What is CWE-916?
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.
Analyzing data...
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.
Analyzing data...
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.
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.
| Impact | Scope | Explanation |
|---|---|---|
| Bypass Protection Mechanism, Gain Privileges or Assume Identity | 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. |
| Method | Approach | Effectiveness |
|---|---|---|
| Automated Static Analysis - Binary or Bytecode | According to SOAR [REF-1479], the following detection techniques may be useful: ``` Cost effective for partial coverage: ``` Bytecode Weakness Analysis - including disassembler + source code weakness analysis Binary Weakness Analysis - including disassembler + source code weakness analysis | 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: ``` Binary / Bytecode disassembler - then use manual analysis for vulnerabilities & anomalies | SOAR Partial |
| Manual Static Analysis - Source Code | According to SOAR [REF-1479], the following detection techniques may be useful: ``` Highly cost effective: ``` Focused Manual Spotcheck - Focused manual analysis of source Manual Source Code Review (not inspections) | High |
| Automated Static Analysis - Source Code | According to SOAR [REF-1479], the following detection techniques may be useful: ``` Highly cost effective: ``` Source code Weakness Analyzer Context-configured Source Code Weakness Analyzer | High |
| Automated Static Analysis | According to SOAR [REF-1479], the following detection techniques may be useful: ``` Cost effective for partial coverage: ``` Configuration Checker | SOAR Partial |
| Architecture or Design Review | According to SOAR [REF-1479], the following detection techniques may be useful: ``` Highly cost effective: ``` Formal Methods / Correct-By-Construction ``` Cost effective for partial coverage: ``` Inspection (IEEE 1028 standard) (can apply to requirements, design, source code, etc.) | High |
Below are representative vulnerabilities related to this CWE, prioritized by severity.
CWE™ Program, operated by The MITRE Corporation. Copyright © 2006–2026, The MITRE Corporation. The MITRE Corporation hereby grants you a non-exclusive, royalty-free license to use CWE for research, development, and commercial purposes. CWE Terms of Use.
CyStack VulnScan continuously discovers assets, validates vulnerabilities, and helps security teams prioritize remediation across the organization.
Explore CyStack VulnScanen