CVE-2017-15944

Security testing and evaluation at multiple SDLC stages directly detects missing or flawed input validation, with the required remediation process ensuring fixes are applied.

Security testing and developer training directly verify and enforce proper input validation, reducing exploitability of injection and malformed-data weaknesses.

Managed runtimes used by platform-independent applications (e.g., JVM, CLR) enforce memory safety, preventing most buffer overflows that require direct memory manipulation.

Directly implements checks on information inputs to reject invalid data before processing.

Memory protections (e.g., W^X, ASLR) make exploitation of buffer-boundary violations far harder to turn into code execution.

Detects exploitation attempts that produce memory corruption, crashes, or anomalous behavior.

Spam protection mechanisms perform filtering and detection on inbound/outbound messages, directly compensating for missing or weak input validation of unsolicited content.

A.8.25 mandates security requirements, secure coding guidelines, checkpoints, testing (incl. code scans) and developer training in the SDLC, which reaches a slice of input validation defects but leaves the majority (incomplete enforcement, second-order inputs, parser differentials, post-validation canonicalization) unaddressed as in the SA-3 and A.8.28 anchors.

Mandating input controls that include integrity checks and input validation ensures that untrusted data is examined before use, blocking the root cause of many injection and malformed-data weaknesses.

Security-by-design principles explicitly call for data validation and sanitization at every layer, reducing the chance that malformed or malicious input will be processed without scrutiny.

Requiring language-specific secure coding standards, peer review, SAST and documented mitigation of common programming errors forces validation of all inputs before they are trusted.

Testing against a defined set of requirements and using code review plus vulnerability scanning forces validation of inputs and handling of unanticipated conditions, reducing the chance that malformed data will be accepted.