Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:L/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:XSummary
CVE-2026-8202 is a medium-severity Allocation of Resources Without Limits or Throttling (CWE-770) vulnerability in Mongodb Mongodb. Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Application or System Exploitation (T1499.004); ranked at the 18th 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 SC-6 (Resource Availability) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-29894
Vulnerability Data
Using a densely populated chars mask and a large input string in the MongoDB aggregation operators $trim, $ltrim, and $rtrim, an authenticated user with aggregation permissions can pin CPU utilization at 100% for an extended period of time. This issue…
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impacts MongoDB Server v7.0 versions prior to 7.0.34, v8.0 versions prior to 8.0.23, v8.2 versions prior to 8.2.9 and v8.3 versions prior to 8.3.2.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise TechniquesAI
Why these techniques?
Direct CPU exhaustion via crafted aggregation input matches application exploitation for endpoint DoS.
Likely ATT&CK TechniquesAI
Techniques this vulnerability likely enables, inferred from its description, weakness type, and attributed-actor tradecraft. Confidence is per-technique.
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
Mitigating Controls (NIST 800-53 r5) AI
Directly requires protection against denial-of-service attacks that exhaust CPU via unbounded resource allocation, matching the $trim/$ltrim/$rtrim algorithmic-complexity attack.
Mandates allocation of finite resources to user processes (aggregation pipelines), preventing the CPU pinning described in CWE-770.
Restricts aggregation permissions to the minimum set of users, reducing the population that can submit the malicious chars-mask + large-string inputs.
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.