CVE-2026-24783
Script3 Soroban-Fixed-Point-Math 1.3.0 … 1.4.0
Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:NSummary
CVE-2026-24783 is a high-severity Incorrect Calculation (CWE-682) vulnerability in Script3 Soroban-Fixed-Point-Math. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploitation for Privilege Escalation (T1068); ranked at the 30th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
The strongest mitigations our analysis identified map to SA-11 (Developer Testing and Evaluation) and SA-15 (Development Process, Standards, and Tools) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2026-24783 affects the soroban-fixed-point-math library, a fixed-point math implementation for Soroban smart contracts, specifically in versions 1.3.0 and 1.4.0. The vulnerability resides in the mulDiv(x, y, z) function, which incorrectly handles cases where both the intermediate product x*y and the divisor z are negative. The function assumes a negative intermediate product implies a negative final result, ignoring z's sign and causing rounding in the wrong direction. This issue impacts fixed_div_floor and fixed_div_ceil functions, which commonly pass non-constant divisors to mulDiv, and extends to all signed FixedPoint and SorobanFixedPoint types, including i64, i128, and I256 implementations.
The vulnerability carries a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N), indicating network-accessible exploitation with low complexity, no privileges or user interaction required. Attackers can exploit it by interacting with affected Soroban smart contracts that invoke the flawed mulDiv logic, supplying negative inputs to trigger incorrect rounding in division operations. This leads to high integrity impacts, such as erroneous fixed-point arithmetic that could manipulate contract balances, computations, or logic in financial or DeFi applications relying on precise math.
Patches are available in soroban-fixed-point-math versions 1.3.1 and 1.4.1, as detailed in the GitHub security advisory (GHSA-x5m4-43jf-hh65), release notes, and the fixing commit (c9233f7094198a49ed66a4d75786a8a3755c936a). No workarounds exist, so security practitioners should urge immediate upgrades for deployments using vulnerable versions.
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-4710
Vulnerability Data
soroban-fixed-point-math is a fixed-point math library for Soroban smart contacts. In versions 1.3.0 and 1.4.0, the `mulDiv(x, y, z)` function incorrectly handled cases where both the intermediate product $x * y$ and the divisor $z$ were negative. The logic assumed…
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that if the intermediate product was negative, the final result must also be negative, neglecting the sign of $z$. This resulted in rounding being applied in the wrong direction for cases where both $x * y$ and $z$ were negative. The functions most at risk are `fixed_div_floor` and `fixed_div_ceil`, as they often use non-constant numbers as the divisor $z$ in `mulDiv`. This error is present in all signed `FixedPoint` and `SorobanFixedPoint` implementations, including `i64`, `i128`, and `I256`. Versions 1.3.1 and 1.4.1 contain a patch. No known workarounds for this issue are available.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V15.2.2
Mitigating Controls (NIST 800-53 r5) AI
Developer testing and evaluation directly exercises calculations and can discover incorrect or unintended results used in security decisions.
Requiring documented development processes and standards can enforce coding rules and tool usage that reduce introduction of calculation errors.
Engineering principles applied during design and implementation can require verified algorithms and safe arithmetic that structurally avoid incorrect calculation results.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure SDLC practices directly prevent incorrect calculations via reviews, testing, and verification in security-critical code.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development and acceptance can detect calculation flaws before deployment.
Secure development lifecycle mandates verification steps that catch incorrect calculations before they reach production.
Application security requirements can explicitly call for numeric accuracy and bounds checking.
Secure architecture principles include input validation and safe arithmetic design that reduce calculation errors.
Secure coding standards directly prohibit unsafe arithmetic and require defensive checks against incorrect results.