Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:HSummary
CVE-2023-24536 is a high-severity Allocation of Resources Without Limits or Throttling (CWE-770) vulnerability in Golang Go. Its CVSS base score is 7.5 (High).
Operationally, ranked in the top 29% of CVEs by exploit likelihood; it is not currently listed in the CISA KEV catalog.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-28552
Vulnerability Data
Multipart form parsing can consume large amounts of CPU and memory when processing form inputs containing very large numbers of parts. This stems from several causes: 1. mime/multipart.Reader.ReadForm limits the total memory a parsed multipart form can consume. ReadForm can…
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undercount the amount of memory consumed, leading it to accept larger inputs than intended. 2. Limiting total memory does not account for increased pressure on the garbage collector from large numbers of small allocations in forms with many parts. 3. ReadForm can allocate a large number of short-lived buffers, further increasing pressure on the garbage collector. The combination of these factors can permit an attacker to cause an program that parses multipart forms to consume large amounts of CPU and memory, potentially resulting in a denial of service. This affects programs that use mime/multipart.Reader.ReadForm, as well as form parsing in the net/http package with the Request methods FormFile, FormValue, ParseMultipartForm, and PostFormValue. With fix, ReadForm now does a better job of estimating the memory consumption of parsed forms, and performs many fewer short-lived allocations. In addition, the fixed mime/multipart.Reader imposes the following limits on the size of parsed forms: 1. Forms parsed with ReadForm may contain no more than 1000 parts. This limit may be adjusted with the environment variable GODEBUG=multipartmaxparts=. 2. Form parts parsed with NextPart and NextRawPart may contain no more than 10,000 header fields. In addition, forms parsed with ReadForm may contain no more than 10,000 header fields across all parts. This limit may be adjusted with the environment variable GODEBUG=multipartmaxheaders=.
- CWE(s)
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 5 hardening rules · 3 OS baselines
V15.4.4
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.
This control implements explicit throttling on session allocation, addressing the weakness of allocating resources without limits.
Plan testing exercises resource allocation limits and throttling during simulated failures, directly addressing weaknesses that allow unbounded resource use.
Contingency plan updates ensure recovery strategies address unbounded resource allocation, making it harder for attackers to exploit lack of throttling to cause prolonged outages.
Provides continuity when unbounded resource allocation at the primary site leads to exhaustion and downtime.
Alternate services allow operations to continue when primary allocation of resources lacks limits or throttling.
Explicit planning of security-related actions requires defining limits, windows, and resource allocations, making allocation without throttling far less likely.
Measures of performance include tracking allocation behavior and throttling effectiveness, reducing the window for resource exhaustion attacks.
Imposes an inactivity-based limit on network resource allocation, throttling the number of concurrently held connections.
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.