Use of Password Hash With Insufficient Computational Effort

The product generates a hash for a password, but it uses a scheme that does not provide a sufficient level of computational effort that would make password cracking attacks infeasible or expensive.

Description

Many password storage mechanisms compute a hash and store the hash, instead of storing the original password in plaintext. In this design, authentication involves accepting an incoming password, computing its hash, and comparing it to the stored hash.

Many hash algorithms are designed to execute quickly with minimal overhead, even cryptographic hashes. However, this efficiency is a problem for password storage, because it can reduce an attacker's workload for brute-force password cracking. If an attacker can obtain the hashes through some other method (such as SQL injection on a database that stores hashes), then the attacker can store the hashes offline and use various techniques to crack the passwords by computing hashes efficiently. Without a built-in workload, modern attacks can compute large numbers of hashes, or even exhaust the entire space of all possible passwords, within a very short amount of time, using massively-parallel computing (such as cloud computing) and GPU, ASIC, or FPGA hardware. In such a scenario, an efficient hash algorithm helps the attacker.

There are several properties of a hash scheme that are relevant to its strength against an offline, massively-parallel attack:

The amount of CPU time required to compute the hash ("stretching")

The amount of memory required to compute the hash ("memory-hard" operations)

Including a random value, along with the password, as input to the hash computation ("salting")

Given a hash, there is no known way of determining an input (e.g., a password) that produces this hash value, other than by guessing possible inputs ("one-way" hashing)

Relative to the number of all possible hashes that can be generated by the scheme, there is a low likelihood of producing the same hash for multiple different inputs ("collision resistance")

Note that the security requirements for the product may vary depending on the environment and the value of the passwords. Different schemes might not provide all of these properties, yet may still provide sufficient security for the environment. Conversely, a solution might be very strong in preserving one property, which still being very weak for an attack against another property, or it might not be able to significantly reduce the efficiency of a massively-parallel attack.

Demonstrations

The following examples help to illustrate the nature of this weakness and describe methods or techniques which can be used to mitigate the risk.

Note that the examples here are by no means exhaustive and any given weakness may have many subtle varieties, each of which may require different detection methods or runtime controls.

Example One

In this example, a new user provides a new username and password to create an account. The program hashes the new user's password then stores it in a database.

def storePassword(userName,Password):
  hasher = hashlib.new('md5')
  hasher.update(Password)
  hashedPassword = hasher.digest()

  # UpdateUserLogin returns True on success, False otherwise
  return updateUserLogin(userName,hashedPassword)

While it is good to avoid storing a cleartext password, the program does not provide a salt to the hashing function, thus increasing the chances of an attacker being able to reverse the hash and discover the original password if the database is compromised.

Fixing this is as simple as providing a salt to the hashing function on initialization:

def storePassword(userName,Password):
  hasher = hashlib.new('md5',b'SaltGoesHere')
  hasher.update(Password)
  hashedPassword = hasher.digest()

  # UpdateUserLogin returns True on success, False otherwise
  return updateUserLogin(userName,hashedPassword)

Note that regardless of the usage of a salt, the md5 hash is no longer considered secure, so this example still exhibits CWE-327.

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Use of Password Hash With Insufficient Computational Effort

Description

Demonstrations

Example One

See Also