Difference between revisions of "Insecure Randomness"

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{{Template:Fortify}}
 
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==Abstract==
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[[Category:FIXME|This is the text from the old template. This needs to be rewritten using the new template.]]
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Last revision (mm/dd/yy): '''{{REVISIONMONTH}}/{{REVISIONDAY}}/{{REVISIONYEAR}}'''
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[[ASDR_TOC_Vulnerabilities|Vulnerabilities Table of Contents]]
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[[ASDR Table of Contents]]
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__TOC__
  
Standard pseudo-random number generators cannot withstand cryptographic attacks.
 
  
 
==Description==
 
==Description==
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Standard pseudo-random number generators cannot withstand cryptographic attacks.
  
 
Insecure randomness errors occur when a function that can produce predictable values is used as a source of randomness in security-sensitive context.
 
Insecure randomness errors occur when a function that can produce predictable values is used as a source of randomness in security-sensitive context.
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There are two types of PRNGs: statistical and cryptographic. Statistical PRNGs provide useful statistical properties, but their output is highly predictable and forms an easy to reproduce numeric stream that is unsuitable for use in cases where security depends on generated values being unpredictable. Cryptographic PRNGs address this problem by generating output that is more difficult to predict. For a value to be cryptographically secure, it must be impossible or highly improbable for an attacker to distinguish between it and a truly random value. In general, if a PRNG algorithm is not advertised as being cryptographically secure, then it is probably a statistical PRNG and should not be used in security-sensitive contexts.
 
There are two types of PRNGs: statistical and cryptographic. Statistical PRNGs provide useful statistical properties, but their output is highly predictable and forms an easy to reproduce numeric stream that is unsuitable for use in cases where security depends on generated values being unpredictable. Cryptographic PRNGs address this problem by generating output that is more difficult to predict. For a value to be cryptographically secure, it must be impossible or highly improbable for an attacker to distinguish between it and a truly random value. In general, if a PRNG algorithm is not advertised as being cryptographically secure, then it is probably a statistical PRNG and should not be used in security-sensitive contexts.
  
==Examples ==
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==Risk Factors==
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TBD
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==Examples==
  
 
The following code uses a statistical PRNG to create a URL for a receipt that remains active for some period of time after a purchase.
 
The following code uses a statistical PRNG to create a URL for a receipt that remains active for some period of time after a purchase.
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This code uses the Random.nextInt() function to generate "unique" identifiers for the receipt pages it generates. Because Random.nextInt() is a statistical PRNG, it is easy for an attacker to guess the strings it generates. Although the underlying design of the receipt system is also faulty, it would be more secure if it used a random number generator that did not produce predictable receipt identifiers, such as a cryptographic PRNG.
 
This code uses the Random.nextInt() function to generate "unique" identifiers for the receipt pages it generates. Because Random.nextInt() is a statistical PRNG, it is easy for an attacker to guess the strings it generates. Although the underlying design of the receipt system is also faulty, it would be more secure if it used a random number generator that did not produce predictable receipt identifiers, such as a cryptographic PRNG.
  
==Related Threats==
 
  
==Related Attacks==
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==Related [[Attacks]]==
  
==Related Vulnerabilities==
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* [[Attack 1]]
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* [[Attack 2]]
  
==Related Countermeasures==
 
  
[[Random Number Generator]]
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==Related [[Vulnerabilities]]==
  
[[:Category:Cryptography]]
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* [[Vulnerability 1]]
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* [[Vulnerabiltiy 2]]
  
==Categories==
 
  
[[Category:Cryptographic Vulnerability]]
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==Related [[Controls]]==
  
[[Category:Java]]  
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* [[Random Number Generator]]
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* [[:Category:Cryptography]]
  
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==Related [[Technical Impacts]]==
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* [[Technical Impact 1]]
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* [[Technical Impact 2]]
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==References==
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TBD
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[[Category:FIXME|add links
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In addition, one should classify vulnerability based on the following subcategories: Ex:<nowiki>[[Category:Error Handling Vulnerability]]</nowiki>
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Availability Vulnerability
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Authorization Vulnerability
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Authentication Vulnerability
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Concurrency Vulnerability
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Configuration Vulnerability
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Cryptographic Vulnerability
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Encoding Vulnerability
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Error Handling Vulnerability
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Input Validation Vulnerability
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Logging and Auditing Vulnerability
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Session Management Vulnerability]]
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__NOTOC__
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[[Category:OWASP ASDR Project]]
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[[Category:Cryptographic Vulnerability]]
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[[Category:Java]]
 
[[Category:Code Snippet]]
 
[[Category:Code Snippet]]

Revision as of 09:27, 26 September 2008

This is a Vulnerability. To view all vulnerabilities, please see the Vulnerability Category page.

This article includes content generously donated to OWASP by Fortify.JPG.

Last revision (mm/dd/yy): 09/26/2008

Vulnerabilities Table of Contents

ASDR Table of Contents


Description

Standard pseudo-random number generators cannot withstand cryptographic attacks.

Insecure randomness errors occur when a function that can produce predictable values is used as a source of randomness in security-sensitive context.

Computers are deterministic machines, and as such are unable to produce true randomness. Pseudo-Random Number Generators (PRNGs) approximate randomness algorithmically, starting with a seed from which subsequent values are calculated.

There are two types of PRNGs: statistical and cryptographic. Statistical PRNGs provide useful statistical properties, but their output is highly predictable and forms an easy to reproduce numeric stream that is unsuitable for use in cases where security depends on generated values being unpredictable. Cryptographic PRNGs address this problem by generating output that is more difficult to predict. For a value to be cryptographically secure, it must be impossible or highly improbable for an attacker to distinguish between it and a truly random value. In general, if a PRNG algorithm is not advertised as being cryptographically secure, then it is probably a statistical PRNG and should not be used in security-sensitive contexts.

Risk Factors

TBD

Examples

The following code uses a statistical PRNG to create a URL for a receipt that remains active for some period of time after a purchase.

	String GenerateReceiptURL(String baseUrl) {
		Random ranGen = new Random();
		ranGen.setSeed((new Date()).getTime());
		return(baseUrl + Gen.nextInt(400000000) + ".html");
	}

This code uses the Random.nextInt() function to generate "unique" identifiers for the receipt pages it generates. Because Random.nextInt() is a statistical PRNG, it is easy for an attacker to guess the strings it generates. Although the underlying design of the receipt system is also faulty, it would be more secure if it used a random number generator that did not produce predictable receipt identifiers, such as a cryptographic PRNG.


Related Attacks


Related Vulnerabilities


Related Controls


Related Technical Impacts


References

TBD