Designing “honest ransomware” with Ethereum smart contracts (part II)

[continued from part I]

There are special-case solutions for common public-key algorithms to prove that a given ciphertext decrypts to an alleged plaintext. For example, with RSA the key-holder can return the plaintext without removing its padding. Recall that RSA is typically used in conjunction with a padding scheme such as PKCS1.5 or OAEP. These schemes apply randomized transformation to plaintext prior to encryption and undo that transformation after decryption. Without knowing the padding used during encryption, it is not possible to check that a given unpadded plaintext corresponds to some known ciphertext. But once the fully padded version is revealed, the user can both check that it encrypts to the original ciphertext and that removing the padding results in expected plaintext, because both of those steps are fully deterministic.

This straightforward approach does not carry over to other algorithms. For example ElGamal is a randomized public-key encryption scheme—each encryption operation uses a randomly chosen nonce, so reencrypting the exact same message can yield different ciphertexts. Yet it is not possible to recover the random nonce used after the fact, even with knowledge of the private key.  Unless the private-key owner takes additional steps to stash that nonce someplace, they are stuck in a strange position: they can decrypt any ciphertext but they can not simply prove the decryption is correct by sharing the result. That is not the case for RSA: if you can decrypt, you can also recover the transformed input complete with randomized padding. ECDSA calls for something more complex, such as a zero-knowledge proof of discrete logarithm equality to show that the multiplication of the random point (first part of the ciphertext) by the private-key was done correctly.

For a more generic solution, we can leverage blind decryption: ask the private-key holder to decrypt a ciphertext without that party realizing which ciphertext is being decrypted. This is typically achieved by exploiting homomorphic properties of cryptosystems. For instance raw RSA—without any padding— has a simple multiplicative relationship: encryption of a product is the product of encryptions.

RSA-ENC(a·b) = RSA-ENC(a) * RSA-ENC(b)

where all multiplication is done modulo N associated with the key. A similar property also holds true for decryption where X and Y are ciphertexts:


Looked another way, we can decrypt a ciphertext indirectly by decrypting a different ciphertext with known relationship to the original:


To decrypt X, we ask the ransomware operator to instead decrypt X·Y as long we know the decryption of Y. (Typically because we obtained Y by encrypting a random plaintext m of our choice to begin with.) Note the original encryption can still be using a strict padding mode such as OAEP, as long as the decryption side is willing to handle arbitrary ciphertext that results in plaintext with no specific padding format.

This additional step prevents the ransomware author from cheating: X·Y looks like a random ciphertext, completely unrelated to the original encryption X of the symmetric key. Even if there is a cheat sheet listing every such X and its associated plaintext to answer chalenges, there is no way to correlate the particular challenge presented to one of these entries. Each challenge is equally likely to be derived from any ciphertext in the collection. The intuition is that if files were not encrypted according to a consistent scheme with the same RSA public-key, it would not be possible to produce the correct answer when presented with such a random-looking ciphertext.

This step can be repeated for a small subset of files to achieve high-confidence that most files have been encrypted according to the expected scheme. As long as the challenges are selected randomly, even a small number of successful tests provides high assurance against cheating. For example, suppose ransomware encrypted a million files but replaced 2% of them with random data instead of following the claimed hybrid-encryption process. If 100 files out of that collection are randomly selected for spot-checking, odds are 87% that this departure from protocol will be caught. The downside is diminishing returns with increased coverage. While a handful of challenges can rule out cheating on a wide scale— for example every other file being corrupted— it is not feasible to prove that 100% of data is recoverable. If ransomware deliberately mangled exactly 1 file in the collection, it would take a great deal of luck to discover that; one must pick that specific file as a challenge. That also suggests a strategy of picking the files you care about most for the challenge phase, given that for every other files there is a small but non-zero probability of failure to recover. (Incidentally the ransomware author has a diametrically opposed interest in making sure users do not get to choose the challenge subset unilaterally. Otherwise they could pick the 100 files they care about most and abandon the rest.)

There is one more subtlety here: the decryption challenge returns a symmetric key, which is then used to undo the bulk symmetric-encryption applied to the file. But there is still the problem of deciding whether the outcome of that decryption is “correct” in the sense that the plaintext was a file originally belonging to this user. Neither authenticated encryption or integrity checks help with that. After all ransomware could have replaced an MP3 music file with the “correct” AES-GCM encryption of random noise. Given the right AES key, that file will decrypt successfully, including validation of the GCM tag. It will not result in recovery of the original data, which is the only outcome the user cares about. To work around this we have to posit that users have access to an oracle that can examine a file (complete with all meta-data such as directory path and timestamps) and determine whether it is one of the documents originally belonging to their collection. In practice this could be based on a catalog of hashes or digitally signatures over documents, or in the worst-case scenario, manual inspection of files.

Once the user is convinced all files are indeed encrypted correctly, the next step is crafting a smart-contract to release payment conditional on the private-key being revealed. This contract will have a function intended to be invoked by the key-holder. After checking that the parameters supplied reveal enough information to recover the private-key, the function sends funds to an address agreed upon in advance. There is one subtlety here: specifying the destination address as part of the function call or inferring it from the message sender results in a race condition. Since Ethereum contract calls are broadcast on the network before they are mind in, anyone could copy the disclosed private-key and craft an alternative method invocation to shuttle funds some place else, hoping to get mined in first. Fixing the destination during contract creation solves this problem. Even if someone else succeeds in preempting the original method invocation with a different one sending the exact same information, the funds are still delivered to the intended address.

Just in case the private-key holder never shows up, the contract also needs an “escape hatch.” That is a second, time-locked method that can be invoked by the user after a mandatory delay to recover unclaimed funds. It is critical that these are the only ways of withdrawing any funds from the contract. If there was some other avenue for getting funds out, it would result in a race condition. When the private-key holder invokes the contract to collect payment, the contract owner can observe that transaction (including the disclosed private-key) and try to race them with a different transaction that siphons funds from the contract before it can pay out.

In terms of disclosing a private-key in a manner that can be verified by Ethereum smart-contracts, there are two natural solutions:

  1. Staying in the RSA setting, the smart-contract method that receives two large integers p and q, and verifies that their product is equal to the modulus N. While doable in principle, this requires implementing arbitrary precision integer multiplication in Solidity, which does not natively support such operations. The underlying Ethereum Virtual Machine (EVM) has 256-bit integer primitives and supports multiplication of words into 256-bit product, discarding more significant bits. One could write a big-number library to multiple large numbers by splitting them into 128-bit chunks. But this runs into another practical issue around gas costs: Ethereum smart-contract execution costs money proportional to the complexity of operations. Trying to check whether the product of two 1024-bit factors is equal to a known RSA modulus can become an “expensive” operation.
  2. Switch to an elliptic-curve setting and leverage the fragility of ECDSA for deliberately disclosing private keys. Because Ethereum natively supports verification of ECDSA signatures over the secp256k1 curve, this makes for a straightforward implementation. So instead of trying to make RSA operations work in Ethereum, we alter file-encryption model. ECIES or ElGamal can both be adapted to work over secp256k1. ElGamal in particular has a simple homomorphism that can be used to mask ciphertexts: multiplying both components of an ElGamal ciphertext by a scalar produces the encryption of the original message multiplied by that scalar. As with ECDSA, the public-key is a point on the curve and the private-key is the discrete logarithm of that with respect to the generator point. Since that key-pair is equally usable for ECDSA signatures, built-in EVM operations are sufficient to check for private key disclosure. As before, the function expects two valid ECDSA signatures over fixed messages such as “hello” and “world.” But in addition verifying these signatures— which is a primitive operation built into EVM— the contract also confirms these signatures share an identical nonce.


To recap: an honest ransomware scheme— or “third-party backup encryption service”— can be implemented using smart-contracts to make data recovery contingent on payment. We encrypt all files of interest using a hybrid encryption scheme with a single public-key. When it is time to recover the data, the user and TBES execute an interactive challenge protocol to decrypt randomly selected files, verifying that the encryption followed the expected format. (This step is redundant if encryption was done by the user, unless the integrity of encrypted backups is itself in question.) Assuming the proofs check out, the next step is for the user to create a smart-contract on the Ethereum blockchain. This contract is parametrized by an amount of Ether agreed upon, public-key used for encryption and address chosen by the TBES. Once the contract is setup and funded, TBES can invoke one of its methods to disclose the private-key associated with that public-key and collect the funds.

The logic of Ethereum smart-contract execution guarantees this exchange will be fair to both sides: payment only in exchange for valid private-key and no way to get out of payment once private-key is delivered.



Updated: 6/19, to describe alternative solution for ElGamal.

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