Mobile Weak Cryptography
What Is Broken and Why
Mobile apps frequently implement cryptography incorrectly: using broken algorithms (DES, RC4), insecure modes (ECB), static/reused IVs, hardcoded keys embedded in source or resources, or non-cryptographic RNGs for key generation. Android's java.util.Random is not a CSPRNG. iOS's arc4random() is acceptable but older code uses rand(). ECB mode leaks plaintext patterns in ciphertext. Hardcoded keys are extractable via static analysis of the APK or IPA in seconds.
Key Signals
Cipher.getInstance("AES/ECB/NoPadding") or Cipher.getInstance("DES/...") in Android code
kCCAlgorithmDES, kCCAlgorithmRC4 in iOS CommonCrypto calls
- Hardcoded hex/base64 strings adjacent to crypto API calls
new Random() or Math.random() used to generate keys or IVs
arc4random() replaced by rand() or custom PRNG in security-critical iOS code
- Static byte arrays used as IV:
byte[] iv = {0,0,0,0,...}
SecretKeySpec initialized directly from a string literal: new SecretKeySpec("hardcoded".getBytes(), "AES")
- RSA without OAEP:
Cipher.getInstance("RSA/ECB/PKCS1Padding")
- Key sizes below 128-bit (AES), 2048-bit (RSA), 256-bit (EC)
Methodology
- Static analysis — Android: Decompile APK with
jadx or apktool; search for Cipher.getInstance, SecretKeySpec, MessageDigest, SecureRandom, Random()
- Static analysis — iOS: Extract IPA; search Swift/ObjC source or binary strings for
CCCrypt, kCCAlgorithm, SecKey, hardcoded key strings
- Identify algorithm strings — grep for
"DES", "ECB", "RC4", "MD5", "SHA-1" in decompiled code
- Locate hardcoded key material — search for 16/32-byte hex strings, base64-encoded strings near crypto calls
- Check IV handling — look for static IV byte arrays or IVs derived from non-random sources
- Check key storage — verify keys are in Android Keystore / iOS Secure Enclave, not in SharedPreferences or NSUserDefaults
- Dynamic analysis — use Frida to hook
Cipher.doFinal() / CCCrypt() and log key, IV, and plaintext at runtime
- Verify RNG — check that
SecureRandom (Android) and SecRandomCopyBytes (iOS) are used for all security-sensitive randomness
Payloads & Tools
# jadx search for weak algorithms
grep -r "ECB\|DES\|RC4\|MD5\|SHA-1\|new Random()" jadx-output/
# Frida — Android: hook Cipher.doFinal and log key+plaintext
Java.use("javax.crypto.Cipher").doFinal.overload("[B").implementation = function(b) {
var key = this.getParameters(); console.log("Key:", key); return this.doFinal(b); };
# Frida — iOS: hook CCCrypt to log algorithm and key
Interceptor.attach(Module.findExportByName("libSystem.B.dylib", "CCCrypt"), {
onEnter: function(args) {
console.log("alg:", args[0], "key:", hexdump(args[3], {length: args[4].toInt32()})); }});
# MobSF static analysis (Docker)
docker run -it -p 8000:8000 opensecurity/mobile-security-framework-mobsf
# Upload APK/IPA via web UI — check Crypto section of report
# semgrep rules for Android crypto
semgrep --config p/owasp-top-ten android-source/
Bypass Techniques
- String obfuscation — keys obfuscated via XOR or base64 in strings.xml; decode with CyberChef
- Split key reconstruction — key split across multiple constants assembled at runtime; trace with Frida
- Native library crypto — crypto implemented in JNI
.so; use Frida to hook CCCrypt/AES_encrypt in native code
- ProGuard obfuscation — class/method names mangled; search by API signature rather than name
Exploitation Scenarios
Scenario 1 — Hardcoded AES Key
Setup: App encrypts local SQLite DB with SecretKeySpec("SuperSecret1234".getBytes(), "AES"). → Trigger: Attacker decompiles APK, extracts key string. → Impact: Decrypts all user data without authentication.
Scenario 2 — ECB Mode Pattern Leak
Setup: App encrypts user profile images with AES-ECB. → Trigger: Attacker observes ciphertext blocks; identical plaintext blocks produce identical ciphertext. → Impact: Partial plaintext recovery and pattern detection in encrypted files.
Scenario 3 — Predictable IV Leads to Decryption
Setup: App uses new Random(System.currentTimeMillis()).nextBytes(iv) as IV for AES-CBC. → Trigger: Attacker knows approximate encryption time (from file timestamp). → Impact: Brute-forces seed space (~ms precision), recovers IV, decrypts ciphertext.
False Positives
- MD5/SHA-1 used for non-security purposes (cache key hashing, file checksums for integrity only)
Random used for UI animations or non-security feature (retry delay jitter)
- Hardcoded strings that look like keys but are test vectors or example data in comments
- ECB mode used for single-block encryption where semantic security is irrelevant (e.g., 16-byte fixed-format ID)
Fix Patterns
// Android — correct AES-GCM with Android Keystore
val keyGen = KeyGenerator.getInstance(KeyProperties.KEY_ALGORITHM_AES, "AndroidKeyStore")
keyGen.init(KeyGenParameterSpec.Builder("myKey",
KeyProperties.PURPOSE_ENCRYPT or KeyProperties.PURPOSE_DECRYPT)
.setBlockModes(KeyProperties.BLOCK_MODE_GCM)
.setEncryptionPaddings(KeyProperties.ENCRYPTION_PADDING_NONE)
.setKeySize(256).build())
val secretKey = keyGen.generateKey()
val cipher = Cipher.getInstance("AES/GCM/NoPadding")
cipher.init(Cipher.ENCRYPT_MODE, secretKey) // IV auto-generated
// iOS — AES-GCM via CryptoKit (iOS 13+)
import CryptoKit
let key = SymmetricKey(size: .bits256)
let sealedBox = try AES.GCM.seal(plaintext, using: key)
// Store key in Secure Enclave or Keychain, never in UserDefaults
- Never hardcode keys — generate at first launch and store in Android Keystore / iOS Secure Enclave
- Use AES-GCM or AES-CBC with random IV; never reuse IV with the same key
- Prefer authenticated encryption (AEAD) to detect tampering
- Use
SecureRandom (Android) / SecRandomCopyBytes (iOS) for all security-sensitive randomness
Related Skills
[[mobile-insecure-storage]] and weak crypto are tightly paired: data stored in SQLite or SharedPreferences with a hardcoded AES key is effectively the same as storing it in plaintext. [[mobile-auth-bypass]] is often enabled by weak crypto — if biometric authentication relies on a poorly keyed token rather than a hardware-bound key, cryptographic bypass is possible. The predictable IV and weak PRNG issues here parallel the session token predictability analysis in [[session-fixation]] and [[cookie-attacks]] on the web side.