Skip to content

Zebra: Cached Mempool Verification Bypasses Consensus Rules for Ahead-of-Tip Blocks

High severity GitHub Reviewed Published Apr 17, 2026 in ZcashFoundation/zebra • Updated Apr 18, 2026

Package

cargo zebra-consensus (Rust)

Affected versions

< 5.0.2

Patched versions

5.0.2
cargo zebrad (Rust)
< 4.3.1
4.3.1

Description

CVE-2026-40880: Cached Mempool Verification Bypasses Consensus Rules for Ahead-of-Tip Blocks

Summary

A logic error in Zebra's transaction verification cache could allow a malicious miner to induce a consensus split. By carefully submitting a 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.

Severity

High - This is a Consensus Vulnerability that could allow a malicious miner to induce network partitioning, service disruption, and potential double-spend attacks against affected nodes.

Affected Versions

All Zebra versions prior to version 4.3.1. (Some older versions are not affected but are no longer supported by the network)

Description

The vulnerability exists due to a performance optimization whose goal is to improve performance of transaction validation if the transaction was previously accepted into the mempool (and thus was verified as valid). That however did not take into account that a transaction can be valid for a specific height, but invalid at higher heights; for example, it can contain an expiry height, a lock time, and it is always bound to a network upgrade, all of which are height-dependant.

An attacker (specifically a malicious miner) could exploit this by (e.g. in the expiry height case):

  • Submitting a transaction with expiry height H+1 (where H is the height of the current tip)
  • Mining a block H+1, and a block H+2 that contains that same transaction, and submitting block H+2 before H+1
  • Zebra nodes would accept H+2 as valid (pending contextual verification) and wait for block H+1; when it arrives, Zebra would commit both blocks even if H+2 contains an expired transaction
  • Other nodes (like zcashd or zebrad nodes without that transaction in their mempool) reject the block, resulting in a chain fork where the poisoned Zebra node is isolated.

Impact

Consensus Failure

Attack Vector: Network (specifically via a malicious miner).
Effect: Network partition/consensus split.
Scope: Any Zebra node utilizing the transaction verification cache optimization for V5 transactions.

Fixed Versions

This issue is fixed in Zebra 4.3.1.

We removed the performance optimization altogether, since we deemed it too risky.

The fix ensures that verification is only skipped if the transaction's full integrity—including authorization data—is validated against the mempool entry.

Mitigation

Users should upgrade to Zebra 4.3.0 or later immediately.

There are no known workarounds for this issue. Immediate upgrade is the only way to ensure the node remains on the correct consensus path and is protected against malicious chain forks.

Credits

Thanks to @sangsoo-osec for a thorough advisory submission that noticed the lock time issue, and to @shieldedonly with an also thorough advisory (that was submitted while we were working on the first one) who noticed that the issue applied to other aspects of the transaction validation.

References

@mpguerra mpguerra published to ZcashFoundation/zebra Apr 17, 2026
Published to the GitHub Advisory Database Apr 18, 2026
Reviewed Apr 18, 2026
Last updated Apr 18, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity High
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity High
Availability High

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:N/VI:H/VA:H/SC:N/SI:H/SA:H

EPSS score

Weaknesses

Comparison Using Wrong Factors

The code performs a comparison between two entities, but the comparison examines the wrong factors or characteristics of the entities, which can lead to incorrect results and resultant weaknesses. Learn more on MITRE.

CVE ID

CVE-2026-40880

GHSA ID

GHSA-xvj8-ph7x-65gf

Source code

Credits

Loading Checking history
See something to contribute? Suggest improvements for this vulnerability.