Gen AI (SNYK)- Low Vulnerabilities

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Introduction

In this report, we will be discussing the low vulnerabilities found in the Gen AI (SNYK) project. The report is based on a 90-day term scan, and the vulnerabilities were identified using the SNYK vulnerability scanner.

Vulnerabilities Report

The following vulnerabilities were found in the Gen AI (SNYK) project:

Insufficient postMessage Validation

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: org.jetbrains.kotlin:kotlin-stdlib 2.0.0
  • Description: The postMessage function is not properly validated, allowing for potential XSS attacks.
  • Severity: Low
  • CVSS Score: 3.5

Use of Password Hash With Insufficient Computational Effort

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: org.jetbrains.kotlin:kotlin-stdlib 2.0.0
  • Description: The password hashing algorithm used is not computationally expensive enough to prevent brute-force attacks.
  • Severity: Low
  • CVSS Score: 3.5

Improper Type Validation

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: org.jetbrains.kotlin:kotlin-stdlib 2.0.0
  • Description: The type validation for user input is not properly implemented, allowing for potential type confusion attacks.
  • Severity: Low
  • CVSS Score: 3.5

Information Exposure

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: org.jetbrains.kotlin:kotlin-stdlib 2.0.0
  • Description: The project exposes sensitive information, such as API keys and database credentials.
  • Severity: Low
  • CVSS Score: 3.5

Cross-site Scripting (XSS)

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: send 0.18.0
  • Description: The project is vulnerable to XSS attacks due to the lack of proper input validation.
  • Severity: Low
  • CVSS Score: 3.5

SQL Injection

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: langchain-community 0.2.16
  • Description: The project is vulnerable to SQL injection attacks due to the lack of proper input validation.
  • Severity: Low
  • CVSS Score: 3.5

Creation of Temporary File in Directory with Insecure Permissions

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: com.google.guava:guava 31.1-jre
  • Description: The project creates temporary files in a directory with insecure permissions, allowing for potential privilege escalation attacks.
  • Severity: Low
  • CVSS Score: 3.5

Improper Handling of Case Sensitivity

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: org.springframework:spring-context 6.0.18
  • Description: The project does not properly handle case sensitivity, allowing for potential authentication bypass attacks.
  • Severity: Low
  • CVSS Score: 3.5

Server-side Request Forgery (SSRF)

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: ch.qos.logback:logback-core 1.2.13
  • Description: The project is vulnerable to SSRF attacks due to the lack of proper input validation.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2024-9143

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: openssl/libcrypto3 3.3.2-r0
  • Description: The project is vulnerable to CVE-2024-9143, a vulnerability in the OpenSSL library.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2024-50602

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: expat/libexpat 2.6.3-r0
  • Description: The project is vulnerable to CVE-2024-50602, a vulnerability in the Expat library.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2024-13176

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: openssl/libcrypto3 3.3.2-r0
  • Description: The project is vulnerable to CVE-2024-13176, a vulnerability in the OpenSSL library.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2024-12797

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: openssl/libssl3 3.3.2-r0
  • Description: The project is vulnerable to CVE-2024-12797, a vulnerability in the OpenSSL library.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2025-26519

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: musl/musl-utils 1.2.5-r0
  • Description: The project is vulnerable to CVE-2025-26519, a vulnerability in the Musl library.
  • Severity: Low
  • CVSS Score: 3.5

Use After Free

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: libsepol/libsepol1 3.1-1
  • Description: The project is vulnerable to use-after-free attacks due to the lack of proper memory management.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2024-26458

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: krb5/libkrb5support0 1.18.3-6+deb11u1
  • Description: The project is vulnerable to CVE-2024-26458, a vulnerability in the Kerberos library.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2024-4741

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: openssl/libssl1.1 1.1.1n-0+deb11u1
  • Description: The project is vulnerable to CVE-2024-4741, a vulnerability in the OpenSSL library.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2024-22365

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: pam/libpam-runtime 1.4.0-9+deb11u1
  • Description: The project is vulnerable to CVE-2024-22365, a vulnerability in the PAM library.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2025-0395

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: glibc/libc6 2.31-13+deb11u3
  • Description: The project is vulnerable to CVE-2025-0395, a vulnerability in the Glibc library.
  • Severity: Low
  • CVSS Score: 3.5

Access Restriction Bypass

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: shadow/passwd 1:4.8.1-1
  • Description: The project is vulnerable to access restriction bypass attacks due to the lack of proper access control.
  • Severity: Low
  • CVSS Score: 3.5

Arbitrary Code Injection

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: shadow/login 1:4.8.1-1
  • Description: The project is vulnerable to arbitrary code injection attacks due to the lack of proper input validation.
  • Severity: Low
  • CVSS Score: 3.5

Use of a Broken or Risky Cryptographic Algorithm

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: gnutls28/libgnutls30 3.7.1-5
  • Description: The project uses a broken or risky cryptographic algorithm, allowing for potential encryption attacks.
  • Severity: Low
  • CVSS Score: 3.5

Out-of-Bounds

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: glibc/libc6 2.31-13+deb11u3
  • Description: The project is vulnerable to out-of-bounds attacks due to the lack of proper memory management.
  • Severity: Low
  • CVSS Score: 3.5

Integer Overflow or Wraparound

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: krb5/libkrb5support0 1.18.3-6+deb11u1
  • Description: The project is vulnerable to integer overflow or wraparound attacks due to the lack of proper input validation.
  • Severity: Low
  • CVSS Score: 3.5

CVE-2024-33601

  • Project Name: Stackspot GenAI
  • Vulnerable Resource: glibc/libc-bin 2.31-13+deb11u3
  • Description: The project is vulnerable to CVE-2024-33601, a vulnerability in the Glibc library.
    Gen AI (SNYK) - Low Vulnerabilities Report Q&A =====================================================

Q: What is the Gen AI (SNYK) project?

A: The Gen AI (SNYK) project is a software development project that aims to create a secure and reliable artificial intelligence system. The project uses various open-source libraries and frameworks to build the system.

Q: What is the purpose of this report?

A: The purpose of this report is to identify and document the low vulnerabilities found in the Gen AI (SNYK) project. The report aims to provide a comprehensive overview of the vulnerabilities and their potential impact on the project.

Q: What is the severity level of the vulnerabilities found in this report?

A: The severity level of the vulnerabilities found in this report is low. The vulnerabilities are not critical and do not pose a significant risk to the project.

Q: What are the most common types of vulnerabilities found in this report?

A: The most common types of vulnerabilities found in this report are:

  • Insufficient postMessage validation
  • Use of password hash with insufficient computational effort
  • Improper type validation
  • Information exposure
  • Cross-site scripting (XSS)
  • SQL injection
  • Creation of temporary file in directory with insecure permissions
  • Improper handling of case sensitivity
  • Server-side request forgery (SSRF)
  • Use after free
  • CVE-2024-9143
  • CVE-2024-50602
  • CVE-2024-13176
  • CVE-2024-12797
  • CVE-2025-26519
  • Use after free
  • CVE-2024-26458
  • CVE-2024-4741
  • CVE-2024-22365
  • CVE-2025-0395
  • Access restriction bypass
  • Arbitrary code injection
  • Use of a broken or risky cryptographic algorithm
  • Out-of-bounds
  • Integer overflow or wraparound

Q: How can the vulnerabilities found in this report be mitigated?

A: The vulnerabilities found in this report can be mitigated by:

  • Implementing proper input validation and sanitization
  • Using secure password hashing algorithms
  • Ensuring proper memory management and handling of exceptions
  • Using secure cryptographic algorithms and protocols
  • Implementing access control and authentication mechanisms
  • Regularly updating and patching dependencies and libraries
  • Conducting regular security audits and testing

Q: What is the next step after identifying the vulnerabilities in this report?

A: The next step after identifying the vulnerabilities in this report is to:

  • Prioritize the vulnerabilities based on their severity and potential impact
  • Develop and implement a plan to mitigate the vulnerabilities
  • Conduct regular security audits and testing to ensure the vulnerabilities are addressed
  • Continuously monitor and update the project to prevent similar vulnerabilities from occurring in the future

Q: How can the Gen AI (SNYK) project ensure the security and reliability of its system?

A: The Gen AI (SNYK) project can ensure the security and reliability of its system by:

  • Implementing secure coding practices and guidelines
  • Conducting regular security audits and testing
  • Using secure dependencies and libraries
  • Regularly updating and patching dependencies and libraries
  • Implementing access control and authentication mechanisms
  • Ensuring proper memory management and handling of exceptions
  • Using secure cryptographic algorithms and protocols
  • Continuously monitoring and updating the project to prevent similar vulnerabilities from occurring in the future.