Raw vector
CVSS:4.0/AV:A/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:L/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:Y/R:A/V:C/RE:M/U:GreenSummary
CVE-2025-52961 is a high-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Juniper Junos Os Evolved. Its CVSS base score is 7.1 (High).
Operationally, ranked at the 37th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
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
- 🇪🇺 ENISA EUVD: EUVD-2025-33401
Vulnerability Data
An Uncontrolled Resource Consumption vulnerability in the Connectivity Fault Management (CFM) daemon and the Connectivity Fault Management Manager (cfmman) of Juniper Networks Junos OS Evolved on PTX10001-36MR, PTX10002-36QDD, PTX10004, PTX10008, PTX10016 allows an unauthenticated, adjacent attacker to cause a Denial-of-Service…
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(DoS). An attacker on an adjacent device sending specific valid traffic can cause cfmd to spike the CPU to 100% and cfmman's memory to leak, eventually to cause the FPC crash and restart. Continued receipt and processes of these specific valid packets will sustain the Denial of Service (DoS) condition. An indicator of compromise is to watch for an increase in cfmman memory rising over time by issuing the following command and evaluating the RSS number. If the RSS is growing into GBs then consider restarting the device to temporarily clear memory. user@device> show system processes node fpc<num> detail | match cfmman Example: show system processes node fpc0 detail | match cfmman F S UID PID PPID PGID SID C PRI NI ADDR SZ WCHAN RSS PSR STIME TTY TIME CMD 4 S root 15204 1 15204 15204 0 80 0 - 90802 - 113652 4 Sep25 ? 00:15:28 /usr/bin/cfmman -p /var/pfe -o -c /usr/conf/cfmman-cfg-active.xml This issue affects Junos OS Evolved on PTX10001-36MR, PTX10002-36QDD, PTX10004, PTX10008, PTX10016: * from 23.2R1-EVO before 23.2R2-S4-EVO, * from 23.4 before 23.4R2-S4-EVO, * from 24.2 before 24.2R2-EVO, * from 24.4 before 24.4R1-S2-EVO, 24.4R2-EVO. This issue does not affect Junos OS Evolved on PTX10001-36MR, PTX10002-36QDD, PTX10004, PTX10008, PTX10016 before 23.2R1-EVO.
- CWE(s)
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly requires mechanisms to protect against or limit the effects of denial-of-service attacks caused by uncontrolled resource consumption from network traffic.
Requires the system to manage and allocate resources so that a single function (cfmd/cfmman) cannot monopolize CPU or memory to the point of FPC failure.
Enables continuous monitoring of process memory (RSS growth) and CPU utilization to identify the cfmman leak and high-CPU condition described in the IoC.
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.
Explicitly requires monitoring and maintaining resource capacity, directly addressing uncontrolled consumption to preserve availability.
Continuous monitoring of computing resources can detect resource exhaustion but does not itself enforce allocation limits.
Resilience mechanisms such as avoiding single points of failure indirectly reduce impact of resource exhaustion.
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.
Resource-utilization monitoring and alerting on bottlenecks or overloads limits the impact of denial-of-service or resource-exhaustion attacks.
By continuously monitoring utilization, stress-testing peak loads, and maintaining documented plans to scale or throttle resources, the control directly limits an attacker’s ability to drive a system into uncontrolled resource exhaustion.
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.
Business-continuity plans that include resource-management controls reduce the likelihood that an attacker can trigger uncontrolled resource consumption by forcing the system into a degraded or fallback state.
Defining RTOs and capacity requirements for ICT services during business-impact analysis forces organizations to provision sufficient resources and throttling mechanisms, reducing the likelihood that an attacker can induce denial-of-service through uncontrolled resource consumption.
Early notification of anomalous resource consumption or system malfunctions enables throttling or isolation before availability is lost.