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Mitigation Strategies Analysis for mikel/mail

Mitigation Strategy: Strict Input Validation and Sanitization (Sending)

Mitigation Strategy: Strict Input Validation and Sanitization (Sending)

Description:

  1. Recipient Validation: Before passing any recipient address to mail, use a robust email validation library (e.g., email_validator in Python) to ensure the address conforms to RFC specifications. Reject invalid addresses.
  2. Subject Sanitization: Limit the subject length. Remove or encode control characters (especially \r and \n) that could be used for header injection. Escape any other special characters that might have meaning in email headers.
  3. Body Sanitization:
    • Plain Text: If the body is plain text, escape any characters that could be misinterpreted as email header syntax or MIME encoding directives.
    • HTML: If the body is HTML, use a strict HTML sanitizer (e.g., OWASP Java HTML Sanitizer, bleach in Python). Allow only a very limited set of safe HTML tags and attributes. Never trust user-provided HTML directly. Use a whitelist-based approach.
  4. Attachment Handling (Filename and Content):
    • Filename Validation: Before passing filenames to mail, validate them. Check for dangerous characters, double extensions (e.g., file.pdf.exe), and excessively long names. Sanitize or reject suspicious filenames.
    • Content Type (MIME Type) Validation: Use the mail library's features (or a separate MIME type detection library) to determine the declared MIME type of the attachment. Compare this against a whitelist of allowed MIME types. Do not rely solely on the file extension. Ideally, this would be combined with magic byte detection (which is less directly related to mail itself, but crucial).
  5. Encoding: Ensure that mail is configured to use the correct character encoding (UTF-8 for text) and appropriate encoding for attachments (usually Base64). This is usually handled by the library, but verify the settings.
  6. Header Control: Be extremely careful when setting any custom headers using mail. Validate and sanitize any user-supplied data used in custom headers. Prefer using the library's built-in methods for setting standard headers (e.g., Subject, From, To, Cc, Bcc) rather than manually constructing headers.

Threats Mitigated:

  • Header Injection (Severity: High): Prevents attackers from injecting malicious email headers.
  • Content Injection (Severity: High): Prevents attackers from injecting malicious content into the email body.
  • Attachment-Based Attacks (Severity: High): Reduces (but doesn't eliminate) the risk of sending malicious attachments. (Requires external validation like magic bytes and anti-malware).
  • Cross-Site Scripting (XSS) (Severity: High): Prevents XSS in HTML emails.
  • Command Injection (Severity: High): (Indirectly) mitigates if email content is ever (incorrectly) used to build commands.

Impact:

  • Header Injection: Risk significantly reduced.
  • Content Injection: Risk significantly reduced.
  • Attachment-Based Attacks: Risk reduced (but further mitigation is essential).
  • XSS: Risk significantly reduced (with robust HTML sanitization).
  • Command Injection: Risk reduced (but this scenario should be avoided).

Currently Implemented:

  • Recipient validation using email_validator.
  • Basic subject sanitization (length limit).
  • HTML sanitization using bleach (limited templates).
  • File extension whitelist (but not MIME type or magic byte).

Missing Implementation:

  • Comprehensive validation for all email sending functions.
  • MIME type validation using mail's features or a dedicated library.
  • Consistent encoding enforcement.
  • Strict control and validation of custom headers.

Mitigation Strategy: Secure MIME Parsing and Handling (Receiving)

Mitigation Strategy: Secure MIME Parsing and Handling (Receiving)

Description:

  1. Robust Parser: Ensure mail is using a secure and up-to-date MIME parser. Vulnerabilities in MIME parsing have been exploited in the past. Keep the library updated.
  2. Limit MIME Depth: Set a reasonable limit on the maximum depth of MIME nesting that your application will process using mail. Deeply nested MIME structures can be used for denial-of-service or to exploit parser vulnerabilities. The mail library might have options to configure this.
  3. Content-Type Validation: When processing MIME parts, carefully validate the Content-Type header. Be suspicious of unusual or unexpected content types. Compare against a whitelist of expected types if possible.
  4. Content-Disposition Handling: Pay attention to the Content-Disposition header (especially for attachments). Ensure that filenames are properly sanitized before being used (e.g., to save the attachment to disk). Avoid using user-supplied filenames directly.
  5. Encoding Handling: Ensure that mail correctly handles different character encodings and MIME encodings (e.g., Base64, Quoted-Printable). Incorrect decoding can lead to vulnerabilities or data corruption.
  6. Header Extraction and Validation: When extracting headers from MIME parts, validate and sanitize them before using them. Be especially cautious with headers that might influence program logic (e.g., Content-ID, custom X- headers).

Threats Mitigated:

  • MIME Parsing Vulnerabilities (Severity: High): Reduces the risk of exploits targeting vulnerabilities in the MIME parser.
  • Denial of Service (DoS) (Severity: Medium): Prevents DoS attacks that use deeply nested MIME structures.
  • Data Corruption (Severity: Medium): Prevents issues caused by incorrect handling of encodings.
  • Injection Attacks (Severity: High): (Indirectly) Mitigates injection attacks if header values are misused.
  • Attachment-Based Attacks (Severity: High): (Partially) Mitigates by validating Content-Type and Content-Disposition.

Impact:

  • MIME Parsing Vulnerabilities: Risk significantly reduced.
  • DoS: Risk reduced.
  • Data Corruption: Risk reduced.
  • Injection Attacks: Risk reduced (if header values are properly handled).
  • Attachment-Based Attacks: Risk partially reduced (further mitigation needed).

Currently Implemented:

  • Using mail for MIME parsing.

Missing Implementation:

  • Explicit limit on MIME depth is not set.
  • Content-Type validation is basic and needs to be more comprehensive (whitelist).
  • Content-Disposition handling is not fully secured (filename sanitization is incomplete).
  • Encoding handling relies on mail defaults; needs explicit verification.
  • Header extraction and validation are not consistently applied.

Mitigation Strategy: Header Analysis (Receiving)

Mitigation Strategy: Header Analysis (Receiving)

Description:

  1. Parse Headers: Use mail to reliably extract all email headers.
  2. "From", "Reply-To", "Return-Path" Consistency Check: Within your code that uses mail, compare these headers. Discrepancies can indicate spoofing.
  3. "Received" Header Parsing (Limited): While full chain analysis is often done at the mail server level, you can use mail to extract the Received headers. Your application code can then perform basic checks, such as:
    • Checking for the presence of known malicious IP addresses or domains (using a local blacklist or a simple API call).
    • Checking for an excessive number of Received headers (a possible sign of routing manipulation).
  4. Message-ID Uniqueness Check: Use mail to get the Message-ID and check if it's unique (within your system's context). Duplicate IDs can indicate spam or replay attacks. This requires maintaining a database of seen Message-IDs.
  5. X-Header Examination: Use mail to extract custom X- headers. Examine these for any suspicious patterns or information. Define a set of known/expected X- headers and treat others with caution.
  6. Authentication-Results Parsing: Use mail to extract the Authentication-Results header. Parse this header to get the results of SPF, DKIM, and DMARC checks. This is crucial for detecting spoofing. Your application logic should then act on these results (e.g., reject or flag emails that fail DMARC).

Threats Mitigated:

  • Email Spoofing (Severity: High): Detects forged sender information.
  • Phishing (Severity: High): Helps identify phishing emails.
  • Spam (Severity: Medium): Helps identify spam based on header anomalies.
  • Business Email Compromise (BEC) (Severity: High): Helps detect BEC attacks.

Impact:

  • Email Spoofing: Risk significantly reduced (especially with Authentication-Results parsing).
  • Phishing: Risk significantly reduced.
  • Spam: Risk reduced.
  • BEC: Risk reduced.

Currently Implemented:

  • Header parsing using mail.
  • Basic "From" address consistency check.

Missing Implementation:

  • Authentication-Results parsing and handling.
  • "Received" header basic checks (blacklist lookup).
  • Message-ID uniqueness check.
  • Comprehensive X-header examination.
  • "Reply-To" and "Return-Path" consistency checks.