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:
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.
| Impact | Details |
|---|---|
|
Bypass Protection Mechanism; Gain Privileges or Assume Identity |
Scope: Access Control
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.
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| Phase(s) | Mitigation |
|---|---|
|
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. Effectiveness: High |
|
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.
|
| Nature | Type | ID | Name |
|---|---|---|---|
| ChildOf | Base Base - a weakness that is still mostly independent of a resource or technology, but with sufficient details to provide specific methods for detection and prevention. Base level weaknesses typically describe issues in terms of 2 or 3 of the following dimensions: behavior, property, technology, language, and resource. | 328 | Use of Weak Hash |
| ParentOf | Variant Variant - a weakness that is linked to a certain type of product, typically involving a specific language or technology. More specific than a Base weakness. Variant level weaknesses typically describe issues in terms of 3 to 5 of the following dimensions: behavior, property, technology, language, and resource. | 759 | Use of a One-Way Hash without a Salt |
| ParentOf | Variant Variant - a weakness that is linked to a certain type of product, typically involving a specific language or technology. More specific than a Base weakness. Variant level weaknesses typically describe issues in terms of 3 to 5 of the following dimensions: behavior, property, technology, language, and resource. | 760 | Use of a One-Way Hash with a Predictable Salt |
| Nature | Type | ID | Name |
|---|---|---|---|
| MemberOf | Category Category - a CWE entry that contains a set of other entries that share a common characteristic. | 255 | Credentials Management Errors |
| MemberOf | Category Category - a CWE entry that contains a set of other entries that share a common characteristic. | 310 | Cryptographic Issues |
| Nature | Type | ID | Name |
|---|---|---|---|
| ChildOf | Class Class - a weakness that is described in a very abstract fashion, typically independent of any specific language or technology. More specific than a Pillar Weakness, but more general than a Base Weakness. Class level weaknesses typically describe issues in terms of 1 or 2 of the following dimensions: behavior, property, and resource. | 327 | Use of a Broken or Risky Cryptographic Algorithm |
| Nature | Type | ID | Name |
|---|---|---|---|
| MemberOf | Category Category - a CWE entry that contains a set of other entries that share a common characteristic. | 1010 | Authenticate Actors |
| Phase | Note |
|---|---|
| Architecture and Design | REALIZATION: This weakness is caused during implementation of an architectural security tactic. |
Class: Not Language-Specific (Undetermined Prevalence)
Example 1
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.
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:
Note that regardless of the usage of a salt, the md5 hash is no longer considered secure, so this example still exhibits CWE-327.
Note: this is a curated list of examples for users to understand the variety of ways in which this weakness can be introduced. It is not a complete list of all CVEs that are related to this CWE entry.
| Reference | Description |
|---|---|
|
Router does not use a salt with a hash, making it easier to crack passwords.
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Router does not use a salt with a hash, making it easier to crack passwords.
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Blogging software uses a hard-coded salt when calculating a password hash.
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Database server uses the username for a salt when encrypting passwords, simplifying brute force attacks.
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Server uses a constant salt when encrypting passwords, simplifying brute force attacks.
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chain: product generates predictable MD5 hashes using a constant value combined with username, allowing authentication bypass.
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| Ordinality | Description |
|---|---|
|
Primary
|
(where the weakness exists independent of other weaknesses)
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| Method | Details |
|---|---|
|
Automated Static Analysis - Binary or Bytecode |
According to SOAR [REF-1479], the following detection techniques may be useful: Cost effective for partial coverage:
Effectiveness: SOAR Partial |
|
Manual Static Analysis - Binary or Bytecode |
According to SOAR [REF-1479], the following detection techniques may be useful: Cost effective for partial coverage:
Effectiveness: SOAR Partial |
|
Manual Static Analysis - Source Code |
According to SOAR [REF-1479], the following detection techniques may be useful: Highly cost effective:
Effectiveness: High |
|
Automated Static Analysis - Source Code |
According to SOAR [REF-1479], the following detection techniques may be useful: Highly cost effective:
Effectiveness: High |
|
Automated Static Analysis |
According to SOAR [REF-1479], the following detection techniques may be useful: Cost effective for partial coverage:
Effectiveness: SOAR Partial |
|
Architecture or Design Review |
According to SOAR [REF-1479], the following detection techniques may be useful: Highly cost effective:
Cost effective for partial coverage:
Effectiveness: High |
| Nature | Type | ID | Name |
|---|---|---|---|
| MemberOf | CategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic. | 1346 | OWASP Top Ten 2021 Category A02:2021 - Cryptographic Failures |
| MemberOf | CategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic. | 1402 | Comprehensive Categorization: Encryption |
Rationale
This CWE entry is at the Base level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.Comments
Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.| CAPEC-ID | Attack Pattern Name |
|---|---|
| CAPEC-55 | Rainbow Table Password Cracking |
| Submissions | ||
|---|---|---|
| Submission Date | Submitter | Organization |
|
2013年01月28日
(CWE 2.4, 2013年02月21日) |
CWE Content Team | MITRE |
| Created with input from members of the secure password hashing community. | ||
| Modifications | ||
| Modification Date | Modifier | Organization |
|
2025年09月09日
(CWE 4.18, 2025年09月09日) |
CWE Content Team | MITRE |
| updated Detection_Factors, References | ||
|
2024年02月29日
(CWE 4.14, 2024年02月29日) |
CWE Content Team | MITRE |
| updated Demonstrative_Examples | ||
| 2023年06月29日 | CWE Content Team | MITRE |
| updated Mapping_Notes, Relationships | ||
| 2023年04月27日 | CWE Content Team | MITRE |
| updated References, Relationships | ||
| 2023年01月31日 | CWE Content Team | MITRE |
| updated Description | ||
| 2021年10月28日 | CWE Content Team | MITRE |
| updated Relationships | ||
| 2020年02月24日 | CWE Content Team | MITRE |
| updated Relationships | ||
| 2019年06月20日 | CWE Content Team | MITRE |
| updated Related_Attack_Patterns, Relationships | ||
| 2019年01月03日 | CWE Content Team | MITRE |
| updated Description | ||
| 2017年11月08日 | CWE Content Team | MITRE |
| updated Modes_of_Introduction, References, Relationships | ||
| 2017年01月19日 | CWE Content Team | MITRE |
| updated Relationships | ||
| 2014年07月30日 | CWE Content Team | MITRE |
| updated Detection_Factors | ||
| 2014年02月18日 | CWE Content Team | MITRE |
| updated Potential_Mitigations, References | ||
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