CWE-546: Suspicious Comment

What is Suspicious Comment?

• Overview: CWE-546 refers to the presence of suspicious comments in code that may indicate bugs, incomplete functionality, or potential security weaknesses. These comments often include keywords like BUG, HACK, FIXME, TODO, and others that suggest unresolved issues or areas needing attention.

• Exploitation Methods:

• Attackers can exploit this vulnerability by reviewing code for comments that expose weak points or unfinished sections, targeting these for further investigation or attack.
• Common attack patterns include searching for keywords that suggest neglected areas where security measures may be insufficient or absent.

• Security Impact:

• Direct consequences of successful exploitation could include unauthorized access, data breaches, or the execution of malicious code.
• Potential cascading effects may involve broader system failures or escalated privileges leading to further exploitation.
• Business impact can include financial loss, reputational damage, and legal liabilities due to compromised sensitive information or system downtime.

• Prevention Guidelines:

• Specific code-level fixes include removing or resolving any suspicious comments and ensuring all TODOs and FIXMEs are addressed.
• Security best practices involve conducting regular code reviews and audits to identify and mitigate potential weaknesses indicated by comments.
• Recommended tools and frameworks include static analysis tools that can scan code for suspicious comments and automated systems for continuous monitoring of code quality and security.

Corgea can automatically detect and fix Suspicious Comment in your codebase. [Try Corgea free today](https://corgea.app).

Technical Details

Likelihood of Exploit: Not specified

Affected Languages: Not Language-Specific

Affected Technologies: Not specified

Vulnerable Code Example

// FIXME: The following function might have performance issues with large datasets
// TODO: Optimize the algorithm
function fetchData() {
    // Simulated data fetching logic
    let data = [];
    for (let i = 0; i < 1000000; i++) {
        data.push({id: i, value: `Data \${i}`});
    }
    return data;
}

Explanation:

• The comments on lines {3-5} indicate known performance issues with the fetchData function, particularly when handling large datasets. These comments are suspicious because they highlight a potential weakness in the application that has not been addressed.

How to fix Suspicious Comment?

• Optimize the Function: Improve the function to efficiently handle large datasets, perhaps by implementing pagination or using more efficient data structures.
• Remove or Resolve the Comment: After addressing the performance concerns, remove the suspicious comment or update it to accurately reflect the improvements.
• Use Profiling Tools: Utilize profiling tools to identify and address performance bottlenecks, ensuring the function operates efficiently.

Fixed Code Example

function fetchDataPaged(page, pageSize) {
    // Optimized data fetching logic using pagination
    // Handles large datasets efficiently by fetching data in chunks

    // Example of optimized logic
    const totalData = 1000000; // Assume this is the total number of records
    let data = [];
    let start = page * pageSize;
    let end = start + pageSize;
    for (let i = start; i < end && i < totalData; i++) {
        data.push({id: i, value: `Data \${i}`});
    }
    return data;
}

// The function now uses pagination to handle large datasets efficiently, and the suspicious comment has been removed.

Explanation:

• The fetchDataPaged function is optimized by implementing pagination, allowing it to handle large datasets efficiently without loading all data into memory at once.
• The previous suspicious comments are removed, and the function is now documented with meaningful comments explaining the optimizations made. This ensures the function is well-documented and free from indicators of potential weaknesses.