reverse-skills-max: initial public release (restored, redacted, hardened)

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+# CTF Reverse - Competition-Specific Patterns (Part 2)
+
+## Table of Contents
+- [Multi-Layer Self-Decrypting Binary (DiceCTF 2026)](#multi-layer-self-decrypting-binary-dicectf-2026)
+- [Embedded ZIP + XOR License Decryption (MetaCTF 2026)](#embedded-zip--xor-license-decryption-metactf-2026)
+- [Stack String Deobfuscation from .rodata XOR Blob (Nullcon 2026)](#stack-string-deobfuscation-from-rodata-xor-blob-nullcon-2026)
+- [Prefix Hash Brute-Force (Nullcon 2026)](#prefix-hash-brute-force-nullcon-2026)
+- [CVP/LLL Lattice for Constrained Integer Validation (HTB ShadowLabyrinth)](#cvplll-lattice-for-constrained-integer-validation-htb-shadowlabyrinth)
+- [Decision Tree Function Obfuscation (HTB WonderSMS)](#decision-tree-function-obfuscation-htb-wondersms)
+- [GF(2^8) Gaussian Elimination for Flag Recovery (ApoorvCTF 2026)](#gf28-gaussian-elimination-for-flag-recovery-apoorvctf-2026)
+- [ROP Chain Obfuscation in Modified Binary (PlaidCTF 2016)](#rop-chain-obfuscation-in-modified-binary-plaidctf-2016)
+
+---
+
+## Multi-Layer Self-Decrypting Binary (DiceCTF 2026)
+
+**Pattern (another-onion):** Binary with N layers (e.g., 256), each reading 2 key bytes, deriving keystream via SHA-256 NI instructions, XOR-decrypting the next layer, then jumping to it. Must solve within a time limit (e.g., 30 minutes).
+
+**Oracle for correct key:** Wrong key bytes produce garbage code. Correct key bytes produce code with exactly 2 `call read@plt` instructions (next layer's reads). Brute-force all 65536 candidates per layer using this oracle.
+
+**JIT execution approach (fastest):**
+```c
+// Map binary's memory at original virtual addresses into solver process
+// Compile solver at non-overlapping address: -Wl,-Ttext-segment=0x10000000
+void *text = mmap((void*)0x400000, text_size, PROT_RWX, MAP_FIXED|MAP_PRIVATE, fd, 0);
+void *bss = mmap((void*)bss_addr, bss_size, PROT_RW, MAP_FIXED|MAP_SHARED, shm_fd, 0);
+
+// Patch read@plt to inject candidate bytes instead of reading stdin
+// Patch tail jmp/call to next layer with ret/NOP to return from layer
+
+// Fork-per-candidate: COW gives isolated memory without memcpy
+for (int candidate = 0; candidate < 65536; candidate++) {
+    pid_t pid = fork();
+    if (pid == 0) {
+        // Child: remap BSS as MAP_PRIVATE (COW from shared file)
+        mmap(bss_addr, bss_size, PROT_RW, MAP_FIXED|MAP_PRIVATE, shm_fd, 0);
+        inject_key(candidate >> 8, candidate & 0xff);
+        ((void(*)())layer_addr)();  // Execute layer as function call
+        // Check: does decrypted code contain exactly 2 call read@plt?
+        if (count_read_calls(next_layer_addr) == 2) signal_found(candidate);
+        _exit(0);
+    }
+}
+```
+
+**Performance tiers:**
+| Approach | Speed | 256-layer estimate |
+|----------|-------|--------------------|
+| Python subprocess | ~2/s | days |
+| Ptrace fork injection | ~119/s | 6+ hours |
+| JIT + fork-per-candidate | ~1000/s | 140 min |
+| JIT + shared BSS + 32 workers | ~3500/s | **~17 min** |
+
+**Shared BSS optimization:** BSS (16MB+) stored in `/dev/shm` as `MAP_SHARED` in parent. Children remap as `MAP_PRIVATE` for COW. Reduces fork overhead from 16MB page-table setup to ~4KB.
+
+**Key insight:** Multi-layer decryption challenges are fundamentally about building fast brute-force engines. JIT execution (mapping binary memory into solver, running code directly as function calls) is orders of magnitude faster than ptrace. Fork-based COW provides free memory isolation per candidate.
+
+**Gotchas:**
+- Real binary may use `call` (0xe8) instead of `jmp` (0xe9) for layer transitions — adjust tail patching
+- BSS may extend beyond ELF MemSiz via kernel brk mapping — map extra space
+- SHA-NI instructions work even when not advertised in `/proc/cpuinfo`
+
+---
+
+## Embedded ZIP + XOR License Decryption (MetaCTF 2026)
+
+**Pattern (License To Rev):** Binary requires a license file as argument. Contains an embedded ZIP archive with the expected license, and an XOR-encrypted flag.
+
+**Recognition:**
+- `strings` reveals `EMBEDDED_ZIP` and `ENCRYPTED_MESSAGE` symbols
+- Binary is not stripped — `nm` or `readelf -s` shows data symbols in `.rodata`
+- `file` shows PIE executable, source file named `licensed.c`
+
+**Analysis workflow:**
+1. **Find data symbols:**
+```bash
+readelf -s binary | grep -E "EMBEDDED|ENCRYPTED|LICENSE"
+# EMBEDDED_ZIP at offset 0x2220, 384 bytes
+# ENCRYPTED_MESSAGE at offset 0x21e0, 35 bytes
+```
+
+2. **Extract embedded ZIP:**
+```python
+import struct
+with open('binary', 'rb') as f:
+    data = f.read()
+# Find PK\x03\x04 magic in .rodata
+zip_start = data.find(b'PK\x03\x04')
+# Extract ZIP (size from symbol table or until next symbol)
+open('embedded.zip', 'wb').write(data[zip_start:zip_start+384])
+```
+
+3. **Extract license from ZIP:**
+```bash
+unzip embedded.zip  # Contains license.txt
+```
+
+4. **XOR decrypt the flag:**
+```python
+license = open('license.txt', 'rb').read()
+enc_msg = open('encrypted_msg.bin', 'rb').read()  # Extract from .rodata
+flag = bytes(a ^ b for a, b in zip(enc_msg, license))
+print(flag.decode())
+```
+
+**Key insight:** No need to run the binary or bypass the expiry date check. The embedded ZIP and encrypted message are both in `.rodata` — extract and XOR offline.
+
+**Disassembly confirms:**
+- `memcmp(user_license, decompressed_embedded_zip, size)` — license validation
+- Date parsing with `sscanf("%d-%d-%d")` on `EXPIRY_DATE=` field
+- XOR loop: `ENCRYPTED_MESSAGE[i] ^ license[i]` → `putc()` per byte
+
+**Lesson:** When a binary has named symbols (`EMBEDDED_*`, `ENCRYPTED_*`), extract data directly from the binary without execution. XOR with known plaintext (the license) is trivially reversible.
+
+---
+
+## Stack String Deobfuscation from .rodata XOR Blob (Nullcon 2026)
+
+**Pattern (stack_strings_1/2):** Binary mmaps a blob from `.rodata`, XOR-deobfuscates it, then uses the blob to validate input. Flag is recovered by reimplementing the verification loop.
+
+**Recognition:**
+- `mmap()` call followed by XOR loop over `.rodata` data
+- Verification loop with running state (`eax`, `ebx`, `r9`) updated with constants like `0x9E3779B9`, `0x85EBCA6B`, `0xA97288ED`
+- `rol32()` operations with position-dependent shifts
+- Expected bytes stored in deobfuscated buffer
+
+**Approach:**
+1. Extract `.rodata` blob with pyelftools:
+   ```python
+   from elftools.elf.elffile import ELFFile
+   with open(binary, "rb") as f:
+       elf = ELFFile(f)
+       ro = elf.get_section_by_name(".rodata")
+       blob = ro.data()[offset:offset+size]
+   ```
+2. Recover embedded constants (length, magic values) by XOR with known keys from disassembly
+3. Reimplement the byte-by-byte verification loop:
+   - Each iteration: compute two hash-like values from running state
+   - XOR them together and with expected byte to recover input byte
+   - Update running state with constant additions
+
+**Variant (stack_strings_2):** Adds position permutation + state dependency on previous character:
+- Position permutation: byte `i` may go to position `pos[i]` in the output
+- State dependency: `need = (expected - rol8(prev_char, 1)) & 0xFF`
+- Must track `state` variable that updates to current character each iteration
+
+**Key constants to look for:**
+- `0x9E3779B9` (golden ratio fractional, common in hash functions)
+- `0x85EBCA6B` (MurmurHash3 finalizer constant)
+- `0xA97288ED` (related hash constant)
+- `rol32()` with shift `i & 7`
+
+---
+
+## Prefix Hash Brute-Force (Nullcon 2026)
+
+**Pattern (Hashinator):** Binary hashes every prefix of the input independently and outputs one digest per prefix. Given N output digests, the flag has N-1 characters.
+
+**Attack:** Recover input one character at a time:
+```python
+for pos in range(1, len(target_hashes)):
+    for ch in charset:
+        candidate = known_prefix + ch + padding
+        hashes = run_binary(candidate)
+        if hashes[pos] == target_hashes[pos]:
+            known_prefix += ch
+            break
+```
+
+**Key insight:** If each prefix hash is independent (no chaining/HMAC), the problem decomposes into `N` x `|charset|` binary executions. This is the hash equivalent of byte-at-a-time block cipher attacks.
+
+**Detection:** Binary outputs multiple hash lines. Changing last character only changes last hash. Different input lengths produce different numbers of output lines.
+
+---
+
+## CVP/LLL Lattice for Constrained Integer Validation (HTB ShadowLabyrinth)
+
+**Pattern:** Binary validates flag via matrix multiplication where grouped input characters are multiplied by coefficient matrices and checked against expected 64-bit results. Standard algebra fails because solutions must be printable ASCII (32-126). Lattice-based CVP (Closest Vector Problem) with LLL reduction solves this efficiently.
+
+**Identification:**
+1. Binary groups input characters (e.g., 4 at a time)
+2. Each group is multiplied by a coefficient matrix
+3. Results compared against hardcoded 64-bit values
+4. Need integer solutions in a constrained range (printable ASCII)
+
+**SageMath CVP solver:**
+```python
+from sage.all import *
+
+def solve_constrained_matrix(coefficients, targets, char_range=(32, 126)):
+    """
+    coefficients: list of coefficient rows (e.g., 4 values per group)
+    targets: expected output values
+    char_range: valid character range (printable ASCII)
+    """
+    n = len(coefficients[0])  # characters per group
+    mid = (char_range[0] + char_range[1]) // 2
+
+    # Build lattice: [coeff_matrix | I*scale]
+    # The target vector includes adjusted targets
+    M = matrix(ZZ, n + len(targets), n + len(targets))
+    scale = 1000  # Weight to constrain character range
+
+    for i, row in enumerate(coefficients):
+        for j, c in enumerate(row):
+            M[j, i] = c
+        M[n + i, i] = 1  # padding
+
+    for j in range(n):
+        M[j, len(targets) + j] = scale
+
+    target_vec = vector(ZZ, [t - sum(c * mid for c in row)
+                              for row, t in zip(coefficients, targets)]
+                        + [0] * n)
+
+    # LLL + CVP
+    L = M.LLL()
+    closest = L * L.solve_left(target_vec)  # or use Babai
+    solution = [closest[len(targets) + j] // scale + mid for j in range(n)]
+    return bytes(solution)
+```
+
+**Two-phase validation pattern:**
+1. **Phase 1 (matrix math):** Solve via CVP/LLL → recovers first N characters
+2. First N characters become AES key → decrypt `file.bin` (XOR last 16 bytes + AES-256-CBC + zlib decompress)
+3. **Phase 2 (custom VM):** Decrypted bytecode runs in custom VM, validates remaining characters via another linear system (mod 2^32)
+
+**Modular linear system solving (Phase 2 — VM validation):**
+```python
+import numpy as np
+from sympy import Matrix
+
+# M * x = v (mod 2^32)
+M_mod = Matrix(coefficients) % (2**32)
+v_mod = Matrix(targets) % (2**32)
+# Gaussian elimination in Z/(2^32)
+solution = M_mod.solve(v_mod)  # Returns flag characters
+```
+
+**Key insight:** When a binary validates input through linear combinations with large coefficients and the solution must be in a small range (printable ASCII), this is a lattice problem in disguise. LLL reduction + CVP finds the nearest lattice point, recovering the constrained solution. Cross-reference: invoke `/ctf-crypto` for LLL/CVP fundamentals (advanced-math.md in ctf-crypto).
+
+**Detection:** Binary performs matrix-like operations on grouped input, compares against 64-bit constants, and a brute-force search space is too large (e.g., 256^4 per group × 12 groups).
+
+---
+
+## Decision Tree Function Obfuscation (HTB WonderSMS)
+
+**Pattern:** Binary routes input through ~200+ auto-generated functions, each computing a polynomial expression from input positions, comparing against a constant, and branching left/right. The tree makes static analysis impractical without scripted extraction.
+
+**Identification:**
+1. Large number of similar functions with random-looking names (e.g., `f315732804`)
+2. Each function computes arithmetic on specific input positions
+3. Functions call other tree functions or a final validation function
+4. Decompiled code shows `if (expr cmp constant) call_left() else call_right()`
+
+**Ghidra headless scripting for mass extraction:**
+```python
+# Extract comparison constants from all tree functions
+# Run via: analyzeHeadless project/ tmp -import binary -postScript extract_tree.py
+from ghidra.program.model.listing import *
+from ghidra.program.model.symbol import *
+
+fm = currentProgram.getFunctionManager()
+results = []
+for func in fm.getFunctions(True):
+    name = func.getName()
+    if name.startswith('f') and name[1:].isdigit():
+        # Find CMP instruction and extract immediate constant
+        inst_iter = currentProgram.getListing().getInstructions(func.getBody(), True)
+        for inst in inst_iter:
+            if inst.getMnemonicString() == 'CMP':
+                operand = inst.getOpObjects(1)
+                if operand:
+                    results.append((name, int(operand[0].getValue())))
+```
+
+**Constraint propagation from known output format:**
+1. Start from known output bytes (e.g., `http://HTB{...}`) → fix several input positions
+2. Fixed positions cascade through arithmetic constraints → determine dependent positions
+3. Tree root equation pins down remaining free variables
+4. Recognize English words in partial flag to disambiguate multiple solutions
+
+**Key insight:** Auto-generated decision trees look overwhelming but are repetitive by construction. Script the extraction (Ghidra, Binary Ninja, radare2) rather than reversing each function manually. The tree is just a dispatcher — the real logic is in the leaf function and its constraints.
+
+**Detection:** Binary with hundreds of similarly-structured functions, 3-5 input position references per function, branching to two other functions or a common leaf.
+
+---
+
+## GF(2^8) Gaussian Elimination for Flag Recovery (ApoorvCTF 2026)
+
+**Pattern (Forge):** Stripped binary performs Gaussian elimination over GF(2^8) (Galois Field with 256 elements, using the AES polynomial). A matrix and augmentation vector are embedded in `.rodata`. The solution vector is the flag.
+
+**GF(2^8) arithmetic with AES polynomial (x^8+x^4+x^3+x+1 = 0x11b):**
+```python
+def gf_mul(a, b):
+    """Multiply in GF(2^8) with AES reduction polynomial."""
+    p = 0
+    for _ in range(8):
+        if b & 1:
+            p ^= a
+        hi = a & 0x80
+        a = (a << 1) & 0xff
+        if hi:
+            a ^= 0x1b  # Reduction: x^8 = x^4+x^3+x+1
+        b >>= 1
+    return p
+
+def gf_inv(a):
+    """Brute-force multiplicative inverse (fine for 256 elements)."""
+    if a == 0: return 0
+    for x in range(1, 256):
+        if gf_mul(a, x) == 1:
+            return x
+    return 0
+```
+
+**Solving the linear system:**
+```python
+# Extract N×N matrix + N-byte augmentation from binary .rodata
+N = 56  # Flag length
+# Build augmented matrix: N rows × (N+1) cols
+
+for col in range(N):
+    # Find non-zero pivot
+    pivot = next((r for r in range(col, N) if aug[r][col] != 0), -1)
+    if pivot != col:
+        aug[col], aug[pivot] = aug[pivot], aug[col]
+    # Scale pivot row by inverse
+    inv = gf_inv(aug[col][col])
+    aug[col] = [gf_mul(v, inv) for v in aug[col]]
+    # Eliminate column in all other rows
+    for row in range(N):
+        if row == col: continue
+        factor = aug[row][col]
+        if factor == 0: continue
+        aug[row] = [v ^ gf_mul(factor, aug[col][j]) for j, v in enumerate(aug[row])]
+
+flag = bytes(aug[i][N] for i in range(N))
+```
+
+**Key insight:** GF(2^8) is NOT regular integer arithmetic — addition is XOR, multiplication uses polynomial reduction. The AES polynomial (0x11b) is the most common; look for the constant `0x1b` in disassembly. The binary may encrypt the result with AES-GCM afterward, but the raw solution vector (pre-encryption) is the flag.
+
+**Detection:** Binary with a large matrix in `.rodata` (N² bytes), XOR-based row operations, constants `0x1b` or `0x11b`, and flag length matching sqrt of matrix size.
+
+---
+
+## ROP Chain Obfuscation in Modified Binary (PlaidCTF 2016)
+
+**Pattern (quite quixotic quest):** Modified `curl` binary with a custom `--pctfkey KEY` option. Key validation replaces `esp` with a buffer address and returns into a ~250KB ROP chain stored in a `magic_buf` symbol. The ROP chain validates the key through XOR, MD5, and constant comparisons.
+
+**Analysis approach:**
+
+1. **Detect the ROP dispatch:** Look for `mov esp, eax; ret` or similar stack pivot — this redirects execution into the ROP chain
+2. **Dump the ROP chain:** Script GDB to disassemble instructions after each return address in the chain:
+```python
+# GDB script to trace ROP gadgets
+import gdb
+
+magic_buf = 0x080b0000  # symbol address
+buf_size = 0x40000       # quarter megabyte
+offset = 0
+
+while offset < buf_size:
+    addr = int.from_bytes(gdb.selected_inferior().read_memory(magic_buf + offset, 4), 'little')
+    gdb.execute(f'x/3i {addr}')
+    # Advance past the gadget (typically 4 bytes per return address)
+    offset += 4
+```
+
+3. **Identify patterns in the chain:** Look for unrolled loops (repeated gadget sequences), `pop` instructions that skip data, and `ret imm16` that skip large blocks
+4. **Reconstruct the algorithm:** The chain typically performs:
+   - Key length check (compare with constant)
+   - Character-level operations (sum ASCII values, XOR with constants)
+   - Hash computation (MD5 of derived value)
+   - Hash prefix comparison
+   - XOR of input with hash as keystream
+   - Comparison with embedded constants
+
+5. **Extract and solve:** Dump the embedded constants, brute-force any intermediate values (e.g., character sum → MD5 with matching prefix), then XOR to recover the key:
+```python
+import hashlib
+
+# Brute-force the sum that produces correct MD5 prefix
+target_prefix = 0xc0050bdd  # extracted from ROP chain
+for s in range(128 * 0x35):  # max sum of printable chars * key_length
+    h = hashlib.md5(str(s ^ xor_constant).encode()).hexdigest()
+    if int(h[:8], 16) == target_prefix:
+        md5_key = bytes.fromhex(h)
+        break
+
+# XOR embedded values with MD5 keystream to get flag
+flag = bytes(v ^ md5_key[i % 16] for i, v in enumerate(embedded_values))
+```
+
+**Key insight:** ROP chain obfuscation ("ROPfuscation") hides algorithms in chains of return-oriented gadgets. The chain looks incomprehensible as raw addresses but becomes analyzable when you: (a) dump each gadget's disassembly, (b) filter repetitions and skip regions, (c) annotate register effects. The chain is functionally equivalent to normal code — it just uses `ret` instead of sequential execution. Large chains (100K+ gadgets) often contain unrolled loops that compress to ~1000 lines of pseudocode.
+
+See also: [patterns-ctf.md](patterns-ctf.md) for Part 1 (hidden emulator opcodes, SPN static extraction, image XOR smoothness, byte-at-a-time cipher, mathematical convergence bitmap, Windows PE XOR bitmap OCR, two-stage RC4+VM loaders, kernel module maze solving, multi-threaded VM channels). [patterns-ctf-3.md](patterns-ctf-3.md) for Part 3 (Z3 single-line Python circuit, sliding window popcount, keyboard LED Morse code, C++ destructor-hidden validation, syscall side-effect memory corruption, MFC dialog event handlers, VM sequential key-chain brute-force, Burrows-Wheeler transform inversion, OpenType font ligature exploitation, GLSL shader VM with self-modifying code, instruction counter as cryptographic state).