CWE-916

Name

Use of Password Hash With Insufficient Computational Effort

Status

Incomplete

Publié

2013-02-21 00:00 +00:00

Dernière modif.

2024-02-29 00:00 +00:00

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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.

Extended 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.

Informations

Modes Of Introduction

Architecture and Design : REALIZATION: This weakness is caused during implementation of an architectural security tactic.

Applicable Platforms

Language

Class: Not Language-Specific (Undetermined)

Common Consequences

Scope	Impact	Likelihood
Access Control	Bypass Protection Mechanism, Gain Privileges or Assume Identity Note: If an attacker can gain access to the hashes, then the lack of sufficient computational effort will make it easier to conduct brute force attacks using techniques such as rainbow tables, or specialized hardware such as GPUs, which can be much faster than general-purpose CPUs for computing hashes.

Observed Examples

Reference	Description
CVE-2008-1526	Router does not use a salt with a hash, making it easier to crack passwords.
CVE-2006-1058	Router does not use a salt with a hash, making it easier to crack passwords.
CVE-2008-4905	Blogging software uses a hard-coded salt when calculating a password hash.
CVE-2002-1657	Database server uses the username for a salt when encrypting passwords, simplifying brute force attacks.
CVE-2001-0967	Server uses a constant salt when encrypting passwords, simplifying brute force attacks.
CVE-2005-0408	chain: product generates predictable MD5 hashes using a constant value combined with username, allowing authentication bypass.

Potential Mitigations

Phases : Architecture and Design

Use an adaptive hash function that can be configured to change the amount of computational effort needed to compute the hash, such as the number of iterations ("stretching") or the amount of memory required. Some hash functions perform salting automatically. These functions can significantly increase the overhead for a brute force attack compared to intentionally-fast functions such as MD5. For example, rainbow table attacks can become infeasible due to the high computing overhead. Finally, since computing power gets faster and cheaper over time, the technique can be reconfigured to increase the workload without forcing an entire replacement of the algorithm in use.

Some hash functions that have one or more of these desired properties include bcrypt [REF-291], scrypt [REF-292], and PBKDF2 [REF-293]. While there is active debate about which of these is the most effective, they are all stronger than using salts with hash functions with very little computing overhead.

Note that using these functions can have an impact on performance, so they require special consideration to avoid denial-of-service attacks. However, their configurability provides finer control over how much CPU and memory is used, so it could be adjusted to suit the environment's needs.

Phases : Implementation // Architecture and Design
When using industry-approved techniques, use them correctly. Don't cut corners by skipping resource-intensive steps (CWE-325). These steps are often essential for preventing common attacks.