# [HIGH] Node-gyp Supply Chain Compromise: A Self-Propagating npm Worm That Hides in binding.gyp

**Source:** Snyk
**Published:** 2026-06-04
**Article:** https://snyk.io/blog/node-gyp-supply-chain-compromise-self-propagating-npm-worm-binding-gyp/

## Threat Profile

Snyk Blog In this article
Written by Liran Tal 
June 4, 2026
0 mins read A supply chain attack is actively spreading through the npm registry by abusing a file most security tooling never looks at: binding.gyp . Instead of relying on the well-monitored preinstall or postinstall lifecycle scripts, the malware ships a weaponized binding.gyp that triggers node-gyp to execute attacker-controlled code automatically during npm install . Snyk is tracking the incident as Node-gyp Supply Chain Compromise…

## Indicators of Compromise (high-fidelity only)

- **SHA256:** `ef641e956f91d501b748085996303c96a64d67f63bfeef0dda175e5aa19cca90`
- **SHA256:** `5926b86b642e00672252953eb30d8f75cfb7797fe3118bd6fa2cfbee92905d61`
- **SHA256:** `ceff7c51d70832c3ec8dd2744b606a23b3c924ef664ae23439b9b742ea154108`
- **SHA256:** `da39146ef451d1b174a24d00b1e2a45cd38d54e849737f8f35333dcb22175707`
- **SHA256:** `e3dbe63aded45278f49c4746ab938ed9472b36def79b43e2dd2d7eff014481d1`
- **SHA256:** `82d83274680df928fdda296a348e01802f595e412308c399565c320df444052a`
- **SHA256:** `288f26c2eadcb1a7923fe376d16f5404216cce15d9fc162a4a78574dc7df399a`
- **SHA1:** `8bf051251ec3b973e39a313547e53421a2f8d2f6`
- **SHA1:** `608d01124cd6b5b8c55888e984b4c4d9b06fa686`
- **SHA1:** `ab9903d9edc720d1e11ea7d3d3e7a1c456f44ff7`

## MITRE ATT&CK Techniques

- **T1071.001** — Web Protocols
- **T1071.004** — DNS
- **T1566.002** — Spearphishing Link
- **T1204.001** — User Execution: Malicious Link
- **T1059.001** — PowerShell
- **T1204.004** — User Execution: Malicious Copy and Paste
- **T1027** — Obfuscated Files or Information
- **T1195.002** — Compromise Software Supply Chain
- **T1204.002** — User Execution: Malicious File

## 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
```

### 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
```

### PowerShell encoded / obfuscated command

`UC_PS_OBFUSCATED` · 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.process_name IN ("powershell.exe","pwsh.exe")
      AND (Processes.process="*-enc *" OR Processes.process="*EncodedCommand*"
        OR Processes.process="*FromBase64String*" OR Processes.process="*-nop*"
        OR Processes.process="*-w hidden*" OR Processes.process="*Invoke-Expression*"
        OR Processes.process="*IEX(*" OR Processes.process="*DownloadString*"
        OR Processes.process="*Net.WebClient*")
    by Processes.dest, Processes.user, Processes.process_name, Processes.process, Processes.parent_process_name
| `drop_dm_object_name(Processes)`
```

**Defender KQL:**
```kql
DeviceProcessEvents
| where Timestamp > ago(7d)
| where AccountName !endswith "$"
| where FileName in~ ("powershell.exe","pwsh.exe")
| where ProcessCommandLine matches regex @"(?i)(-enc|encodedcommand|frombase64string|-nop|-w\s+hidden|invoke-expression|iex\s*\(|downloadstring|net\.webclient)"
| project Timestamp, DeviceName, AccountName, ProcessCommandLine,
          InitiatingProcessFileName, InitiatingProcessCommandLine
```

### Trusted vendor binary / installer launching unusual children

`UC_SUPPLY_CHAIN` · phase: **exploit** · confidence: **Medium**

**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 ("setup.exe","installer.exe","update.exe")
      AND Processes.process_name IN ("powershell.exe","cmd.exe","rundll32.exe","regsvr32.exe","mshta.exe","wscript.exe","cscript.exe","wmic.exe","bitsadmin.exe")
    by Processes.dest, Processes.user, Processes.parent_process_name, Processes.process_name, Processes.process
| `drop_dm_object_name(Processes)`
```

**Defender KQL:**
```kql
DeviceProcessEvents
| where Timestamp > ago(7d)
| where AccountName !endswith "$"
| where InitiatingProcessFileName in~ ("setup.exe","installer.exe","update.exe")
| where FileName in~ ("powershell.exe","cmd.exe","rundll32.exe","regsvr32.exe","mshta.exe","wscript.exe","cscript.exe","wmic.exe","bitsadmin.exe")
| project Timestamp, DeviceName, AccountName, InitiatingProcessFileName, FileName, ProcessCommandLine
```

### Article-specific behavioural hunt — Node-gyp Supply Chain Compromise: A Self-Propagating npm Worm That Hides in bind

`UC_130_6` · phase: **exploit** · confidence: **High**

**Splunk SPL (CIM):**
```spl
``` Article-specific bespoke detection — Node-gyp Supply Chain Compromise: A Self-Propagating npm Worm That Hides in bind ```
| tstats `summariesonly` count earliest(_time) AS firstTime latest(_time) AS lastTime
    from datamodel=Endpoint.Processes
    where (Processes.process_name IN ("index.js","node.js"))
    by Processes.dest, Processes.user, Processes.process_name,
       Processes.process, Processes.parent_process_name, Processes.process_path
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| append [
| tstats `summariesonly` count
    from datamodel=Endpoint.Filesystem
    where Filesystem.action IN ("created","modified")
      AND (Filesystem.file_path="*/dev/null*" OR Filesystem.file_name IN ("index.js","node.js"))
    by Filesystem.dest, Filesystem.user, Filesystem.process_name,
       Filesystem.file_path, Filesystem.file_name
| `drop_dm_object_name(Filesystem)`
]
```

**Defender KQL:**
```kql
// Article-specific bespoke detection — Node-gyp Supply Chain Compromise: A Self-Propagating npm Worm That Hides in bind
// Hunts the actual binaries / paths / commandline fragments named
// in the article instead of a generic technique-class template.
DeviceProcessEvents
| where Timestamp > ago(30d)
| where (FileName in~ ("index.js", "node.js"))
| project Timestamp, DeviceName, AccountName, FileName,
          FolderPath, ProcessCommandLine,
          InitiatingProcessFileName, InitiatingProcessCommandLine
| order by Timestamp desc

// File-creation events for the named binaries / paths
DeviceFileEvents
| where Timestamp > ago(30d)
| where ActionType in ("FileCreated","FileModified")
| where (FolderPath has_any ("/dev/null") or FileName in~ ("index.js", "node.js"))
| project Timestamp, DeviceName, AccountName, FolderPath,
          FileName, ActionType, InitiatingProcessFileName,
          InitiatingProcessCommandLine
| order by Timestamp desc
```

### 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.

- **File hash IOCs — endpoint file/process match** ([template](../_TEMPLATES.md#hash-ioc)) — phase: **install**, confidence: **High**
  - file hash IOC(s): `ef641e956f91d501b748085996303c96a64d67f63bfeef0dda175e5aa19cca90`, `5926b86b642e00672252953eb30d8f75cfb7797fe3118bd6fa2cfbee92905d61`, `ceff7c51d70832c3ec8dd2744b606a23b3c924ef664ae23439b9b742ea154108`, `da39146ef451d1b174a24d00b1e2a45cd38d54e849737f8f35333dcb22175707`, `e3dbe63aded45278f49c4746ab938ed9472b36def79b43e2dd2d7eff014481d1`, `82d83274680df928fdda296a348e01802f595e412308c399565c320df444052a`, `288f26c2eadcb1a7923fe376d16f5404216cce15d9fc162a4a78574dc7df399a`, `8bf051251ec3b973e39a313547e53421a2f8d2f6` _(+2 more)_


## Why this matters

Severity classified as **HIGH** based on: IOCs present, 7 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.