Researchers are applying machine learning techniques to crack historical hand-written ciphers used in medieval correspondence, including diplomatic and personal communications. While academically fascinating, this work demonstrates that AI can systematically analyse and break pattern-based encryption schemes that were previously considered too obscure to decode at scale. It highlights the broader capability of AI to accelerate cryptanalysis against weak or legacy cipher designs.

Architect’s Take: No immediate action is required, but this research serves as a timely reminder to audit any legacy or proprietary encryption schemes in your environment — AI-assisted cryptanalysis lowers the bar for breaking non-standard ciphers. Ensure all sensitive data at rest and in transit is protected by modern, well-vetted standards such as AES-256 and TLS 1.3, and avoid reliance on security through obscurity.

Original advisory: AI Used to Decrypt Medieval Ciphers

Researchers are applying machine learning techniques to decode historical hand-written ciphers used in medieval correspondence, including diplomatic and personal communications. Whilst not a direct cybersecurity threat, it demonstrates AI’s growing capability to break encryption schemes that were previously considered uncrackable. This has broader implications for understanding how AI might be applied to attack legacy or weak cryptographic implementations.

Architect’s Take: No immediate action required, but treat this as a signal to audit any legacy or non-standard encryption schemes in your environment — if AI can crack medieval ciphers, weak or deprecated algorithms (e.g. DES, MD5, RC4) are increasingly at risk. Ensure your cryptographic inventory is up to date and aligned with current NCSC guidance.

Original advisory: AI Used to Decrypt Medieval Ciphers

AWS has published guidance on identifying unused KMS encryption keys and protecting them from accidental deletion across large, multi-account environments. Orphaned or forgotten keys can inflate costs, create compliance gaps, and pose a risk if unexpectedly deleted — potentially making encrypted data permanently inaccessible. The post outlines tooling and processes to audit key usage and apply deletion safeguards at scale.

Architect’s Take: Implement regular KMS key usage audits using AWS CloudTrail and CloudWatch metrics, and ensure deletion windows and key policies are configured to prevent accidental removal — particularly in multi-account organisations where key ownership can become unclear over time.

Original advisory: Identify unused AWS KMS keys and prevent accidental key deletions