Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HSummary
CVE-2023-24580 is a high-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Djangoproject Django. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique OS Exhaustion Flood (T1499.001); ranked in the top 0.9% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
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-2023-24580 affects the Multipart Request Parser in Django versions 3.2 before 3.2.18, 4.0 before 4.0.10, and 4.1 before 4.1.7. The flaw stems from insufficient limits on multipart form inputs, such as an excessive number of parts, which can trigger uncontrolled resource consumption under CWE-400 and lead to either exhaustion of available file descriptors or memory depletion.
Unauthenticated remote attackers can exploit the issue over the network by submitting specially crafted multipart requests to any Django application endpoint that processes forms. Successful exploitation results in denial of service through resource exhaustion, with no impact on confidentiality or integrity, consistent with the CVSS 7.5 rating.
Django security advisories and the associated release notes direct users to upgrade to the patched versions 3.2.18, 4.0.10, or 4.1.7, which introduce stricter parsing limits. Corresponding package updates have been issued through distribution channels such as Debian LTS and Fedora.
EPSS scores for the CVE rose from lower values to a recorded peak of 0.2541 before receding to the current 0.1967, indicating a period of increased exploitation interest after disclosure. No confirmed reports of in-the-wild exploitation appear in the referenced advisories.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-0067
Vulnerability Data
An issue was discovered in the Multipart Request Parser in Django 3.2 before 3.2.18, 4.0 before 4.0.10, and 4.1 before 4.1.7. Passing certain inputs (e.g., an excessive number of parts) to multipart forms could result in too many open files…
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or memory exhaustion, and provided a potential vector for a denial-of-service attack.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Limiting concurrent sessions directly prevents uncontrolled resource consumption by capping the number of active sessions per user or account.
Analysis identifies uncontrolled resource consumption indicative of denial-of-service or abuse attempts.
Contingency plan testing includes resource exhaustion scenarios to verify recovery, making it harder for attackers to sustain exploits that cause uncontrolled consumption.
Updated contingency plans include current procedures to detect, contain, and recover from resource exhaustion, limiting an attacker's ability to sustain impact from uncontrolled consumption.
Alternate site allows resumption of operations if resource exhaustion at the primary site is exploited to cause unavailability.
Alternate telecommunications services enable resumption of essential functions when primary services become unavailable due to uncontrolled resource consumption.
The team can analyze and respond to resource exhaustion incidents, reducing the impact of attacks that exploit uncontrolled consumption weaknesses.
Timely maintenance support and spare parts enable rapid recovery from failures induced by uncontrolled resource consumption, shortening the impact window of denial-of-service attacks.
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.