transilienceai Cryptography
Scope
Practical cryptanalysis for CTF and pentest engagements: identifying when a cryptographic primitive's structure (custom hash, partial leaks, related primes, bad RNG, weak modes) admits a faster-than-brute-force solver, then implementing that solver in pure Python where possible. Covers RSA-style algebraic factoring, lattice/AGCD recovery, GF(2) linear collapse of "complicated-looking" custom ciphers, smooth-order DLP, differential fault attacks, and Shamir-style secret-sharing recovery over non-prime moduli. Always read source first to detect linearity/algebraic structure before reaching for SageMath or symbolic solvers.
When to use
- A challenge or target ships custom crypto (custom hash, custom block cipher, hand-rolled key derivation) and you need to look for affine / GF(2)-linear collapse.
- RSA-style primitives with structured primes (
p = a·r + b,phi(n)perfect square, multi-prime hint files, common factors). - A service exposes a chosen-ciphertext / chosen-input oracle and you suspect padding-oracle, smooth-order DLP, or Bleichenbacher-style recovery.
- AES with fault injection (correct + faulty ciphertext for the same key — Piret-Quisquater DFA).
- Shamir secret sharing or threshold schemes with non-prime moduli (2-adic recovery via Lagrange interpolation with valuation tracking).
References
- reference/lattice-attacks.md — AGCD lattice, discriminant-square factoring, smooth-order DLP, Piret-Quisquater DFA.
- reference/linear-secret-recovery.md — GF(2) affine collapse of custom hashes/ciphers via column-by-column linear recovery.