cryptography

Name: cryptography
Author: transilienceai

github.com/transilienceaiSecurity598151 installsUpdated 13w ago

About cryptography

cryptography is a security skill for practical cryptanalysis in CTF and penetration-testing engagements. It focuses on finding algebraic or linear structure that enables faster-than-brute-force recovery, and implementing solvers in Python where possible.

Key features

01Custom cipher and hash analysis
02RSA factoring and lattice recovery
03Smooth-order discrete-log attacks
04Differential fault analysis
05Secret recovery over non-prime moduli

Use cases

01Analyzing custom cryptographic challenges
02Recovering RSA secrets from structured primes
03Using chosen-input oracles to test attack paths
04Recovering keys from faulty AES ciphertexts

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/transilienceai/communitytools --skill cryptography

After installing, type/cryptographyin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

reference/

cryptography-principles.md

INDEX.md

lattice-attacks.md

linear-secret-recovery.md

reference/scenarios/classical/

repeating-key-xor.md

reference/scenarios/lattice/

agcd-attack.md

boneh-durfee-low-d.md

coppersmith-known-bits.md

lll-basis-reduction.md

reference/scenarios/padding-oracle/

cbc-padding-oracle.md

ecb-prefix-oracle.md

pkcs1-v1.5-bleichenbacher.md

reference/scenarios/rsa-quirks/

common-modulus.md

fermat-close-primes.md

low-public-exponent.md

small-prime-factorization.md

wiener-attack.md

reference/scenarios/secret-sharing/

shamir-non-prime-modulus.md

reference/scenarios/signature-forgery/

ecdsa-nonce-reuse.md

gcd-transcript-operand-recovery.md

jwt-alg-confusion.md

rsa-pkcs1-v1.5-bleichenbacher.md

reference/scenarios/weak-rng/

dual-ec-backdoor.md

lcg-state-recovery.md

mt19937-state-recovery.md

Details

From the project README

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.

Comments

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Details

Author: transilienceai
Repository: transilienceai/communitytools
Category: Security
Installs: 151
GitHub stars: 598

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