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attack-surface.md

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Attack Surface Analysis for rsyslog/liblognorm

Attack Surface: Malicious Rule Set Injection

  • Description: liblognorm processes rule sets to define log parsing and normalization. If these rule sets are maliciously crafted or modified, they can directly manipulate liblognorm's behavior.
  • liblognorm Contribution: liblognorm's core functionality relies on external rule sets. It directly interprets and executes the logic defined within these rule sets.
  • Example: A malicious rule set could contain rules designed to trigger excessive CPU usage within liblognorm's processing engine, leading to a Denial of Service. Alternatively, rules could be crafted to extract and expose sensitive data from log messages during normalization.
  • Impact: Denial of Service (DoS), Information Disclosure, Bypass of Security Controls.
  • Risk Severity: High
  • Mitigation Strategies:
    • Secure Rule Set Loading: Ensure liblognorm loads rule sets from trusted and protected locations only.
    • Rule Set Validation: Implement mechanisms to validate the integrity and structure of rule sets before they are loaded by liblognorm. This could include schema validation or digital signatures.
    • Principle of Least Privilege for Rule Sets: Limit write access to rule set files to only authorized users or processes.

Attack Surface: Regular Expression Denial of Service (ReDoS) in Rule Processing

  • Description: liblognorm utilizes regular expressions within its rule processing logic. Inefficient or maliciously crafted regular expressions in rule sets can lead to Regular Expression Denial of Service (ReDoS) when processed by liblognorm.
  • liblognorm Contribution: liblognorm's rule engine directly executes regular expressions defined in rule sets for pattern matching and log parsing. Vulnerable regex patterns within rules are processed by liblognorm.
  • Example: A rule set might contain a regex like (a+)+b which, when processed by liblognorm against a crafted log message like aaaaaaaaaaaaaaaaaaaaac, can cause exponential backtracking and consume excessive CPU time, leading to a DoS.
  • Impact: Denial of Service (DoS).
  • Risk Severity: High
  • Mitigation Strategies:
    • Regex Security Audits: Thoroughly audit rule sets for potentially vulnerable regular expressions before loading them into liblognorm.
    • Regex Complexity Limits: Implement limits on the complexity of regular expressions allowed in rule sets to prevent overly resource-intensive patterns.
    • Timeouts for Regex Matching within liblognorm: Consider if liblognorm or the application using it can implement timeouts for regular expression matching operations to prevent unbounded CPU consumption during rule processing.

Attack Surface: Buffer Overflow in Log Message Parsing within liblognorm

  • Description: liblognorm's internal log message parsing routines might be vulnerable to buffer overflows when handling excessively long or specially crafted log messages.
  • liblognorm Contribution: liblognorm is responsible for parsing and processing raw log messages. Vulnerabilities in its internal buffer management during parsing can lead to buffer overflows.
  • Example: Sending a log message that exceeds the buffer size allocated within liblognorm's parsing functions could overwrite adjacent memory regions. This could lead to crashes or potentially code execution if an attacker can control the overflowed data.
  • Impact: Denial of Service (Crash), Potential Code Execution.
  • Risk Severity: Critical (if code execution is possible), High (if only DoS).
  • Mitigation Strategies:
    • Use Latest liblognorm Version: Ensure you are using the latest stable version of liblognorm as vulnerabilities are often patched in newer releases.
    • Report Potential Vulnerabilities: If you suspect a buffer overflow vulnerability in liblognorm, report it to the developers so they can investigate and fix it.
    • Code Audits of liblognorm (if feasible): If possible, conduct or review code audits of liblognorm's source code, specifically focusing on buffer handling and string manipulation routines within its parsing logic.

Attack Surface: Integer Overflow/Underflow in Rule or Log Processing within liblognorm

  • Description: Integer overflow or underflow vulnerabilities within liblognorm's internal calculations during rule or log processing can lead to unexpected behavior and potential security issues.
  • liblognorm Contribution: liblognorm performs various integer arithmetic operations during rule processing and log message manipulation. Flaws in these operations can lead to integer overflows/underflows within liblognorm itself.
  • Example: If liblognorm uses an integer to track the length of a processed log component and an overflow occurs, it could lead to incorrect memory allocation or processing logic within liblognorm, potentially causing crashes or exploitable conditions.
  • Impact: Denial of Service (Crash), Unexpected Behavior, Potential for Exploitation.
  • Risk Severity: High (potentially Critical depending on the context and exploitability).
  • Mitigation Strategies:
    • Use Latest liblognorm Version: As with buffer overflows, ensure you are using the latest version of liblognorm which may contain fixes for integer handling issues.
    • Report Potential Vulnerabilities: Report any suspected integer overflow/underflow vulnerabilities in liblognorm to the developers.
    • Code Audits of liblognorm (if feasible): Review code related to integer arithmetic within liblognorm's source code for potential overflow/underflow issues.