Two Approaches

Analysis Using TypeScript Scripts

By leveraging TypeScript scripts, we can perform static code analysis to identify potential security flaws in the codebase. This method involves writing scripts that parse and analyze the code to find common vulnerabilities.

Example: Buffer Overflow Detection

Vulnerable Code:

let bufferOverflow: string[] = [];

function addToBuffer(input: string) {
  // Simulating buffer overflow by not checking the length of input
  bufferOverflow.push(input);
}

Detection by Script:

Our script will look for array manipulations and check if there are any safeguards for buffer limits.

Script Code:

import {
  Node,
  isCallExpression,
  createSourceFile,
  ScriptTarget,
  SyntaxKind,
  forEachChild,
} from "typescript";

const sourceCode = `
let bufferOverflow: string[] = [];

function addToBuffer(input: string) {
  bufferOverflow.push(input);
}
`;

const sourceFile = createSourceFile(
  "tempFile.ts",
  sourceCode,
  ScriptTarget.Latest,
  true
);

const securityIssues: string[] = [];

const analyzeNode = (node: Node) => {
  if (isCallExpression(node)) {
    const functionName = node.expression.getText();
    if (functionName.includes(".push")) {
      securityIssues.push(
        `Potential buffer overflow detected in function using array. Ensure proper length checks.`
      );
    }
  }
  forEachChild(node, analyzeNode);
};

forEachChild(sourceFile, analyzeNode);

if (securityIssues.length > 0) {
  console.log("Security issues found:");
  securityIssues.forEach((issue) => console.log(`- ${issue}`));
} else {
  console.log("No significant security issues found.");
}

Script Output:

Security issues found:
- Potential buffer overflow detected in function using array. Ensure proper length checks.

OTHER CHECK:

Security issues found:
- Plain text password storage detected in user creation method.

Security issues found:
- Insecure token generation found using Math.random.
- Insecure token generation found using Math.random.
- Insecure token generation found using Math.random.

Analysis Using AI

This approach involves sending the code to an AI for analysis. The AI reviews the code and identifies security flaws, providing detailed reports with severity levels and proposed solutions.

Example AI Output:

{
  "report": [
    {
      "codeWithBug": "//! @Himasnhu-AT Improve token generation logic",
      "severity": "medium",
      "proposedSolution": "Tokens should be generated using a secure random number generator and should be cryptographically strong."
    },
    {
      "codeWithBug": "//! @Himasnhu-AT Improve verification Code generation logic",
      "severity": "medium",
      "proposedSolution": "Verification codes should be generated using a secure random number generator and should be cryptographically strong."
    },
    {
      "codeWithBug": "if (body.token != verificationCode)",
      "severity": "medium",
      "proposedSolution": "Verification codes should be compared using a constant-time comparison function to prevent timing attacks."
    },
    {
      "codeWithBug": "//! @Himasnhu-AT Hash this password",
      "severity": "high",
      "proposedSolution": "Passwords should be hashed using a strong hashing algorithm such as bcrypt or scrypt."
    },
    {
      "codeWithBug": "const token = Math.random().toString(36).substring(2);",
      "severity": "medium",
      "proposedSolution": "Tokens should be generated using a secure random number generator and should be cryptographically strong."
    },
    {
      "codeWithBug": "const verificationCode = Math.random().toString(36).substring(2);",
      "severity": "medium",
      "proposedSolution": "Verification codes should be generated using a secure random number generator and should be cryptographically strong."
    }
  ]
}