Raw vector
CVSS:4.0/AV:A/AC:L/AT:N/PR:L/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-2025-2811 is a medium-severity Uncontrolled Resource Consumption (CWE-400) vulnerability in Gl Inet (inferred from references). Its CVSS base score is 6.9 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Endpoint Denial of Service (T1499); ranked at the 32th 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 SA-11 (Developer Testing and Evaluation) and SC-5 (Denial-of-service Protection) — see the control section below for these in your framework.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-12487
Vulnerability Data
A vulnerability was found in GL.iNet GL-A1300 Slate Plus, GL-AR300M16 Shadow, GL-AR300M Shadow, GL-AR750 Creta, GL-AR750S-EXT Slate, GL-AX1800 Flint, GL-AXT1800 Slate AX, GL-B1300 Convexa-B, GL-B3000 Marble, GL-BE3600 Slate 7, GL-E750, GL-E750V2 Mudi, GL-MT300N-V2 Mango, GL-MT1300 Beryl, GL-MT2500 Brume 2, GL-MT3000…
more
Beryl AX, GL-MT6000 Flint 2, GL-SFT1200 Opal, GL-X300B Collie, GL-X750 Spitz, GL-X3000 Spitz AX, GL-XE300 Puli and GL-XE3000 Puli AX 4.x. It has been declared as problematic. This vulnerability affects unknown code of the component API. The manipulation leads to inefficient regular expression complexity. It is recommended to upgrade the affected component.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation can discover inefficient regex patterns via performance or static analysis.
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.
Development standards and tools can require safe regex construction and forbid known exponential patterns.
Process isolation confines resource consumption to separate domains, reducing blast radius without stopping the root flaw.
Input validation can constrain data that would otherwise trigger worst-case regex complexity.
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 directly prevent inefficient regex via reviews, static analysis, and safe libraries.
Continuous monitoring of computing resources can detect resource exhaustion but does not itself enforce allocation limits.
Vulnerability identification processes can discover ReDoS issues in existing code but do not stop their introduction.
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 detect and reject regex patterns with exponential worst-case 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.