Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:LSummary
CVE-2026-34230 is a medium-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Rack Rack. Its CVSS base score is 5.3 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique OS Exhaustion Flood (T1499.001); ranked at the 36th 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-2026-34230 affects Rack, a modular Ruby web server interface, in versions prior to 2.2.23, 3.1.21, and 3.2.6. The vulnerability resides in the Rack::Utils.select_best_encoding method, which processes Accept-Encoding HTTP header values with quadratic time complexity when the header includes many wildcard (*) entries. This flaw impacts applications using the Rack::Deflater middleware, as the method is invoked to select the optimal response encoding during compression.
An unauthenticated remote attacker can exploit this vulnerability by sending a single HTTP request with a crafted Accept-Encoding header containing numerous wildcard entries. The quadratic processing leads to disproportionate CPU consumption on the server-side compression path, enabling a denial-of-service condition that degrades application availability. The issue carries a CVSS v3.1 base score of 5.3 (AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L) and is associated with CWE-400 (Uncontrolled Resource Consumption) and CWE-407 (Algorithmic Complexity).
The vulnerability has been patched in Rack versions 2.2.23, 3.1.21, and 3.2.6. Security practitioners should upgrade affected applications to these fixed releases. Additional details on the advisory and patch are available at https://github.com/rack/rack/security/advisories/GHSA-v569-hp3g-36wr.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-18378
Vulnerability Data
Rack is a modular Ruby web server interface. Prior to versions 2.2.23, 3.1.21, and 3.2.6, Rack::Utils.select_best_encoding processes Accept-Encoding values with quadratic time complexity when the header contains many wildcard (*) entries. Because this method is used by Rack::Deflater to choose…
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a response encoding, an unauthenticated attacker can send a single request with a crafted Accept-Encoding header and cause disproportionate CPU consumption on the compression middleware path. This results in a denial of service condition for applications using Rack::Deflater. This issue has been patched in versions 2.2.23, 3.1.21, and 3.2.6.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.2.9
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.
Secure SDLC practices (code review, complexity analysis, safe algorithm selection) prevent introduction of exploitable worst-case behavior.
Continuous monitoring of computing resources can detect resource exhaustion but does not itself enforce allocation limits.
Identifying and recording algorithmic-complexity vulnerabilities directly addresses the root cause before exploitation.
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 can uncover performance issues stemming from algorithmic complexity.
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.