# T1057 - Process Discovery

## SOC Recommendation
Investigate Process Discovery activity in the context of Discovery: confirm scope, affected host/identity, and whether it matches expected administrative behaviour before deciding this is benign.

## D3FEND Mappings
| D3FEND Technique | Relationship | Practical SOC Action |
|---|---|---|
| System Call Analysis | Detect | Monitor for System Call Analysis indicators relevant to this technique. |
| System Call Filtering | Isolate | Apply System Call Filtering to contain the blast radius once this technique is observed. |

## Investigation Steps
1. Review Defender for Endpoint / Defender XDR alerts and timeline for the affected host or identity.
2. Check Sentinel analytics rules and incidents correlated with this technique.
3. Review Entra ID sign-in and audit logs if the technique involves an identity or cloud resource.

## Evidence to Collect
- Host or resource affected
- Account or identity involved
- Timestamp of the activity
- Related process, file, or network artifact
- Any preceding or follow-on alerts

## Response Actions
| Action | Risk | Automation Safe | Approval Required |
|---|---|---|---|
| Contain the affected host or account | Medium | No | Yes |
| Collect and preserve evidence | Low | Yes | No |

## KQL
```kql
// File Hash Indicators with Block Action and Malware
let timeFrame = 5m;
CyfirmaIndicators_CL 
| where ConfidenceScore >= 80
    and TimeGenerated between (ago(timeFrame) .. now())
    and pattern contains 'file:hashes' and RecommendedActions has 'Block' and (Roles contains "Malware")
| extend MD5 = extract(@"file:hashes\.md5\s*=\s*'([a-fA-F0-9]{32})'", 1, pattern)
| extend SHA1 = extract(@"file:hashes\.'SHA-1'\s*=\s*'([a-fA-F0-9]{40})'", 1, pattern)
| extend SHA256 = extract(@"file:hashes\.'SHA-256'\s*=\s*'([a-fA-F0-9]{64})'", 1, pattern)
| extend
    Algo_MD5='md5',
    Algo_SHA1= 'SHA1',
    Algo_SHA256='SHA256',
    ProviderName = 'CYFIRMA',
    ProductName = 'DeCYFIR/DeTCT'
| project  
    MD5,
    Algo_MD5,
    SHA1,
    Algo_SHA1,
    SHA256,
    Algo_SHA256,
    ThreatActors,
    Sources,
    RecommendedActions,
    Roles,
    Country,
    name,
    Description,
    ConfidenceScore,
    SecurityVendors,
    IndicatorID,
    created,
    modified,
    valid_from,
    Tags,
    ThreatType,
    TimeGenerated,
    ProductName,
    ProviderName
```
```kql
Lookout_CL
| where details_action_s == 'DETECTED' and type_s == 'THREAT'
| extend DetailsPackageName = details_packageName_s
| extend TargetPlatform = target_platform_s
| extend TargetOsVersion = target_osVersion_s
| extend Type = type_s
| extend Severity = details_severity_s
| extend Classifications = details_classifications_s
| extend Platform = target_platform_s
```
```kql
let regexEmpire = tostring(toscalar(externaldata(cmdlets:string)[@"https://raw.githubusercontent.com/Azure/Azure-Sentinel/master/Sample%20Data/Feeds/EmpireCommandString.txt"] with (format="txt")));
(union isfuzzy=true
 (SecurityEvent
| where EventID == 4688
//consider filtering on filename if perf issues occur
//where FileName in~ ("powershell.exe","powershell_ise.exe","pwsh.exe")
| where not(ParentProcessName has_any ('gc_worker.exe', 'gc_service.exe'))
| where CommandLine has "-encodedCommand"
| parse kind=regex flags=i CommandLine with * "-EncodedCommand " encodedCommand
| extend encodedCommand = iff(encodedCommand has " ", tostring(split(encodedCommand, " ")[0]), encodedCommand)
// Note: currently the base64_decode_tostring function is limited to supporting UTF8
| extend decodedCommand = translate('\0','', base64_decode_tostring(substring(encodedCommand, 0, strlen(encodedCommand) -  (strlen(encodedCommand) %8)))), encodedCommand, CommandLine , strlen(encodedCommand)
| extend EfectiveCommand = iff(isnotempty(encodedCommand), decodedCommand, CommandLine)
| where EfectiveCommand matches regex regexEmpire
| project timestamp = TimeGenerated, Computer, SubjectUserName, SubjectDomainName, FileName = Process, EfectiveCommand, decodedCommand, encodedCommand, CommandLine, ParentProcessName
| extend HostName = split(Computer, '.', 0)[0], DnsDomain = strcat_array(array_slice(split(Computer, '.'), 1, -1), '.')
),
(WindowsEvent
| where EventID == 4688
| where EventData has_any ("-encodedCommand", "powershell.exe","powershell_ise.exe","pwsh.exe")
| where not(EventData has_any ('gc_worker.exe', 'gc_service.exe'))
//consider filtering on filename if perf issues occur
//extend NewProcessName = tostring(EventData.NewProcessName)
//extend Process=tostring(split(NewProcessName, '\\')[-1])
//FileName = Process
//where FileName in~ ("powershell.exe","powershell_ise.exe","pwsh.exe")
| extend ParentProcessName = tostring(EventData.ParentProcessName)
| where not(ParentProcessName has_any ('gc_worker.exe', 'gc_service.exe'))
| extend CommandLine = tostring(EventData.CommandLine)
| where CommandLine has "-encodedCommand"
| parse kind=regex flags=i CommandLine with * "-EncodedCommand " encodedCommand
| extend encodedCommand = iff(encodedCommand has " ", tostring(split(encodedCommand, " ")[0]), encodedCommand)
// Note: currently the base64_decode_tostring function is limited to supporting UTF8
| extend decodedCommand = translate('\0','', base64_decode_tostring(substring(encodedCommand, 0, strlen(encodedCommand) -  (strlen(encodedCommand) %8)))), encodedCommand, CommandLine , strlen(encodedCommand)
| extend EfectiveCommand = iff(isnotempty(encodedCommand), decodedCommand, CommandLine)
| where EfectiveCommand matches regex regexEmpire
| extend SubjectUserName = tostring(EventData.SubjectUserName)
| extend SubjectDomainName = tostring(EventData.SubjectDomainName)
| extend NewProcessName = tostring(EventData.NewProcessName)
| extend Process=tostring(split(NewProcessName, '\\')[-1])
| project timestamp = TimeGenerated, Computer, SubjectUserName, SubjectDomainName, FileName = Process, EfectiveCommand, decodedCommand, encodedCommand, CommandLine, ParentProcessName
| extend HostName = split(Computer, '.', 0)[0], DnsDomain = strcat_array(array_slice(split(Computer, '.'), 1, -1), '.')
))
```

## Escalation Criteria
- Process Discovery activity observed on a privileged account or critical system.
- Activity follows or precedes other suspicious behaviour in the same investigation.
- Automated triage cannot confidently rule out malicious intent.

## False Positive Considerations
- Legitimate administrative or maintenance activity matching this pattern.
- Approved security testing or red team exercise.
- Known benign software producing similar telemetry.

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