Agent skill

Lattice Crypto Attacks

by yaklang in yaklang/hack-skills

Lattice-based cryptanalysis playbook. An agent skill from yaklang/hack-skills.

MITAuto-check passedSecurity

Install Lattice Crypto Attacks

skills CLI
$ npx skills add yaklang/hack-skills --skill lattice-crypto-attacks -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install yaklang/hack-skills lattice-crypto-attacks --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/yaklang/hack-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/lattice-crypto-attacks .claude/skills/lattice-crypto-attacks && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
lattice-crypto-attacks
GitHub stars
2.4k
Token cost
~3.5k tokens
SKILL.md length
787 words
Files
1
Skills in repo
27
Repo updated
First seen
Licence
MIT

At a glance

Lattice-based cryptanalysis playbook. An agent skill from yaklang/hack-skills.

  • Works in 11 steps: RELATED ROUTING → LATTICE FUNDAMENTALS → LLL ALGORITHM → …
  • Attacking RSA via Coppersmith small roots
  • SKILL.md covers 0. RELATED ROUTING, 1. LATTICE FUNDAMENTALS, 2. LLL ALGORITHM and 3. BKZ (BLOCK KORKINE-ZOLOTAREV), plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Lattice Crypto Attacks is an agent skill from yaklang/hack-skills. Lattice-based cryptanalysis playbook. Use when attacking RSA via Coppersmith small roots, recovering DSA/ECDSA nonces from bias, solving knapsack problems, or applying LLL/BKZ reduction to cryptographic constructions.

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Security, covering Cryptography. The repository describes itself as: Helping AI Agent become an awesome practical hacker! The licence is MIT.

When your agent uses it

  • Attacking RSA via Coppersmith small roots
  • Recovering DSA/ECDSA nonces from bias
  • Solving knapsack problems
  • Applying LLL/BKZ reduction to cryptographic constructions

Example prompts

  • “/lattice-crypto-attacks”

Requirements

  • Python 3

Workflow steps

11 steps, taken from the step headings in SKILL.md.

  1. RELATED ROUTING
  2. LATTICE FUNDAMENTALS
  3. LLL ALGORITHM
  4. BKZ (BLOCK KORKINE-ZOLOTAREV)
  5. COPPERSMITH'S METHOD
  6. HIDDEN NUMBER PROBLEM (HNP) — DSA/ECDSA NONCE RECOVERY
  7. KNAPSACK / SUBSET SUM ATTACKS
  8. NTRU CRYPTANALYSIS
  9. CONSTRUCTING ATTACK LATTICES — METHODOLOGY
  10. DECISION TREE
  11. COMMON PITFALLS

What it can do on your machine

Read from SKILL.md and the folder at commit 6fbf0bc. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Lattice Crypto Attacks loads about 3.5k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 787 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from yaklang/hack-skills at commit 6fbf0bc, republished under its MIT licence (© yaklang). 787 words, ~3,463 tokens.

Download SKILL.mdSave it as .claude/skills/lattice-crypto-attacks/SKILL.md (or your agent's skills folder).
name
lattice-crypto-attacks
description
Lattice-based cryptanalysis playbook. Use when attacking RSA via Coppersmith small roots, recovering DSA/ECDSA nonces from bias, solving knapsack problems, or applying LLL/BKZ reduction to cryptographic constructions.

SKILL: Lattice-Based Cryptanalysis — Expert Attack Playbook

AI LOAD INSTRUCTION: Expert lattice techniques for CTF and cryptanalysis. Covers LLL/BKZ reduction, Coppersmith's method (univariate and multivariate), Hidden Number Problem for DSA/ECDSA nonce recovery, knapsack attacks, and NTRU analysis. Base models often fail to construct the correct attack lattice (wrong dimensions, missing scaling factors) or misapply Coppersmith bounds.

Quick application guide
Problem TypeLattice TechniqueKey Parameter
RSA small rootsCoppersmith (LLL on polynomial lattice)Root bound X < N^(1/e)
RSA small dBoneh-Durfee (multivariate Coppersmith)d < N^0.292
DSA/ECDSA nonce biasHidden Number Problem → CVPBias bits known
Knapsack cipherLow-density lattice attackDensity < 0.9408
LCG truncated outputCVP on recurrence latticeUnknown bits per output
Subset sumLLL reduction on knapsack latticeElement size vs count
NTRU key recoveryLattice reduction on NTRU latticeDimension and key size

1. LATTICE FUNDAMENTALS

1.1 Definitions

A lattice L is the set of all integer linear combinations of basis vectors:

L = { a₁·b₁ + a₂·b₂ + ... + aₙ·bₙ | aᵢ ∈ ℤ }

where b₁, ..., bₙ are linearly independent vectors in ℝᵐ.

Key problems:

  • SVP (Shortest Vector Problem): Find the shortest non-zero vector in L
  • CVP (Closest Vector Problem): Given target t, find v ∈ L closest to t
  • SVP is NP-hard in general, but LLL finds an approximately short vector in polynomial time
1.2 Lattice Quality Metrics
Determinant: det(L) = |det(B)| where B is the basis matrix
Gaussian heuristic: shortest vector ≈ √(n/(2πe)) · det(L)^(1/n)

2. LLL ALGORITHM

2.1 What LLL Does

Takes a lattice basis B and produces a reduced basis B' where:

  • Vectors are nearly orthogonal
  • First vector is approximately short (within 2^((n-1)/2) factor of SVP)
  • Runs in polynomial time: O(n^5 · d · log³ B) where d = dimension, B = max entry size
2.2 SageMath Usage
python
# SageMath
M = matrix(ZZ, [
    [1, 0, 0, large_value_1],
    [0, 1, 0, large_value_2],
    [0, 0, 1, large_value_3],
    [0, 0, 0, modulus],
])

L = M.LLL()
# Short vectors in L reveal the solution
short_vector = L[0]  # first row is typically shortest
2.3 Python (fpylll)
python
from fpylll import IntegerMatrix, LLL

n = 4
A = IntegerMatrix(n, n)
# Fill matrix A...
A[0] = (1, 0, 0, large_value_1)
A[1] = (0, 1, 0, large_value_2)
A[2] = (0, 0, 1, large_value_3)
A[3] = (0, 0, 0, modulus)

LLL.reduction(A)
print(A[0])  # shortest vector

3. BKZ (BLOCK KORKINE-ZOLOTAREV)

3.1 Comparison with LLL
PropertyLLLBKZ-β
Quality2^((n-1)/2) approximation2^(n/(β-1)) approximation
SpeedPolynomialExponential in β
Block sizeFixed (2)Configurable β
Best forQuick reductionHigh-quality reduction
3.2 Usage
python
# SageMath
M = matrix(ZZ, [...])
L = M.BKZ(block_size=20)  # β = 20

# fpylll
from fpylll import BKZ
BKZ.reduction(A, BKZ.Param(block_size=20))

Rule of thumb: start with LLL, increase to BKZ if needed. BKZ block size 20-40 is usually sufficient for CTF.


4. COPPERSMITH'S METHOD

4.1 Univariate Case

Given f(x) ≡ 0 (mod N) with small root |x₀| < X, find x₀.

Bound: X < N^(1/d) where d = degree of f.

python
# SageMath — built-in small_roots
N = ...
R.<x> = PolynomialRing(Zmod(N))
f = x^3 + a*x^2 + b*x + c  # known polynomial
roots = f.small_roots(X=2^100, beta=1.0, epsilon=1/30)

Parameters:

  • X: upper bound on the root
  • beta: N = p^beta (beta=1.0 for modular root of N itself; beta=0.5 for root mod unknown factor p ≈ √N)
  • epsilon: smaller = better results but slower (try 1/30 to 1/100)
4.2 Stereotyped Message Attack (RSA)
python
# SageMath
n, e, c = ...  # RSA parameters
known_msb = ...  # known upper portion of message

R.<x> = PolynomialRing(Zmod(n))
f = (known_msb + x)^e - c

# x represents the unknown lower bits
X = 2^(unknown_bit_count)
roots = f.small_roots(X=X, beta=1.0)
if roots:
    m = known_msb + int(roots[0])
4.3 Partial Key Exposure (Factor p)

Known MSBs of p: p = p_known + x where x is small.

python
# SageMath
n = ...
p_known = ...  # known upper bits of p

R.<x> = PolynomialRing(Zmod(n))
f = p_known + x
roots = f.small_roots(X=2^unknown_bits, beta=0.5)
# beta=0.5 because p ≈ √n
if roots:
    p = p_known + int(roots[0])
    q = n // p
4.4 Multivariate Coppersmith (Howgrave-Graham)

For f(x, y) ≡ 0 (mod N):

  • No polynomial-time algorithm guaranteed
  • Heuristic methods work in practice
  • Used in Boneh-Durfee for RSA small d
python
# SageMath — Boneh-Durfee
# e*d ≡ 1 (mod phi) where phi = (p-1)(q-1)
# Rewrite: e*d = 1 + k*((n+1) - (p+q))
# Let x = k, y = (p+q), both small relative to n

R.<x, y> = PolynomialRing(ZZ)
A = (n + 1) // 2
f = 1 + x * (A + y)  # mod e

# Build shift polynomials and construct lattice
# Apply LLL to find small (x₀, y₀)

5. HIDDEN NUMBER PROBLEM (HNP) — DSA/ECDSA NONCE RECOVERY

Show full SKILL.md (324 more words)Show less
5.1 Problem Statement

Given: signatures (rᵢ, sᵢ) where nonces kᵢ have known bias (leaked MSBs or LSBs).

DSA equation: s = k⁻¹(H(m) + xr) mod q

Rearranged: k = s⁻¹(H(m) + xr) mod q

If partial bits of k are known: reduces to CVP on a lattice.

5.2 Attack Setup
python
# SageMath
def ecdsa_nonce_attack(signatures, q, known_bits, bit_position='msb'):
    """
    signatures: list of (r, s, hash, known_nonce_bits)
    q: curve order
    known_bits: number of known bits per nonce
    """
    n = len(signatures)

    # Build lattice
    B = 2^(q.nbits() - known_bits)  # bound on unknown part
    M = matrix(QQ, n + 2, n + 2)

    for i in range(n):
        r_i, s_i, h_i, a_i = signatures[i]
        t_i = Integer(inverse_mod(s_i, q) * r_i % q)
        u_i = Integer(inverse_mod(s_i, q) * h_i % q)

        M[i, i] = q
        M[n, i] = t_i
        M[n+1, i] = u_i - a_i  # a_i = known nonce bits

    M[n, n] = B / q
    M[n+1, n+1] = B

    # LLL reduction
    L = M.LLL()

    # Find row containing the private key x
    for row in L:
        x_candidate = Integer(row[n] * q / B) % q
        # Verify x_candidate against one signature
        if verify_private_key(x_candidate, signatures[0], q):
            return x_candidate

    return None
5.3 Practical Nonce Bias Sources
SourceLeaked BitsRequired Signatures
MSB bias (always 0)1 bit~100 signatures
k generated with wrong lengthVariable~50 signatures
Timing side channel1-4 bits20-100 signatures
Insecure PRNGManyFew
Reused nonce (k₁ = k₂)All2 signatures

For reused nonce (simplest case):

python
def ecdsa_reused_nonce(r, s1, s2, h1, h2, q):
    """Recover private key when nonce k is reused."""
    # s1 - s2 = k⁻¹(h1 - h2) mod q  (since r is same)
    k = ((h1 - h2) * inverse_mod(s1 - s2, q)) % q
    x = ((s1 * k - h1) * inverse_mod(r, q)) % q
    return x, k

6. KNAPSACK / SUBSET SUM ATTACKS

6.1 Low-Density Attack

Knapsack: given weights a₁,...,aₙ and target S, find x₁,...,xₙ ∈ {0,1} such that Σxᵢaᵢ = S.

Density d = n / max(log₂ aᵢ). If d < 0.9408, lattice attack works.

python
# SageMath
def knapsack_lattice(weights, target):
    """Solve subset sum via LLL lattice attack."""
    n = len(weights)

    # Build lattice (Lagarias-Odlyzko style)
    N = ceil(sqrt(n) / 2)  # scaling factor
    M = matrix(ZZ, n + 1, n + 1)

    for i in range(n):
        M[i, i] = 1
        M[i, n] = N * weights[i]
    M[n, n] = N * target

    # Alternative: CJLOSS embedding
    M2 = matrix(ZZ, n + 1, n + 2)
    for i in range(n):
        M2[i, i] = 1
        M2[i, n + 1] = N * weights[i]
    M2[n, n] = 1
    M2[n, n + 1] = N * (-target)

    L = M2.LLL()

    # Look for short vector with entries in {0, 1, -1}
    for row in L:
        if all(v in (0, 1) for v in row[:n]):
            solution = list(row[:n])
            if sum(solution[i] * weights[i] for i in range(n)) == target:
                return solution

    return None

7. NTRU CRYPTANALYSIS

7.1 NTRU Lattice
python
# SageMath
def ntru_lattice_attack(h, q, N):
    """
    Construct NTRU lattice for key recovery.
    h = public key polynomial (mod q)
    q = modulus
    N = dimension
    """
    # NTRU lattice:
    # | qI  0 |
    # | H   I |
    # where H is the circulant matrix of h

    H = matrix(ZZ, N, N)
    for i in range(N):
        for j in range(N):
            H[i, j] = h[(j - i) % N]

    M = block_matrix([
        [q * identity_matrix(N), zero_matrix(N)],
        [H, identity_matrix(N)]
    ])

    L = M.LLL()

    # Short vector in reduced basis = (f, g) private key
    for row in L:
        f = vector(row[:N])
        g = vector(row[N:])
        if f.norm() < q and g.norm() < q:
            return f, g

    return None

8. CONSTRUCTING ATTACK LATTICES — METHODOLOGY

8.1 General Recipe
1. Express the cryptographic problem as:
   "Find small x such that f(x) ≡ 0 (mod N)"
   or "Find x close to target t in some lattice L"

2. Choose lattice type:
   ├─ Polynomial lattice → Coppersmith-style
   ├─ Modular lattice → HNP-style CVP
   └─ Knapsack lattice → subset sum / CJLOSS

3. Determine dimensions:
   └─ More dimensions = better approximation but slower

4. Set scaling factors:
   └─ Balance the rows so short vector has roughly equal entries
   └─ Common: multiply by N/X where X is the root bound

5. Apply reduction:
   ├─ LLL first (fast, usually sufficient)
   └─ BKZ if LLL fails (increase block size: 20, 30, 40)

6. Extract solution:
   └─ Check reduced basis rows for valid solutions
8.2 Embedding Technique (CVP → SVP)

Transform CVP into SVP by embedding the target into the lattice:

python
# SageMath
def cvp_to_svp(basis_matrix, target, scale=1):
    """Convert CVP to SVP via Kannan's embedding."""
    n = basis_matrix.nrows()
    m = basis_matrix.ncols()

    # Augment matrix
    M = matrix(ZZ, n + 1, m + 1)
    for i in range(n):
        for j in range(m):
            M[i, j] = basis_matrix[i, j]
        M[i, m] = 0

    for j in range(m):
        M[n, j] = target[j]
    M[n, m] = scale  # scaling factor (try 1, then adjust)

    L = M.LLL()

    # Look for row with last entry = ±scale
    for row in L:
        if abs(row[m]) == scale:
            return vector(target) - vector(row[:m]) * (row[m] // abs(row[m]))

    return None
8.3 Dimension Selection Guide
ProblemTypical DimensionNotes
Coppersmith univariate (degree d)d × m where m ≈ 1/εLarger m = smaller root bound
HNP with n signaturesn + 2n ≥ known_bits_ratio × q_bits
Knapsack with n weightsn + 1 or n + 2Depends on density
LCG with n outputsn + 1More outputs = easier
Boneh-Durfee(m+1)(m+2)/2m = parameter depth

9. DECISION TREE

Lattice approach needed — which construction?
│
├─ RSA-related?
│  ├─ Small unknown part of message → Coppersmith univariate
│  │  └─ Check: unknown_bits < n_bits / e
│  ├─ Partial factor knowledge → Coppersmith mod p
│  │  └─ Use beta=0.5, X=2^unknown_bits
│  ├─ Small private exponent d → Boneh-Durfee
│  │  └─ Check: d < N^0.292
│  └─ Multiple related equations → multivariate Coppersmith
│
├─ DSA/ECDSA-related?
│  ├─ Reused nonce → direct algebraic recovery (no lattice needed)
│  ├─ Partial nonce leakage → HNP → CVP lattice
│  │  └─ Need enough signatures: n ≥ q_bits / leaked_bits
│  └─ Nonce bias → statistical HNP → larger lattice
│
├─ Knapsack / subset sum?
│  ├─ Low density (d < 0.9408) → CJLOSS lattice attack
│  ├─ High density → lattice attack unlikely to work
│  └─ Super-increasing → greedy algorithm (no lattice needed)
│
├─ LCG / PRNG?
│  ├─ Full outputs known → algebraic recovery (no lattice)
│  ├─ Truncated outputs → CVP on recurrence lattice
│  └─ Unknown modulus → use GCD of output differences
│
├─ NTRU?
│  └─ Build circulant lattice → LLL/BKZ for short key vector
│
└─ Custom problem?
   ├─ Express as "find small root of polynomial mod N" → Coppersmith
   ├─ Express as "find lattice point close to target" → CVP
   ├─ Express as "find short vector in lattice" → SVP / LLL
   └─ If none fit → probably not a lattice problem

10. COMMON PITFALLS

PitfallSymptomFix
Root bound too largesmall_roots() returns emptyReduce X, increase epsilon, verify bound satisfies Coppersmith criterion
Wrong scalingLLL finds irrelevant short vectorScale columns so target vector has balanced entries
Insufficient dimensionSolution not in reduced basisIncrease m parameter (more shift polynomials)
Wrong betaCoppersmith doesn't find factorbeta=0.5 for half-size factor, beta=1.0 for full modulus
Too few signatures (HNP)Lattice attack failsCollect more signatures with nonce bias
BKZ block size too smallSolution not short enoughIncrease block size (try 25, 30, 40)
Integer overflowSageMath crashesUse ZZ ring explicitly, avoid mixing QQ and ZZ

© yaklang, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/lattice-crypto-attacks of yaklang/hack-skills.

Open the folder on GitHubat commit 6fbf0bc

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Categories

Questions about Lattice Crypto Attacks

What does Lattice Crypto Attacks do?

Lattice-based cryptanalysis playbook. An agent skill from yaklang/hack-skills. Lattice Crypto Attacks is an agent skill from yaklang/hack-skills. Lattice-based cryptanalysis playbook.

When should I use Lattice Crypto Attacks?

Lattice Crypto Attacks fits situations like: attacking RSA via Coppersmith small roots; recovering DSA/ECDSA nonces from bias; solving knapsack problems; applying LLL/BKZ reduction to cryptographic constructions.

How do I install Lattice Crypto Attacks in Claude Code?

Run `npx skills add yaklang/hack-skills --skill lattice-crypto-attacks -a claude-code`. Or copy the skill folder (skills/lattice-crypto-attacks in yaklang/hack-skills) into .claude/skills/lattice-crypto-attacks in your project. Claude Code loads it when a task matches its description.

How do I install Lattice Crypto Attacks in Codex?

Run `npx skills add yaklang/hack-skills --skill lattice-crypto-attacks -a codex`. Or copy the skill folder (skills/lattice-crypto-attacks in yaklang/hack-skills) into .agents/skills/lattice-crypto-attacks in your project. Codex loads it when a task matches its description.

Can I use Lattice Crypto Attacks in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yaklang/hack-skills --skill lattice-crypto-attacks -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lattice-crypto-attacks, .gemini/skills/lattice-crypto-attacks, .github/skills/lattice-crypto-attacks and .opencode/skills/lattice-crypto-attacks in your project.

What does Lattice Crypto Attacks need to run?

SKILL.md names no scripts, command-line tools or credentials: Lattice Crypto Attacks is instructions for the agent only. Our summary lists: Python 3.

Does Lattice Crypto Attacks access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Lattice Crypto Attacks safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Lattice Crypto Attacks use?

Lattice Crypto Attacks is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Lattice Crypto Attacks use?

About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Lattice Crypto Attacks?

Skills that share tags, products or a category with Lattice Crypto Attacks: Bom Explore (cdxgen/cdxgen, 1.1k stars), Webcrypt MCP (putervision/state-memory-mcp, 114 stars), Crypto Analysis (hypnguyen1209/offensive-claude, 388 stars) and Security Review (valory-xyz/open-autonomy, 129 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Lattice Crypto Attacks?

yaklang (a GitHub organization) maintains it in yaklang/hack-skills, which has 2,409 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on September 13, 2026.

Source: yaklang/hack-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.