Developer-native infrastructure for cryptographic discovery, migration, and verification.
QuanteraAI parses source with real language tooling — an AST for Python, the JCA's getInstance() call pattern (which also catches Bouncy Castle) for Java — and resolves symbols rather than pattern-matching text.
parsed 284 files · resolved 1,041 symbols
✕ RSA-2048/OAEP RsaKeyProtectionService.java:47
! ECDSA P-256 TransactionSigner.java:29
✓ AES-256-GCM VaultEncryptionService.java:42
QuanteraAI doesn't stop after detecting vulnerable cryptography. It traces each algorithm from externally exposed endpoints through infrastructure and application dependencies down to the code and configuration implementing it, then generates and verifies the migration.
Caller tracing, transitive caller tracing, key origins, variable sinks, protected assets, key roles, and application dependencies — resolved, not guessed.
Every change traces back to an explicitly approved recipe — not a model deciding on the fly.
| Finding | Recipe |
|---|---|
| RSA + key protection | → ML-KEM migration recipe |
| AES + data encryption | Retain |
| Unsupported pattern | Manual Review |
Changes the specific call sites a finding points to — not a broad refactor of surrounding code.
Implementation respects the cryptographic provider already in use rather than silently swapping it.
Application interfaces stay the same shape; new tests cover round-trip, tamper, and interop behavior.
Every migration ships as a reviewable diff with its exact inverse patch stored alongside it.
The baseline application and the migrated application are both built and tested, so "it still works" is measured, not asserted.
Crypto inventory, migration status, verification history, and an audit trail combine into one evidence report per repository.