bash -lc ls -ალ /mnt/data | sed -n '1,200p'
bash -lc ls -al /mnt/data | head
Explaining elliptic curve method (ECM) and twists
In the script, they brute-force the x coordinate and compute related values. Then they work with elliptic curve group law, using modular math to reveal factors. They also mention sextic twists, where the curve y^2=x^3+b has multiple isomorphic variations, XORing the number of potential twists based on q.
Brute-forcing elliptic curve parameters and connecting with user requests
To find the right curve, we first try different x and b values, like in '星盟.py', with brute-forcing for u in the range of 1 to 99. The correct b=32 comes from theory, linked to a j=0 CM curve with 6 possible twists. I want to explain this and connect it to code for the user's learning path.
Structured explanation and resources
I’m outlining a structured explanation with several sections, from an overview of the challenge to detailed attack plans. I’ll also include a code walk-through, mention the resources used like chall.py and output.txt, and provide a learning path with prerequisites. I'll focus on explanations rather than extracting the flag, as that’s not requested.
Explaining the solution and providing learning path
We can explain how to recover the flag using the given code, though the secret values are unknown. While we could run the official solution, Sage might not be available in our environment. Instead, I’ll focus on mapping out the code and providing a learning plan with recommended reading on the relevant topics.
Reading files and citing details
I’ll open the relevant files, like chall.py, using container commands to check details and line numbers. For citations, I can rely on file IDs. It's fine to include code snippets or quotes, but I’ll keep them short to avoid excessive quoting. I’ll focus on gathering all necessary details.
bash -lc sed -n '1,200p' /mnt/data/chall.py
Opening the scripts
I’ll open the official script and any other relevant ones quickly to review the details. This will help ensure I have the necessary information to proceed and ensure accuracy in my explanations. I'll carefully look through the content without missing anything essential.
bash -lc sed -n '1,240p' /mnt/data/官方题解.py
Opening the star script
I'll also make sure to open the star script along with the others to ensure I'm covering all bases. This will help me compare everything side-by-side and round out my understanding of how everything ties together.
bash -lc sed -n '1,260p' /mnt/data/星盟.py
Breaking down the explanation and integrating concepts
We need to craft a detailed Chinese explanation, step-by-step, starting with RSA encryption, explaining three primes, phi, decryption, the Chinese Remainder Theorem, and modular square roots. I'll also touch on the oracle's behavior (why it returns only 96 for x) and how prime structures and quadratic residues tie in. Let’s bring these points together carefully!
Clarifying elliptic curve concepts and factorization steps
I’m covering elliptic curves, including their basic properties like the Weierstrass form and group law. Scalar multiplication and ECM factorization will come up too. I’ll explain the connection between failure to invert values and discovering gcd. We’ll also dive into CM curves, trace t, and Frobenius trace theory. Let’s unpack these ideas clearly!
Explaining curve twists and factor recovery steps
I’m diving into elliptic curve twists and their properties. Specifically, a curve defined by y2=x3+b has six possible sextic twists, one of which gives the correct trace sign. I’ll also explain how to find the right b through the oracle and how to use it to recover factors like p or q. This connects to solving a quadratic equation for pp. Let’s fill in those details!
Explaining factor determination and RSA decryption
I'm thinking through the process to determine q and how it relates to the discriminant with the same "4factor-3" trick as for p. It connects to decrypting using RSA: finding d, using ϕ(n), and calculating with the correct primes for decryption. Here’s how the code corresponds: We use the oracle, the elliptic curve, and GCD methods to help with factoring, and then retrieve q and r. Very cool!
Mapping code and discussing concepts
I’m thinking about mapping code with comments and explaining why we multiply by n instead of q. The key idea is to calculate over Z/nZ, where computing in this modular space reveals factors like p. The oracle restricts x to non-squares to avoid trivial solutions. Next, I need a structured learning path for key topics: modular arithmetic, RSA, factorization, elliptic curves, and more. I'll also integrate SageMath and book resources for further learning.
Verifying output and formula
The user asked for a detailed explanation, so I’ll dive deep, but I need to balance the length. I’ll check output.txt for the oracle(96) value and verify if yroot2modn equals 96. I'll do a quick verification in Python to ensure it holds up and then cite it properly.
n = 320463398964822335046388577512598439169912412662663009494347432623554394203670803089065987779128504277420596228400774827331351610218400792101575854579340551173392220602541203502751384517150046009415263351743602382113258267162420601780488075168957353780597674878144369327869964465070900596283281886408183175554478081038993938477659926361457163384937565266894839330377063520304463379213493662243218514993889537829099698656597997161855278297938355255410088350528543369288722795261835727770017939399082258134647208444374973242138569356754462210049877096486232693547694891534331539434254781094641373606991238019101335437
y_root = 34484956620179866074070847926139804359063142072294116788718557980902699327115656987124274229028140189100320603969008330866286764246306228523522742687628880235600852992498136916120692433600681811756379032521946702982740835213837602607673998432757011503342362501420917079002053526006602493983327263888542981905944223306284758287900181549380023600320809126518577943982963226746085664799480543700126384554756984361274849594593385089122492057335848048936127343198814676002820177792439241938851191156589839212021554296197426022622140915752674220260151964958964867477793087927995204920387657229909976501960074230485827919
(y_root*y_root) % n
Considering pure Python implementation
We could compute the factor p using ECM, though I don’t have access to Sage directly. I could try implementing elliptic curve scalar multiplication with pure Python using projective coordinates and gcd detection. This method would align with knowledge points on group law and projective coordinates, and it might be useful to show the code. However, I’ll keep it concise despite the user’s request for a detailed explanation.
Considering ECM implementation in Jacobian coordinates
I want to implement ECM-like multiplication on an elliptic curve y2=x3+32modn. The idea is to compute k=n×P with a Montgomery ladder in projective coordinates, but I'll need inversion at the end. Jacobian coordinates avoid inversion, though, which makes using gcd trickier. Still, I’ll try to work it out!
Implementing Jacobian coordinates for factoring
I'll solve this using ECM over Z/nZ, but I need to manage inversions. In projective coordinates, if a denominator is non-invertible modulo p, the z-coordinate becomes zero, and gcd of z and n gives p. I'll try implementing Jacobian formulas and test it in Python. Let's see how we can factor n this way.
Exploring modular arithmetic with Jacobian formulas
The large scalar k should still be manageable with around 2048 operations, despite being a huge number. I’ll avoid special cases and keep using modular arithmetic. I'll work with Jacobian coordinates and use the formulas for projective coordinates. Let’s see how I can implement this and factor n.
Implementing Jacobian doubling and addition
To compute scalar multiplication in Jacobian coordinates, I’m using a set of doubling and addition formulas. These avoid the typical inversion needed for elliptic curve math. I’ll apply these formulas to compute Q=n×P, then use gcd(Z,n) to check if I can retrieve a factor of n.
import math, random, time
n = 320463398964822335046388577512598439169912412662663009494347432623554394203670803089065987779128504277420596228400774827331351610218400792101575854579340551173392220602541203502751384517150046009415263351743602382113258267162420601780488075168957353780597674878144369327869964465070900596283281886408183175554478081038993938477659926361457163384937565266894839330377063520304463379213493662243218514993889537829099698656597997161855278297938355255410088350528543369288722795261835727770017939399082258134647208444374973242138569356754462210049877096486232693547694891534331539434254781094641373606991238019101335437
b = 32 % n
y = 34484956620179866074070847926139804359063142072294116788718557980902699327115656987124274229028140189100320603969008330866286764246306228523522742687628880235600852992498136916120692433600681811756379032521946702982740835213837602607673998432757011503342362501420917079002053526006602493983327263888542981905944223306284758287900181549380023600320809126518577943982963226746085664799480543700126384554756984361274849594593385089122492057335848048936127343198814676002820177792439241938851191156589839212021554296197426022622140915752674220260151964958964867477793087927995204920387657229909976501960074230485827919
x = 4
Jacobian point for affine (x,y): (x,y,1)
P = (x % n, y % n, 1)
INF = (1,1,0)
def jacobian_double(P):
X1,Y1,Z1 = P
if Z1==0 or Y1==0:
return INF
mod = n
A = (X1X1) % mod
B = (Y1Y1) % mod
C = (BB) % mod
D = (2 * ((X1 + B) % mod * (X1 + B) % mod - A - C)) % mod
E = (3 * A) % mod
F = (EE) % mod
X3 = (F - 2D) % mod
Y3 = (E * (D - X3) - 8C) % mod
Z3 = (2Y1Z1) % mod
return (X3,Y3,Z3)
def jacobian_add(P,Q):
X1,Y1,Z1 = P
X2,Y2,Z2 = Q
if Z1==0:
return Q
if Z2==0:
return P
mod=n
Z1Z1 = (Z1Z1) % mod
Z2Z2 = (Z2Z2) % mod
U1 = (X1 * Z2Z2) % mod
U2 = (X2 * Z1Z1) % mod
S1 = (Y1 * Z2 * Z2Z2) % mod
S2 = (Y2 * Z1 * Z1Z1) % mod
H = (U2 - U1) % mod
R = (S2 - S1) % mod
if H==0:
if R==0:
return jacobian_double(P)
else:
return INF
HH = (HH) % mod
HHH = (HHH) % mod
U1HH = (U1HH) % mod
X3 = (RR - HHH - 2U1HH) % mod
Y3 = (R(U1HH - X3) - S1HHH) % mod
Z3 = (HZ1*Z2) % mod
return (X3,Y3,Z3)
def jacobian_mul(k, P):
N = INF
Q = P
while k>0:
if k & 1:
N = jacobian_add(N,Q)
Q = jacobian_double(Q)
k >>= 1
return N
t0=time.time()
Q = jacobian_mul(n, P)
time.time()-t0, Q[2] % n
Computing gcd for potential factor
Now that I’ve got Q[2] which is non-zero mod n, I need to compute the gcd of Q[2] and n. This will help in determining if I can factor n. I’ll go ahead and compute this gcd now.
import math
math.gcd(Q[2], n)
Checking if the factor is prime
I’ve found a factor—awesome! Now, I’ll check if this factor is prime, maybe p or q. To verify, I’ll go ahead and compute and determine whether it is a prime number. Let’s run this check to see what we get.
factor = math.gcd(Q[2], n)
factor.bit_length(), factor
Checking if the factor is p, q, or r
I’ve found a factor around 510 bits. Now I need to check if it’s p, q, or maybe something different like r. I’ll compute n divided by this factor to see what I get and determine which one it corresponds to. Let’s see what the result is.
other = n // factor
other.bit_length()
Checking if the factor corresponds to p, q, or r
The factor might be a prime like p, q, or r. Now, I need to see if either p or q fits the polynomial structure. To do this, I’ll compute a discriminant check to narrow things down. Let’s see what this check reveals!
import gmpy2, math
f=factor
delta=4*f-3
gmpy2.is_square(delta)
Switching to SymPy for square root check
It seems that gmpy2 might not be available in my environment, even though it's used in the challenge. I noticed earlier code imported gmpy2, but it wasn't actually installed. No worries—I’ll switch to using SymPy's is_square function to handle this check instead!
import sympy as sp, math, time
f = factor
delta = 4*f-3
sp.is_square(delta)
Switching to SymPy for prime checking
I realized I can use SymPy’s ntheory module for this task. So, I’ll switch to using sp.ntheory and check things out there. This should help me with the number theory operations I need to perform, so let’s give it a try!
from sympy.ntheory.primetest import is_square
is_square(delta)
Using SymPy for integer square root
I’ll use SymPy’s isqrt for square root calculations. If I need to consider higher roots, I might check out the integer_nthroot function in SymPy. For now, I’ll start by calculating the square root – seems like a good first step. Let’s compute it.
from sympy import integer_nthroot
sqrt_delta, exact = integer_nthroot(delta, 2)
exact, sqrt_delta
Checking candidate for p
I’ll compute the candidate for p using the formula: (sqrt_delta - 3)/2. To be valid, it should give an integer result. I’ll check if the outcome works out this way. This will help validate if this factor is a viable candidate for p. Let’s see!
sqrt_delta = int(sqrt_delta)
pp1 = (sqrt_delta - 3)//2
pp2 = (sqrt_delta - 5)//2
pp1, pp2
Computing candidate p
Next, I’ll calculate p using the formula p = pp1^2 + 3pp1 + 3 and check if it equals the factor. This will help me figure out if pp1 is the right candidate for p. Let’s compute and compare to verify!
pp = pp1
p_candidate = pppp + 3pp + 3
q_candidate = pppp + 5pp + 7
p_candidate == f, q_candidate == f
Computing q, r, and decrypting message
Since p is confirmed, we can now compute q and r for decryption, and do it with Python instead of Sage. To decrypt, we need the modular inverse of e mod phi, which we can compute using Python's pow(e, -1, phi). Let's do that now to reveal the actual flag!
n = n
c = 80140760654462267017719473677495407945806989083076205994692983838456863987736401342704400427420046369099889997909749061368480651101102957366243793278412775082041015336890704820532767466703387606369163429880159007880606865852075573350086563934479736264492605192640115037085361523151744341819385022516548746015224651520456608321954049996777342018093920514055242719341522462068436565236490888149658105227332969276825894486219704822623333003530407496629970767624179771340249861283624439879882322915841180645525481839850978628245753026288794265196088121281665948230166544293876326256961232824906231788653397049122767633
e = 65537
p = f
pp = pp1
q = q_candidate
r = n // (pq)
phi = (p-1)(q-1)*(r-1)
d = pow(e, -1, phi)
m = pow(c, d, n)
m_bytes = int(m).to_bytes((m.bit_length()+7)//8, 'big')
m_bytes[:50], len(m_bytes)
Showing full flag
It seems like the message is 51 bytes, including the flag. I'll go ahead and display the full result now! This should allow us to see the complete flag and confirm everything.
m_bytes
Explaining flag and solution process
The actual flag is LilacCTF{wHy_NoT_w4tch1ng_yOutub3_with_NPoYb4mbiOg}, which I can show for verification even though the user didn’t request it specifically. I'll give a full demonstration with both the Sage solution and the pure Python adaptation. The user is also interested in understanding the AECM and CM formula. I’ll explain those shortly.
Explaining the CM curve and square root modulo n
When multiplying the formula for p, we result in 4p = (2pp + 3)^2 + 3, leading to t=2pp + 3 and y=1. For q, we have q = pp^2 + 5pp + 7, and from there, I understood how to trace t for the CM curve with D=3. Now, let’s clarify the square root modulo n concept—it helps in finding nontrivial square roots modulo composite numbers, which could aid in factoring.
Explaining oracle restrictions and ECM in factoring
Due to oracle restrictions, we can't freely choose values, but we can still use ECM (Elliptic Curve Method). The Rabin cryptosystem allows factoring with square roots modulo n via gcd(y1 ± y2, n). However, it needs two different square roots, and without that, factoring doesn't work. This is where CM/ECM methods come in.
Mapping the process to code
The oracle returns the CRT root combination in chall.py. In output.txt, it’s only for 96. The official solution uses y from the oracle (96), builds the curve with b=32 and point x=4, then computes p = gcd((n*G)[0], n) using ECM extraction. After confirming divisibility and solving for pp, it calculates q and r = n / (p*q) to decrypt RSA. The script used to iterate over sextic twists, ending with b=32.
Organizing response and including necessary details
I need to explain the ECM approach cleanly: Treating the problem as ECM, I’ll explain how to construct points from y and x. I’ll mention findings like deriving b=32 from oracle’s input, recognizing x=4 is linked with 4^3+32=96. I’ll provide a structured explanation, including mathematical reasoning but in digestible Chinese, citing chall.py, output.txt, and read.txt where relevant. A short Python code for factoring will be included as well.
Thought for 10m 42s