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C#

C# static code analysis

Unique rules to find Bugs, Vulnerabilities, Security Hotspots, and Code Smells in your C# code

  • All rules 493
  • Vulnerability46
  • Bug88
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  • Quick Fix 61
Filtered: 17 rules found
symbolic-execution
    Impact
      Clean code attribute
        1. Locks should be released within the same method

           Bug
        2. A write lock should not be released when a read lock has been acquired and vice versa

           Bug
        3. First/Single should be used instead of FirstOrDefault/SingleOrDefault on collections that are known to be non-empty

           Code Smell
        4. JWT secret keys should not be disclosed

           Vulnerability
        5. Types allowed to be deserialized should be restricted

           Vulnerability
        6. Secure random number generators should not output predictable values

           Vulnerability
        7. Empty collections should not be accessed or iterated

           Bug
        8. Objects should not be disposed more than once

           Code Smell
        9. Calculations should not overflow

           Bug
        10. Arguments of public methods should be validated against null

           Code Smell
        11. Empty nullable value should not be accessed

           Bug
        12. Cipher Block Chaining IVs should be unpredictable

           Vulnerability
        13. Boolean expressions should not be gratuitous

           Code Smell
        14. Conditionally executed code should be reachable

           Bug
        15. Null pointers should not be dereferenced

           Bug
        16. Locks should be released on all paths

           Bug
        17. Password hashing functions should use an unpredictable salt

           Vulnerability

        Secure random number generators should not output predictable values

        intentionality - logical
        security
        Vulnerability
        • cwe
        • pitfall
        • symbolic-execution

        Cryptographic operations often rely on unpredictable random numbers to enhance security. These random numbers are created by cryptographically secure pseudo-random number generators (CSPRNG). It is important not to use a predictable seed with these random number generators otherwise the random numbers will also become predictable.

        Why is this an issue?

        How can I fix it?

        More Info

        Implementation Specification

        Random number generators are often used to generate random values for cryptographic algorithms. When a random number generator is used for cryptographic purposes, the generated numbers must be as random and unpredictable as possible. When the random number generator is improperly seeded with a constant or a predictable value, its output will also be predictable.

        This can have severe security implications for cryptographic operations that rely on the randomness of the generated numbers. By using a predictable seed, an attacker can potentially guess or deduce the generated numbers, compromising the security of whatever cryptographic algorithm relies on the random number generator.

        What is the potential impact?

        It is crucial to understand that the strength of cryptographic algorithms heavily relies on the quality of the random numbers used. By improperly seeding a CSPRNG, we introduce a significant weakness that can be exploited by attackers.

        Insecure cryptographic keys

        One of the primary use cases for CSPRNGs is generating cryptographic keys. If an attacker can predict the seed used to initialize the random number generator, they may be able to derive the same keys. Depending on the use case, this can lead to multiple severe outcomes, such as:

        • Being able to decrypt sensitive documents, leading to privacy breaches or identity theft.
        • Gaining access to a private key used for signing, allowing an attacker to forge digital signatures and impersonate legitimate entities.
        • Bypassing authentication mechanisms that rely on public-key infrastructure (PKI), which can be abused to gain unauthorized access to systems or networks.

        Session hijacking and man-in-the-middle attack

        Another scenario where this vulnerability can be exploited is in the generation of session tokens or nonces for secure communication protocols. If an attacker can predict the seed used to generate these tokens, they can impersonate legitimate users or intercept sensitive information.

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