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Severity
HIGH
CVSS
7.5
Priority
0.685
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Executive
Executive Summary
Threat actors are reported to be using Python-based automation paired with AI/ML tooling to systematically probe major endpoint detection and response platforms, including CrowdStrike Falcon, Sophos EDR, and Microsoft Defender, before deploying malware. This industrialization of EDR testing may reduce the technical expertise barrier previously required for EDR bypass, potentially allowing a broader pool of threat actors to develop evasion-capable malware. The trend signals a structural shift in the attacker economics of endpoint evasion, where automation and AI may increasingly commoditize capabilities once limited to sophisticated threat actors. However, this pattern has been reported by security news outlets and vendor observations, not yet confirmed as a widespread operational campaign.
Impact Assessment
CISA KEV Status
Not listed
Threat Severity
HIGH
High severity — prioritize for investigation
Actor Attribution
HIGH
Unknown — no attribution in source reporting
TTP Sophistication
HIGH
9 MITRE ATT&CK techniques identified
Detection Difficulty
HIGH
Multiple evasion techniques observed
Target Scope
INFO
CrowdStrike Falcon, Sophos EDR, Microsoft Windows Defender (all current versions)
Are You Exposed?
⚠
Your industry is targeted by Unknown — no attribution in source reporting → Heightened risk
⚠
You use products/services from CrowdStrike Falcon → Assess exposure
⚠
9 attack techniques identified — review your detection coverage for these TTPs
✓
Your EDR/XDR detects the listed IOCs and TTPs → Reduced risk
✓
You have incident response procedures for this threat type → Prepared
Assessment estimated from severity rating and threat indicators
Business Context
This tradecraft development effectively erodes the detection confidence of endpoint security investments across organizations of all sizes — the EDR platforms being tested represent the dominant enterprise endpoint security market, meaning the majority of organizations with mature security programs are directly relevant. If attackers can reliably identify and eliminate detection signals before deployment, the assumed risk reduction from endpoint controls must be recalibrated, which affects cyber insurance underwriting, compliance attestations that rely on EDR coverage claims, and incident response assumptions. Organizations in regulated sectors (financial services, healthcare, critical infrastructure) that treat EDR as a primary compensating control in risk frameworks should treat this as a control-confidence issue requiring immediate reassessment of layered detection strategy.
You Are Affected If
Your organization deploys CrowdStrike Falcon, Sophos EDR, or Microsoft Defender as primary endpoint detection
Your detection architecture relies heavily on EDR as the last or primary line of defense, with limited SIEM or network-layer visibility
Your security program has not recently validated EDR detection coverage against obfuscation and injection techniques (T1027, T1055)
Your threat model assumes EDR bypass requires sophisticated, nation-state-level tradecraft expertise
Your risk assessments or compliance attestations cite EDR coverage as a primary control against malware deployment
Board Talking Points
Attackers are now using AI tools to automatically test and bypass the endpoint security software most enterprises rely on before launching attacks, reducing the protection those investments provide.
Security teams should audit whether endpoint tools are deployed in active prevention mode with layered network and log monitoring as backup, and report findings to leadership within 30 days.
Without layered detection beyond endpoint tools, a successfully evaded malware payload may execute undetected until significant damage — data theft, ransomware, or operational disruption — has already occurred.
Technical Analysis
The tradecraft evolution documented here represents a qualitative change in how threat actors approach endpoint evasion, not a new vulnerability, but a reported new operational workflow.
Historically, evading a specific EDR product required hands-on knowledge of that platform's behavioral detection logic, memory scanning routines, and telemetry hooks.
The reported technique pairs Python automation with AI/ML tooling to create iterative feedback loops: a malware sample is tested against a target EDR (CrowdStrike Falcon, Sophos EDR, or Microsoft Defender), the detection result is captured, and the AI component suggests or applies obfuscation or injection modifications to reduce detection signal.
The loop repeats until the sample achieves acceptable evasion rates. This maps directly to MITRE ATT&CK T1622 (Debugger Evasion) and T1497.001 (System Checks), which describe adversary techniques for identifying whether an analysis or detection environment is present; the automated framework would operationalize these checks at scale.
The MITRE techniques associated with this reported activity span the evasion spectrum: T1027 and T1027.002 (Obfuscated Files or Information, Software Packing), T1027.005 (Indicator Removal from Tools), T1055 (Process Injection), T1562.001 (Impair Defenses: Disable or Modify Tools), T1620 (Reflective Code Loading), and T1588.001 (Obtain Capabilities: Malware). Taken together, these represent the complete toolchain for producing a detection-resistant payload; if the automation orchestrates these techniques iteratively, each could be tuned rather than applied once.
CWE-1039 (Automated Recognition Mechanism with Inadequate Detection or Handling of Adversarial Input Conditions) is the applicable weakness classification. CWE-1039 describes exactly the condition where an automated detection mechanism, the EDR, fails when adversarial inputs are crafted to exploit gaps in its recognition logic. The AI-driven evasion loop is, in effect, an adversarial input generator targeting the EDR's detection models.
The downstream implication for security operations is significant. Detection rules and behavioral signatures that security teams currently trust are being actively and systematically tested by attackers before deployment. An EDR that correctly flags a sample in a vendor's test environment may not flag the operationally tuned variant the attacker ultimately deploys. Organizations relying primarily on endpoint controls as their last line of defense are exposed; those with layered detection across network, identity, and log telemetry have more durable coverage. This pattern has been reported via security news outlets (Dark Reading) and vendor observations, but has not yet been attributed to a specific threat actor or widespread campaign, which may indicate either emerging adoption or limited current deployment.
Action Checklist IR ENRICHED
Triage Priority:
URGENT
Escalate to immediate priority and engage IR leadership if Sysmon Event ID 8 (CreateRemoteThread) or Event ID 7036 (EDR service stop) is detected on hosts where CrowdStrike Falcon, Sophos EDR, or Microsoft Defender was the primary prevention control, indicating active evasion tooling may have already probed or disabled endpoint defenses ahead of payload deployment.
1
Step 1: Assess exposure, confirm which EDR platforms are deployed across your environment (CrowdStrike Falcon, Sophos EDR, Microsoft Defender, or combinations); organizations using any of these are directly relevant to this story
IR Detail
Preparation
NIST 800-61r3 §2 — Preparation: establishing IR capability and asset/tool inventory as a precondition for effective detection and response
NIST IR-4 (Incident Handling)
NIST SI-4 (System Monitoring)
CIS 1.1 (Establish and Maintain Detailed Enterprise Asset Inventory)
CIS 2.1 (Establish and Maintain a Software Inventory)
Compensating Control
Run 'sc query' on Windows hosts or 'systemctl list-units --type=service' on Linux to enumerate running security agents. Cross-reference against your CMDB or a simple osquery query: SELECT name, version, status FROM programs WHERE name LIKE '%CrowdStrike%' OR name LIKE '%Sophos%' OR name LIKE '%Windows Defender%'; — pipe output to a CSV for a 2-person team asset sweep across a sample of endpoints.
Preserve Evidence
Before conducting the sweep, snapshot the current EDR agent version and policy assignment from the CrowdStrike Falcon console (Host Management > Hosts), Sophos Central (Devices > Computers), or Microsoft Defender Security Center (Device Inventory) — these baselines are needed to identify any agents that were silently degraded or uninstalled by AI-assisted evasion tooling probing your environment prior to discovery.
2
Step 2: Review EDR detection posture, audit whether your EDR deployment is in prevention mode or detection-only mode; verify behavioral detection and memory scanning are enabled, not just signature-based scanning; reference NIST SI-3 (Malicious Code Protection) for control baseline
IR Detail
Preparation
NIST 800-61r3 §2 — Preparation: ensuring detection tools are configured to maximum effectiveness before an incident occurs
NIST SI-3 (Malicious Code Protection)
NIST SI-4 (System Monitoring)
NIST CM-6 (Configuration Settings)
CIS 7.1 (Establish and Maintain a Vulnerability Management Process)
Compensating Control
For CrowdStrike: use Falcon console Prevention Policies to confirm 'Suspicious Processes', 'Memory Scanning', and 'Exploit Mitigation' toggles are ON, not just 'Detect'. For Defender: run 'Get-MpPreference | Select-Object -Property DisableRealtimeMonitoring, DisableBehaviorMonitoring, DisableIOAVProtection' in PowerShell — any True value is a gap. For Sophos: check Central > Policies > Threat Protection and confirm 'Live Protection' and 'Deep Learning' are enabled. Document findings in a configuration audit spreadsheet.
Preserve Evidence
Pull the current policy configuration export from each EDR platform before making changes — CrowdStrike: Falcon console > Prevention Policies > Export; Defender: 'Get-MpPreference | Export-Csv'; Sophos: Central > Policies > Export. These snapshots establish whether AI-assisted evasion testing exploited a pre-existing detection gap (detection-only mode) or whether the evasion tooling succeeded against a fully hardened policy, which has different risk implications.
3
Step 3: Layer defenses beyond endpoint, validate that SIEM/log aggregation (NIST AU-2, AU-6; CIS 8.2) is capturing process creation, parent-child process relationships, and suspicious injection events that behavioral EDR may miss on tuned evasion variants; process injection (T1055) and reflective code loading (T1620) leave artifacts in Windows event logs even when EDR is evaded
IR Detail
Detection & Analysis
NIST 800-61r3 §3.2 — Detection and Analysis: correlating multiple log sources to identify adversary activity that a single sensor may not surface
NIST AU-2 (Event Logging)
NIST AU-6 (Audit Record Review, Analysis, and Reporting)
NIST SI-4 (System Monitoring)
CIS 8.2 (Collect Audit Logs)
Compensating Control
Deploy Sysmon with SwiftOnSecurity's config (https://github.com/SwiftOnSecurity/sysmon-config) to capture Event ID 1 (Process Create), Event ID 8 (CreateRemoteThread — indicative of T1055 injection), Event ID 10 (ProcessAccess — reflective loading attempts), and Event ID 25 (ProcessTampering). Forward Sysmon logs to a free ELK stack or Windows Event Forwarding (WEF) collector. Apply the public Sigma rule 'proc_creation_win_susp_parent_child.yml' to flag anomalous parent-child chains from your EDR host processes (CSFalconService.exe, SophosHealth.exe, MsMpEng.exe).
Preserve Evidence
Capture Windows Security Event Log Event ID 4688 (Process Creation with command-line logging enabled via GPO: Computer Configuration > Windows Settings > Security Settings > Advanced Audit Policy > Detailed Tracking > Audit Process Creation + 'Include command line in process creation events'), and Sysmon Event ID 8 (CreateRemoteThread) targeting CrowdStrike, Sophos, or Defender process handles — these are the primary Windows-native artifacts that AI-assisted evasion frameworks leave behind even when the EDR agent itself fails to alert.
4
Step 4: Tune detection for evasion-indicating behaviors, hunt for T1562.001 indicators (EDR process tampering, service disablement attempts) and T1497.001 (sandbox/VM detection queries); these upstream behaviors often precede a successfully evaded payload and may be more reliably detected than the payload itself; reference NIST SI-4 (System Monitoring)
IR Detail
Detection & Analysis
NIST 800-61r3 §3.2 — Detection and Analysis: using precursor and indicator analysis to identify intrusion activity earlier in the kill chain before payload execution
NIST SI-4 (System Monitoring)
NIST AU-6 (Audit Record Review, Analysis, and Reporting)
NIST IR-5 (Incident Monitoring)
CIS 7.1 (Establish and Maintain a Vulnerability Management Process)
Compensating Control
Write a Sigma rule targeting Windows Security Event ID 7036 (Service Control Manager) for stop/disable events on 'CrowdStrike Falcon Sensor Service', 'Sophos Endpoint Defense', or 'Windows Defender Antivirus Service'. Additionally, query Sysmon Event ID 1 for WMI queries or PowerShell commands checking 'VBOX', 'VMware', 'QEMU', 'SandboxEnvironment', or 'GetTickCount' thresholds — these are the exact sandbox-detection queries AI-assisted evasion frameworks execute during the pre-deployment testing phase (T1497.001). Script: 'Get-WinEvent -LogName System | Where-Object {$_.Id -eq 7036 -and $_.Message -match "CrowdStrike|Sophos|Defender"}' for rapid triage.
Preserve Evidence
Preserve Windows System Event Log Event ID 7036 and 7040 entries (service state changes) and Windows Security Event ID 4657 (registry value modification) targeting HKLM\SYSTEM\CurrentControlSet\Services\CSAgent, HKLM\SYSTEM\CurrentControlSet\Services\SophosEndpointDefense, and HKLM\SYSTEM\CurrentControlSet\Services\WinDefend — registry-level tamper of these keys is a direct forensic indicator that AI-assisted EDR evasion tooling probed or attempted to disable your specific deployed platform prior to payload staging.
5
Step 5: Update threat model, incorporate the reported AI-assisted EDR evasion pattern as a potential tradecraft evolving in your threat register; adjust your assumed technical barrier for EDR bypass in risk assessments if the pattern gains adoption; this affects risk ratings for any control architecture where EDR is the primary detection layer
IR Detail
Post-Incident
NIST 800-61r3 §4 — Post-Incident Activity: translating incident lessons and threat intelligence into updated policies, risk models, and detection improvements
NIST RA-3 (Risk Assessment)
NIST IR-8 (Incident Response Plan)
NIST SI-5 (Security Alerts, Advisories, and Directives)
CIS 7.1 (Establish and Maintain a Vulnerability Management Process)
CIS 7.2 (Establish and Maintain a Remediation Process)
Compensating Control
Use MITRE ATT&CK Navigator (free, browser-based) to map T1562.001, T1055, T1620, and T1497.001 against your current detection layer coverage. Export the heatmap and mark any technique where CrowdStrike, Sophos, or Defender is the sole detection source as 'single-point-of-failure' — this visualization is sufficient to brief a risk committee and justify compensating controls without a commercial risk platform.
Preserve Evidence
Before updating the threat register, collect the current risk register entry for 'endpoint evasion' or 'malware bypass' as a baseline document. Also preserve any prior EDR efficacy test results (e.g., past red team reports, Atomic Red Team test outputs, or vendor-provided detection rate benchmarks) so the delta in assumed attacker skill threshold — now lowered by AI-assisted tooling — is documented as a justified risk rating change rather than a subjective judgment.
6
Step 6: Communicate findings, brief leadership on the reported EDR evasion pattern and confirm whether your organization is deploying EDR platforms potentially at risk; frame as a detection-confidence assessment requiring layered validation, not a current incident
IR Detail
Post-Incident
NIST 800-61r3 §4 — Post-Incident Activity: communicating lessons learned to organizational leadership and updating stakeholder understanding of detection capability gaps
NIST IR-6 (Incident Reporting)
NIST IR-8 (Incident Response Plan)
NIST IR-7 (Incident Response Assistance)
Compensating Control
Prepare a one-page brief using the NIST CSF outcome language leadership already understands: frame CrowdStrike Falcon, Sophos EDR, and Defender as 'DE.CM' (Detect/Monitor) controls that are now subject to adversarial testing before use, and present the compensating Sysmon/SIEM layer as the 'detect what EDR misses' control. Attach the ATT&CK Navigator heatmap from Step 5 as the visual evidence — no commercial tooling required to make this case credible.
Preserve Evidence
Attach to the leadership brief: (1) the EDR policy configuration snapshots from Step 2 showing current prevention vs. detection-only posture, (2) a count of Sysmon Event ID 8 or 10 detections from the past 30 days that EDR did not independently alert on — this gap metric is the most persuasive evidence that detection confidence is reduced, and it is entirely derivable from free tooling already in place.
7
Step 7: Monitor developments, track for follow-up research from CrowdStrike, Sophos, and Microsoft on detection engineering responses; watch for updated MITRE ATT&CK sub-technique coverage related to AI-assisted evasion tooling
IR Detail
Post-Incident
NIST 800-61r3 §4 — Post-Incident Activity: maintaining situational awareness post-event and integrating updated threat intelligence into detection and response improvements
NIST SI-5 (Security Alerts, Advisories, and Directives)
NIST IR-5 (Incident Monitoring)
NIST AU-6 (Audit Record Review, Analysis, and Reporting)
CIS 7.1 (Establish and Maintain a Vulnerability Management Process)
Compensating Control
Subscribe to CrowdStrike's Adversary Intelligence RSS feed, Sophos X-Ops blog, and Microsoft Threat Intelligence Blog via free RSS aggregator (Feedly free tier). Create a MITRE ATT&CK watch list for T1562, T1055, T1620, and T1497 sub-technique pages — MITRE publishes technique updates publicly and the ATT&CK changelog is available on GitHub (github.com/mitre/cti). Set a calendar reminder for monthly ATT&CK version release checks; version updates relevant to AI-assisted evasion will appear in the techniques JSON diff.
Preserve Evidence
Maintain a running log of CrowdStrike Falcon sensor version changelogs, Sophos Central policy update history, and Microsoft Defender platform update notes (published at aka.ms/mdatpportal) — when vendors release detection engineering responses to AI-assisted evasion, the changelog entries for 'behavioral detection', 'memory scanning', or 'ML model update' are the forensic markers that your environment's detection posture has improved, and they anchor your threat model revision dates.
Recovery Guidance
After confirming no active compromise, re-validate all three EDR platforms are in prevention mode (not detection-only) and that Sysmon is deployed with parent-child process and injection event logging active across 100% of in-scope endpoints. Monitor Sysmon Event IDs 1, 8, 10, and 25 daily for a minimum of 30 days post-assessment, as AI-assisted evasion frameworks may re-probe the environment on a delayed schedule after an initial failed attempt. Document all configuration changes made during this response cycle in your change management system to support a post-incident review and updated detection baseline.
Key Forensic Artifacts
Sysmon Event ID 8 (CreateRemoteThread) logs targeting CSFalconService.exe, SophosHealth.exe, or MsMpEng.exe process handles — direct indicator of T1055 injection attempts against the specific EDR agents deployed in this environment
Windows System Event Log Event ID 7036 and 7040 entries recording stop or disable state changes for 'CrowdStrike Falcon Sensor Service', 'Sophos Endpoint Defense', or 'WinDefend' — the primary Windows-native record of T1562.001 EDR tampering by AI-assisted evasion tooling
Windows Security Event ID 4657 (Registry Value Modified) for HKLM\SYSTEM\CurrentControlSet\Services\CSAgent, HKLM\SYSTEM\CurrentControlSet\Services\SophosEndpointDefense, and HKLM\SYSTEM\CurrentControlSet\Services\WinDefend — registry-level evidence of service configuration tampering that persists even if the EDR agent was successfully blinded
Windows Security Event ID 4688 (Process Creation) with full command-line logging for processes executing WMI sandbox detection queries (e.g., Win32_ComputerSystem queries for 'VirtualBox', 'VMware', 'QEMU') — the T1497.001 fingerprint left by AI-assisted evasion frameworks during their pre-deployment environment validation phase
EDR policy configuration exports (CrowdStrike Prevention Policy export, Sophos Central policy JSON, Defender 'Get-MpPreference' output) timestamped at assessment start — establishes whether evasion testing succeeded against a hardened or already-degraded detection posture, which is critical for determining whether a gap existed prior to the threat actor's probing activity
Detection Guidance
Detection for this tradecraft pattern must shift upstream from payload execution to evasion-signaling behaviors, because a successfully tuned sample may not trigger EDR signatures by design.
Key behavioral patterns to hunt (mapped to MITRE techniques):
- T1497.001 / T1622 , Sandbox and debugger evasion checks: Look for processes querying registry keys, WMI classes, or environment variables commonly associated with sandbox or analysis environment fingerprinting (e.g., queries to HKLM\SYSTEM\CurrentControlSet\Services\VBoxGuest, checks for analysis tool process names, CPUID timing checks).
These system checks often precede deployment of an evasion-tuned payload.
- T1055 (Process Injection): Hunt for anomalous parent-child process relationships, unexpected cross-process memory writes (WriteProcessMemory API calls), and processes with no image on disk (hollow processes).
Windows Sysmon Event IDs 8 (CreateRemoteThread), 10 (ProcessAccess), and 25 (ProcessTampering) are relevant. Reference NIST SI-4 for system monitoring control baseline.
- T1620 (Reflective Code Loading): Monitor for modules loaded without a corresponding file path on disk. Sysmon Event ID 7 (ImageLoad) with no mapped path is a useful signal. EDR telemetry that captures in-memory module loads provides coverage here.
- T1562.001 (Impair Defenses): Alert on any attempt to stop, suspend, or modify EDR services or their registry entries. Windows Event Log 7036 (service state changes) for known EDR service names warrants immediate triage. Reference NIST SI-4 and CIS 8.2.
- T1027 / T1027.002 / T1027.005 (Obfuscation and Packing): Entropy analysis on executable sections can flag packed or obfuscated binaries. High-entropy PE sections (.text above ~7.0 bits/byte) warrant sandbox detonation before execution. D3-FMBV (File Magic Byte Verification) and D3-SFA (System File Analysis) are applicable D3FEND countermeasures.
Log sources to prioritize: Windows Security Event Log (process creation 4688), Sysmon (if deployed), EDR telemetry, PowerShell script block logging (Event ID 4104), and WMI activity logs. Organizations without Sysmon or equivalent process telemetry have a significant visibility gap against this tradecraft.
Audit gap to check: Verify that AU-3 (Content of Audit Records) requirements are met, specifically that process creation logs capture full command-line arguments and parent process information. Without this, injection and obfuscation chains are difficult to reconstruct after the fact.
Indicators of Compromise (2)
Export as
Splunk SPL
KQL
Elastic
Copy All (2)
2 tools
Platform Playbooks
Microsoft Sentinel / Defender
CrowdStrike Falcon
AWS Security
🔒
Microsoft 365 E3
3 log sources
Basic identity + audit. No endpoint advanced hunting. Defender for Endpoint requires separate P1/P2 license.
🛡
Microsoft 365 E5
18 log sources
Full Defender suite: Endpoint P2, Identity, Office 365 P2, Cloud App Security. Advanced hunting across all workloads.
🔍
E5 + Sentinel
27 log sources
All E5 tables + SIEM data (CEF, Syslog, Windows Security Events, Threat Intelligence). Analytics rules, playbooks, workbooks.
Hard indicator (direct match)
Contextual (behavioral query)
Shared platform (review required)
IOC Detection Queries (2)
Known attack tool — NOT a legitimate system binary. Any execution is suspicious.
KQL Query Preview
Read-only — detection query only
// Threat: AI-Automated EDR Evasion Testing Accelerates Malware Deployment Cycle
// Attack tool: Python-based EDR evasion automation framework
// Context: Python automation scripts paired with AI/ML tooling used to iteratively test malware samples against CrowdStrike Falcon, Sophos EDR, and Microsoft Defender to identify detection gaps prior to deployme
DeviceProcessEvents
| where Timestamp > ago(30d)
| where FileName =~ "Python-based EDR evasion automation framework"
or ProcessCommandLine has "Python-based EDR evasion automation framework"
or InitiatingProcessCommandLine has "Python-based EDR evasion automation framework"
| project Timestamp, DeviceName, FileName, FolderPath,
ProcessCommandLine, AccountName, AccountDomain,
InitiatingProcessFileName, InitiatingProcessCommandLine
| sort by Timestamp desc
Known attack tool — NOT a legitimate system binary. Any execution is suspicious.
KQL Query Preview
Read-only — detection query only
// Threat: AI-Automated EDR Evasion Testing Accelerates Malware Deployment Cycle
// Attack tool: attackers-automate-edr-evasion-testing) for published indicators
// Context: Source reporting describes AI-assisted EDR evasion tooling but available source text does not contain specific tool names, hashes, or infrastructure indicators; consult original Dark Reading article f
DeviceProcessEvents
| where Timestamp > ago(30d)
| where FileName =~ "attackers-automate-edr-evasion-testing) for published indicators"
or ProcessCommandLine has "attackers-automate-edr-evasion-testing) for published indicators"
or InitiatingProcessCommandLine has "attackers-automate-edr-evasion-testing) for published indicators"
| project Timestamp, DeviceName, FileName, FolderPath,
ProcessCommandLine, AccountName, AccountDomain,
InitiatingProcessFileName, InitiatingProcessCommandLine
| sort by Timestamp desc
MITRE ATT&CK Hunting Queries (3)
Sentinel rule: Encoded command execution
KQL Query Preview
Read-only — detection query only
DeviceProcessEvents
| where Timestamp > ago(7d)
| where ProcessCommandLine matches regex @"[A-Za-z0-9+/]{50,}={0,2}"
or ProcessCommandLine has_any ("-enc ", "-encodedcommand", "frombase64string", "certutil -decode")
| where FileName in~ ("powershell.exe", "pwsh.exe", "cmd.exe", "certutil.exe")
| project Timestamp, DeviceName, FileName, ProcessCommandLine, AccountName
| sort by Timestamp desc
Sentinel rule: Process injection / hollowing
KQL Query Preview
Read-only — detection query only
DeviceEvents
| where Timestamp > ago(7d)
| where ActionType in ("CreateRemoteThreadApiCall", "QueueUserApcRemoteApiCall", "WriteToLsassProcessMemory", "NtAllocateVirtualMemoryApiCall", "NtMapViewOfSectionRemoteApiCall")
| project Timestamp, DeviceName, FileName, ProcessCommandLine, InitiatingProcessFileName, ActionType
| sort by Timestamp desc
Sentinel rule: Security tool tampering
KQL Query Preview
Read-only — detection query only
DeviceProcessEvents
| where Timestamp > ago(7d)
| where ProcessCommandLine has_any (
"Set-MpPreference", "DisableRealtimeMonitoring",
"net stop", "sc stop", "sc delete", "taskkill /f",
"Add-MpPreference -ExclusionPath"
)
| where ProcessCommandLine has_any ("defender", "sense", "security", "antivirus", "firewall", "crowdstrike", "sentinel")
| project Timestamp, DeviceName, ProcessCommandLine, AccountName, InitiatingProcessFileName
| sort by Timestamp desc
No actionable IOCs for CrowdStrike import (benign/contextual indicators excluded).
No hard IOCs available for AWS detection queries (contextual/benign indicators excluded).
Compliance Framework Mappings
T1027.005
T1622
T1027.002
T1055
T1562.001
T1620
+3
MITRE ATT&CK Mapping
T1027.005
Indicator Removal from Tools
defense-evasion
T1622
Debugger Evasion
defense-evasion
T1055
Process Injection
defense-evasion
T1562.001
Disable or Modify Tools
defense-evasion
T1620
Reflective Code Loading
defense-evasion
T1027
Obfuscated Files or Information
defense-evasion
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Guidance Disclaimer
The analysis, framework mappings, and incident response recommendations in this intelligence
item are derived from established industry standards including NIST SP 800-61, NIST SP 800-53,
CIS Controls v8, MITRE ATT&CK, and other recognized frameworks. This content is provided
as supplemental intelligence guidance only and does not constitute professional incident response
services. Organizations should adapt all recommendations to their specific environment, risk
tolerance, and regulatory requirements. This material is not a substitute for your organization's
official incident response plan, legal counsel, or qualified security practitioners.
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