CVE-2026-41585
Zfnd Zebra-Rpc 2.0.0 – 6.0.2
Raw vector
CVSS:4.0/AV:N/AC:L/AT:P/PR:H/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:H/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-2026-41585 is a medium-severity Uncaught Exception (CWE-248) vulnerability in Zfnd Zebra-Rpc. Its CVSS base score is 6.9 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Application or System Exploitation (T1499.004); ranked at the 17th 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 SA-8 (Security and Privacy Engineering Principles) — see the control section below for these in your framework.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-28655
Vulnerability Data
ZEBRA is a Zcash node written entirely in Rust. From zebrad versions 2.2.0 to before 4.3.1 and from zebra-rpc versions 1.0.0-beta.45 to before 6.0.2, a vulnerability in Zebra's JSON-RPC HTTP middleware allows an authenticated RPC client to cause a Zebra…
more
node to crash by disconnecting before the request body is fully received. The node treats the failure to read the HTTP request body as an unrecoverable error and aborts the process instead of returning an error response. This issue has been patched in zebrad version 4.3.1 and zebra-rpc version 6.0.2.
- 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 finds reachable assertions during development.
Security engineering principles include robust exception management to keep the system in a defined state.
Fail-in-known-state reduces the impact when an uncaught exception occurs by preserving a safe condition.
Validating untrusted inputs structurally prevents attacker data from reaching and triggering assertions.
Error handling requirements force structured catching and response to exceptions instead of allowing them to propagate uncaught.
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.
Secure SDLC practices explicitly require structured exception handling to prevent uncaught exceptions from reaching production.
Runtime monitoring of software can detect assertion-triggered crashes as adverse events.
Vulnerability identification processes can discover and record reachable-assertion flaws before deployment.
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.
Security testing can detect uncaught exceptions before production deployment.
Secure development lifecycle includes exception-handling standards that reduce uncaught exceptions.
Application security requirements typically mandate robust error and exception handling.
Secure architecture principles call for centralized, comprehensive exception management.
Secure coding standards directly require catching and handling exceptions to prevent crashes or leaks.