CWE-330 使用不充分的随机数
Use of Insufficiently Random Values
结构: Simple
Abstraction: Class
状态: Stable
被利用可能性: High
基本描述
The software may use insufficiently random numbers or values in a security context that depends on unpredictable numbers.
扩展描述
When software generates predictable values in a context requiring unpredictability, it may be possible for an attacker to guess the next value that will be generated, and use this guess to impersonate another user or access sensitive information.
适用平台
Language: {'cwe_Class': 'Language-Independent', 'cwe_Prevalence': 'Undetermined'}
常见的影响
范围 | 影响 | 注释 |
---|---|---|
['Confidentiality', 'Other'] | Other | When a protection mechanism relies on random values to restrict access to a sensitive resource, such as a session ID or a seed for generating a cryptographic key, then the resource being protected could be accessed by guessing the ID or key. |
['Access Control', 'Other'] | ['Bypass Protection Mechanism', 'Other'] | If software relies on unique, unguessable IDs to identify a resource, an attacker might be able to guess an ID for a resource that is owned by another user. The attacker could then read the resource, or pre-create a resource with the same ID to prevent the legitimate program from properly sending the resource to the intended user. For example, a product might maintain session information in a file whose name is based on a username. An attacker could pre-create this file for a victim user, then set the permissions so that the application cannot generate the session for the victim, preventing the victim from using the application. |
Access Control | ['Bypass Protection Mechanism', 'Gain Privileges or Assume Identity'] | When an authorization or authentication mechanism relies on random values to restrict access to restricted functionality, such as a session ID or a seed for generating a cryptographic key, then an attacker may access the restricted functionality by guessing the ID or key. |
检测方法
DM-11.4 Black Box
Use monitoring tools that examine the software's process as it interacts with the operating system and the network. This technique is useful in cases when source code is unavailable, if the software was not developed by you, or if you want to verify that the build phase did not introduce any new weaknesses. Examples include debuggers that directly attach to the running process; system-call tracing utilities such as truss (Solaris) and strace (Linux); system activity monitors such as FileMon, RegMon, Process Monitor, and other Sysinternals utilities (Windows); and sniffers and protocol analyzers that monitor network traffic.
Attach the monitor to the process and look for library functions that indicate when randomness is being used. Run the process multiple times to see if the seed changes. Look for accesses of devices or equivalent resources that are commonly used for strong (or weak) randomness, such as /dev/urandom on Linux. Look for library or system calls that access predictable information such as process IDs and system time.
Automated Static Analysis - Binary or Bytecode
According to SOAR, the following detection techniques may be useful:
- Bytecode Weakness Analysis - including disassembler + source code weakness analysis
- Binary Weakness Analysis - including disassembler + source code weakness analysis
Manual Static Analysis - Binary or Bytecode
According to SOAR, the following detection techniques may be useful:
- Binary / Bytecode disassembler - then use manual analysis for vulnerabilities & anomalies
Dynamic Analysis with Manual Results Interpretation
According to SOAR, the following detection techniques may be useful:
- Man-in-the-middle attack tool
Manual Static Analysis - Source Code
According to SOAR, the following detection techniques may be useful:
- Focused Manual Spotcheck - Focused manual analysis of source
- Manual Source Code Review (not inspections)
Automated Static Analysis - Source Code
According to SOAR, the following detection techniques may be useful:
- Source code Weakness Analyzer
- Context-configured Source Code Weakness Analyzer
Architecture or Design Review
According to SOAR, the following detection techniques may be useful:
- Inspection (IEEE 1028 standard) (can apply to requirements, design, source code, etc.)
可能的缓解方案
Architecture and Design
策略:
Use a well-vetted algorithm that is currently considered to be strong by experts in the field, and select well-tested implementations with adequate length seeds.
In general, if a pseudo-random number generator is not advertised as being cryptographically secure, then it is probably a statistical PRNG and should not be used in security-sensitive contexts.
Pseudo-random number generators can produce predictable numbers if the generator is known and the seed can be guessed. A 256-bit seed is a good starting point for producing a "random enough" number.
Implementation
策略:
Consider a PRNG that re-seeds itself as needed from high quality pseudo-random output sources, such as hardware devices.
Testing
策略:
Use automated static analysis tools that target this type of weakness. Many modern techniques use data flow analysis to minimize the number of false positives. This is not a perfect solution, since 100% accuracy and coverage are not feasible.
MIT-2 ['Architecture and Design', 'Requirements']
策略: Libraries or Frameworks
Use products or modules that conform to FIPS 140-2 [REF-267] to avoid obvious entropy problems. Consult FIPS 140-2 Annex C ("Approved Random Number Generators").
Testing
策略:
Use tools and techniques that require manual (human) analysis, such as penetration testing, threat modeling, and interactive tools that allow the tester to record and modify an active session. These may be more effective than strictly automated techniques. This is especially the case with weaknesses that are related to design and business rules.
示例代码
例
This code generates a unique random identifier for a user's session.
bad PHP
return rand();
}
Because the seed for the PRNG is always the user's ID, the session ID will always be the same. An attacker could thus predict any user's session ID and potentially hijack the session.
This example also exhibits a Small Seed Space (CWE-339).
例
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.
bad Java
ranGen.setSeed((new Date()).getTime());
return(baseUrl + ranGen.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.
分析过的案例
标识 | 说明 | 链接 |
---|---|---|
CVE-2009-3278 | Crypto product uses rand() library function to generate a recovery key, making it easier to conduct brute force attacks. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2009-3278 |
CVE-2009-3238 | Random number generator can repeatedly generate the same value. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2009-3238 |
CVE-2009-2367 | Web application generates predictable session IDs, allowing session hijacking. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2009-2367 |
CVE-2009-2158 | Password recovery utility generates a relatively small number of random passwords, simplifying brute force attacks. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2009-2158 |
CVE-2009-0255 | Cryptographic key created with a seed based on the system time. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2009-0255 |
CVE-2008-5162 | Kernel function does not have a good entropy source just after boot. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-5162 |
CVE-2008-4905 | Blogging software uses a hard-coded salt when calculating a password hash. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-4905 |
CVE-2008-4929 | Bulletin board application uses insufficiently random names for uploaded files, allowing other users to access private files. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-4929 |
CVE-2008-3612 | Handheld device uses predictable TCP sequence numbers, allowing spoofing or hijacking of TCP connections. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-3612 |
CVE-2008-2433 | Web management console generates session IDs based on the login time, making it easier to conduct session hijacking. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-2433 |
CVE-2008-0166 | SSL library uses a weak random number generator that only generates 65,536 unique keys. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-0166 |
CVE-2008-2108 | Chain: insufficient precision causes extra zero bits to be assigned, reducing entropy for an API function that generates random numbers. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-2108 |
CVE-2008-2020 | CAPTCHA implementation does not produce enough different images, allowing bypass using a database of all possible checksums. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-2020 |
CVE-2008-0087 | DNS client uses predictable DNS transaction IDs, allowing DNS spoofing. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-0087 |
CVE-2008-0141 | Application generates passwords that are based on the time of day. | https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2008-0141 |
Notes
分类映射
映射的分类名 | ImNode ID | Fit | Mapped Node Name |
---|---|---|---|
PLOVER | Randomness and Predictability | ||
7 Pernicious Kingdoms | Insecure Randomness | ||
OWASP Top Ten 2004 | A2 | CWE More Specific | Broken Access Control |
CERT C Secure Coding | CON33-C | Imprecise | Avoid race conditions when using library functions |
CERT C Secure Coding | MSC30-C | CWE More Abstract | Do not use the rand() function for generating pseudorandom numbers |
CERT C Secure Coding | MSC32-C | CWE More Abstract | Properly seed pseudorandom number generators |
WASC | 11 | Brute Force | |
WASC | 18 | Credential/Session Prediction | |
The CERT Oracle Secure Coding Standard for Java (2011) | MSC02-J | Generate strong random numbers |
相关攻击模式
- CAPEC-112
- CAPEC-485
- CAPEC-59
引用
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