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Host Intrusion and Destructive Impact

An adversary has bypassed local security controls using system patchers and is executing AI-generated scripts to perform mass file encryption for ransomware extortion.

Based on research by Cisco Talos 2026-09-28 9 steps · 3 queries T1059 T1486 T1562

Brief

Why This Hunt Matters

Adversaries refine their evasion techniques by using system patchers and activator tools to suppress security alerts. Recent research by Cisco Talos in the article "Should you care about an AI slowdown?" (https://blog.talosintelligence.com/should-you-care-about-an-ai-slowdown/) highlights how actors like Qilin and "The Gentlemen" use automation to accelerate their impact. These groups use AI-generated scripts to handle complex tasks once they establish a foothold. This hunt targets the intersection of defense evasion and destructive behavior.

How the Hunt Flows

The first phase focuses on scoping via hb_process_activity. The query searches for known activator tools and system patchers such as SECOH-QAD.exe, AAct.exe, or KMSAuto. The presence of these tools is a precursor to more aggressive actions, as the adversary uses them to ensure their payloads run without interference from local defense mechanisms. The analyst uses this list of hosts to focus the rest of the hunt. The second phase runs two parallel checks on the hosts identified in the scoping step. The first check examines hb_script_activity for destructive keywords or specific script names like content.js. The second check uses hb_file_activity to baseline file modifications, specifically looking for processes touching more than 500 files within a short window. This high-volume activity provides the behavioral evidence of ransomware encryption. The final phase uses an agent to correlate the findings. The agent weighs the presence of bypass tools against the temporal evidence of script execution and mass file touches. It checks if the script content contains commands to delete shadow copies or encrypt data. If a host shows both the evasion tool and the impact behavior, the playbook routes the host for network isolation and analyst review to confirm the extent of the damage.

What the Hunt Cannot See

This hunt has two primary blind spots. First, it relies on host-level file telemetry. If the sensor does not capture file-level renames or updates on network shares via SMB, the hunt misses encryption occurring on shared storage. Second, if the adversary uses multi-stage obfuscation for their scripts, the initial script content query might fail to identify the destructive intent if the de-obfuscated code never reaches the script logging surface as a discrete block.

In this series

Steps

  1. Execution of Defense Evasion Patchers

    Query · scoping

    Identify hosts running known activator or patching tools used to suppress security alerts or bypass licensing via hash, original filename, or path.

    reads hb_process_activitysql
    SELECT device_hostname, process_name, process_path, process_hash_sha256, process_original_file_name, user_name, time FROM hb_process_activity WHERE (instr(',' || '{{patcher_hashes}}' || ',', ',' || LOWER(process_hash_sha256) || ',') > 0 OR instr(',' || '{{patcher_names}}' || ',', ',' || LOWER(process_original_file_name) || ',') > 0 OR LOWER(process_path) LIKE '%\\kmsauto\\%') AND time >= datetime('now', '-{{lookback_days}} days')

    What a hit looks like. Rows identify specific hosts running known bypass tools. Silence suggests no known malicious patcher behavior occurred in the timeframe.

  2. Suspicious Script Execution

    Query · enrichment

    Locate destructive script execution by name or content keywords, restricted to the hosts found in the scoping step.

    reads hb_script_activitysql
    SELECT device_hostname, script_name, script_type, actor_user_name, time, script_content FROM hb_script_activity WHERE ('{{scope_hosts}}' = '' OR instr(',' || '{{scope_hosts}}' || ',', ',' || device_hostname || ',') > 0) AND (instr(',' || '{{script_names}}' || ',', ',' || LOWER(script_name) || ',') > 0 OR LOWER(script_content) LIKE '%encrypt%' OR LOWER(script_content) LIKE '%delete%shadow%') AND time >= datetime('now', '-{{lookback_days}} days')

    What a hit looks like. Script names from the report or scripts containing destructive keywords on scoped hosts. High signal when found on hosts running activator tools.

  3. High-Volume File Encryption Lead

    Query · baseline

    Detect mass file modification or renaming characteristic of ransomware impact on the scoped hosts.

    reads hb_file_activitysql
    SELECT device_hostname, process_name, COUNT(*) as file_touches, MIN(time) as first_touch, MAX(time) as last_touch FROM hb_file_activity WHERE ('{{scope_hosts}}' = '' OR instr(',' || '{{scope_hosts}}' || ',', ',' || device_hostname || ',') > 0) AND activity_id IN (3, 5) AND time >= datetime('now', '-{{lookback_days}} days') GROUP BY device_hostname, process_name HAVING file_touches > 500 ORDER BY file_touches DESC

    What a hit looks like. Processes touching more than 500 files on scoped hosts within the window. Validates ransomware behavior.

  4. Weigh Intrusion and Impact Evidence

    Agent triage

    Evaluate whether the combination of patcher execution, script activity, and mass file changes indicates a successful ransomware attack.

  5. Containment Route

    Decision

    Route malicious findings to automated containment and others to analyst review.

  6. Isolate Infected Host

    Response action

    Stop the spread of ransomware encryption.

  7. Manual Analyst Review

    Analyst task

    Verify the agent verdict and assess the extent of data loss.

  8. Close Out

    Analyst task

    Finalize findings and record tuning notes for detection engineering.

Coverage

Scenario coverage

StageCoveredHow, or why not
System Patching and Bypass Tools
T1562
Yes patcher-tool-execution
AI-Driven Destructive Scripting
T1059
Yes suspicious-script-activity
Data Encryption and Double Extortion
T1486
Yes high-volume-file-encryption
VPN Access and Credential Abuse
T1133
Out of scope Belongs to another part of the 'Should you care about an “AI slowdown?”' series.
AdaptixC2 Command and Control
T1071
Out of scope Belongs to another part of the 'Should you care about an “AI slowdown?”' series.

Blind spots

  • Needs hb_file_activity with rename/update coverage. If the sensor does not capture SMB activity at the file level for remote drives, we will miss encryption occurring on shared storage. It would answer Can we see file renames on all network shares?.
  • Needs hb_script_activity with full block content. Adversaries use AI to generate scripts that often include multi-stage obfuscation; if the agent only sees the first stage, it may misjudge the intent. It would answer Does the script content capture de-obfuscated AI code?.

Parameters & data

Parameters

ParameterTypeDefaultWhat it is
lookback_daysnumber14Days of history to examine.
patcher_hasheslist[hash]9896a6fcb9bb5ac1ec5297b4a65be3f647589adf7c37b45f3f7466decd6a4a7f, fed979f93bcaf4e73ebd25748093a92095d5109cbd01d55f97bdc50ce509ad2fHashes for known bypass tools and system patchers (e.g., SECOH-QAD.exe, AAct.exe).
patcher_nameslist[string]aact.exe, secoh-qad.exe, kmsauto.exeOriginal file names for known activator tools used to evade licensing/security.
scope_hostslist[host]—Hosts identified in the first step; paste hostnames here to scope the subsequent queries.
script_nameslist[string]content.jsFilenames of suspicious scripts identified in the research.

Telemetry

SourceCategoryTelemetry
Endpoint telemetry (hb_ surfaces)endpointendpoint

Source

Download hunt.md Definition (JSON) An open hunt.md file; it runs anywhere that reads the format.
---
analysis: A single rule flags a known hash; this hunt pivots from the presence of
  activator tools to verify if the same host executes destructive scripts and modifies
  files at ransomware-scale. It identifies the intent (encryption) and the tool (activator)
  together, which a standard rule cannot correlate across surfaces.
blind_spots:
- id: incomplete-file-telemetry
  question: Can we see file renames on all network shares?
  requires: hb_file_activity with rename/update coverage
  risk: If the sensor does not capture SMB activity at the file level for remote drives,
    we will miss encryption occurring on shared storage.
  stage: impact-double-extortion-ransomware
- id: obfuscated-scripts
  question: Does the script content capture de-obfuscated AI code?
  requires: hb_script_activity with full block content
  risk: Adversaries use AI to generate scripts that often include multi-stage obfuscation;
    if the agent only sees the first stage, it may misjudge the intent.
  stage: execution-ai-generated-scripts
coverage:
- stage: persistence-and-defense-evasion-patchers
  status: covered
  steps:
  - patcher-tool-execution
- stage: execution-ai-generated-scripts
  status: covered
  steps:
  - suspicious-script-activity
- stage: impact-double-extortion-ransomware
  status: covered
  steps:
  - high-volume-file-encryption
- reason: "Belongs to another part of the 'Should you care about an \u201CAI slowdown?\u201D\
    ' series."
  stage: initial-access-external-remote-services
  status: out_of_scope
- reason: "Belongs to another part of the 'Should you care about an \u201CAI slowdown?\u201D\
    ' series."
  stage: c2-red-team-tooling
  status: out_of_scope
guardrails:
  claims: no_unsupported
  evidence: citation_required
  missing_data: not_benign
  telemetry: untrusted
hunt:
  applicability: campaign-specific
  handoff: keep-as-periodic-hunt
  justification: The rise in ransomware activity by actors like Qilin using AI-driven
    automation requires proactive hunting for activator tools and destructive scripting.
    This hunt ensures that internal hosts are monitored for the 'cyber-vegetables'
    of intrusion even if perimeter defenses are bypassed.
  methodology: model-assisted
  trigger: intel-report
hypothesis: An adversary has bypassed local security controls using system patchers
  and is executing AI-generated scripts to perform mass file encryption for ransomware
  extortion.
labels:
- hunt
- attack.t1562
- attack.t1059
- attack.t1486
name: Host Intrusion and Destructive Impact
parameters:
  lookback_days:
    default: '14'
    description: Days of history to examine.
    type: number
  patcher_hashes:
    default:
    - 9896a6fcb9bb5ac1ec5297b4a65be3f647589adf7c37b45f3f7466decd6a4a7f
    - fed979f93bcaf4e73ebd25748093a92095d5109cbd01d55f97bdc50ce509ad2f
    description: Hashes for known bypass tools and system patchers (e.g., SECOH-QAD.exe,
      AAct.exe).
    from:
      kind: article
      observed: '2026-09-17'
      ref: talos-ai-slowdown
    type: list[hash]
  patcher_names:
    default:
    - aact.exe
    - secoh-qad.exe
    - kmsauto.exe
    description: Original file names for known activator tools used to evade licensing/security.
    from:
      kind: article
      observed: '2026-09-17'
      ref: talos-ai-slowdown
    type: list[string]
  scope_hosts:
    default: []
    description: Hosts identified in the first step; paste hostnames here to scope
      the subsequent queries.
    type: list[host]
  script_names:
    default:
    - content.js
    description: Filenames of suspicious scripts identified in the research.
    from:
      kind: article
      observed: '2026-09-17'
      ref: talos-ai-slowdown
    type: list[string]
provenance:
  authors:
  - name: Huntbase hunt generation
    org: huntbase.io
  generated:
    by: huntbase-hunt-generation
    from: https://blog.talosintelligence.com/should-you-care-about-an-ai-slowdown/
    gates:
    - dry-run
    - lint
    model: hb_google/gemini-3-flash-preview
rationale: Focus on endpoints where users might have administrative rights or where
  legacy business applications are hosted, as these are primary targets for 'The Gentlemen'
  and Qilin actors. Use the first step to identify specific hosts and then paste them
  into the scope_hosts parameter.
references:
- name: "Cisco Talos \u2014 Should you care about an AI slowdown?"
  url: https://blog.talosintelligence.com/should-you-care-about-an-ai-slowdown/
related:
- hunt: external-remote-service-auditing
  reason: Initial access via VPN or Citrix belongs to the companion hunt focused on
    external remote services.
  relation: out-of-scope-alternative
- hunt: remote-access-abuse-red-team-implants
  relation: follows
scenario:
  stages:
  - name: VPN Access and Credential Abuse
    observables:
    - External-facing VPN services
    - Administrative account logins
    - Sign-ins without multi-factor authentication (MFA)
    slug: initial-access-external-remote-services
    tactic: initial-access
    techniques:
    - T1133
  - name: AdaptixC2 Command and Control
    observables:
    - AdaptixC2 framework
    - VID001.exe
    - WCInstaller_NonAdmin.exe
    - w32.9f1f11a708-100.sbx.tg
    - w32.c4dd71e347-95.sbx.tg
    slug: c2-red-team-tooling
    tactic: command-and-control
    techniques:
    - T1071
  - name: System Patching and Bypass Tools
    observables:
    - SECOH-QAD.exe
    - AAct.exe
    - win.tool.procpatcher
    - w32.fed979f93b-95.sbx.tg
    slug: persistence-and-defense-evasion-patchers
    tactic: persistence
    techniques:
    - T1562
  - name: AI-Driven Destructive Scripting
    observables:
    - content.js
    - w32.38d053135d-95.sbx.tg
    - LLM-generated destructive scripts
    slug: execution-ai-generated-scripts
    tactic: execution
    techniques:
    - T1059
  - name: Data Encryption and Double Extortion
    observables:
    - Encryption of local and remote drives
    - Attempts to disable backup systems
    - Double-extortion communications
    slug: impact-double-extortion-ransomware
    tactic: impact
    techniques:
    - T1486
  summary: The Qilin and The Gentlemen ransomware groups are targeting Japanese SMEs
    using a combination of AI-generated destructive scripts and the AdaptixC2 red-teaming
    framework. Initial access is typically gained via external remote services like
    VPNs, leading to lateral movement, data theft, and double-extortion ransomware
    attacks.
series:
  index: 2
  slug: should-you-care-about-an-ai-slowdown
  title: "Should you care about an \u201CAI slowdown?\u201D"
  total: 2
severity: high
targets:
  analyst:
    name: Tier-2 analyst
    role: analyst
  endpoint:
    category: endpoint
    name: Endpoint telemetry (hb_ surfaces)
    telemetry:
    - endpoint
  hunter:
    agent: true
    name: Hunt agent
tlp: clear
type: investigation
---


# Host Intrusion and Destructive Impact

This hunt identifies host intrusion by finding bypass tools and destructive scripting. It searches for activator tools like SECOH-QAD.exe that adversaries use to evade detection and license validation. The hunt then evaluates script execution and high-volume file touches specifically on the affected hosts to confirm ransomware impact. An agent weighs the correlation between these bypass tools, script content, and encryption behavior to settle on a verdict.

## patcher-tool-execution
<!-- Execution of Defense Evasion Patchers -->
Identify hosts running known activator or patching tools used to suppress security alerts or bypass licensing via hash, original filename, or path.

```sqlite target=endpoint role=scoping params=(patcher_hashes=patcher_hashes, patcher_names=patcher_names, lookback_days=lookback_days)
~~~yaml
expected: Rows identify specific hosts running known bypass tools. Silence suggests
  no known malicious patcher behavior occurred in the timeframe.
reads:
- device_hostname
- process_name
- process_path
- process_hash_sha256
- process_original_file_name
- user_name
- time
silence: not_evidence_of_absence
source: hb_process_activity
verified: dry-run
verified_at: '2026-09-28'
~~~
SELECT device_hostname, process_name, process_path, process_hash_sha256, process_original_file_name, user_name, time FROM hb_process_activity WHERE (instr(',' || '{{patcher_hashes}}' || ',', ',' || LOWER(process_hash_sha256) || ',') > 0 OR instr(',' || '{{patcher_names}}' || ',', ',' || LOWER(process_original_file_name) || ',') > 0 OR LOWER(process_path) LIKE '%\\kmsauto\\%') AND time >= datetime('now', '-{{lookback_days}} days')
```

## fan-out-corroboration
<!-- Corroborate Execution and Impact -->
parallel:
- → suspicious-script-activity
- → high-volume-file-encryption
join: → agent-triage

## suspicious-script-activity
<!-- Suspicious Script Execution -->
Locate destructive script execution by name or content keywords, restricted to the hosts found in the scoping step.

```sqlite target=endpoint role=enrichment params=(script_names=script_names, scope_hosts=scope_hosts, lookback_days=lookback_days)
~~~yaml
expected: Script names from the report or scripts containing destructive keywords
  on scoped hosts. High signal when found on hosts running activator tools.
reads:
- device_hostname
- script_name
- script_type
- actor_user_name
- time
- script_content
silence: not_evidence_of_absence
source: hb_script_activity
verified: dry-run
verified_at: '2026-09-28'
~~~
SELECT device_hostname, script_name, script_type, actor_user_name, time, script_content FROM hb_script_activity WHERE ('{{scope_hosts}}' = '' OR instr(',' || '{{scope_hosts}}' || ',', ',' || device_hostname || ',') > 0) AND (instr(',' || '{{script_names}}' || ',', ',' || LOWER(script_name) || ',') > 0 OR LOWER(script_content) LIKE '%encrypt%' OR LOWER(script_content) LIKE '%delete%shadow%') AND time >= datetime('now', '-{{lookback_days}} days')
```

## high-volume-file-encryption
<!-- High-Volume File Encryption Lead -->
Detect mass file modification or renaming characteristic of ransomware impact on the scoped hosts.

```sqlite target=endpoint role=baseline params=(scope_hosts=scope_hosts, lookback_days=lookback_days)
~~~yaml
baseline:
  compare: first_seen
  window: '{{lookback_days}}d'
expected: Processes touching more than 500 files on scoped hosts within the window.
  Validates ransomware behavior.
prevalence:
  by: device_hostname
  key:
  - process_name
  rare_below: 3
reads:
- device_hostname
- process_name
- time
- activity_id
silence: not_evidence_of_absence
source: hb_file_activity
verified: dry-run
verified_at: '2026-09-28'
~~~
SELECT device_hostname, process_name, COUNT(*) as file_touches, MIN(time) as first_touch, MAX(time) as last_touch FROM hb_file_activity WHERE ('{{scope_hosts}}' = '' OR instr(',' || '{{scope_hosts}}' || ',', ',' || device_hostname || ',') > 0) AND activity_id IN (3, 5) AND time >= datetime('now', '-{{lookback_days}} days') GROUP BY device_hostname, process_name HAVING file_touches > 500 ORDER BY file_touches DESC
```

## agent-triage
<!-- Weigh Intrusion and Impact Evidence -->
```agent target=hunter
cite: required
context:
- patcher-tool-execution
- suspicious-script-activity
- high-volume-file-encryption
max_iterations: 4
objective: Determine if any host shows evidence of an active ransomware intrusion
  based on activator tool use and destructive scripts or file activity.
success_criteria: A per-host verdict of malicious | suspicious | benign with cited
  rows.
tools:
- endpoint
```

## decide-on-containment
<!-- Containment Route -->
if~: "the triage verdict is malicious for at least one host and includes evidence of mass file encryption" (confidence: high, judge=hunter)
then: → isolate-infected-host
indeterminate: → manual-investigation
unavailable: → manual-investigation (blind_spot: incomplete-file-telemetry)
else: → close-out-hunt

## isolate-infected-host
<!-- Isolate Infected Host -->
```action target=endpoint
~~~yaml
approval: required
~~~
Isolate the identified host to prevent further data encryption or lateral movement. Revoke the credentials of the user involved.
```
→ manual-investigation

## manual-investigation
<!-- Manual Analyst Review -->
```manual target=analyst
Review the script content and file activity cited by the agent. Check for common ransomware extensions in the file activity rows. Determine if the script successfully disabled backups.
```
→ close-out-hunt

## close-out-hunt
<!-- Close Out -->
```manual target=analyst
Document the hosts examined. If no malicious activity was found, record the absence of patcher tools as a successful hygiene check. Suggest new detection rules for the identified bypass hashes and behavioral original file names.
```
→ end

Run it

Take this hunt into your environment.

Open it in Huntbase to run every step against your own connections, with Scout weighing the evidence and your analysts in command. Or take the open hunt.md file anywhere that reads the format.

Machine-drafted by huntbase-hunt-generation using hb_google/gemini-3-flash-preview, gated by dry-run, lint, then reviewed by a person.