Rsa Attack Techniques

SKILL: RSA Attack Techniques — Expert Cryptanalysis Playbook

AI LOAD INSTRUCTION: Expert RSA attack techniques for CTF and authorized security assessments. Covers factorization attacks, small exponent exploits, lattice-based approaches (Wiener/Boneh-Durfee/Coppersmith), broadcast attacks, common modulus, padding oracles, and fault attacks. Base models often suggest attacks that don't match the given parameters or miss the correct attack selection based on what's known.

0. RELATED ROUTING

• lattice-crypto-attacks for deep lattice theory behind Coppersmith/Boneh-Durfee
• hash-attack-techniques when RSA signature forgery involves hash weaknesses
• symmetric-cipher-attacks when RSA protects a symmetric key (hybrid encryption)

Advanced Reference

Also load RSA_ATTACK_CATALOG.md when you need:

• Detailed SageMath/Python implementation for each attack
• Step-by-step mathematical derivation
• Edge cases and failure conditions per attack

Quick attack selection

1. FACTORIZATION ATTACKS

1.1 Direct Factorization (Small n)

from sympy import factorint

n = 0x...  # small modulus
factors = factorint(n)
p, q = list(factors.keys())

When: n < ~512 bits, or known to be in factordb.

1.2 Fermat's Factorization

Works when p and q are close together: |p - q| is small.

from gmpy2 import isqrt, is_square

def fermat_factor(n):
    a = isqrt(n) + 1
    while True:
        b2 = a * a - n
        if is_square(b2):
            b = isqrt(b2)
            return (a + b, a - b)
        a += 1

1.3 Pollard's p-1

Works when p-1 has only small prime factors (B-smooth).

from gmpy2 import gcd

def pollard_p1(n, B=2**20):
    a = 2
    for j in range(2, B):
        a = pow(a, j, n)
    d = gcd(a - 1, n)
    if 1 < d < n:
        return d
    return None

1.4 Batch GCD (Multiple n share a factor)

from math import gcd
from functools import reduce

def batch_gcd(moduli):
    """Find shared factors among multiple RSA moduli."""
    product = reduce(lambda a, b: a * b, moduli)
    results = {}
    for i, n in enumerate(moduli):
        remainder = product // n
        g = gcd(n, remainder)
        if g != 1 and g != n:
            results[i] = (g, n // g)
    return results

2. SMALL EXPONENT ATTACKS

2.1 Cube Root Attack (e = 3, small m)

If m^e < n (no modular reduction occurred), simply take the e-th root.

from gmpy2 import iroot

c = 0x...  # ciphertext
e = 3
m, exact = iroot(c, e)
if exact:
    print(f"Plaintext: {bytes.fromhex(hex(m)[2:])}")

2.2 Hastad Broadcast Attack

Same message encrypted with same small e under different moduli (n₁, n₂, ..., nₑ).

from sympy.ntheory.modular import crt
from gmpy2 import iroot

# e = 3, three ciphertexts under three different n
n_list = [n1, n2, n3]
c_list = [c1, c2, c3]

# CRT: find x such that x ≡ ci (mod ni) for all i
r, M = crt(n_list, c_list)
m, exact = iroot(r, 3)
assert exact

2.3 Related Message Attack (Franklin-Reiter)

Two messages related by a known linear function: m₂ = a·m₁ + b. Same n and e.

# SageMath
def franklin_reiter(n, e, c1, c2, a, b):
    R.<x> = PolynomialRing(Zmod(n))
    f1 = x^e - c1
    f2 = (a*x + b)^e - c2
    return Integer(n - gcd(f1, f2).coefficients()[0])

3. LARGE e / SMALL d ATTACKS

3.1 Wiener's Attack (Continued Fractions)

When d < n^(1/4) / 3, the continued fraction expansion of e/n reveals d.

def wiener_attack(e, n):
    """Recover d when d is small via continued fractions."""
    cf = continued_fraction(e, n)
    convergents = get_convergents(cf)

    for k, d in convergents:
        if k == 0:
            continue
        phi_candidate = (e * d - 1) // k
        # phi(n) = n - p - q + 1 → p + q = n - phi + 1
        s = n - phi_candidate + 1
        # p, q are roots of x^2 - s*x + n = 0
        discriminant = s * s - 4 * n
        if discriminant >= 0:
            from gmpy2 import isqrt, is_square
            if is_square(discriminant):
                return d
    return None

def continued_fraction(a, b):
    cf = []
    while b:
        cf.append(a // b)
        a, b = b, a % b
    return cf

def get_convergents(cf):
    convergents = []
    h_prev, h_curr = 0, 1
    k_prev, k_curr = 1, 0
    for a in cf:
        h_prev, h_curr = h_curr, a * h_curr + h_prev
        k_prev, k_curr = k_curr, a * k_curr + k_prev
        convergents.append((h_curr, k_curr))
    return convergents

3.2 Boneh-Durfee Attack (Lattice-Based)

Extends Wiener: works when d < n^0.292. Uses lattice reduction (LLL/BKZ).

Use SageMath implementation — see lattice-crypto-attacks for theory.

4. COPPERSMITH'S METHOD

4.1 Stereotyped Message

Known portion of plaintext, unknown part is small.

# SageMath
n = ...
e = 3
c = ...
known_prefix = b"flag{" + b"\x00" * 27  # known prefix, unknown suffix
known_int = int.from_bytes(known_prefix, 'big')

R.<x> = PolynomialRing(Zmod(n))
f = (known_int + x)^e - c
roots = f.small_roots(X=2^(27*8), beta=1.0)
if roots:
    m = known_int + int(roots[0])
    print(bytes.fromhex(hex(m)[2:]))

4.2 Partial Key Exposure

Known MSB or LSB of p → recover full p via Coppersmith.

# SageMath — known MSB of p
p_msb = ...  # known upper bits of p
R.<x> = PolynomialRing(Zmod(n))
f = p_msb + x
roots = f.small_roots(X=2^unknown_bits, beta=0.5)
if roots:
    p = p_msb + int(roots[0])
    q = n // p

5. COMMON MODULUS ATTACK

Two ciphertexts of same message under same n but different e₁, e₂ where gcd(e₁, e₂) = 1.

from gmpy2 import gcd, invert

def common_modulus(n, e1, e2, c1, c2):
    """Recover m when same message encrypted with two different e under same n."""
    assert gcd(e1, e2) == 1
    _, s1, s2 = extended_gcd(e1, e2)  # s1*e1 + s2*e2 = 1

    if s1 < 0:
        c1 = invert(c1, n)
        s1 = -s1
    if s2 < 0:
        c2 = invert(c2, n)
        s2 = -s2

    m = (pow(c1, s1, n) * pow(c2, s2, n)) % n
    return m

def extended_gcd(a, b):
    if a == 0:
        return b, 0, 1
    g, x, y = extended_gcd(b % a, a)
    return g, y - (b // a) * x, x

6. ORACLE ATTACKS

6.1 LSB Oracle (Parity Oracle)

An oracle reveals whether decrypted message is even or odd.

from gmpy2 import mpz

def lsb_oracle_attack(n, e, c, oracle_func):
    """Decrypt using LSB (parity) oracle. oracle_func(c) returns m%2."""
    from fractions import Fraction
    lo, hi = Fraction(0), Fraction(n)

    for _ in range(n.bit_length()):
        c = (c * pow(2, e, n)) % n  # multiply plaintext by 2
        if oracle_func(c) == 0:
            hi = (lo + hi) / 2
        else:
            lo = (lo + hi) / 2

    return int(hi)

6.2 Bleichenbacher (PKCS#1 v1.5 Padding Oracle)

Given a padding validity oracle (valid/invalid PKCS#1 v1.5), iteratively narrow down the plaintext range.

Complexity: O(2^16) oracle queries per byte on average.

Target: TLS implementations returning different errors for valid/invalid padding.

6.3 Manger's Attack (PKCS#1 OAEP)