A Security Device Threat Model: The Substitution Attack

I’d like to describe and discuss a threat model for computational devices. This is generic but we will narrow it down to security-related devices. For example, portable hardware dongles used for OpenPGP/OpenSSH keys, FIDO/U2F, OATH HOTP/TOTP, PIV, payment cards, wallets etc and more permanently attached devices like a Hardware Security Module (HSM), a TPM-chip, or the hybrid variant of a mostly permanently-inserted but removable hardware security dongles.

Our context is cryptographic hardware engineering, and the purpose of the threat model is to serve as as a thought experiment for how to build and design security devices that offer better protection. The threat model is related to the Evil maid attack.

Our focus is to improve security for the end-user rather than the traditional focus to improve security for the organization that provides the token to the end-user, or to improve security for the site that the end-user is authenticating to. This is a critical but often under-appreciated distinction, and leads to surprising recommendations related to onboard key generation, randomness etc below.

The Substitution Attack

An attacker is able to substitute any component of the device (hardware or software) at any time for any period of time.

Your takeaway should be that devices should be designed to mitigate harmful consequences if any component of the device (hardware or software) is substituted for a malicious component for some period of time, at any time, during the lifespan of that component. Some designs protect better against this attack than other designs, and the threat model can be used to understand which designs are really bad, and which are less so.


The threat model involves at least one device that is well-behaving and one that is not, and we call these Good Device and Bad Device respectively. The bad device may be the same physical device as the good key, but with some minor software modification or a minor component replaced, but could also be a completely separate physical device. We don’t care about that distinction, we just care if a particular device has a malicious component in it or not. I’ll use terms like “security device”, “device”, “hardware key”, “security co-processor” etc interchangeably.

From an engineering point of view, “malicious” here includes “unintentional behavior” such as software or hardware bugs. It is not possible to differentiate an intentionally malicious device from a well-designed device with a critical bug.

Don’t attribute to malice what can be adequately explained by stupidity, but don’t na├»vely attribute to stupidity what may be deniable malicious.

What is “some period of time”?

“Some period of time” can be any length of time: seconds, minutes, days, weeks, etc.

It may also occur at any time: During manufacturing, during transportation to the user, after first usage by the user, or after a couple of months usage by the user. Note that we intentionally consider time-of-manufacturing as a vulnerable phase.

Even further, the substitution may occur multiple times. So the Good Key may be replaced with a Bad Key by the attacker for one day, then returned, and later this repeats a month later.

What is “harmful consequences”?

Since a security key has a fairly well-confined scope and purpose, we can get a fairly good exhaustive list of things that could go wrong. Harmful consequences include:

  • Attacker learns any secret keys stored on a Good Key.
  • Attacker causes user to trust a public generated by a Bad Key.
  • Attacker is able to sign something using a Good Key.
  • Attacker learns the PIN code used to unlock a Good Key.
  • Attacker learns data that is decrypted by a Good Key.

Thin vs Deep solutions

One approach to mitigate many issues arising from device substitution is to have the host (or remote site) require that the device prove that it is the intended unique device before it continues to talk to it. This require an authentication/authorization protocol, which usually involves unique device identity and out-of-band trust anchors. Such trust anchors is often problematic, since a common use-case for security device is to connect it to a host that has never seen the device before.

A weaker approach is to have the device prove that it merely belongs to a class of genuine devices from a trusted manufacturer, usually by providing a signature generated by a device-specific private key signed by the device manufacturer. This is weaker since then the user cannot differentiate two different good devices.

In both cases, the host (or remote site) would stop talking to the device if it cannot prove that it is the intended key, or at least belongs to a class of known trusted genuine devices.

Upon scrutiny, this “solution” is still vulnerable to a substitution attack, just earlier in the manufacturing chain: how can the process that injects the per-device or per-class identities/secrets know that it is putting them into a good key rather than a malicious device? Consider also the consequences if the cryptographic keys that guarantee that a device is genuine leaks.

The model of the “thin solution” is similar to the old approach to network firewalls: have a filtering firewall that only lets through “intended” traffic, and then run completely insecure protocols internally such as telnet.

The networking world has evolved, and now we have defense in depth: even within strongly firewall’ed networks, it is prudent to run for example SSH with publickey-based user authentication even on locally physical trusted networks. This approach requires more thought and adds complexity, since each level has to provide some security checking.

I’m arguing we need similar defense-in-depth for security devices. Security key designs cannot simply dodge this problem by assuming it is working in a friendly environment where component substitution never occur.

Example: Device authentication using PIN codes

To see how this threat model can be applied to reason about security key designs, let’s consider a common design.

Many security keys uses PIN codes to unlock private key operations, for example on OpenPGP cards that lacks built-in PIN-entry functionality. The software on the computer just sends a PIN code to the device, and the device allows private-key operations if the PIN code was correct.

Let’s apply the substitution threat model to this design: the attacker replaces the intended good key with a malicious device that saves a copy of the PIN code presented to it, and then gives out error messages. Once the user has entered the PIN code and gotten an error message, presumably temporarily giving up and doing other things, the attacker replaces the device back again. The attacker has learnt the PIN code, and can later use this to perform private-key operations on the good device.

This means a good design involves not sending PIN codes in clear, but use a stronger authentication protocol that allows the card to know that the PIN was correct without learning the PIN. This is implemented optionally for many OpenPGP cards today as the key-derivation-function extension. That should be mandatory, and users should not use setups that sends device authentication in the clear, and ultimately security devices should not even include support for that. Compare how I build Gnuk on my PGP card with the kdf_do=required option.

Example: Onboard non-predictable key-generation

Many devices offer both onboard key-generation, for example OpenPGP cards that generate a Ed25519 key internally on the devices, or externally where the device imports an externally generated cryptographic key.

Let’s apply the subsitution threat model to this design: the user wishes to generate a key and trust the public key that came out of that process. The attacker substitutes the device for a malicious device during key-generation, imports the private key into a good device and gives that back to the user. Most of the time except during key generation the user uses a good device but still the attacker succeeded in having the user trust a public key which the attacker knows the private key for. The substitution may be a software modification, and the method to leak the private key to the attacker may be out-of-band signalling.

This means a good design never generates key on-board, but imports them from a user-controllable environment. That approach should be mandatory, and users should not use setups that generates private keys on-board, and ultimately security devices should not even include support for that.

Example: Non-predictable randomness-generation

Many devices claims to generate random data, often with elaborate design documents explaining how good the randomness is.

Let’s apply the substitution threat model to this design: the attacker replaces the intended good key with a malicious design that generates (for the attacker) predictable randomness. The user will never be able to detect the difference since the random output is, well, random, and typically not distinguishable from weak randomness. The user cannot know if any cryptographic keys generated by a generator was faulty or not.

This means a good design never generates non-predictable randomness on the device. That approach should be mandatory, and users should not use setups that generates non-predictable randomness on the device, and ideally devices should not have this functionality.

Case-Study: Tillitis

I have warmed up a bit for this. Tillitis is a new security device with interesting properties, and core to its operation is the Compound Device Identifier (CDI), essentially your Ed25519 private key (used for SSH etc) is derived from the CDI that is computed like this:

cdi = blake2s(UDS, blake2s(device_app), USS)

Let’s apply the substitution threat model to this design: Consider someone replacing the Tillitis key with a malicious key during postal delivery of the key to the user, and the replacement device is identical with the real Tillitis key but implements the following key derivation function:

cdi = weakprng(UDS’, weakprng(device_app), USS)

Where weakprng is a compromised algorithm that is predictable for the attacker, but still appears random. Everything will work correctly, but the attacker will be able to learn the secrets used by the user, and the user will typically not be able to tell the difference since the CDI is secret and the Ed25519 public key is not self-verifiable.


Remember that it is impossible to fully protect against this attack, that’s why it is merely a thought experiment, intended to be used during design of these devices. Consider an attacker that never gives you access to a good key and as a user you only ever use a malicious device. There is no way to have good security in this situation. This is not hypothetical, many well-funded organizations do what they can to derive people from having access to trustworthy security devices. Philosophically it does not seem possible to tell if these organizations have succeeded 100% already and there are only bad security devices around where further resistance is futile, but to end on an optimistic note let’s assume that there is a non-negligible chance that they haven’t succeeded. In these situations, this threat model becomes useful to improve the situation by identifying less good designs, and that’s why the design mantra of “mitigate harmful consequences” is crucial as a takeaway from this. Let’s improve the design of security devices that further the security of its users!