Raw vector
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:N/I:N/A:LCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2023-39180 is a medium-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Linux Linux Kernel. Its CVSS base score is 4.0 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique OS Exhaustion Flood (T1499.001); ranked in the top 29% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SC-5 (Denial-of-service Protection) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-42915
Vulnerability Data
A flaw was found within the handling of SMB2_READ commands in the kernel ksmbd module. The issue results from not releasing memory after its effective lifetime. An attacker can leverage this to create a denial-of-service condition on affected installations of…
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Linux. Authentication is not required to exploit this vulnerability, but only systems with ksmbd enabled are vulnerable.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation directly finds out-of-bounds read flaws through static analysis, fuzzing, and dynamic bounds checks.
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.
Secure engineering principles require bounds checking and memory-safe constructs that stop out-of-bounds reads from being introduced.
Process isolation confines resource consumption to separate domains, reducing blast radius without stopping the root flaw.
Input validation rejects malformed indices or lengths that would otherwise cause reads outside buffer bounds.
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.
Secure-development practices such as bounds checking and memory-safe languages directly prevent out-of-bounds reads.
Continuous monitoring of computing resources can detect resource exhaustion but does not itself enforce allocation limits.
Vulnerability scanning and recording can discover instances of out-of-bounds reads after code is deployed.
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.
Security testing in development and acceptance includes fuzzing and static analysis that detect out-of-bounds read defects before release.
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.