025-32436Shared CWE-400
CVE-2024-6036Shared CWE-400
CVE-2024-3153Shared CWE-400
CVE-2025-8849Shared CWE-400
CVE-2025-32437Shared CWE-400
CVE-2024-12063Shared CWE-400
CVE-2026-42343Shared CWE-400
CVE-2026-33235Shared CWE-400
CVE-2024-11043Shared CWE-400

Affected Assets

Mitigating Controls

Mitigating Controls (NIST 800-53 r5) AI

SC-5 directly limits the effects of resource-exhaustion events that constitute uncontrolled consumption.

SC-6 enforces explicit allocation limits on resources, structurally preventing the weakness from occurring.

Process isolation confines resource consumption to separate domains, reducing blast radius without stopping the root flaw.

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.

DE.CM-09 partial match
prevents

Continuous monitoring of computing resources can detect resource exhaustion but does not itself enforce allocation limits.

PR.IR-03 partial match
prevents

Resilience mechanisms such as avoiding single points of failure indirectly reduce impact of resource exhaustion.

PR.IR-04 partial match
prevents

Explicitly requires monitoring and maintaining resource capacity, directly addressing uncontrolled consumption to preserve availability.

PR.PS-01 partial match
prevents

Hardened configuration baselines can include resource quotas and limits that constrain consumption.

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.

finds

Pre-agreed severity-based prioritization and resource allocation during incident triage reduce the likelihood that an attacker-induced resource exhaustion will overwhelm the organization before corrective action is taken.

finds

Early notification of anomalous resource consumption or system malfunctions enables throttling or isolation before availability is lost.

A.8.15 Logging partial match
finds

Specifying log storage limits and rotation procedures reduces the risk that unbounded log growth will exhaust disk or memory resources and cause denial of service.

finds

Resource-utilization monitoring and alerting on bottlenecks or overloads limits the impact of denial-of-service or resource-exhaustion attacks.

prevents

A.8.20 implements network-level protections (firewalls, segmentation, protocol hardening, monitoring, authentication of systems/devices) that can limit abuse of a resource-consuming weakness but do not stop the weakness from being exploitable; the flaw remains present in the product and can still be triggered from an authorized or internal context.

prevents

Monitoring network service usage and applying controls to restrict access when necessary limits an attacker’s ability to consume excessive resources through unrestricted or unauthenticated service calls.

References