CWE

Common Weakness Enumeration

A community-developed list of SW & HW weaknesses that can become vulnerabilities

New to CWE? click here!
CWE Most Important Hardware Weaknesses
CWE Top 25 Most Dangerous Weaknesses
Home > CWE List > CWE-407: Inefficient Algorithmic Complexity (4.16)  
ID

CWE-407: Inefficient Algorithmic Complexity

Weakness ID: 407
Vulnerability Mapping: ALLOWED This CWE ID could be used to map to real-world vulnerabilities in limited situations requiring careful review (with careful review of mapping notes)
Abstraction: 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.
View customized information:
For users who are interested in more notional aspects of a weakness. Example: educators, technical writers, and project/program managers. For users who are concerned with the practical application and details about the nature of a weakness and how to prevent it from happening. Example: tool developers, security researchers, pen-testers, incident response analysts. For users who are mapping an issue to CWE/CAPEC IDs, i.e., finding the most appropriate CWE for a specific issue (e.g., a CVE record). Example: tool developers, security researchers. For users who wish to see all available information for the CWE/CAPEC entry. For users who want to customize what details are displayed.
×

Edit Custom Filter


+ Description
An algorithm in a product has an inefficient worst-case computational complexity that may be detrimental to system performance and can be triggered by an attacker, typically using crafted manipulations that ensure that the worst case is being reached.
+ Alternate Terms
Quadratic Complexity:
Used when the algorithmic complexity is related to the square of the number of inputs (N^2)
+ Common Consequences
Section HelpThis table specifies different individual consequences associated with the weakness. The Scope identifies the application security area that is violated, while the Impact describes the negative technical impact that arises if an adversary succeeds in exploiting this weakness. The Likelihood provides information about how likely the specific consequence is expected to be seen relative to the other consequences in the list. For example, there may be high likelihood that a weakness will be exploited to achieve a certain impact, but a low likelihood that it will be exploited to achieve a different impact.
Scope Impact Likelihood
Availability

Technical Impact: DoS: Resource Consumption (CPU); DoS: Resource Consumption (Memory); DoS: Resource Consumption (Other)

The typical consequence is CPU consumption, but memory consumption and consumption of other resources can also occur.
+ Relationships
Section Help This table shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.
+ Relevant to the view "Research Concepts" (CWE-1000)
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. 405 Asymmetric Resource Consumption (Amplification)
ParentOf 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. 1333 Inefficient Regular Expression Complexity
Section Help This table shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.
+ Relevant to the view "Weaknesses for Simplified Mapping of Published Vulnerabilities" (CWE-1003)
Nature Type ID Name
MemberOf View View - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries). 1003 Weaknesses for Simplified Mapping of Published Vulnerabilities
ParentOf 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. 1333 Inefficient Regular Expression Complexity
+ Modes Of Introduction
Section HelpThe different Modes of Introduction provide information about how and when this weakness may be introduced. The Phase identifies a point in the life cycle at which introduction may occur, while the Note provides a typical scenario related to introduction during the given phase.
Phase Note
Architecture and Design
Implementation
+ Applicable Platforms
Section HelpThis listing shows possible areas for which the given weakness could appear. These may be for specific named Languages, Operating Systems, Architectures, Paradigms, Technologies, or a class of such platforms. The platform is listed along with how frequently the given weakness appears for that instance.

Languages

Class: Not Language-Specific (Undetermined Prevalence)

+ Likelihood Of Exploit
Low
+ Demonstrative Examples

Example 1

This example attempts to check if an input string is a "sentence" [REF-1164].

(bad code)
Example Language: JavaScript 
var test_string = "Bad characters: $@#";
var bad_pattern = /^(\w+\s?)*$/i;
var result = test_string.search(bad_pattern);

The regular expression has a vulnerable backtracking clause inside (\w+\s?)*$ which can be triggered to cause a Denial of Service by processing particular phrases.

To fix the backtracking problem, backtracking is removed with the ?= portion of the expression which changes it to a lookahead and the \2 which prevents the backtracking. The modified example is:

(good code)
Example Language: JavaScript 
var test_string = "Bad characters: $@#";
var good_pattern = /^((?=(\w+))\2\s?)*$/i;
var result = test_string.search(good_pattern);

Note that [REF-1164] has a more thorough (and lengthy) explanation of everything going on within the RegEx.


+ Observed Examples
Reference Description
C++ library for image metadata has "quadratic complexity" issue with unnecessarily repetitive parsing each time an invalid character is encountered
Python has "quadratic complexity" issue when converting string to int with many digits in unexpected bases
server allows ReDOS with crafted User-Agent strings, due to overlapping capture groups that cause excessive backtracking.
Perl-based email address parser has "quadratic complexity" issue via a string that does not contain a valid address
CPU consumption via inputs that cause many hash table collisions.
CPU consumption via inputs that cause many hash table collisions.
Product performs unnecessary processing before dropping an invalid packet.
CPU and memory consumption using many wildcards.
Product allows attackers to cause multiple copies of a program to be loaded more quickly than the program can detect that other copies are running, then exit. This type of error should probably have its own category, where teardown takes more time than initialization.
Network monitoring system allows remote attackers to cause a denial of service (CPU consumption and detection outage) via crafted network traffic, aka a "backtracking attack."
Wiki allows remote attackers to cause a denial of service (CPU consumption) by performing a diff between large, crafted pages that trigger the worst case algorithmic complexity.
Wiki allows remote attackers to cause a denial of service (CPU consumption) by performing a diff between large, crafted pages that trigger the worst case algorithmic complexity.
OS allows attackers to cause a denial of service (CPU consumption) via crafted Gregorian dates.
Memory leak by performing actions faster than the software can clear them.
+ Functional Areas
  • Cryptography
+ Memberships
Section HelpThis MemberOf Relationships table shows additional CWE Categories and Views that reference this weakness as a member. This information is often useful in understanding where a weakness fits within the context of external information sources.
Nature Type ID Name
MemberOf ViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries). 884 CWE Cross-section
MemberOf CategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic. 977 SFP Secondary Cluster: Design
MemberOf CategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic. 1307 CISQ Quality Measures - Maintainability
MemberOf CategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic. 1416 Comprehensive Categorization: Resource Lifecycle Management
+ Vulnerability Mapping Notes

Usage: ALLOWED-WITH-REVIEW

(this CWE ID could be used to map to real-world vulnerabilities in limited situations requiring careful review)

Reason: Abstraction

Rationale:

This CWE entry is a Class and might have Base-level children that would be more appropriate

Comments:

Examine children of this entry to see if there is a better fit
+ Taxonomy Mappings
Mapped Taxonomy Name Node ID Fit Mapped Node Name
PLOVER Algorithmic Complexity
+ References
[REF-395] Scott A. Crosby and Dan S. Wallach. "Algorithmic Complexity Attacks". Proceedings of the 12th USENIX Security Symposium. 2003-08. <https://www.usenix.org/legacy/events/sec03/tech/full_papers/crosby/crosby.pdf>.
[REF-1164] Ilya Kantor. "Catastrophic backtracking". 2020-12-13. <https://javascript.info/regexp-catastrophic-backtracking>.
+ Content History
+ Submissions
Submission Date Submitter Organization
2006-07-19
(CWE Draft 3, 2006-07-19)
PLOVER
+ Modifications
Modification Date Modifier Organization
2008-07-01 Eric Dalci Cigital
updated Time_of_Introduction
2008-09-08 CWE Content Team MITRE
updated Common_Consequences, Relationships, Other_Notes, Taxonomy_Mappings
2009-07-27 CWE Content Team MITRE
updated Functional_Areas, Other_Notes
2009-10-29 CWE Content Team MITRE
updated Common_Consequences
2009-12-28 CWE Content Team MITRE
updated Applicable_Platforms, Likelihood_of_Exploit
2011-06-01 CWE Content Team MITRE
updated Common_Consequences
2012-05-11 CWE Content Team MITRE
updated Observed_Examples, Relationships
2014-07-30 CWE Content Team MITRE
updated Relationships
2015-12-07 CWE Content Team MITRE
updated Relationships
2017-11-08 CWE Content Team MITRE
updated Likelihood_of_Exploit
2019-06-20 CWE Content Team MITRE
updated Name, Relationships, Type
2020-02-24 CWE Content Team MITRE
updated Relationships
2020-08-20 CWE Content Team MITRE
updated Relationships
2021-03-15 CWE Content Team MITRE
updated References, Relationships
2021-07-20 CWE Content Team MITRE
updated References
2022-10-13 CWE Content Team MITRE
updated Alternate_Terms, Observed_Examples, Relationships
2023-01-31 CWE Content Team MITRE
updated Demonstrative_Examples, Observed_Examples, References
2023-04-27 CWE Content Team MITRE
updated Relationships
2023-06-29 CWE Content Team MITRE
updated Mapping_Notes
+ Previous Entry Names
Change Date Previous Entry Name
2019-06-20 Algorithmic Complexity
Page Last Updated: November 19, 2024