Data from Network Shared Drive T1039
- Tactic
- Collection
- Platforms
- Linux, macOS, Windows
- Version
- 1.5
- Created
- 31 May 2017
- Last modified
- 24 October 2025
- Contributor
- David Tayouri
Adversaries may search network shares on computers they have compromised to find files of interest. Sensitive data can be collected from remote systems via shared network drives (host shared directory, network file server, etc.) that are accessible from the current system prior to Exfiltration. Interactive command shells may be in use, and common functionality within cmd may be used to gather information.
Data from Network Shared Drive MITRE reference T1039
8 groups have been recorded using this technique. Newest first; each entry carries MITRE’s procedure text and a link to the group’s full record. Click a name to filter the rules below.
Has searched network shares to access sensitive documents.1
Has collected data of interest from network shares.1
Has exfiltrated files stolen from file shares.1
Extracted Word documents from a file server on a victim network.1
Malware has collected Microsoft Office documents from mapped network drives.12
All 8 groups for this technique · 6 newest in this preview
1 campaign has been recorded using this technique. Listed newest first; dates are year-granularity and attribution is MITRE’s.
During C0015, the threat actors collected files from network shared drives prior to network encryption.1
All 1 campaigns for this technique
4 software entries are documented implementing this technique. MITRE files each as a tool or as malware; newest first, then by how many groups carry them.
Can collect any files found in the enumerated drivers before sending it to its C2 channel.1
Can collect data from network drives and stage it for exfiltration.1
When it first starts, BADNEWS crawls the victim's mapped drives and collects documents with the following extensions: .doc, .docx, .pdf, .ppt, .pptx, and .txt.1
Steals user files from network shared drives with file extensions and keywords that match a predefined list.1
All 4 software entries for this technique
Offense vs defense T1039
Is defensive coverage keeping up with adversary use? Eight counts, each ranked against all 697 ATT&CK techniques. Attack sits left, defense right, so a shape leaning left means adversaries are better documented here than defenders are equipped. Hover any spoke for its percentile and the share of techniques that have more. The timeline below shows when each side arrived.
How it got here
Adversary activity (campaign spans) over cumulative rule output. Each source is plotted independently from zero, so neither line includes the other. Campaign dates are year-granularity.
Data from Network Shared Drive detection strategy DET0410
MITRE names one behaviour worth catching for this technique and breaks it into 3 analytics, one per platform. Each carries the log sources it needs and the fields you tune per environment.
Detection Strategy for Data from Network Shared Drive
AN1145 · Windows
Monitoring of file access to network shares (e.g., C$, Admin$) followed by unusual read or copy operations by processes not typically associated with such activity (e.g., PowerShell, certutil).
Log sources
The data this analytic draws on. You do not need every component — each one you already collect covers part of it. Each links to its ATT&CK record.
| Data component | Name | Channel |
|---|---|---|
| File CreationDC0039 | WinEventLog:Sysmon | EventCode=11 |
| Network Share AccessDC0102 | WinEventLog:Security | EventCode=5145 |
Tunable fields
MITRE calls these the analytic’s mutable elements: the thresholds and filters you set for your own environment.
| Field | What you tune |
|---|---|
| ShareName | Organizations may use custom share paths outside of default C$, Admin$, etc. |
| ProcessName | Common toolsets vary; defenders should tailor to unusual processes for their environment. |
| TimeWindow | Time of day and access duration may need to be tuned to reduce false positives. |
AN1146 · Linux
Unusual access or copying of files from mounted network drives (e.g., NFS, CIFS/SMB) by user shells or scripts followed by large data transfer.
Log sources
The data this analytic draws on. You do not need every component — each one you already collect covers part of it. Each links to its ATT&CK record.
| Data component | Name | Channel |
|---|---|---|
| Drive AccessDC0054 | linux:syslog | mount/umount or file copy logs |
| File AccessDC0055 | auditd:SYSCALL | open,read |
Tunable fields
MITRE calls these the analytic’s mutable elements: the thresholds and filters you set for your own environment.
| Field | What you tune |
|---|---|
| MountPoint | Organization-specific share mount paths may vary (/mnt/share1, /srv/data etc.) |
| UID | May need to scope to service accounts or user ID patterns specific to enterprise policy. |
AN1147 · macOS
Detection of file access from mounted SMB shares followed by copy or exfil commands from Terminal or script interpreter processes.
Log sources
The data this analytic draws on. You do not need every component — each one you already collect covers part of it. Each links to its ATT&CK record.
| Data component | Name | Channel |
|---|---|---|
| Drive AccessDC0054 | fs:fsusage | open/read/mount operations |
| File AccessDC0055 | macos:unifiedlog | filesystem and process events |
Tunable fields
MITRE calls these the analytic’s mutable elements: the thresholds and filters you set for your own environment.
| Field | What you tune |
|---|---|
| ProcessPath | Script interpreters may vary (e.g., zsh, bash, python, osascript). |
| SharePath | Network drive mount points may differ across enterprises. |
Server Message Block (SMB) is used by Windows to allow for file, pipe, and printer sharing over port 445/tcp. It allows for enumerating, and reading from and writing to file shares for a remote computer. Although it is heavily used by Windows servers for legitimate purposes and by users for file and printer sharing, many adversaries also use SMB to achieve Lateral Movement. Looking at this activity more closely to obtain an adequate sense of situational awareness may make it possible to detect adversaries moving between hosts in a way that deviates from normal activity. Because SMB traffic is heavy in many environments, this analytic may be difficult to turn into something that can be used to quickly detect an APT. In some cases, it may make more sense to run this analytic in a forensic fashion. Looking through and filtering its output after an intrusion has been discovered may be helpful in identifying the scope of compromise.
D3FEND techniques
The defensive countermeasure this analytic implements, in MITRE’s D3FEND ontology.
| ID | Name |
|---|---|
| D3-IPCTA | IPC Traffic Analysis |
Data model references
The CAR data model objects, actions and fields the logic reads. Map these to your own schema before implementing.
| Object | Action | Field |
|---|---|---|
| flow | message | dest_port |
| flow | message | proto_info |
Implementations
Pseudocode is the canonical logic; the rest are CAR’s translations into vendor query languages.
Although there may be more native ways to detect detailed SMB events on the host, they can be extracted out of network traffic. With the right protocol decoders, port 445 traffic can be filtered and even the file path (relative to the share) can be retrieved.
flow = search Flow:Message smb_events = filter flow where (dest_port == "445" and protocol == "smb") smb_events.file_name = smb_events.proto_info.file_name output smb_write
Tests from Atomic Red Team (MIT licence) · technique definition