# [CRIT] New macOS ClickFix attack silently mounts DMGs to push infostealer

**Source:** BleepingComputer
**Published:** 2026-06-23
**Article:** https://www.bleepingcomputer.com/news/security/new-macos-clickfix-attack-silently-mounts-dmgs-to-push-infostealer/

## Threat Profile

New macOS ClickFix attack silently mounts DMGs to push infostealer 
By Lawrence Abrams 
June 23, 2026
02:30 PM
0 




A new macOS ClickFix campaign is using Terminal commands to silently download, mount, and launch info-stealing malware from malicious disk image (DMG) files.




The campaign is infecting Mac devices with the Atomic macOS Stealer (AMOS) infostealer, which steals browser credentials, cryptocurrency wallet data, Keychain data, messaging app information, and user documents.




Rese…

## Indicators of Compromise (high-fidelity only)

- **IPv4 (defanged):** `196.251.107.171`
- **Domain (defanged):** `svs-verificationdate.beer`

## MITRE ATT&CK Techniques

- **T1071.001** — Web Protocols
- **T1071.004** — DNS
- **T1071** — Application Layer Protocol
- **T1539** — Steal Web Session Cookie
- **T1555.003** — Credentials from Web Browsers
- **T1566.002** — Spearphishing Link
- **T1204.001** — User Execution: Malicious Link
- **T1059.001** — PowerShell
- **T1204.004** — User Execution: Malicious Copy and Paste

## Kill chain phases observed

_(none detected from narrative keywords)_

## Recommended hunts

### Beaconing — periodic outbound to small set of destinations

`UC_BEACONING` · phase: **c2** · confidence: **Medium**

**Splunk SPL (CIM):**
```spl
| tstats `summariesonly` count, values(All_Traffic.dest_port) AS ports
    from datamodel=Network_Traffic.All_Traffic
    where All_Traffic.action="allowed" AND All_Traffic.dest_category!="internal"
    by _time span=10s, All_Traffic.src, All_Traffic.dest
| `drop_dm_object_name(All_Traffic)`
| streamstats current=f last(_time) AS prev_time by src, dest
| eval delta = _time - prev_time
| stats avg(delta) AS avg_delta stdev(delta) AS sd_delta count by src, dest
| where count > 30 AND sd_delta < 5 AND avg_delta>=30 AND avg_delta<=600
| sort - count
```

**Defender KQL:**
```kql
DeviceNetworkEvents
| where Timestamp > ago(1d)
| where RemoteIPType == "Public" and ActionType == "ConnectionSuccess"
| project DeviceName, RemoteIP, RemotePort, Timestamp
| sort by DeviceName asc, RemoteIP asc, RemotePort asc, Timestamp asc
| extend prev_dev = prev(DeviceName, 1), prev_ip = prev(RemoteIP, 1),
         prev_port = prev(RemotePort, 1), prev_ts = prev(Timestamp, 1)
| where DeviceName == prev_dev and RemoteIP == prev_ip and RemotePort == prev_port
| extend delta_sec = datetime_diff('second', Timestamp, prev_ts)
| summarize conn_count = count(), avg_delta = avg(delta_sec), stdev_delta = stdev(delta_sec)
    by DeviceName, RemoteIP, RemotePort
| where conn_count > 30 and avg_delta between (30.0 .. 600.0) and stdev_delta < 5.0
| order by conn_count desc
```

### Infostealer — non-browser process accessing browser cookie/login DBs

`UC_BROWSER_STEALER` · phase: **actions** · confidence: **High**

**Splunk SPL (CIM):**
```spl
| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime
    from datamodel=Endpoint.Filesystem
    where (Filesystem.file_path="*\Google\Chrome\User Data\*\Login Data*"
        OR Filesystem.file_path="*\Google\Chrome\User Data\*\Cookies*"
        OR Filesystem.file_path="*\Microsoft\Edge\User Data\*\Login Data*"
        OR Filesystem.file_path="*\Mozilla\Firefox\Profiles\*\logins.json*"
        OR Filesystem.file_path="*\Mozilla\Firefox\Profiles\*\cookies.sqlite*")
      AND NOT Filesystem.process_name IN ("chrome.exe","msedge.exe","firefox.exe","brave.exe","opera.exe")
    by Filesystem.dest, Filesystem.process_name, Filesystem.file_path, Filesystem.user
| `drop_dm_object_name(Filesystem)`
```

**Defender KQL:**
```kql
DeviceFileEvents
| where Timestamp > ago(7d)
| where InitiatingProcessAccountName !endswith "$"
| where FolderPath has_any (@"\Google\Chrome\User Data\", @"\Microsoft\Edge\User Data\", @"\Mozilla\Firefox\Profiles\")
| where FileName in~ ("Login Data","Cookies","logins.json","cookies.sqlite")
| where InitiatingProcessFileName !in~ ("chrome.exe","msedge.exe","firefox.exe","brave.exe","opera.exe")
| project Timestamp, DeviceName, InitiatingProcessAccountName, InitiatingProcessFileName, FolderPath, FileName, ActionType
```

### Phishing-link click correlated to endpoint execution

`UC_PHISH_LINK` · phase: **delivery** · confidence: **High**

**Splunk SPL (CIM):**
```spl
``` Phishing-link click that drives endpoint execution within 60s ```
| tstats `summariesonly` earliest(_time) AS click_time
    from datamodel=Web
    where Web.action="allowed"
    by Web.src, Web.user, Web.dest, Web.url
| `drop_dm_object_name(Web)`
| rename user AS recipient, dest AS clicked_domain, url AS clicked_url
| join type=inner recipient
    [| tstats `summariesonly` count
         from datamodel=Email.All_Email
         where All_Email.action="delivered" AND All_Email.url!="-"
         by All_Email.recipient, All_Email.src_user, All_Email.url, All_Email.subject
     | `drop_dm_object_name(All_Email)`
     | rex field=url "https?://(?<email_domain>[^/]+)"
     | rename recipient AS recipient]
| join type=inner src
    [| tstats `summariesonly` earliest(_time) AS exec_time
         values(Processes.process) AS exec_cmd, values(Processes.process_name) AS exec_proc
         from datamodel=Endpoint.Processes
         where Processes.parent_process_name IN ("chrome.exe","msedge.exe","firefox.exe",
                                                   "outlook.exe","brave.exe","arc.exe")
           AND Processes.process_name IN ("powershell.exe","pwsh.exe","cmd.exe","mshta.exe",
                                            "rundll32.exe","regsvr32.exe","wscript.exe",
                                            "cscript.exe","bitsadmin.exe","certutil.exe",
                                            "curl.exe","wget.exe")
         by Processes.dest, Processes.user
     | `drop_dm_object_name(Processes)`
     | rename dest AS src]
| eval delta_sec = exec_time - click_time
| where delta_sec >= 0 AND delta_sec <= 60
| table click_time, exec_time, delta_sec, recipient, src, src_user, subject,
        clicked_domain, clicked_url, exec_proc, exec_cmd
| sort - click_time
```

**Defender KQL:**
```kql
// Phishing-link click that drives endpoint execution within 60s.
// Far higher fidelity than "every clicked URL" — most legitimate clicks
// never spawn a non-browser child process, so the join eliminates the
// 99% of noise that makes a raw click query unactionable.
let LookbackDays = 7d;
let SuspectClicks = UrlClickEvents
    | where Timestamp > ago(LookbackDays)
    | where AccountName !endswith "$"
    | where ActionType in ("ClickAllowed","ClickedThrough")
    | join kind=inner (
        EmailEvents
        | where Timestamp > ago(LookbackDays)
        | where DeliveryAction == "Delivered"
        | where EmailDirection == "Inbound"
        | project NetworkMessageId, Subject, SenderFromAddress, SenderFromDomain,
                  RecipientEmailAddress, EmailTimestamp = Timestamp
      ) on NetworkMessageId
    | join kind=leftouter (
        EmailUrlInfo | project NetworkMessageId, Url, UrlDomain
      ) on NetworkMessageId, Url
    | project ClickTime = Timestamp, AccountUpn, IPAddress, Url, UrlDomain,
              Subject, SenderFromAddress, SenderFromDomain, RecipientEmailAddress,
              ActionType;
// Correlate to a non-browser child process spawned within 60 seconds on
// the recipient's device.
DeviceProcessEvents
| where Timestamp > ago(LookbackDays)
| where InitiatingProcessFileName in~ ("chrome.exe","msedge.exe","firefox.exe",
                                         "outlook.exe","brave.exe","arc.exe")
| where FileName in~ ("powershell.exe","pwsh.exe","cmd.exe","mshta.exe",
                        "rundll32.exe","regsvr32.exe","wscript.exe","cscript.exe",
                        "bitsadmin.exe","certutil.exe","curl.exe","wget.exe")
| join kind=inner SuspectClicks on $left.AccountName == $right.AccountUpn
| where Timestamp between (ClickTime .. ClickTime + 60s)
| project ClickTime, ProcessTime = Timestamp,
          DelaySec = datetime_diff('second', Timestamp, ClickTime),
          DeviceName, AccountName, RecipientEmailAddress, SenderFromAddress,
          Subject, Url, UrlDomain, ActionType,
          FileName, ProcessCommandLine, InitiatingProcessFileName
| order by ClickTime desc
```

### Fake CAPTCHA / clipboard-injected PowerShell (ClickFix / FakeCaptcha)

`UC_FAKECAPTCHA` · phase: **exploit** · confidence: **High**

**Splunk SPL (CIM):**
```spl
| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime
    from datamodel=Endpoint.Processes
    where Processes.parent_process_name IN ("explorer.exe","RuntimeBroker.exe")
      AND Processes.process_name IN ("powershell.exe","pwsh.exe","mshta.exe")
      AND (Processes.process="*iex*" OR Processes.process="*Invoke-Expression*"
        OR Processes.process="*FromBase64*" OR Processes.process="*DownloadString*"
        OR Processes.process="*hxxp*" OR Processes.process="*curl*" OR Processes.process="*wget*")
    by Processes.dest, Processes.user, Processes.process, Processes.parent_process_name
| `drop_dm_object_name(Processes)`
```

**Defender KQL:**
```kql
DeviceProcessEvents
| where Timestamp > ago(7d)
| where AccountName !endswith "$"
| where InitiatingProcessFileName in~ ("explorer.exe","RuntimeBroker.exe")
| where FileName in~ ("powershell.exe","pwsh.exe","mshta.exe")
| where ProcessCommandLine matches regex @"(?i)(iex|invoke-expression|frombase64|downloadstring|hxxp|curl |wget )"
| project Timestamp, DeviceName, AccountName, ProcessCommandLine, InitiatingProcessCommandLine
```

### IOC-driven hunts (use shared templates)

These are standard IOC-substitution hunts — the canonical SPL and KQL live once in [`_TEMPLATES.md`](../_TEMPLATES.md), so we don't repeat the same boilerplate on every CVE / hash / network-IOC briefing.

- **Network connections to article IPs / domains** ([template](../_TEMPLATES.md#network-ioc)) — phase: **c2**, confidence: **High**
  - IP / domain IOC(s): `196.251.107.171`, `svs-verificationdate.beer`


## Why this matters

Severity classified as **CRIT** based on: IOCs present, 5 use case(s) fired, 9 technique(s) inferred. Read the full article for actor attribution, tooling details, and any defanged IOCs in the body that aren't visible in the RSS summary.