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Attack Tree Analysis for symfonycasts/reset-password-bundle

Objective: Gain unauthorized access to a user account by exploiting high-risk vulnerabilities in the password reset functionality provided by the symfonycasts/reset-password-bundle.

Attack Tree Visualization

Attack Goal: Gain Unauthorized Access to User Account via Reset Password Bundle

├───[OR]─ [CRITICAL NODE] Exploit Weaknesses in Token Generation and Handling │ ├───[OR]─ [HIGH-RISK PATH] Predictable Reset Tokens │ │ └───[AND]─ Analyze Token Generation Algorithm │ │ └─── Identify Patterns or Weaknesses in Randomness │ │ └─── Generate Valid Tokens for Target User │ ├───[OR]─ [HIGH-RISK PATH] Token Leakage │ │ ├───[OR]─ [HIGH-RISK PATH] Insecure Token Storage │ │ │ └───[AND]─ Exploit Database Vulnerabilities (e.g., SQL Injection) │ │ │ └───[AND]─ [HIGH-RISK PATH] Access Logs with Token Information │ │ └───[OR]─ [HIGH-RISK PATH] Excessive Token Lifetime │ │ └───[AND]─ Obtain a Valid Token │ │ └─── Wait for Extended Period and Attempt to Use Token

├───[OR]─ [CRITICAL NODE] Exploit Weaknesses in Reset Link and Form Handling │ ├───[OR]─ [HIGH-RISK PATH] Cross-Site Scripting (XSS) in Reset Form │ │ └───[AND]─ Inject Malicious Script into Reset Form Fields │ │ └─── Steal Credentials or Redirect User

├───[OR]─ [CRITICAL NODE] Exploit Weaknesses in Password Reset Logic │ ├───[OR]─ [HIGH-RISK PATH] Weak Password Policy Enforcement After Reset │ │ └───[AND]─ Reset Password to a Weak/Predictable Password │ │ └─── Gain Access via Brute-force Password Guessing

└───[OR]─ [CRITICAL NODE] [HIGH-RISK PATH] Social Engineering related to Reset Process └───[OR]─ [HIGH-RISK PATH] Phishing Attack Mimicking Reset Email └───[AND]─ Craft Fake Reset Email Resembling Legitimate One └─── Trick User into Clicking Malicious Link and Providing Credentials

  • Description: This critical node encompasses vulnerabilities related to how reset tokens are created, managed, and protected. Weaknesses here can directly lead to unauthorized password resets.

    • [HIGH-RISK PATH] Predictable Reset Tokens

      • Attack Vector: If the algorithm used to generate reset tokens is flawed or predictable, an attacker can potentially generate valid tokens for any user without needing to initiate a reset request.
      • Likelihood: Low (if bundle defaults are used correctly, High if custom flawed implementation)
      • Impact: Very High (Full Account Takeover)
      • Effort: High (Reverse Engineering, Cryptography Skills)
      • Skill Level: High
      • Detection Difficulty: High
    • [HIGH-RISK PATH] Token Leakage

      • Description: This path covers scenarios where reset tokens are unintentionally exposed, allowing attackers to obtain valid tokens.

        • [HIGH-RISK PATH] Insecure Token Storage

          • Attack Vector: Reset tokens or sensitive information related to token generation are stored insecurely, such as in plain text in databases or accessible logs.
          • Likelihood: Low (SQLi depends on application, Insecure Logging - Medium if misconfigured)
          • Impact: Very High (Full Account Takeover)
          • Effort: Medium - High
          • Skill Level: Medium
          • Detection Difficulty: Medium
        • [HIGH-RISK PATH] Access Logs with Token Information

          • Attack Vector: Reset tokens are inadvertently logged in application logs, making them accessible to attackers who gain access to these logs.
          • Likelihood: Medium (If logging is not carefully configured)
          • Impact: Very High (Full Account Takeover)
          • Effort: Medium (Log Access)
          • Skill Level: Medium
          • Detection Difficulty: Medium
      • [HIGH-RISK PATH] Excessive Token Lifetime

        • Attack Vector: Reset tokens remain valid for an extended period, increasing the window of opportunity for attackers to intercept or guess a token and use it before it expires.
        • Likelihood: Medium (Depends on configured token lifetime)
        • Impact: Very High (Full Account Takeover)
        • Effort: Low (Patience)
        • Skill Level: Low
        • Detection Difficulty: High
  • Description: This critical node focuses on vulnerabilities in how the reset link is generated and how the password reset form is handled. Exploits here can bypass security measures or compromise user input.

    • [HIGH-RISK PATH] Cross-Site Scripting (XSS) in Reset Form
      • Attack Vector: The password reset form is vulnerable to XSS, allowing an attacker to inject malicious scripts. This can be used to steal newly entered passwords, session cookies, or redirect the user.
      • Likelihood: Medium (Common web vulnerability if not properly handled)
      • Impact: High (Credential theft, Account Compromise, Data Breach)
      • Effort: Low
      • Skill Level: Low
      • Detection Difficulty: Medium
  • Description: This critical node highlights vulnerabilities in the application's logic surrounding the password reset process itself, particularly after token validation.

    • [HIGH-RISK PATH] Weak Password Policy Enforcement After Reset
      • Attack Vector: The application does not enforce strong password policies when a user resets their password, allowing attackers to reset passwords to weak and easily guessable values.
      • Likelihood: Medium (If weak policy is in place)
      • Impact: Very High (Full Account Takeover)
      • Effort: Low (Brute-force tools)
      • Skill Level: Low
      • Detection Difficulty: Low
  • Description: This critical node and high-risk path address the human element of security, focusing on social engineering attacks that exploit user behavior.

    • [HIGH-RISK PATH] Phishing Attack Mimicking Reset Email
      • Attack Vector: An attacker crafts a phishing email that closely resembles the legitimate password reset email, tricking users into clicking a malicious link and providing their new password or credentials on a fake page.
      • Likelihood: Medium (Phishing is a common attack vector)
      • Impact: Very High (Full Account Takeover)
      • Effort: Low (Phishing kits readily available)
      • Skill Level: Low
      • Detection Difficulty: High (Relies on user awareness, technical detection is limited)