Cyber Resilience

CVE-2026-40880

Zfnd Zebra-Consensus ≤ 5.0.2

Published
21 April 2026
Modified
27 April 2026
Patch / advisory
CVSS Score v4 7.2
Click a component to see what it means
Raw vectorCVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:H/VA:H/SC:N/SI:H/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:X
EPSS Score 0.0026 18th percentile
Risk Priority 35 floored blend · peak EPSS

Summary

CVE-2026-40880 is a high-severity Comparison Using Wrong Factors (CWE-1025) vulnerability in Zfnd Zebra-Consensus. Its CVSS base score is 7.2 (High).

Operationally, ranked at the 18th 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-15 (Development Process, Standards, and Tools) — 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-2026-40880 is a logic error in the transaction verification cache of Zebra, a Zcash node written entirely in Rust. The vulnerability affects zebrad versions prior to 4.3.1 and zebra-consensus versions prior to 5.0.2, enabling a consensus split under specific conditions. It has a CVSS v3.1 base score of 8.1 (AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:H) and is associated with CWE-1025.

A malicious miner with low privileges can exploit this vulnerability over the network with low complexity and no user interaction. By submitting a transaction valid for block height H+1 but invalid for H+2, and then mining that transaction into a block at height H+2, the attacker causes vulnerable Zebra nodes to accept the invalid block. This leads to a consensus split, where affected nodes diverge from the rest of the Zcash network, compromising integrity and availability.

The vulnerability is fixed in zebrad version 4.3.1 and zebra-consensus version 5.0.2. Additional details on the issue and mitigation are available in the GitHub Security Advisory at https://github.com/ZcashFoundation/zebra/security/advisories/GHSA-xvj8-ph7x-65gf.

EU & UK References

Vulnerability Data

ZEBRA is a Zcash node written entirely in Rust. Prior to zebrad version 4.3.1 and zebra-consensus version 5.0.2, a logic error in Zebra's transaction verification cache could allow a malicious miner to induce a consensus split. By carefully submitting a…

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transaction that is valid for height H+1 but invalid for H+2 and then mining that transaction in a block at height H+2, a miner could cause vulnerable Zebra nodes to accept an invalid block, leading to a consensus split from the rest of the Zcash network. This vulnerability is fixed in zebrad version 4.3.1 and zebra-consensus version 5.0.2.

CWE(s)

Related Threats

CVEs Like This One

CVE-2026-44498Same product: Zfnd Zebrad
CVE-2026-41583Same product: Zfnd Zebrad
CVE-2026-40881Same product: Zfnd Zebrad
CVE-2026-41585Same product: Zfnd Zebrad
CVE-2026-41584Same product: Zfnd Zebrad
CVE-2026-44497Same product: Zfnd Zebrad
CVE-2026-34377Same product: Zfnd Zebra-Consensus
CVE-2026-44500Same product: Zfnd Zebrad
CVE-2026-34202Same vendor: Zfnd
CVE-2025-2888Shared CWE-1025

Affected Assets

zfnd
zebra-consensus
≤ 5.0.2
zfnd
zebrad
≤ 4.3.1

Mitigating Controls

Mitigating Controls (NIST 800-53 r5) AI

Developer testing and evaluation can discover incorrect comparison logic after implementation but does not stop the flaw from being written.

Requiring a documented development process and tools can embed standards that reduce introduction of erroneous comparison factors.

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.

PR.PS-06 mostly match
prevents

Secure SDLC activities such as code review and logic testing directly prevent incorrect comparison factors in code.

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.

finds

Security testing can detect incorrect comparison results during development and acceptance.

prevents

Secure development lifecycle includes requirements and reviews that can catch incorrect comparison logic.

prevents

Application security requirements can specify correct comparison criteria and validation rules.

prevents

Secure coding standards directly address proper comparison logic and factor selection.

References