Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/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-2026-31958 is a high-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Tornadoweb Tornado. Its CVSS base score is 8.7 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique OS Exhaustion Flood (T1499.001); ranked at the 30th 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-2026-31958 is a denial-of-service vulnerability in Tornado, a Python web framework and asynchronous networking library, affecting versions prior to 6.5.5. The issue arises because there is no dedicated limit on the number of parts in multipart/form-data requests beyond the max_body_size setting, which defaults to 100MB. Parsing of these multipart bodies occurs synchronously on the main thread, resulting in high computational costs when processing large bodies with many parts, as documented in CWE-400 (Uncontrolled Resource Consumption).
The vulnerability 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), indicating it is exploitable remotely over the network by unauthenticated attackers with low complexity and no user interaction. An attacker can send a crafted multipart/form-data request containing numerous parts while staying within the body size limit, forcing the server to expend excessive resources on synchronous parsing and causing denial of service through CPU exhaustion on the main thread.
Tornado version 6.5.5 resolves this vulnerability. Security advisories recommend upgrading to 6.5.5 or later. Key references include the GitHub security advisory at https://github.com/tornadoweb/tornado/security/advisories/GHSA-qjxf-f2mg-c6mc and the Debian LTS announcement at https://lists.debian.org/debian-lts-announce/2026/04/msg00000.html.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-11323
Vulnerability Data
Tornado is a Python web framework and asynchronous networking library. In versions of Tornado prior to 6.5.5, the only limit on the number of parts in multipart/form-data is the max_body_size setting (default 100MB). Since parsing occurs synchronously on the main…
more
thread, this creates the possibility of denial-of-service due to the cost of parsing very large multipart bodies with many parts. This vulnerability is fixed in 6.5.5.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
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.
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.