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
-
Execution of Defense Evasion Patchers
Query · scopingIdentify hosts running known activator or patching tools used to suppress security alerts or bypass licensing via hash, original filename, or path.
reads hb_process_activitysqlSELECT 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.
-
Suspicious Script Execution
Query · enrichmentLocate destructive script execution by name or content keywords, restricted to the hosts found in the scoping step.
reads hb_script_activitysqlSELECT 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.
-
High-Volume File Encryption Lead
Query · baselineDetect mass file modification or renaming characteristic of ransomware impact on the scoped hosts.
reads hb_file_activitysqlSELECT 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 DESCWhat a hit looks like. Processes touching more than 500 files on scoped hosts within the window. Validates ransomware behavior.
-
Weigh Intrusion and Impact Evidence
Agent triageEvaluate whether the combination of patcher execution, script activity, and mass file changes indicates a successful ransomware attack.
-
Containment Route
DecisionRoute malicious findings to automated containment and others to analyst review.
-
Isolate Infected Host
Response actionStop the spread of ransomware encryption.
-
Manual Analyst Review
Analyst taskVerify the agent verdict and assess the extent of data loss.
-
Close Out
Analyst taskFinalize findings and record tuning notes for detection engineering.
Coverage
Scenario coverage
| Stage | Covered | How, 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
| Parameter | Type | Default | What it is |
|---|---|---|---|
lookback_days | number | 14 | Days of history to examine. |
patcher_hashes | list[hash] | 9896a6fcb9bb5ac1ec5297b4a65be3f647589adf7c37b45f3f7466decd6a4a7f, fed979f93bcaf4e73ebd25748093a92095d5109cbd01d55f97bdc50ce509ad2f | Hashes for known bypass tools and system patchers (e.g., SECOH-QAD.exe, AAct.exe). |
patcher_names | list[string] | aact.exe, secoh-qad.exe, kmsauto.exe | Original file names for known activator tools used to evade licensing/security. |
scope_hosts | list[host] | — | Hosts identified in the first step; paste hostnames here to scope the subsequent queries. |
script_names | list[string] | content.js | Filenames of suspicious scripts identified in the research. |
Telemetry
| Source | Category | Telemetry |
|---|---|---|
| Endpoint telemetry (hb_ surfaces) | endpoint | endpoint |
Source
---
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.