eachacha 1.0.2

ChaCha20 SIMD kernels in Eä — encrypt, fused stats, and searchable cipher

eachacha

ChaCha20 (RFC 7539) SIMD kernels in the Eä language. Encrypt at 1.78 GB/s. Search encrypted data without decrypting to disk.

pip install eachacha

Quick Start

from eachacha import encrypt, search

key = bytes(range(32))     # 32-byte key
nonce = bytes(12)          # 12-byte nonce

# Encrypt
ct = encrypt(b"INFO ok\nERROR disk full\nINFO done\n", key, nonce)

# Search encrypted data — plaintext never touches disk
result = search(ct, b"ERROR", key, nonce)
print(result.offsets)  # [8]

# Multi-needle search with context lines (auto-selects v2 kernel)
result = search(ct, [b"ERROR", b"INFO"], key, nonce)
for i, line in enumerate(result.lines):
    print(f"[{result.needle_ids[i]}] {line}")

The Searchable Cipher

Standard process for searching encrypted logs:

Read file → Decrypt to /tmp (vulnerability!) → Read /tmp → Search → Delete /tmp

The Eä process:

Read encrypted file → Decrypt in buffer → Search in buffer → Report match → Zero buffer

Plaintext never exists as a full-file allocation. Only a 4 KB window lives in memory at a time, zeroed after each iteration.

CLI

# Single needle
eachacha-grep "ERROR" encrypted.bin --key <hex> --nonce <hex>

# Multi-needle with context lines
eachacha-grep "ERROR" "FATAL" "PANIC" encrypted.bin --key <hex> --nonce <hex>

Benchmarks

AMD EPYC 9354P (2 vCPUs), 64 MB:

Single-needle search (v1):

Implementation	GB/s
Ea fused decrypt+search	1.28
Ea decrypt → C memmem (two-pass)	0.96
C memmem on plaintext	2.22

Multi-needle search (v2, 3 needles + context lines):

Implementation	GB/s
Ea v2 multi-needle (1 pass)	0.52
Ea v1 single-needle x3 (3 passes)	0.41
C memmem x3 on plaintext	0.78

• v1 fused vs two-pass: 1.34x faster
• v2 multi-needle vs v1 x3: 1.28x faster (one decrypt instead of three)

Security Model

Property	Guarantee
Full-file plaintext buffer	Never created — 4 KB window at a time (v2)
Working buffer	Zeroed after each iteration
Plaintext on disk	Never written
Kernel output	Match offsets + extracted lines only

How It Works

v1 kernel (chacha20_search.ea, 576 lines): Decrypts 256 bytes at a time, searches with .== + movemask SIMD first-byte filter (same algorithm as glibc memmem: vpcmpeqb + vpmovmskb), handles cross-block boundaries via overlap buffer.

v2 kernel (chacha20_search_v2.ea, 866 lines): Decrypts into a 4 KB window, searches for multiple needles by OR:ing .== + movemask bitmasks per unique first-byte, extracts matched log lines by finding \n boundaries with the same SIMD primitives.

Encrypt + Statistics

The fused kernel encrypts data and computes sum/count/min/max in a single pass:

Implementation	GB/s
Generic C (-O3, no SIMD)	0.54
OpenSSL ChaCha20 (Python wrapper)	0.59
Ea ChaCha20 (single core)	1.78
Ea fused (encrypt + stats)	1.43
Ea encrypt + NumPy stats (two passes)	1.08

Fusion adds ~20% overhead vs encrypt-only. The separate approach pays for a second memory traversal — fusion eliminates it.

Complexity

Kernel	Lines	Throughput
chacha20.ea (encrypt)	272	1.78 GB/s
chacha20_fused.ea (encrypt+stats)	384	1.43 GB/s
chacha20_search.ea (v1 search)	576	1.28 GB/s
chacha20_search_v2.ea (v2 multi-needle)	866	0.52 GB/s
Total	2,098

2,098 lines of Eä produce four production-grade kernels. For comparison, OpenSSL's ChaCha20 alone is ~100,000+ lines of C/ASM.

Build from Source

Requires ea-compiler (pip install ea-compiler) and a C compiler.

./build.sh
python3 test_vectors.py && python3 test_fused.py && python3 test_search.py && python3 test_search_v2.py

Files

File	Purpose
chacha20.ea	ChaCha20 encrypt kernel (4-block ILP)
chacha20_fused.ea	Fused encrypt + statistics kernel
chacha20_search.ea	v1: single-needle fused decrypt+search
chacha20_search_v2.ea	v2: multi-needle + context-line extraction
eachacha_grep.py	CLI for searching encrypted files
test_vectors.py	RFC 7539 test vectors + OpenSSL cross-check (8 tests)
test_fused.py	Fused encrypt+stats tests (19 tests)
test_search.py	v1 search tests (17 tests, 38 assertions)
test_search_v2.py	v2 search tests (27 tests, 44 assertions)
bench.py	Encrypt benchmark suite
bench_search.py	v1 search benchmark suite
bench_search_v2.py	v2 multi-needle benchmark suite
autoresearch/	Automated kernel optimization loop