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SP1 V6 Recursion Circuit Row-Count Binding Gap

High severity GitHub Reviewed Published Apr 11, 2026 in succinctlabs/sp1 • Updated Apr 14, 2026

Package

cargo sp1_prover (Rust)

Affected versions

<= 6.0.2

Patched versions

6.1.0
cargo sp1_recursion_circuit (Rust)
<= 6.0.2
6.1.0
cargo sp1_sdk (Rust)
<= 6.0.2
6.1.0

Description

Summary

A soundness vulnerability in the SP1 V6 recursive shard verifier allows a malicious prover to construct a recursive proof from a shard proof that the native verifier would reject.

  • Affected versions: >= 6.0.0, <= 6.0.2
  • Not affected: SP1 V5 (all versions)
  • Severity: High

Details

Background

The recursive shard verifier circuit verifies shard proofs inside a recursive proof. Each shard proof includes a jagged PCS opening, which binds trace-shape metadata into a modified commitment and uses that same shape to evaluate the committed polynomials. These two operations must agree on the committed table heights.

The Bug

In the V6 recursion circuit's jagged verifier, the two checks above are served by separate witnesses: a vector of row counts hashed into the modified commitment (commitment side), and a separate witness of prefix sums derived from row and column counts that drives the jagged polynomial evaluator (evaluation side). The prefix sums are observed within the shard verifier.

The consistency check between these two witnesses was missing in the recursion sub-circuit describing the jagged PCS verifier. A malicious prover can therefore supply one trace shape for commitment binding and a different shape for polynomial evaluation.

Potential Impact

The vulnerability applies to both main trace and preprocessed trace metadata. Because preprocessed traces encode circuit structure (selectors, fixed columns, permutation layout), the potential impact extends beyond data forgery to misrepresentation of the circuit itself.

While a demonstration of a full exploit proving arbitrary statements has not been created — since modifying one table's layout incidentally constrains changes to related tables — this barrier is not by design and should not be relied upon. This is considered a soundness violation that is unacceptable regardless of current exploitability.

Why the Native Verifier Is Not Affected

The native shard verifier uses a single jagged PCS verifier object where row counts and evaluation layout are derived from the same data, so the split-witness divergence cannot occur. The recursion circuit's shard-level checks (prefix-sum and total-area assertions) only constrain the evaluation-side parameters, not the commitment-side row counts, so they do not catch the gap.

Mitigation

The fix adds a post-evaluation consistency constraint in the recursive jagged verifier. After the jagged evaluation returns the prefix-sum values derived from the evaluation layout, the circuit reconstructs expected prefix sums from the commitment-side row counts (repeating each row count by its corresponding column count and accumulating). It then asserts element-wise equality between the reconstructed and returned prefix sums, and verifies that the final accumulated area matches the total area from the evaluation parameters.

This forces both witnesses to describe the same trace geometry. Any divergence is now a constraint failure.

Credit

This vulnerability was identified through the SP1 bug bounty program on Code4rena.

References

@tamirhemo tamirhemo published to succinctlabs/sp1 Apr 11, 2026
Published to the GitHub Advisory Database Apr 14, 2026
Reviewed Apr 14, 2026
Last updated Apr 14, 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 High
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 None

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:H/AT:N/PR:N/UI:N/VC:N/VI:H/VA:N/SC:N/SI:H/SA:N

EPSS score

Weaknesses

Insufficient Verification of Data Authenticity

The product does not sufficiently verify the origin or authenticity of data, in a way that causes it to accept invalid data. Learn more on MITRE.

Improper Validation of Integrity Check Value

The product does not validate or incorrectly validates the integrity check values or checksums of a message. This may prevent it from detecting if the data has been modified or corrupted in transmission. Learn more on MITRE.

CVE ID

CVE-2026-40323

GHSA ID

GHSA-63x8-x938-vx33

Source code

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