October 2025 monthly summary for awslabs/s2n-bignum focused on delivering high-value performance and correctness improvements to cryptographic reduction workflows. The key deliverable was an optimized ML-KEM poly_reduce path for x86 AVX2, including assembly-level reduction and formal correctness proofs. The work mirrors the existing mlkem-native implementation to ensure cross-repo consistency and reuse proven approaches. This milestone enhances throughput on AVX2-enabled systems and strengthens cryptographic correctness guarantees, contributing to more reliable TLS crypto workloads.

Month 2025-09 performance summary: Upgraded the aws/aws-lc cryptographic stack with a forward-looking S2N bignum upgrade and corrected a critical ML-DSA sampling bug. The upgrade introduces ARM-specific optimizations, Curve25519 assembly updates, and updated import script with latest CFI directives, improving performance and security posture on ARM platforms. The ML-DSA poly_uniform fix ensures only one SHAKE128 block is squeezed per iteration, preserving sampling integrity and rejection sampling behavior. These changes reduce risk in production cryptographic operations and align with current security standards.

Month: 2025-08. This monthly summary highlights key feature deliveries and reliability improvements across two repositories, focusing on security hardening and performance optimization. Delivered constant-time hardening for ML-DSA polynomial arithmetic in aws/aws-lc, and introduced runtime dispatch for native backends based on CPU capability in pq-code-package/mlkem-c-aarch64. These changes strengthen security posture against timing side-channel attacks and optimize execution by leveraging hardware features while maintaining safe fallbacks.

Monthly work summary for 2025-07 focusing on performance optimization in pq-code-package/mlkem-c-aarch64, delivering AVX2-based assembly implementations for polyvec_basemul and updating related documentation.

Concise monthly summary for May 2025 focusing on delivering business value and technical excellence across two repositories. The month highlights a mix of performance improvements, expanded vector instruction support, and targeted fixes that improved reliability and throughput, with notable impact on cryptographic and polynomial computation workloads.

December 2024 summary for awslabs/s2n-bignum: Focused on label management in assembly to improve uniqueness and readability. Implemented an initial approach to prefix local labels with their file names, then evaluated and reverted to filename-agnostic labels to maintain simplicity and compatibility. This work targeted maintainability, reduced risk of label collisions, and alignment with build tooling expectations.