mitigations.md

Mitigation Strategies Analysis for rsyslog/liblognorm

Mitigation Strategy: Secure Rulebase Storage and Management

• Description:

  1. Identify Sensitive Data: Determine which parts of your log data and the resulting parsed fields are considered sensitive.
  2. Choose Storage Location: Select a secure directory on the file system outside of any web-accessible root. This directory should not be world-readable or writable.
  3. Set Permissions: Use chmod and chown (or equivalent) to set restrictive permissions:
     • Owner: A dedicated, non-root user account that the application runs under. Read-only access to the rulebase.
     • Group: A dedicated group (if necessary) with read-only permissions.
     • Others: No permissions (---).
     • Write Access: Only an administrative user or a dedicated configuration management process (with elevated privileges only during deployment) should have write access.
  4. Configuration Management (Optional but Recommended):
     • Use Ansible, Chef, Puppet, or SaltStack.
     • Define the rulebase as a "managed resource."
     • Enforce correct permissions and ownership.
     • Version control the rulebase configuration.
  5. Remote Storage (If Applicable):
     • Use HTTPS with strong ciphers (TLS 1.3) and validate the server's certificate.
     • Implement authentication (API keys, client certificates).
     • Consider encrypting the rulebase at rest.
  6. Input Validation for Rulebase Creation (If Applicable):
     • If users can create/modify rules, strictly validate all input.
     • Use a whitelist approach for allowed characters and patterns.
     • Implement input length limits.
     • Sanitize input to remove/escape dangerous characters. Use a dedicated parser for the rulebase syntax, not custom regex.

• Threats Mitigated:

  • Unauthorized Rulebase Modification (Severity: High): An attacker could alter rules to cause incorrect parsing, data leakage, DoS, or potentially code execution (by injecting malicious patterns into the rulebase).
  • Rulebase Disclosure (Severity: Medium to High): Reading the rulebase reveals how logs are parsed, potentially exposing application internals or vulnerabilities.
  • Denial of Service (DoS) via Rulebase Manipulation (Severity: High): Injecting complex or resource-intensive rules to crash or slow down the application.

• Impact:

  • Unauthorized Rulebase Modification: Risk significantly reduced. Attacker needs elevated privileges.
  • Rulebase Disclosure: Risk significantly reduced. Attacker needs to bypass file system permissions.
  • DoS via Rulebase Manipulation: Risk significantly reduced. Attacker needs elevated privileges.

• Currently Implemented: Example: Partially - Permissions set, no config management. (Replace)

• Missing Implementation: Example: Config management integration missing. Manual updates. (Replace)

Mitigation Strategy: Rulebase Integrity Verification

• Description:

  1. Hashing:
     • Use a strong hash function (SHA-256).
     • Before deployment, calculate the rulebase's SHA-256 hash. Store this hash securely.
     • In the application, before loading, calculate the hash again.
     • Compare the calculated hash with the stored hash. If they don't match, abort loading and log an error.
  2. Digital Signatures (Optional but Recommended):
     • Generate a private/public key pair. Secure the private key.
     • Use the private key to digitally sign the rulebase.
     • Store the public key with the application.
     • Before loading, verify the signature using the public key. If verification fails, abort and log.

• Threats Mitigated:

  • Unauthorized Rulebase Modification (Severity: High): Detects any tampering with the rulebase after initial deployment. This is directly related to liblognorm because the rulebase is its core configuration.
  • Man-in-the-Middle (MitM) Attack (Severity: High) - (If rulebase fetched remotely): If an attacker intercepts and modifies the rulebase during transfer, the check will fail.

• Impact:

  • Unauthorized Rulebase Modification: Risk significantly reduced. Any modification is detected.
  • MitM Attack: Risk significantly reduced (if applicable). Tampering is detected.

• Currently Implemented: Example: Not Implemented. (Replace)

• Missing Implementation: Example: Entire mechanism missing. (Replace)

Mitigation Strategy: Regular liblognorm Updates

• Description:

  1. Subscribe to Security Advisories: Subscribe to liblognorm-related security notifications.
  2. Monitor for Updates: Regularly check the liblognorm repository for new releases.
  3. Automated Dependency Management (Recommended): Use a dependency manager to track and update liblognorm.
  4. Testing: After updating, thoroughly test your application, especially the liblognorm integration.
  5. Rollback Plan: Have a plan to quickly roll back to a previous version if needed.

• Threats Mitigated:

  • Exploitation of Known Vulnerabilities (Severity: Varies, potentially Critical): Addresses vulnerabilities discovered and patched in newer liblognorm versions. This is directly related to the library itself.

• Impact:

  • Exploitation of Known Vulnerabilities: Risk significantly reduced. Staying up-to-date is crucial.

• Currently Implemented: Example: Manual updates, no automation. (Replace)

• Missing Implementation: Example: Automated dependency management, testing/rollback process. (Replace)

Mitigation Strategy: Resource Limits (Specifically for liblognorm processing)

• Description:

  1. Identify Resource Limits: Determine appropriate limits for memory, CPU, and processing time specifically for the liblognorm parsing of a single log entry.
  2. Implement Limits:
     • Memory: Use memory allocation limits. In C/C++, consider setrlimit(RLIMIT_AS, ...). This limits the memory liblognorm can use during parsing.
     • CPU: Use CPU time limits (setrlimit(RLIMIT_CPU, ...) in C/C++) or process priorities. This prevents a single log entry + liblognorm from monopolizing the CPU.
     • Processing Time: Implement a timeout around the call to liblognorm's parsing function. If it exceeds the timeout, terminate and log.
  3. Monitor Resource Usage: Continuously monitor liblognorm's resource usage. Investigate if limits are frequently hit.

• Threats Mitigated:

  • Denial of Service (DoS) via Resource Exhaustion (Severity: High): Prevents attackers from crafting log messages that cause liblognorm to consume excessive resources, specifically targeting the library's processing.

• Impact:

  • DoS via Resource Exhaustion: Risk significantly reduced. Attackers are limited in the resources liblognorm can consume per log entry.

• Currently Implemented: Example: Not Implemented. (Replace)

• Missing Implementation: Example: No resource limits on liblognorm. (Replace)

Mitigation Strategy: Fuzz Testing of liblognorm Integration

• Description:

  1. Choose a Fuzzer: Select a fuzzer suitable for your application and the input liblognorm expects. Consider structured input generation.
  2. Define Input Corpus: Create valid log messages representing typical input.
  3. Configure Fuzzer: Target the functions in your application that interact directly with liblognorm.
  4. Run Fuzzing Campaign: Run the fuzzer, monitoring for crashes, hangs, etc.
  5. Analyze Results: Investigate any issues. Determine the root cause and fix.
  6. Integrate into CI/CD: Integrate fuzzing into your CI/CD pipeline.

• Threats Mitigated:

  • Unknown Vulnerabilities (Severity: Unknown, potentially Critical): Discovers vulnerabilities in liblognorm or in your application's interaction with it. This includes buffer overflows, memory leaks, logic errors, etc., specifically within the context of liblognorm.

• Impact:

  • Unknown Vulnerabilities: Risk reduced. Fuzzing can uncover hidden vulnerabilities.

• Currently Implemented: Example: Not Implemented. (Replace)

• Missing Implementation: Example: Fuzz testing not part of the process. (Replace)