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zebrad has consensus divergence via P2SH sigop undercount in pure-Rust disabled-opcode parser

Critical severity GitHub Reviewed Published May 29, 2026 in ZcashFoundation/zebra • Updated Jul 2, 2026

Package

cargo zebra-script (Rust)

Affected versions

<= 6.0.1

Patched versions

7.0.0
cargo zebrad (Rust)
<= 4.4.1
4.5.0

Description

Am I affected

You are affected if:

  1. You run any version of zebrad up to and including v4.4.1.
  2. Your node validates blocks on mainnet, testnet, or any network where both Zebra and zcashd nodes participate.

All default configurations are affected. No feature flags, non-default settings, or special build options are required.

Summary

Zebra's P2SH sigop counter uses a pure-Rust code path that short-circuits on disabled opcodes (such as OP_CODESEPARATOR), returning a partial count of zero for any sigops following the disabled opcode. The reference implementation (zcashd) correctly counts through disabled opcodes in its static sigop analysis. This produces a consensus divergence: Zebra accepts blocks that zcashd rejects when the block-wide MAX_BLOCK_SIGOPS = 20,000 threshold is crossed on one side but not the other.

An attacker can exploit this without mining capability. Broadcasting transactions that spend P2SH outputs with malicious redeem scripts is sufficient; any Zebra miner who includes those transactions in a block triggers a chain split between Zebra and zcashd validators.

Details

The P2SH sigop counter at zebra-script/src/lib.rs:399 calls script::Code(redeemed_bytes).sig_op_count(true), which is a pure-Rust path through zcash_script-0.4.4. The legacy (non-P2SH) sigop counter at lib.rs:282-289 correctly uses the C++ FFI via interpreter.legacy_sigop_count_script(). Only the P2SH path bypasses the FFI.

The Rust parser in zcash_script-0.4.4/src/opcode/mod.rs:1247-1260 treats 16 disabled opcodes (0x7e through 0xab, including OP_CAT, OP_SUBSTR, OP_AND, OP_OR, OP_XOR, OP_2MUL, OP_2DIV, OP_MUL, OP_DIV, OP_MOD, OP_LSHIFT, OP_RSHIFT, and OP_CODESEPARATOR) as Err(Error::Disabled(...)). The sig_op_count function at iter.rs:104-115 uses try_fold, which terminates on the first Err and returns the partial sum accumulated so far.

zcashd's GetOp2 (script.h:514-562) returns true for all non-push opcodes including the disabled range. Its GetSigOpCount(true) (script.cpp:152-174) continues counting through disabled opcodes. zcashd rejects disabled opcodes at execution time in the interpreter, not during static sigop analysis.

A redeem script of [0xab, OP_CHECKMULTISIG x 50] produces: Zebra = 0 sigops, zcashd = 1,000 sigops. Across 21 inputs in a block, Zebra computes 0 while zcashd computes 21,000, crossing the MAX_BLOCK_SIGOPS = 20,000 threshold on one side only.

Patches

Patched in Zebra 4.4.2. The fix routes the P2SH sigop counter through the same C++ FFI already used by the legacy sigop counter.

Workarounds

There is no configuration-level workaround. All Zebra nodes validating blocks on a network shared with zcashd are affected. Upgrade as soon as the patched version is available.

Impact

A chain split between Zebra and zcashd validators. The attacker broadcasts spending transactions referencing P2SH outputs whose redeem scripts contain a disabled opcode followed by OP_CHECKSIG or OP_CHECKMULTISIG opcodes. When a Zebra miner (estimated ~30% of current network hashrate) includes these transactions in a block, Zebra validators accept the block while zcashd validators reject it with bad-blk-sigops. The two halves of the network diverge and every subsequent block extending the Zebra-side tip inherits the divergence.

The attacker does not need mining capability, RPC access, or any special privileges. The cost is the transaction fees for the funding and spending transactions.

Credit

Reported by @samsulselfut via a private GitHub Security Advisory submission.

References

@mpguerra mpguerra published to ZcashFoundation/zebra May 29, 2026
Published to the GitHub Advisory Database Jul 2, 2026
Reviewed Jul 2, 2026
Last updated Jul 2, 2026

Severity

Critical

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 None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity High
Availability None
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:N/UI:N/VC:N/VI:H/VA:N/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.
(21st percentile)

Weaknesses

Incorrect Provision of Specified Functionality

The code does not function according to its published specifications, potentially leading to incorrect usage. Learn more on MITRE.

CVE ID

CVE-2026-52735

GHSA ID

GHSA-gf9r-m956-97qx

Source code

Credits

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