帮我非常详细的讲解这道ctf题目中的每一个知识点,具体是怎样证明怎样利用,把每一个知识点与解决的代码...

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تمت الإجابة باستخدام GPT-5.2 Thinking بواسطة Chat01

سؤال

chall.py
output.txt
read.txt
官方题解.py
星盟.py
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帮我非常详细的讲解这道ctf题目中的每一个知识点,具体是怎样证明怎样利用,把每一个知识点与解决的代码对应起来,并给出学习的相关路径,方法

الفكرة

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+by^2 = x^3 + b has six possible sextic twists, one of which gives the correct trace sign. I’ll also explain how to find the right bb through the oracle and how to use it to recover factors like pp or qq. This connects to solving a quadratic equation for pppp. Let’s fill in those details!

Explaining factor determination and RSA decryption

I'm thinking through the process to determine qq and how it relates to the discriminant with the same "4factor-3" trick as for pp. It connects to decrypting using RSA: finding dd, using ϕ(n)\phi(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 qq and rr. Very cool!

Mapping code and discussing concepts

I’m thinking about mapping code with comments and explaining why we multiply by nn instead of qq. The key idea is to calculate over Z/nZZ/nZ, where computing in this modular space reveals factors like pp. The oracle restricts xx 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 yroot2modny_{\text{root}}^2 \mod n 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 pp 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+32modny^2 = x^3 + 32 \mod n. The idea is to compute k=n×Pk = n \times 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\mathbb{Z}/n\mathbb{Z}, but I need to manage inversions. In projective coordinates, if a denominator is non-invertible modulo pp, the zz-coordinate becomes zero, and gcd of zz and nn gives pp. I'll try implementing Jacobian formulas and test it in Python. Let's see how we can factor nn this way.

Exploring modular arithmetic with Jacobian formulas

The large scalar kk 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 nn.

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×PQ = n \times P, then use gcd(Z,n)\text{gcd}(Z, n) to check if I can retrieve a factor of nn.

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]Q[2] which is non-zero mod nn, I need to compute the gcd of Q[2]Q[2] and nn. This will help in determining if I can factor nn. 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 pp or qq. 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 pp, qq, or maybe something different like rr. I’ll compute nn 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 pp, qq, or rr. Now, I need to see if either pp or qq 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

الإجابة

下面我按“知识点 → 证明/原理 → 如何利用 → 对应代码”的方式,把这题从头到尾拆开讲。你给的文件里已经包含了题目服务端、交互输出、诗歌提示、官方题解和一个更“暴力”的脚本,我会逐段把它们串起来。(chall.py) (output.txt) (read.txt) (官方题解.py) (星盟.py)


0. 题目到底在干嘛(全局视角)

  • 这是 三素数 RSAn=pqrn=pqr,公钥 e=65537e=65537,密文 c=memodnc=m^e\bmod n。服务端打印 n,cn,c。(chall.py) (output.txt)
  • 同时给你一个 oracle:你输入一个 x(80,100)x\in(80,100) 且不能是整数完全平方,oracle 尝试分别在模 p,q,rp,q,r 下开平方根,再用 CRT 合成一个模 nn 的平方根返回;如果任意一个模下无平方根就返回“🤐”。(chall.py)
  • 实际交互发现:只有 x=96x=96 会返回一个数(其余全 🤐)。(output.txt)
  • primes 还带特殊结构: p=pp2+3pp+3,q=pp2+5pp+7p=pp^2+3pp+3,\quad q=pp^2+5pp+7 并且 p,q,rp,q,r 都是素数。(chall.py)

这题的“门”是:oracle 看似只给你一个平方根(很弱),但因为 p,qp,q 的构造是 CM(复乘)椭圆曲线相关的特殊形状,所以你能构造一条“已知群结构”的椭圆曲线来做 Lenstra ECM 因式分解,直接把 pp 挖出来。


1) 知识点:模素数平方根、二次剩余(Quadratic Residue)

原理/证明要点

对奇素数 pp,方程

y2x(modp)y^2\equiv x\pmod p

有解当且仅当 xx 是模 pp 的二次剩余(Legendre 符号 (xp)=1\left(\frac{x}{p}\right)=1)。有解时通常有两个根 y,yy,\,-y

如何被题目利用

服务端对同一个 xx 分别计算:

  • sqrt_mod(x, p), sqrt_mod(x, q), sqrt_mod(x, r) 只要其中一个为 None 就拒绝。(chall.py)

你在交互里看到只有 96 通过,意味着:

96 同时是 modp,modq,modr 的二次剩余96 \text{ 同时是 } \bmod p,\bmod q,\bmod r \text{ 的二次剩余}

也就是 9696 在每个素因子上都能开平方根。(output.txt)

对应代码(题目端)

oracle(x) 里三次 sqrt_mod + 判 None。(chall.py)


2) 知识点:中国剩余定理 CRT(把三个根拼成模 n 的根)

原理/证明要点

n=pqrn=pqr 两两互素,给定

ypy(modp),yqy(modq),yry(modr)y_p\equiv y\pmod p,\quad y_q\equiv y\pmod q,\quad y_r\equiv y\pmod r

则存在唯一 ymodny\bmod n 满足三者同余,这个 yy 可由 CRT 算出。

如何被题目利用

服务端把三个模下的平方根 CRT 合成:

yx(modp), x(modq), x(modr)y2x(modpqr)=x(modn)y \equiv \sqrt{x}\pmod p,\ \sqrt{x}\pmod q,\ \sqrt{x}\pmod r \Rightarrow y^2\equiv x\pmod{pqr}=x\pmod n

所以 oracle 返回的就是“模 nn 的一个平方根”。(chall.py)

在输出里你拿到:

  • nncc
  • 以及 x=96x=96 时返回的那个巨大整数 yrooty_{\text{root}}。(output.txt)
    它满足
yroot296(modn)y_{\text{root}}^2\equiv 96\pmod n

(你脚本里也是这么用的)。(星盟.py)

对应代码(题目端)

ans, _ = crt([p,q,r],[root_p,root_q,root_r])。(chall.py)


3) 知识点:为什么“只给一个平方根”通常没法直接分解 n

经典 Rabin/平方根分解思路需要你拿到 同一个 xx 的两个不同平方根 y1±y2(modn)y_1\neq \pm y_2\pmod n,这样

gcd(y1y2,n) 或 gcd(y1+y2,n)\gcd(y_1-y_2,n)\ \text{或}\ \gcd(y_1+y_2,n)

会泄漏因子。

但这题 oracle 对每个素数用的 sqrt_mod 往往是“固定选择某个根”(例如最小根),你很难拿到另一个根;同时你也没法换 xx(只有 96 有效)。所以必须走另一条路:把这个平方根当作椭圆曲线点的 y 坐标,转成 ECM


4) 知识点:题目 primes 的“多项式结构”到底暗示了什么(CM 的入口)

题目断言:

p=pp2+3pp+3,q=pp2+5pp+7p=pp^2+3pp+3,\qquad q=pp^2+5pp+7

(chall.py)

先做两步代数变形(这是后面 CM/Trace 的核心):

(1) 关键恒等式:4p=(2pp+3)2+34p=(2pp+3)^2+3

4p=4pp2+12pp+12=(2pp+3)2+34p=4pp^2+12pp+12=(2pp+3)^2+3

等价于

4p=t2+312,其中 t=2pp+34p=t^2+3\cdot 1^2,\quad \text{其中 } t=2pp+3

(2) 关键关系:q=p+1+tq=p+1+t

直接算:

p+1+t=(pp2+3pp+3)+1+(2pp+3)=pp2+5pp+7=qp+1+t=(pp^2+3pp+3)+1+(2pp+3)=pp^2+5pp+7=q

这不是“巧合”:这正是 判别式 D=3D=3 的 CM 椭圆曲线里 Frobenius trace 的典型形状。


5) 知识点:椭圆曲线、Frobenius trace、CM(复乘)与 4p=t2+Dy24p=t^2+Dy^2

5.1 椭圆曲线群(最基础)

短 Weierstrass 形式:

E:y2=x3+ax+bE: y^2=x^3+ax+b

在有限域 Fp\mathbb F_p 上,其点集(加上无穷远点 OO)构成一个有限阿贝尔群。群的大小满足 Hasse:

#E(Fp)=p+1t,t2p\#E(\mathbb F_p)=p+1-t,\quad |t|\le 2\sqrt p

这里 tt 就是 Frobenius trace。

5.2 CM 曲线的“trace 受二次型约束”

对于带 CM 的椭圆曲线(对应某个虚二次域 Q(D)\mathbb Q(\sqrt{-D})),当素数 pp 在该域里分裂时,trace 会落在一个二次型表示里,典型形式就是:

4p=t2+Dy24p=t^2+D y^2

直观解释(够用的层级):

  • 在虚二次整数环里,分裂意味着存在 π\pi 使得 p=N(π)=ππˉp=N(\pi)=\pi\bar\pi
  • π=(t+yD)/2\pi=(t+y\sqrt{-D})/2,其范数就是 (t2+Dy2)/4(t^2+Dy^2)/4,于是得到上式。

5.3 本题对应 D=3D=3,曲线是 j=0j=0 家族:y2=x3+by^2=x^3+b

题面截图也点了这个:D=3D=3 的 CM 对应到 j=0j=0 曲线族,也就是

Eb:y2=x3+bE_b: y^2=x^3+b

并且会出现所谓“sextic twist(六次扭曲)”——同一个 j=0j=0 类在 Fp\mathbb F_p 上有 6 个不同 twist(本质原因是自同构群大小为 6)。你截图里那段“six curves / g{1,b,,b5}g\in\{1,b,\dots,b^5\}”就是在说这个。

而本题“精心”挑了 pp 使得 t=2pp+3t=2pp+3y=1y=1,从而某个 twist 会满足:

#E(Fp)=p+1+t=q\#E(\mathbb F_p)=p+1+t=q

(注意 trace 符号正负会随 twist 改变,所以你要找“对的那个 twist”。)


6) 知识点:Lenstra ECM(椭圆曲线因式分解)——为什么能从“点乘失败”里抠出因子

6.1 ECM 的核心不是“椭圆曲线离散对数”,而是“求逆失败”

Fp\mathbb F_p 上,点加法要做除法(求逆):

  • 加法:λ=y2y1x2x1\lambda=\frac{y_2-y_1}{x_2-x_1}
  • 倍点:λ=3x12+a2y1\lambda=\frac{3x_1^2+a}{2y_1}

在模 合数 nn 的环 Z/nZ\mathbb Z/n\mathbb Z 上,“除法”需要求逆元,但逆元不一定存在:当分母与 nn 不互素时就会失败。此时你计算:

gcd(分母,n)\gcd(\text{分母},n)

就可能直接得到 ppqqrr

这就是 ECM 的“泄漏口”。

6.2 为什么这题能“一发入魂”

如果你能让某个素因子 pp 上的点 PP 满足:

kP=O在 E(Fp)k\cdot P = O \quad \text{在 } E(\mathbb F_p)

那么在模 nn 的运算过程中,最终会出现“等价于无穷远点”的情形:在投影坐标里 Z0(modp)Z\equiv 0\pmod p,于是

gcd(Z,n)=p\gcd(Z,n)=p

这正是你脚本里取 Q[2](投影坐标 Z)然后 gcd 的原因。(星盟.py)

本题把

#E(Fp)=q\#E(\mathbb F_p)=q

做成了一个“可控结构”,而 n=pqrn=pqr 本身就含有因子 qq,所以你直接取标量 k=nk=n

nP=(pqr)P=(pr)(qP)=(pr)O=O(modp)nP = (pqr)P = (pr)\cdot(qP)= (pr)\cdot O = O \quad (\bmod p)

于是 ZZ 里带出 pp


7) 知识点:oracle(96) 为什么能直接变成曲线上的点(把平方根塞进曲线方程)

你拿到的是:

yroot296(modn)y_{\text{root}}^2\equiv 96\pmod n

(output.txt)

若我们构造曲线:

E:y2=x3+bE: y^2 = x^3 + b

只要选一个 x=ux=u,令

b96u3(modn)b \equiv 96-u^3 \pmod n

就保证点

P=(u, yroot)P=(u,\ y_{\text{root}})

在模 nn 下满足曲线方程(至少形式上成立)。

这就是“星盟.py”里循环枚举 uu 的那三行注释和计算:(星盟.py)

  • b_val = (96 - u**3) % n
  • E = EllipticCurve(R, [0, b_val])
  • P = E(u, y_root)

官方题解选的是最干净的一组:

  • u=4u=4,因为 43=644^3=64,于是 b=9664=32b=96-64=32
  • 所以曲线是 y2=x3+32y^2=x^3+32,点是 (4,yroot)(4,y_{\text{root}})。(官方题解.py)

8) 把整条 exploit 流程串起来(每一步对应哪段代码)

下面按“步骤→代码”对齐。

Step A:拿到 n,cn,c 和唯一一次有效 oracle 输出

你已经在 output.txt 里拿到了(包括 yrooty_{\text{root}})。(output.txt)

Step B:构造 CM 家族曲线 + 点

官方题解(最直接):(官方题解.py)

python
E = EllipticCurve(Zmod(n), [0, 32]) G = E(4, y_root) # y_root 就是 oracle(96)

对应知识点:

  • b=32b=32j=0j=0 CM 曲线的某个 sextic twist(“挑对 twist”)
  • 43+32=964^3+32=96,而 yroot296y_{\text{root}}^2\equiv 96

“星盟.py”(更通用,不用猜 b):(星盟.py)

python
for u in range(1, 100): b_val = (96 - u**3) % n E = EllipticCurve(R, [0, b_val]) P = E(u, y_root)

Step C:做 ECM:计算 Q=nPQ=n\cdot P,从投影坐标里 gcd 出因子

官方题解:(官方题解.py)

python
p = int(gcd((n*G)[0], n))

它用的是 gcd(x(Q), n) 的写法(Sage 内部实现会让坐标里自然出现那个因子)。

星盟版本(更经典的 ECM 写法):(星盟.py)

python
Q = n * P z = Integer(Q[2]) factor = gcd(z, n)

这里 Q[2] 就是投影坐标 ZZ,理论上 Z0(modp)Z\equiv 0\pmod p 从而 gcd 出 pp

Step D:由拿到的因子恢复 pp,从而恢复 q,再得 r

官方题解先解:

pp2+3pp+3=ppp^2+3pp+3=p

用 Sage solve。(官方题解.py)

星盟版给了更“手算友好”的判别式技巧:(星盟.py)

p=pp2+3pp+3p=pp^2+3pp+3,判别式:

Δ=3241(3p)=912+4p=4p3\Delta = 3^2 -4\cdot 1\cdot (3-p)=9-12+4p=4p-3

所以

pp=3±4p32pp=\frac{-3\pm\sqrt{4p-3}}{2}

同理对 q=pp2+5pp+7q=pp^2+5pp+7 也有 Δ=4q3\Delta=4q-3,所以脚本用 4*factor-3 来判定“拿到的是 p 还是 q”。(星盟.py)

最后:

python
q = pp**2 + 5*pp + 7 r = n // (p*q)

(官方题解.py) (星盟.py)

Step E:标准 RSA 解密

三素数 RSA:

φ(n)=(p1)(q1)(r1),d=e1modφ(n),m=cdmodn\varphi(n)=(p-1)(q-1)(r-1),\quad d=e^{-1}\bmod\varphi(n),\quad m=c^d\bmod n

官方题解就是这么做的:(官方题解.py)
星盟脚本也一样:(星盟.py)


9) 给你一份“把知识点写进代码注释里”的纯 Python 版(不用 Sage 的思路)

你现在的脚本依赖 Sage 的 EllipticCurve/Zmod。如果你想把“ECM 的求逆失败=泄漏 gcd”自己手搓出来,最核心就是:用 Jacobian 投影坐标做点加/倍点(不需要求逆),最后取 ZZ 做 gcd。

下面这份代码就是把第 6 节的原理落地(结构和你星盟脚本一致,只是不用 Sage):

python
import math # 已知 n, c, e, 以及 oracle(96) 给出的 y_root n = ... c = ... e = 65537 y_root = ... # CM 选定的 twist:E: y^2 = x^3 + 32 b = 32 % n x = 4 P = (x % n, y_root % n, 1) # Jacobian: (X,Y,Z), affine=(X/Z^2, Y/Z^3) INF = (1, 1, 0) def jac_double(P): X1,Y1,Z1 = P if Z1 == 0 or Y1 == 0: return INF A = (X1*X1) % n B = (Y1*Y1) % n C = (B*B) % n D = (2 * (((X1 + B) % n)**2 - A - C)) % n E = (3 * A) % n F = (E*E) % n X3 = (F - 2*D) % n Y3 = (E * (D - X3) - 8*C) % n Z3 = (2*Y1*Z1) % n return (X3,Y3,Z3) def jac_add(P,Q): X1,Y1,Z1 = P X2,Y2,Z2 = Q if Z1 == 0: return Q if Z2 == 0: return P Z1Z1 = (Z1*Z1) % n Z2Z2 = (Z2*Z2) % n U1 = (X1 * Z2Z2) % n U2 = (X2 * Z1Z1) % n S1 = (Y1 * Z2 * Z2Z2) % n S2 = (Y2 * Z1 * Z1Z1) % n H = (U2 - U1) % n R = (S2 - S1) % n # 注意:这里的分支判断是在 mod n 上, # 如果只是“mod p 为 0”但 mod n 不为 0,就不会走进来, # 因子会继续“藏”在 Z 里,最终 gcd(Z,n) 抠出来。 if H == 0: if R == 0: return jac_double(P) else: return INF HH = (H*H) % n HHH = (H*HH) % n U1HH = (U1*HH) % n X3 = (R*R - HHH - 2*U1HH) % n Y3 = (R*(U1HH - X3) - S1*HHH) % n Z3 = (H*Z1*Z2) % n return (X3,Y3,Z3) def jac_mul(k, P): N = INF Q = P while k > 0: if k & 1: N = jac_add(N, Q) Q = jac_double(Q) k >>= 1 return N Q = jac_mul(n, P) Z = Q[2] p = math.gcd(Z, n) # ECM 关键:Z ≡ 0 (mod p) => gcd 泄漏 p print(p)

把它和你星盟脚本对照,你会发现“知识点对应关系”非常直观:

  • “椭圆曲线群 law” → jac_add/jac_double
  • “在模合数里求逆失败泄漏因子” → 被投影坐标的 ZZ 吸收,最终 gcd(Z,n)
  • “用 n 当标量因为 n 含 q” → jac_mul(n, P)

10) 学习路径(按你要“能推导+能写 exploit”的目标来)

我给你一条从 CTF 实战出发、每一步都能练的路线(每阶段都有“你要会什么 / 练什么 / 推荐材料”):

Phase 1:数论与 RSA(1–2 周扎实)

你要会:

  • 模运算、欧几里得算法、扩展欧几里得(逆元)
  • CRT
  • 二次剩余/勒让德符号、Tonelli–Shanks(模素数开方)
  • RSA/多素数 RSA、φ(n)\varphi(n)、解密

练习法:

  • 手写 CRT、手写 Tonelli–Shanks
  • 做 10 道“给你 n,e,cn,e,c + 某种泄漏,恢复明文”的题

推荐:

  • CryptoHack 的 modular arithmetic / RSA 系列(非常适合 CTF)
  • 任意一本初等数论讲义(重点:CRT、Legendre、平方根算法)

Phase 2:椭圆曲线基础(1–2 周)

你要会:

  • y2=x3+ax+by^2=x^3+ax+b 群 law(加法/倍点)
  • 投影坐标(Jacobian)为何能避免频繁求逆
  • Hasse 定理与 trace 的定义:#E(Fp)=p+1t\#E(\mathbb F_p)=p+1-t

练习法:

  • 自己实现 Jacobian add/double/mul(就像上面那份)
  • 随机选小素数 p,写程序暴力数点验证 #E(Fp)\#E(\mathbb F_p)

推荐:

  • Washington《Elliptic Curves: Number Theory and Cryptography》(前半足够)
  • SageMath 文档:EllipticCurve 的基本用法(CTF 超常用)

Phase 3:ECM 因式分解(1–2 周,直接贴近这题)

你要会:

  • ECM 的“本质泄漏点”:模合数求逆失败 → gcd
  • 为什么要选“点阶在某素因子上 smooth”的曲线/点
  • 实战:如何在代码里捕捉 gcd(分母、或投影 Z)

练习法:

  • 自己写一个迷你 ECM:随机曲线 + 随机点 + 选一个 smooth 标量 kk(如 logB\prod \ell^{\lfloor\log_\ell B\rfloor}
  • 目标:能分解 60–100 bit 的合数

推荐:

  • HAC(Handbook of Applied Cryptography)里 ECM 章节(读原理即可)
  • 直接读 Sage 的 ECM 实现/文档也很有帮助(偏工程)

Phase 4:CM(复乘)与 twist(加分项,用来“看穿出题人”)

你要会:

  • CM 曲线的分类:j=0j=0(D=3)和 j=1728j=1728(D=1)是 CTF 最爱
  • 为什么会出现 4p=t2+Dy24p=t^2+Dy^2
  • twist 如何改变 trace 符号,从而改变群阶 p+1±tp+1\pm t

练习法:

  • 固定 j=0j=0 曲线 y2=x3+by^2=x^3+b,在不同 bb 上数点观察 #E(Fp)\#E(\mathbb F_p) 的变化规律
  • 练会“看到 4p=t2+34p=t^2+3”就能联想到 D=3、j=0 家族

推荐:

  • 任何 “CM method / j=0 curve” 的讲义或博客(不用追到严谨代数数论深处也能做题)
  • Silverman《AEC》太厚但权威;CTF 其实用不到那么深

11) 最后把“这题每个知识点”压缩成一句话(你复盘/写 writeup 用)

  • oracle 的本质:给你一个固定的 yy 使 y296(modn)y^2\equiv 96\pmod n(CRT 拼出来的)。(chall.py) (output.txt)
  • primes 的本质:用 p=pp2+3pp+3p=pp^2+3pp+3 做出 4p=(2pp+3)2+34p=(2pp+3)^2+3,对应 CM 判别式 3(j=0)。(chall.py)
  • 利用的本质:在 j=0j=0 家族里挑到一个 twist,让 #E(Fp)=q\#E(\mathbb F_p)=q,而 qnq\mid n,于是算 nPnPZ0(modp)Z\equiv 0\pmod p,gcd 泄漏 pp。(官方题解.py) (星盟.py)
  • 解密的本质:拿到 pp 后用判别式恢复 pppp,进而算出 q,rq,r,标准 RSA 解密。(官方题解.py) (星盟.py)

如果你愿意,我也可以按你自己的写作风格帮你把这题整理成一篇“可直接发布的中文 writeup”(包含:推导、关键公式、失败尝试、Sage 版 + 纯 Python 版两套 payload、以及每一步的 debug 观察点)。

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