Cyber Resilience

CVE-2024-56940

DoS in Learndash 6.7.1

Published
12 February 2025
Modified
13 March 2025
CVSS Score v3.1 7.5
Click a component to see what it means
Raw vectorCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
EPSS Score 0.0056 44th percentile
Risk Priority 58 floored blend · peak EPSS

Summary

CVE-2024-56940 is a high-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Learndash Learndash. Its CVSS base score is 7.5 (High).

Operationally, exploitation aligns with the MITRE ATT&CK technique OS Exhaustion Flood (T1499.001); ranked at the 44th 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.

Deeper analysis AI-assisted summary

Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.

CVE-2024-56940 affects the profile image upload function in LearnDash version 6.7.1, a WordPress learning management system plugin. The vulnerability enables attackers to trigger a Denial of Service (DoS) condition by performing excessive file uploads, leading to uncontrolled resource consumption as indicated by CWE-400. It carries a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H), reflecting high severity due to its potential for significant availability disruption.

Unauthenticated attackers can exploit this vulnerability remotely over the network with low attack complexity and no user interaction required. By uploading excessive files to the profile image function, they can overwhelm server resources, causing the service to become unavailable and impacting legitimate users.

Details on mitigation, including any patches or workarounds, can be found in the referenced GitHub repository at https://github.com/nikolas-ch/CVEs/tree/main/LearnDash_v6.7.1, which documents the issue.

EU & UK References

Vulnerability Data

An issue in the profile image upload function of LearnDash v6.7.1 allows attackers to cause a Denial of Service (DoS) via excessive file uploads.

CWE(s)

Related Threats

MITRE ATT&CK Enterprise Techniques

T1499.001 OS Exhaustion Flood Impact
Adversaries may launch a denial of service (DoS) attack targeting an endpoint's operating system (OS).
T1498 Network Denial of Service Impact
Adversaries may perform Network Denial of Service (DoS) attacks to degrade or block the availability of targeted resources to users.
T1499 Endpoint Denial of Service Impact
Adversaries may perform Endpoint Denial of Service (DoS) attacks to degrade or block the availability of services to users.
T1499.002 Service Exhaustion Flood Impact
Adversaries may target the different network services provided by systems to conduct a denial of service (DoS).
T1499.003 Application Exhaustion Flood Impact
Adversaries may target resource intensive features of applications to cause a denial of service (DoS), denying availability to those applications.
Derived from this CVE’s CWE(s) via the direct CWE→ATT&CK cross-walk.

CVEs Like This One

CVE-2024-56939Same product: Learndash Learndash
CVE-2024-1210Same product: Learndash Learndash
CVE-2024-56938Same product: Learndash Learndash
CVE-2024-1208Same product: Learndash Learndash
CVE-2024-1209Same product: Learndash Learndash
CVE-2023-28777Same product: Learndash Learndash
CVE-2023-3105Same product: Learndash Learndash
CVE-2023-52425Shared CWE-400
CVE-2024-20716Shared CWE-400
CVE-2025-9341Shared CWE-400

Affected Assets

learndash
learndash
6.7.1

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.

PR.IR-04 mostly match
prevents

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

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.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

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

prevents

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.

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.

mitigates

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.

mitigates

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.

finds

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

References