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Zebra has a Consensus Failure due to Improper Verification of V5 Transactions

High severity GitHub Reviewed Published Mar 27, 2026 in ZcashFoundation/zebra • Updated Apr 9, 2026

Package

cargo zebra-consensus (Rust)

Affected versions

< 5.0.1

Patched versions

5.0.1
cargo zebrad (Rust)
< 4.3.0
4.3.0

Description


CVE-2026-34377: Consensus Failure via Crafted V5 Authorization Data

Summary

A logic error in Zebra's transaction verification cache could allow a malicious miner to induce a consensus split. By matching a valid transaction's txid while providing invalid authorization data, a miner could cause vulnerable Zebra nodes to accept an invalid block, leading to a consensus split from the rest of the Zcash network. To be clear, this would not allow invalid transactions to be accepted but could result in a consensus split between vulnerable Zebra nodes and invulnerable Zebra and Zcashd nodes.

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 supporting V5 transactions (Network Upgrade 5 and later) prior to version 4.3.0.

Description

The vulnerability exists in the find_verified_unmined_tx function within transaction.rs. This function was designed to optimize block verification by checking if a transaction was already verified in the mempool.

The lookup mechanism used the ZIP-244 txid as the unique key. However, for V5 transactions, the txid specifically excludes the Authorization Data Root (signatures and proofs). Because Zebra returned a "verified" status based solely on the txid, it skipped the essential check_v5_auth() call for the transaction version provided in the block.

An attacker (specifically a malicious miner) could exploit this by:

  1. Observing a valid V5 transaction broadcast to the network and entering a Zebra node's mempool.
  2. Creating a block containing a modified version of that transaction. The modified version has the same txid but contains invalid signatures or proofs.
  3. The affected Zebra node identifies the txid in its mempool and incorrectly assumes the block's version of the transaction is already verified.
  4. The node commits the block with the invalid transaction data.
  5. Other nodes (like zcashd or zebra 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 4.3.0.

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.

Resources


References

@alchemydc alchemydc published to ZcashFoundation/zebra Mar 27, 2026
Published to the GitHub Advisory Database Mar 30, 2026
Reviewed Mar 30, 2026
Published by the National Vulnerability Database Mar 31, 2026
Last updated Apr 9, 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 None
Privileges Required High
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:N/PR:H/UI:N/VC:N/VI:H/VA:H/SC:N/SI:H/SA:H

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(5th percentile)

Weaknesses

Improper Verification of Cryptographic Signature

The product does not verify, or incorrectly verifies, the cryptographic signature for data. Learn more on MITRE.

CVE ID

CVE-2026-34377

GHSA ID

GHSA-3vmh-33xr-9cqh

Source code

Credits

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