Pass 1: Writes a zero and verifies the write The DoD 5220.22-M data sanitization method is usually implemented in the following way: The DoD 5220.22-M method is often incorrectly referenced as DoD 5220.2-M (.2-M instead of. A review of the ATA specifications and recent white papers indicate that these areas can be accessed, modified, and written to by end users using specific open source and freely available tools, allowing data to be stored and/or hidden in these areas. These areas can be problematic for computer forensic investigators, since many of the common industry tools cannot detect the presence of the HPA and DCO. There are also other issues deleting data in Host Protected Areas (HPA) and Device Configuration Overlays (DCO). This is known as a DOD 5220.22-m Erasure for data residing on hard drives and solid-state drives (SSD), DoD 5220.22-m is a software based data sanitization method used in various file shredder and data destruction programs to overwrite existing information on a SSD or magnetic hard drive or other storage device.Įrasing a hard drive or solid state device using the DoD 5220.22-M data sanitization method will possibly prevent all software based file recovery methods from lifting information from the drive and should also prevent most if not all hardware based recovery methods.
Overwriting sanitizing is the removal of sensitive data from a system or storage device with the intent that the data cannot be reconstructed by any known technique. Since the manufacturer has “full knowledge” of the drive’s design, these techniques should be reliable, but researchers found many of the implementations were flawed.ĭOD 5220.22-M 3 Pass Overwrite Methodology This is most likely the ATA Secure Erase Command, the DOD 5220.22-M 3 pass sanitization method, or some support Secure Erasure Command otherwise known as the Crypto Erase Command. Most modern SSDs and HDD’s have built-in commands to instruct on-board firmware to run a sanitization standard protocol on the Magnetic or Solid State drive to remove all data.
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