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Sharks has a Bias of Polynomial Coefficients in Secret SharingGHSA-jp37-5qhw-mffw

GHSA-jp37-5qhw-mffw is a security vulnerability in sharks. The records list no fixed version yet; check the vendor advisory below and apply the mitigations in the meantime.

Also known asRUSTSEC-2024-0398
Published
Updated
Affected
1 pkg
Patched
None yet
Exploits
None indexed
Exploitation data as of Oct 28, 2025 · OSV.dev, FIRST.org (EPSS)

Real-World Exposure

1 pkg affected
🦀sharks

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects crates.io packages — download data is not available via public APIs for these ecosystems.

Description

Affected versions of this crate allowed for a bias when generating random polynomials for Shamir Secret Sharing, where instead of being within the range [0, 255] they were instead in the range [1, 255]. A description from Cure53, who originally found the issue, is available:

The correct method to select a random polynomial would be to select all coefficients (including the most significant coefficient) uniformly in the range 0..255 (inclusive). Otherwise, knowledge that a coefficient in a polynomial cannot be 0 permits the exclusion of single byte values for the shared secret given one share less than required. [...] Exploiting this weakness necessitates sharing the same secret multiple times. In this scenario, an attacker could exclude an exponential number of values for each of the shared bytes until sufficiently few values remain for brute forcing. Cure53 estimates that under ideal circumstances (e.g., a 2-out-of-N scheme) a shared secret can be reconstructed if the same secret has been distributed 500-1500 times.

Secrets that have been shared a low amount of times (ideally, once) would not be impacted. However, secrets that are repeatedly shared may be vulnerable, especially if the shares are still available, and should be rotated.

The vulnerability does not impact reconstitution of secrets: secrets that have already been split can be recombined without issue.

The flaw can be corrected by changing the lower bound of the polynomial coefficient range in the sharks::math::random_polynomial function to 0. The blahaj crate has been made available with a fixed version of the code, after attempts to reach the maintainer of the sharks crate were unsuccessful.

Affected Packages

1 total
EcosystemPackageVulnerable rangeFix
🦀crates.iosharksall versionsNo fix

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for sharks, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Remediation status

    The records we use list no patched version of sharks for GHSA-jp37-5qhw-mffw. Check the maintainer's advisory, and where your build allows, override or pin the dependency away from the vulnerable range.

  3. Mitigate without a patch

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Frequently Asked Questions

Affected versions of this crate allowed for a bias when generating random polynomials for Shamir Secret Sharing, where instead of being within the range `[0, 255]` they were instead in the range `[1, 255]`. A description from Cure53, who originally found the issue, is available: > The correct method to select a random polynomial would be to select all coefficients (including the most significant coefficient) uniformly in the range 0..255 (inclusive). Otherwise, knowledge that a coefficient in a polynomial cannot be 0 permits the exclusion of single byte values for the shared secret given one
O3 Security · Impact-Aware SCA

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Sharks has a Bias of Polynomial Coefficients in Secret…