Dhole Moments

2020-05-13 10:00:22

If you’re reading this wondering if you should stop using AES-GCM in some standard protocol (TLS 1.3), the short answer is “No, you’re fine”.

I specialize in secure implementations of cryptography, and my years of experience in this field have led me to dislike AES-GCM.

This post is about why I dislike AES-GCM’s design, not “why AES-GCM is insecure and should be avoided”. AES-GCM is still miles above what most developers reach for when they want to encrypt (e.g. ECB mode or CBC mode). If you want a detailed comparison, read this.

To be clear: This is solely my opinion and not representative of any company or academic institution.

What is AES-GCM?

AES-GCM is an authenticated encryption mode that uses the AES block cipher in counter mode with a polynomial MAC based on Galois field multiplication.

In order to explain why AES-GCM sucks, I have to first explain what I dislike about the AES block cipher. Then, I can describe why I’m filled with sadness every time I see the AES-GCM construction used.

What is AES?

The Advanced Encryption Standard (AES) is a specific subset of a block cipher called Rijndael.

Rijndael’s design is based on a substitution-permutation network, which broke tradition from many block ciphers of its era (including its predecessor, DES) in not using a Feistel network.

AES only includes three flavors of Rijndael: AES-128, AES-192, and AES-256. The difference between these flavors is the size of the key and the number of rounds used, but–and this is often overlooked–not the block size.

As a block cipher, AES always operates on 128-bit (16 byte) blocks of plaintext, regardless of the key size.

This is generally considered acceptable because AES is a secure pseudorandom permutation (PRP), which means that every possible plaintext block maps directly to one ciphertext block, and thus birthday collisions are not possible. (A pseudorandom function (PRF), conversely, does have birthday bound problems.)

Why AES Sucks

Art by Khia.

Side-Channels

The biggest reason why AES sucks is that its design uses a lookup table (called an S-Box) indexed by secret data, which is inherently vulnerable to cache-timing attacks (PDF).

There are workarounds for this AES vulnerability, but they either require hardware acceleration (AES-NI) or a technique called bitslicing.

The short of it is: With AES, you’re either using hardware acceleration, or you have to choose between performance and security. You cannot get fast, constant-time AES without hardware support.

Block Size

AES-128 is considered by experts to have a security level of 128 bits.

Similarly, AES-192 gets certified at 192-bit security, and AES-256 gets 256-bit security.

However, the AES block size is only 128 bits!

That might not sound like a big deal, but it severely limits the constructions you can create out of AES.

Consider the case of AES-CBC, where the output of each block of encryption is combined with the next block of plaintext (using XOR). This is typically used with a random 128-bit block (called the initialization vector, or IV) for the first block.

This means you expect a collision after encrypting (at 50% probability) blocks.

When you start getting collisions, you can break CBC mode, as this video demonstrates:

https://www.youtube.com/watch?v=v0IsYNDMV7A

This is significantly smaller than the you expect from AES.

Post-Quantum Security?

With respect to the number of attempts needed to find the correct key, cryptographers estimate that AES-128 will have a post-quantum security level of 64 bits, AES-192 will have a post-quantum security level of 96 bits, and AES-256 will have a post-quantum security level of 128 bits.

This is because Grover’s quantum search algorithm can search unsorted items in time, which can be used to reduce the total number of possible secrets from to . This effectively cuts the security level, expressed in bits, in half.

Note that this heuristic estimate is based on the number of guesses (a time factor), and doesn’t take circuit size into consideration. Grover’s algorithm also doesn’t parallelize well. The real-world security of AES may still be above 100 bits if you consider these nuances.

But remember, even AES-256 operates on 128-bit blocks.

Consequently, for AES-256, there should be approximately (plaintext, key) pairs that produce any given ciphertext block.

Furthermore, there will be many keys that, for a constant plaintext block, will produce the same ciphertext block despite being a different key entirely. (n.b. This doesn’t mean for all plaintext/ciphertext block pairings, just some arbitrary pairing.)

Concrete example: Encrypting a plaintext block consisting of sixteen NUL bytes will yield a specific 128-bit ciphertext exactly once for each given AES-128 key. However, there are times as many AES-256 keys as there are possible plaintext/ciphertexts. Keep this in mind for AES-GCM.

This means it’s conceivable to accidentally construct a protocol that, despite using AES-256 safely, has a post-quantum security level on par with AES-128, which is only 64 bits.

This would not be nearly as much of a problem if AES’s block size was 256 bits.

Real-World Example: Signal

The Signal messaging app is the state-of-the-art for private communications. If you were previously using PGP and email, you should use Signal instead.

Signal aims to provide private communications (text messaging, voice calls) between two mobile devices, piggybacking on your pre-existing contacts list.

Part of their operational requirements is that they must be user-friendly and secure on a wide range of Android devices, stretching all the way back to Android 4.4.

The Signal Protocol uses AES-CBC + HMAC-SHA256 for message encryption. Each message is encrypted with a different AES key (due to the Double Ratchet), which limits the practical blast radius of a cache-timing attack and makes practical exploitation difficult (since you can’t effectively replay decryption in order to leak bits about the key).

Thus, Signal’s message encryption is still secure even in the presence of vulnerable AES implementations.

Hooray for well-engineered protocols managing to actually protect users.
Art by Swizz.

However, the storage service in the Signal App uses AES-GCM, and this key has to be reused in order for the encrypted storage to operate.

This means, for older phones without dedicated hardware support for AES (i.e. low-priced phones from 2013, which Signal aims to support), the risk of cache-timing attacks is still present.

This is unacceptable!

What this means is, a malicious app that can flush the CPU cache and measure timing with sufficient precision can siphon the AES-GCM key used by Signal to encrypt your storage without ever violating the security boundaries enforced by the Android operating system.

As a result of the security boundaries never being crossed, these kind of side-channel attacks would likely evade forensic analysis, and would therefore be of interest to the malware developers working for nation states.

Of course, if you’re on newer hardware (i.e. Qualcomm Snapdragon 835), you have hardware-accelerated AES available, so it’s probably a moot point.

Why AES-GCM Sucks Even More

AES-GCM is an authenticated encryption mode that also supports additional authenticated data. Cryptographers call these modes AEAD.

AEAD modes are more flexible than simple block ciphers. Generally, your encryption API accepts the following:

1. The plaintext message.
2. The encryption key.
3. A nonce (: A number that must only be used once).
4. Optional additional data which will be authenticated but not encrypted.

The output of an AEAD function is both the ciphertext and an authentication tag, which is necessary (along with the key and nonce, and optional additional data) to decrypt the plaintext.

Cryptographers almost universally recommend using AEAD modes for symmetric-key data encryption.

That being said, AES-GCM is possibly my least favorite AEAD, and I’ve got good reasons to dislike it beyond simply, “It uses AES”.

The deeper you look into AES-GCM’s design, the harder you will feel this sticker.

GHASH Brittleness

The way AES-GCM is initialized is stupid: You encrypt an all-zero block with your AES key (in ECB mode) and store it in a variable called . This value is used for authenticating all messages authenticated under that AES key, rather than for a given (key, nonce) pair.
Diagram describing Galois/Counter Mode, taken from Wikipedia.
This is often sold as an advantage: Reusing allows for better performance. However, it makes GCM brittle: Reusing a nonce allows an attacker to recover H and then forge messages forever. This is called the “forbidden attack”, and led to real world practical breaks.

Let’s contrast AES-GCM with the other AEAD mode supported by TLS: ChaCha20-Poly1305, or ChaPoly for short.

ChaPoly uses one-time message authentication keys (derived from each key/nonce pair). If you manage to leak a Poly1305 key, the impact is limited to the messages encrypted under that (ChaCha20 key, nonce) pair.

While that’s still bad, it isn’t “decrypt all messages under that key forever” bad like with AES-GCM.

Note: “Message Authentication” here is symmetric, which only provides a property called message integrity, not sender authenticity. For the latter, you need asymmetric cryptography (wherein the ability to verify a message doesn’t imply the capability to generate a new signature), which is totally disparate from symmetric algorithms like AES or GHASH. You probably don’t need to care about this nuance right now, but it’s good to know in case you’re quizzed on it later.

H Reuse and Multi-User Security

If you recall, AES operates on 128-bit blocks even when 256-bit keys are used.

If we assume AES is well-behaved, we can deduce that there are approximately different 256-bit keys that will map a single plaintext block to a single ciphertext block.

This is trivial to calculate. Simply divide the number of possible keys () by the number of possible block states () to yield the number of keys that produce a given ciphertext for a single block of plaintext: .

Each key that will map an arbitrarily specific plaintext block to a specific ciphertext block is also separated in the keyspace by approximately .

This means there are approximately independent keys that will map a given all-zero plaintext block to an arbitrarily chosen value of (if we assume AES doesn’t have weird biases).

Credit: Harubaki

“Why Does This Matter?”

It means that, with keys larger than 128 bits, you can model the selection of as a 128-bit pseudorandom function, rather than a 128-bit permutation. As a result, you an expect a collision with 50% probability after only different keys are selected.

Note: Your 128-bit randomly generated AES keys already have this probability baked into their selection, but this specific analysis doesn’t really apply for 128-bit keys since AES is a PRP, not a PRF, so there is no “collision” risk. However, you end up at the same upper limit either way.

But 50% isn’t good enough for cryptographic security.

In most real-world systems, we target a collision risk. So that means our safety limit is actually different AES keys before you have to worry about reuse.

This isn’t the same thing as symmetric wear-out (where you need to re-key after a given number of encryptions to prevent nonce reuse). Rather, it means after your entire population has exhausted the safety limit of different AES keys, you have to either accept the risk or stop using AES-GCM.

If you have a billion users (), the safety limit is breached after AES keys per user (approximately 262,000).

“What Good is H Reuse for Attackers if HF differs?”

There are two numbers used in AES-GCM that are derived from the AES key. is used for block multiplication, and (the value of with a counter of 0 from the following diagram) is XORed with the final result to produce the authentication tag.

The arrow highlighted with green is HF.

It’s tempting to think that a reuse of isn’t a concern because will necessarily be randomized, which prevents an attacker from observing when collides. It’s certainly true that the single-block collision risk discussed previously for will almost certainly not also result in a collision for . And since isn’t reused unless a nonce is reused (which also leaks directly), this might seem like a non-issue.

Art by Khia.

However, it’s straightforward to go from a condition of reuse to an adaptive chosen-ciphertext attack.

1. Intercept multiple valid ciphertexts.
   
   • e.g. Multiple JWTs encrypted with {"alg":"A256GCM"}

   
   

2. Use your knowledge of , the ciphertext, and the AAD to calculate the GCM tag up to the final XOR. This, along with the existing authentication tag, will tell you the value of for a given nonce.
3. Calculate a new authentication tag for a chosen ciphertext using and your candidate value, then replay it into the target system.

While the blinding offered by XORing the final output with is sufficient to stop from being leaked directly, the protection is one-way.

Ergo, a collision in is not sufficiently thwarted by .

“How Could the Designers Have Prevented This?”

The core issue here is the AES block size, again.

If we were analyzing a 256-bit block variant of AES, and a congruent GCM construction built atop it, none of what I wrote in this section would apply.

However, the 128-bit block size was a design constraint enforced by NIST in the AES competition. This block size was during an era of 64-bit block ciphers (e.g. Triple-DES and Blowfish), so it was a significant improvement at the time.

NIST’s AES competition also inherited from the US government’s tradition of thinking in terms of “security levels”, which is why there are three different permitted key sizes (128, 192, or 256 bits).

“Why Isn’t This a Vulnerability?”

There’s always a significant gap in security, wherein something isn’t safe to recommend, but also isn’t susceptible to a known practical attack. This gap is important to keep systems secure, even when they aren’t on the bleeding edge of security.

Using 1024-bit RSA is a good example of this: No one has yet, to my knowledge, successfully factored a 1024-bit RSA public key. However, most systems have recommended a minimum 2048-bit for years (and many recommend 3072-bit or 4096-bit today).

With AES-GCM, the expected distance between collisions in is , and finding an untargeted collision requires being able to observe more than different sessions, and somehow distinguish when collides.

As a user, you know that after different keys, you’ve crossed the safety boundary for avoiding collisions. But as an attacker, you need bites at the apple, not . Additionally, you need some sort of oracle or distinguisher for when this happens.

We don’t have that kind of distinguisher available to us today. And even if we had one available, the amount of data you need to search in order for any two users in the population to reuse/collide is challenging to work with. You would need the computational and data storages of a major cloud service provider to even think about pulling the attack off.

Naturally, this isn’t a practical vulnerability. This is just another gripe I have with AES-GCM, as someone who has to work with cryptographic algorithms a lot.

Short Nonces

Although the AES block size is 16 bytes, AES-GCM nonces are only 12 bytes. The latter 4 bytes are dedicated to an internal counter, which is used with AES in Counter Mode to actually encrypt/decrypt messages.

(Yes, you can use arbitrary length nonces with AES-GCM, but if you use nonces longer than 12 bytes, they get hashed into 12 bytes anyway, so it’s not a detail most people should concern themselves with.)

If you ask a cryptographer, “How much can I encrypt safely with AES-GCM?” you’ll get two different answers.

1. Message Length Limit: AES-GCM can be used to encrypt messages up to bytes long, under a given (key, nonce) pair.
2. Number of Messages Limit: If you generate your nonces randomly, you have a 50% chance of a nonce collision after messages.
   However, 50% isn’t conservative enough for most systems, so the safety margin is usually much lower. Cryptographers generally set the key wear-out of AES-GCM at random nonces, which represents a collision probability of one in 4 billion.

These limits are acceptable for session keys for encryption-in-transit, but they impose serious operational limits on application-layer encryption with long-term keys.

Random Key Robustness

Before the advent of AEAD modes, cryptographers used to combine block cipher modes of operation (e.g. AES-CBC, AES-CTR) with a separate message authentication code algorithm (e.g. HMAC, CBC-MAC).

You had to be careful in how you composed your protocol, lest you invite Cryptographic Doom into your life. A lot of developers screwed this up. Standardized AEAD modes promised to make life easier.

Many developers gained their intuition for authenticated encryption modes from protocols like Signal’s (which combines AES-CBC with HMAC-SHA256), and would expect AES-GCM to be a drop-in replacement.

Unfortunately, GMAC doesn’t offer the same security benefits as HMAC: Finding a different (ciphertext, HMAC key) pair that produces the same authentication tag is a hard problem, due to HMAC’s reliance on cryptographic hash functions. This makes HMAC-based constructions “message committing”, which instills Random Key Robustness.

Critically, AES-GCM doesn’t have this property. You can calculate a random (ciphertext, key) pair that collides with a given authentication tag very easily.

This fact prohibits AES-GCM from being considered for use with OPAQUE (which requires RKR), one of the upcoming password-authenticated key exchange algorithms. (Read more about them here.)

Better-Designed Algorithms

You might be thinking, “Okay random furry, if you hate AES-GCM so much, what would you propose we use instead?”

I’m glad you asked!

XChaCha20-Poly1305

For encrypting messages under a long-term key, you can’t really beat XChaCha20-Poly1305.

• ChaCha is a stream cipher based on a 512-bit ARX hash function in counter mode. ChaCha doesn’t use S-Boxes. It’s fast and constant-time without hardware acceleration.
• ChaCha20 is ChaCha with 20 rounds.
• XChaCha nonces are 24 bytes, which allows you to generate them randomly and not worry about a birthday collision until about messages (for the same collision probability as AES-GCM).
• Poly1305 uses different 256-bit key for each (nonce, key) pair and is easier to implement in constant-time than AES-GCM.
• XChaCha20-Poly1305 uses the first 16 bytes of the nonce and the 256-bit key to generate a distinct subkey, and then employs the standard ChaCha20-Poly1305 construction used in TLS today.

For application-layer cryptography, XChaCha20-Poly1305 contains most of the properties you’d want from an authenticated mode.

However, like AES-GCM (and all other Polynomial MACs I’ve heard of), it is not message committing.

The Gimli Permutation

For lightweight cryptography (n.b. important for IoT), the Gimli permutation (e.g. employed in libhydrogen) is an attractive option.

Gimli is a Round 2 candidate in NIST’s Lightweight Cryptography project. The Gimli permutation offers a lot of applications: a hash function, message authentication, encryption, etc.

Critically, it’s possible to construct a message-committing protocol out of Gimli that will hit a lot of the performance goals important to embedded systems.

Closing Remarks

Despite my personal disdain for AES-GCM, if you’re using it as intended by cryptographers, it’s good enough.

Don’t throw AES-GCM out just because of my opinions. It’s very likely the best option you have.

Although I personally dislike AES and GCM, I’m still deeply appreciative of the brilliance and ingenuity that went into both designs.

My desire is for the industry to improve upon AES and GCM in future cipher designs so we can protect more people, from a wider range of threats, in more diverse protocols, at a cheaper CPU/memory/time cost.

We wouldn’t have a secure modern Internet without the work of Vincent Rijmen, Joan Daemen, John Viega, David A. McGrew, and the countless other cryptographers and security researchers who made AES-GCM possible.

Change Log

• 2021-10-26: Added section on H Reuse and Multi-User Security.

https://soatok.blog/2020/05/13/why-aes-gcm-sucks/

#AES #AESGCM #cryptography #GaloisCounterMode #opinion #SecurityGuidance #symmetricCryptography

Dhole Moments

2020-04-26 05:03:26

Let’s talk about digital signature algorithms.

Digital signature algorithms are one of the coolest ideas to come out of asymmetric (a.k.a. public-key) cryptography, but they’re so simple and straightforward that most cryptography nerds don’t spend a lot of time thinking about them.

Even though you are more likely to run into a digital signature as a building block (e.g. certificate signatures in TLS) than think about them in isolation (e.g. secure software releases), they’re still really cool and worth learning about.

What’s a Digital Signature?

A digital signature is some string that proves that a specific message was signed by some specific entity in possession of the secret half of an asymmetric key-pair. Digital Signature Algorithms define the process for securely signing and verifying messages with their associated signatures.

For example, if I have the following keypair:

• Secret key: 9080a2c7897faeb8526968161695da0f7b3afa2e8e7d8e8369a85547ab48ea05
• Public key: 482b8d3430445cdad6b5ce59778e09ab59d099120f32d316e881db1a6330390b

I can cryptographically sign the message “Dhole Moments: Never a dull moment!” with the above secret key, and it will generate the signature string: 63629779a31b623486145359c6f1d56602d8d9135e4b17fa2ae3667c8947397decd7ae01bfed08645a429f5dee906e87df4e18eefdfff9acb5b1488c9dec800f.

If you only have the message, signature string, and my public key, you can verify that I signed the message. But, very crucially, you cannot sign messages and convince someone else that they came from me. (With symmetric authentication schemes, such as HMAC, you can.)

A digital signature algorithm is considered secure if, in order for anyone else to pass off a different message as being signed by me, they would need my secret key to succeed. When this assumption holds true, we say the scheme is secure against existential forgery attacks.

How Do Digital Signatures Work?

Simple answer: They generally combine a cryptographic hash function (e.g. SHA-256) with some asymmetric operation, and the details beyond that are all magic.

More complicated answer: That depends entirely on the algorithm in question!

Art by Swizz

For example, with RSA signatures, you actually encrypt a hash of the message with your secret key to sign the message, and then you RSA-decrypt it with your public key to verify the signature. This is backwards from RSA encryption (where you do the totally sane thing: encrypt with public key, decrypt with secret key).

In contrast, with ECDSA signatures, you’re doing point arithmetic over an elliptic curve (with a per-signature random value).

Yet another class of digital signature algorithms are hash-based signatures, such as SPHINCS+ from the NIST Post-Quantum Cryptography Standardization effort, wherein your internals consist entirely of hash functions (and trees of hash functions, and stream ciphers built with other hash functions).

In all cases, the fundamental principle stays the same: You sign a message with a secret key, and can verify it with a public key.

In the interest of time, I’m not going to dive deep into how each signature algorithm works. That can be the subject of future blog posts (one for each of the algorithms in question).

Quick aside: Cryptographers who stumble across my blog might notice that I deviate from convention a bit. They typically refer to the sensitive half of an asymmetric key pair as a “private key”, but I instead call it a “secret key”.

The main reason for this is that “secret key” can be abbreviated as “sk” and public key can be abbreviated as “pk”, whereas private/public doesn’t share this convenience. If you ever come across their writings and wonder about this discrepancy, I’m breaking away from the norm and their way is more in line with the orthodoxy.

What Algorithms Should I Use?

What algorithm, indeed! (Art by circuitslime)

If you find yourself asking this question, you’re probably dangerously close to rolling your own crypto. If so, you’ll want to hire a cryptographer to make sure your designs aren’t insecure. (It’s extremely easy to design or implement otherwise-secure cryptography in an insecure way.)

Recommended Digital Signature Algorithms

(Update, 2022-05-19): I’ve published a more in-depth treatment of the Elliptic Curve Digital Signature Algorithms a few years after this post was created. A lot of the topics covered by EdDSA and ECDSA are focused on there.

EdDSA: Edwards Curve DSA

EdDSA comes in two variants: Ed25519 (widely supported in a lot of libraries and protocols) and Ed448 (higher security level, but not implemented or supported in as many places).

The IETF standardized EdDSA in RFC 8032, in an effort related to the standardization of RFC 7748 (titled: Elliptic Curves for Security).

Formally, EdDSA is derived from Schnorr signatures and defined over Edwards curves. EdDSA’s design was motivated by the real-world security failures of ECDSA:

1. Whereas ECDSA requires a per-signature secret number () to protect the secret key, EdDSA derives the per-signature nonce deterministically from a hash of the secret key and message.
2. ECDSA with biased nonces can also leak your secret key through lattice attacks. To side-step this, EdDSA uses a hash function twice the size as the prime (i.e. SHA-512 for Ed25519), which guarantees that the distribution of the output of the modular reduction is unbiased (assuming uniform random inputs).
3. ECDSA implemented over the NIST Curves is difficult to implement in constant-time: Complicated point arithmetic rules, point division, etc. EdDSA only uses operations that are easy to implement in constant-time.

For a real-world example of why EdDSA is better than ECDSA, look no further than the Minerva attacks, and the Ed25519 designer’s notes on why EdDSA stood up to the attacks.

The security benefits of EdDSA over ECDSA are so vast that FIPS 186-5 is going to include Ed25519 and Ed448.

Hooray for EdDSA adoption even in federal hellscapes.

This is kind of a big deal! The FIPS standards are notoriously slow-moving, and they’re deeply committed to a sunk cost fallacy on algorithms they previously deemed acceptable for real-world deployment.

RFC 6979: Deterministic ECDSA

Despite EdDSA being superior to ECDSA in virtually every way (performance, security, misuse-resistance), a lot of systems still require ECDSA support for the foreseeable future.

If ECDSA is here to stay, we might as well make it suck less in real-world deployments. And that’s exactly what Thomas Pornin did when he wrote RFC 6979: Deterministic Usage of DSA and ECDSA.

(Like EdDSA, Deterministic ECDSA is on its way to FIPS 186-5. Look for it in FIPS-compliant hardware 5 years from now when people actually bother to update their implementations.)

Acceptable Digital Signature Algorithms

ECDSA Signatures

The Elliptic Curve Digital Signature Algorithm (ECDSA) is the incumbent design for signatures. Unlike EdDSA, ECDSA is a more flexible design that has been applied to many different types of curves.

This is more of a curse than a blessing, as Microsoft discovered with CVE-2020-0601: You could take an existing (signature, public key) pair with standard curve, explicitly set the generator point equal to the victim’s public key, and set your secret key to 1, and Windows’s cryptography library would think, “This is fine.”

For this reason, cryptographers were generally wary of proposals to add support for Koblitz curves (including secp256k1–the Bitcoin curve) or Brainpool curves into protocols that are totally fine with NIST P-256 (and maybe NIST P-384 if you need it for compliance reasons).

For that reason, if you can’t use EdDSA or RFC 6979, your fallback option is ECDSA with one of those two curves (secp256r1, secp384r1), and making sure that you have access to a reliable cryptographic random number generator.

RSA Signatures

It’s high time the world stopped using RSA.

Not just for the reasons that Trail of Bits is arguing (which I happen to agree with), but more importantly:

Replacing RSA with EdDSA (or Deterministic ECDSA) also gives teams an opportunity to practice migrating from one cryptography algorithm suite to another, which will probably be a much-needed experience when quantum computers come along and we’re all forced to migrate to post-quantum cryptography.

Encryption is a bigger risk of being broken by quantum computers than signature schemes: If you encrypt data today, a quantum computer 20 years down the line can decrypt it immediately. Conversely, messages that are signed today cannot be broken until after a quantum computer exists.

That being said, if you only need signatures and not encryption, RSA is still acceptable. If you also need encryption, don’t use RSA for that purpose.

If you can, use PSS padding rather than PKCS#1 v1.5 padding, with SHA-256 or SHA-384. But for signatures (i.e. not encryption), PKCS#1 v1.5 padding is fine.

Dishonorable Mention

DSA Signatures

There’s really no point in using classical DSA, when ECDSA is widely supported and has more ongoing attention from cryptography experts.

If you’re designing a system in 2020 that uses DSA, my only question for you is…

WHYYYYYY?! (Art by Khia)

Upcoming Signature Algorithms

Although it is far too early to consider adopting these yet, cryptographers are working on new designs that protect against wider ranges of real-world threats.

Let’s briefly look at some of them and speculate wildly about what the future looks like. For fun. Don’t use these yet, unless you have a very good reason to do so.

Digital Signature Research Topics

Hedged Signatures

Above, we concluded that EdDSA and Deterministic ECDSA were generally the best choice (and what I’d recommend for software developers). There is one important caveat: Fault attacks.

A fault attack is when you induce a hardware fault into a computer chip, and thereby interfere with the correct functioning of a cryptography algorithm. This is especially relevant to embedded devices and IoT.

The IETF’s CFRG is investigating the use of additional randomization of messages (rather than randomizing signatures) as a safeguard against leaking secret keys through fault injection.

Of course, the Dhole Cryptography Library (my libsodium wrapper for JavaScript and PHP) already provides a form of Hedged Signatures.

If this technique is proven successful at mitigating fault injection attacks, then libsodium users will be able to follow the technique outlined in Dhole Crypto to safeguard their own protocols against fault attacks. Until then, they’re at least as safe as deterministic EdDSA today.

Threshold ECDSA Signatures

Suppose you have a scenario where you want 3-or-more people to have to sign a message before it’s valid. That’s exactly what Threshold ECDSA with Fast Trustless Setup aspires to provide.

Although this is mostly being implemented in cryptocurrency projects today, the cryptography underpinnings are fascinating. At worst, this will be one good side-effect to come from blockchain mania.

Post-Quantum Digital Signatures

Hash-Based Signatures

The best hash-based signature schemes are based on the SPHINCS design for one simple reason: It’s stateless.

In earlier hash-based digital signatures, such as XMSS, you have to maintain a state of which keys you’ve already used, to prevent attacks. Google’s Adam Langley previously described this as a “huge foot-cannon” for security (although probably okay in some environments, such as an HSM).

Lattice-Based Signatures

There are a lot of post-quantum signature algorithm designs defined over lattice groups, but my favorite lattice-based design is called FALCON. FALCON stands for FAst-Fourier Lattice-based COmpact Signatures Over NTRU.

Sign Here, Please

Who knew there would be so much complexity involved with such a simple cryptographic operation? And we didn’t even dive deep on how any of them work.

That’s the problem with cryptography: It’s a fractal of complexity. The more you know about these topics, the deeper the complexity becomes.

But if you’re implementing a protocol today and need a digital signature algorithm, use (in order of preference):

1. Ed25519 or Ed448
2. ECDSA over NIST P-256 or P-384, with RFC 6979
3. ECDSA over NIST P-256 or P-384, without RFC 6979
4. RSA (as a last resort)

But most importantly: make sure you have a cryptographer audit your designs.

(Header art by Kyume.)

https://soatok.blog/2020/04/26/a-furrys-guide-to-digital-signature-algorithms/

#crypto #cryptography #DeterministicSignatures #digitalSignatureAlgorithm #ECDSA #Ed25519 #Ed448 #EdDSA #FIPS #FIPS186 #FIPSCompliance #RFC6979 #SecurityGuidance