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Mitigation Strategies Analysis for apache/commons-lang

Mitigation Strategy: Dependency Management and Version Pinning for commons-lang

Description:

  1. Utilize a Dependency Management Tool: Ensure your project uses a dependency management tool like Maven or Gradle.
  2. Explicitly Declare commons-lang Dependency: In your project's dependency file (e.g., pom.xml, build.gradle), declare commons-lang as a dependency.
  3. Pinpoint a Specific commons-lang Version: Instead of using version ranges (like commons-lang3:3.+), specify a precise and known-good version (e.g., commons-lang3:3.12.0). This prevents automatic updates to potentially vulnerable or unstable versions.
  4. Establish a Regular Update Cadence: Schedule periodic reviews of commons-lang releases. Check for security updates and bug fixes. When a new stable and secure version is available, update the pinned version in your dependency configuration.

List of Threats Mitigated:

  • Exposure to Vulnerable commons-lang Versions (High Severity): Using an outdated version of commons-lang with known security flaws.
  • Unintended Behavior from Automatic commons-lang Updates (Medium Severity): Unexpected application behavior or regressions caused by automatic updates to newer commons-lang versions that might introduce breaking changes or new issues.

Impact:

  • Exposure to Vulnerable commons-lang Versions: Significantly reduces risk by ensuring a controlled and (ideally) up-to-date version of commons-lang is used. Regular updates further minimize this risk.
  • Unintended Behavior from Automatic commons-lang Updates: Eliminates the risk of unexpected changes from automatic updates, promoting stability and predictable dependency management for commons-lang.

Currently Implemented: Partially implemented. Maven is used for dependency management. commons-lang3 is declared as a dependency.

Missing Implementation: Version pinning is not consistently applied; version ranges are sometimes used. A formal process for regularly reviewing and updating commons-lang versions is lacking.

Mitigation Strategy: Dependency Scanning for commons-lang Vulnerabilities in CI/CD

Description:

  1. Select a Dependency Scanning Tool: Choose a tool capable of scanning dependencies for vulnerabilities (e.g., OWASP Dependency-Check, Snyk).
  2. Integrate into CI/CD Pipeline: Incorporate the chosen tool into your CI/CD pipeline as a build step.
  3. Configure Scan for commons-lang: Ensure the tool is configured to specifically scan for vulnerabilities within the commons-lang library and its transitive dependencies.
  4. Define Vulnerability Thresholds: Set severity levels for alerts (e.g., alert on high and critical vulnerabilities in commons-lang).
  5. Automate Reporting and Notifications: Configure the tool to generate reports and send notifications (e.g., email, chat) to relevant teams when vulnerabilities in commons-lang are detected.
  6. Implement Build Failure on Critical commons-lang Vulnerabilities (Recommended): Configure the CI/CD pipeline to fail the build if vulnerabilities in commons-lang (or its dependencies) exceed a defined critical severity level, preventing deployment of vulnerable code.

List of Threats Mitigated:

  • Usage of Vulnerable commons-lang Library (High Severity): Proactively identifies known security vulnerabilities present in the specific version of commons-lang used by the application.
  • Vulnerable Transitive Dependencies of commons-lang (High Severity): Detects vulnerabilities in libraries that commons-lang relies upon, which could indirectly affect the application's security through commons-lang's usage.

Impact:

  • Usage of Vulnerable commons-lang Library: Significantly reduces the risk by providing automated and continuous detection of vulnerabilities directly within commons-lang.
  • Vulnerable Transitive Dependencies of commons-lang: Significantly reduces risk by extending vulnerability detection to the full dependency tree related to commons-lang.

Currently Implemented: Partially implemented. GitHub Dependency Scanning is enabled, offering basic dependency vulnerability detection.

Missing Implementation: Full CI/CD pipeline integration is not automated. Alert thresholds are not finely tuned for commons-lang specifically. Build failure on vulnerability detection (especially for commons-lang) is not implemented. Comprehensive reporting and notification beyond GitHub's defaults are not configured.

Mitigation Strategy: Context-Aware Sanitization When Using commons-lang for Input Manipulation

Description:

  1. Identify commons-lang Usage in Input Handling: Pinpoint code sections where commons-lang functions (like StringUtils, StringEscapeUtils, etc.) are used to process or manipulate user-provided input.
  2. Analyze Context of Input Usage: Determine how the manipulated input is subsequently used (e.g., displayed in UI, used in database queries, passed to external systems).
  3. Implement Context-Specific Sanitization (Beyond commons-lang): Recognize that commons-lang's string utilities are not security sanitization libraries. Supplement commons-lang usage with dedicated sanitization or encoding methods appropriate for the context. For example:
    • For HTML output: Use a dedicated HTML escaping library (like OWASP Java Encoder) after any commons-lang string manipulation, not instead of.
    • For database queries: Utilize parameterized queries or prepared statements to prevent SQL injection, even if commons-lang is used to format parts of the query.
  4. Avoid Relying Solely on commons-lang for Security Validation: Do not treat commons-lang functions as a primary security validation mechanism. Use dedicated validation libraries for security-critical input validation.

List of Threats Mitigated:

  • Cross-Site Scripting (XSS) due to Improper Output Encoding (High Severity): If commons-lang string manipulation is used before displaying user input in web pages without proper HTML escaping.
  • SQL Injection Vulnerabilities (High Severity): If commons-lang string functions are used to construct SQL queries from user input without using parameterized queries or prepared statements.
  • Command Injection Vulnerabilities (High Severity): If commons-lang is used to process user input that is later used to construct system commands without proper command sanitization.

Impact:

  • Cross-Site Scripting (XSS): Significantly reduces risk by ensuring proper output encoding is applied after any commons-lang based string manipulation, preventing injection of malicious scripts.
  • SQL Injection: Significantly reduces risk by promoting the use of parameterized queries/prepared statements, even when commons-lang is used for string operations related to queries.
  • Command Injection: Significantly reduces risk by emphasizing the need for dedicated command sanitization, not relying on commons-lang for this purpose.

Currently Implemented: Partially implemented. Basic input validation exists in some areas. commons-lang string manipulation is sometimes used for basic input cleaning, but context-aware sanitization and dedicated security libraries are not consistently used.

Missing Implementation: Systematic context-aware sanitization is missing, especially in areas where commons-lang is used for input processing. Reliance on commons-lang for security-critical validation needs to be eliminated.

Mitigation Strategy: Regular Expression Security Review in Code Using commons-lang String Utilities

Description:

  1. Identify Regex Usage with commons-lang: Locate instances where commons-lang string utility methods (e.g., StringUtils.splitByWholeSeparatorPreserveAllTokens, StringUtils.replacePattern) are used in conjunction with regular expressions, or where custom regex logic is present in code that also uses commons-lang.
  2. Analyze Regex Complexity for ReDoS: Review the complexity of regular expressions used in these contexts. Look for patterns known to be vulnerable to Regular Expression Denial of Service (ReDoS), such as nested quantifiers or alternations.
  3. Test Regex Performance: Test regex performance with potentially malicious input strings designed to trigger ReDoS vulnerabilities.
  4. Simplify or Refactor Vulnerable Regexes: If complex and potentially vulnerable regexes are identified, simplify them or refactor the code to avoid regex usage if possible.
  5. Implement Input Size Limits for Regex Operations: When using regex operations (especially with commons-lang utilities) on user-provided input, enforce reasonable input size limits to mitigate ReDoS risks.

List of Threats Mitigated:

  • Regular Expression Denial of Service (ReDoS) (High Severity): Malicious input can cause excessive processing time in regular expression operations, leading to denial of service, particularly if commons-lang string utilities are used in regex-intensive code paths.

Impact:

  • Regular Expression Denial of Service (ReDoS): Significantly reduces risk by proactively identifying and mitigating potentially vulnerable regex patterns used in conjunction with commons-lang utilities, and by limiting input sizes for regex operations.

Currently Implemented: Partially implemented. Basic code reviews are conducted, but specific regex review for ReDoS vulnerabilities, especially in the context of commons-lang usage, is not a standard practice. Input size limits are inconsistently applied.

Missing Implementation: Dedicated regex review process focused on ReDoS prevention is needed, particularly for code sections using commons-lang string utilities and regex. Automated ReDoS vulnerability scanning is not implemented. Systematic input size limit enforcement for regex-related input processing is missing.

Mitigation Strategy: Deserialization Context Awareness When Using commons-lang in Components Handling Deserialization

Description:

  1. Identify Deserialization Points: Locate all points in the application where deserialization of Java objects occurs, especially from untrusted sources.
  2. Analyze commons-lang Usage in Deserialization Components: Review code in deserialization handlers or related components to see if commons-lang is used for any operations (e.g., string manipulation, object creation, reflection).
  3. Minimize Deserialization of Untrusted Data: Reduce or eliminate deserialization of data from untrusted sources if possible. Explore alternative data formats (like JSON) and parsing methods that are less prone to vulnerabilities than Java serialization.
  4. Restrict Deserialization Classes (If Java Serialization is Necessary): If Java serialization is unavoidable, implement mechanisms to restrict the classes that can be deserialized to a safe whitelist. This can help mitigate gadget chain attacks.
  5. Monitor Dependencies (Including Transitive) for Deserialization Vulnerabilities: Be aware that vulnerabilities in other libraries used alongside commons-lang (including transitive dependencies) within deserialization components could pose risks. Dependency scanning (as previously mentioned) is crucial here to detect vulnerabilities in the broader dependency context.

List of Threats Mitigated:

  • Java Deserialization Vulnerabilities (High Severity): While commons-lang itself is not directly vulnerable to deserialization attacks like commons-collections, if your application uses commons-lang in components that do handle deserialization of untrusted data, it can be indirectly involved in deserialization exploits. Vulnerabilities in other libraries used alongside commons-lang in deserialization contexts can also be a threat.

Impact:

  • Java Deserialization Vulnerabilities: Reduces risk by minimizing deserialization of untrusted data, restricting deserialization classes, and increasing awareness of deserialization risks in components that might use commons-lang. Dependency scanning helps identify vulnerabilities in the broader dependency context related to deserialization.

Currently Implemented: Partially implemented. Awareness of deserialization risks exists within the team, but specific mitigation measures related to commons-lang's context of use in deserialization components are not fully implemented.

Missing Implementation: Systematic review of deserialization points and commons-lang usage within those components is needed. Formal policies for minimizing deserialization of untrusted data and restricting deserialization classes are lacking. Dependency scanning for deserialization-related vulnerabilities in the broader dependency tree needs to be consistently applied.