Raw vector
CVSS: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:U/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:XSummary
CVE-2025-69229 is a medium-severity Allocation of Resources Without Limits or Throttling (CWE-770) vulnerability in Aiohttp Aiohttp. Its CVSS base score is 6.6 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Application or System Exploitation (T1499.004); ranked at the 26th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SC-5 (Denial-of-service Protection) and SI-10 (Information Input Validation) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-1043
Vulnerability Data
AIOHTTP is an asynchronous HTTP client/server framework for asyncio and Python. In versions 3.13.2 and below, handling of chunked messages can result in excessive blocking CPU usage when receiving a large number of chunks. If an application makes use of…
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the request.read() method in an endpoint, it may be possible for an attacker to cause the server to spend a moderate amount of blocking CPU time (e.g. 1 second) while processing the request. This could potentially lead to DoS as the server would be unable to handle other requests during that time. This issue is fixed in version 3.13.3.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
CVE enables Endpoint DoS via application exploitation of chunked transfer handling (CWE-770 resource exhaustion).
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly requires protection against DoS via resource exhaustion from unbounded chunked HTTP input.
Enforces validation and limits on incoming request data (chunk count/size) before request.read() processing.
Enables monitoring of CPU usage and anomalous request patterns that indicate chunk-induced blocking.
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.
Monitoring capacity and taking action to maintain availability directly reduces unchecked resource allocation.
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.
Baseline comparison of CPU, memory and bandwidth usage helps surface uncontrolled resource allocations before they cause service degradation.
Capacity projections and elasticity measures ensure that allocation requests are bounded and can be throttled, reducing the window in which an attacker can force unbounded resource reservations.
Defining retention periods and deletion schedules for backup copies prevents indefinite accumulation of data on storage media without corresponding resource-management controls.
Architectural redundancy and automatic failover limit the impact of an attacker who forces excessive allocations, because spare capacity can absorb the load until the primary instance recovers.
Documented incident response procedures that include activation of continuity plans and controlled recovery help ensure that resource consumption triggered by an incident is bounded and managed rather than left unbounded.
Mandating tested continuity procedures that preserve or replace resource-limiting controls prevents an attacker from exploiting the absence of throttling mechanisms during an outage.