Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects endpoint execution of specific known brute-force scripts and tools (such as ssh_brute.py, brute3.py, auto_login.py, etc.) using Python or shell interpreters, correlated with a high outbound network connection fan-out (50 or more distinct target IPs) from the same process.
Detects repeated authentication failures against the wireless controller. Wireless
authentication attacks require physical proximity, so unlike internet-facing
brute force this indicates somebody near the building — which changes the response
entirely.
Onboarding: CISCO-AIR-CT5508-K9 is ingested via Syslog (Bloo extractor 201).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=authentication where sourcename='CISCO-AIR-CT5508-K9' and action='LOGIN'
| duration 15m
| groupby srcip, reason
| select srcip, reason, distinct_count(user)
| having distinct_count_col1 > 5
authentication attacks require physical proximity, so unlike internet-facing
brute force this indicates somebody near the building — which changes the response
entirely.
Onboarding: CISCO-AIR-CT5508-K9 is ingested via Syslog (Bloo extractor 201).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=authentication where sourcename='CISCO-AIR-CT5508-K9' and action='LOGIN'
| duration 15m
| groupby srcip, reason
| select srcip, reason, distinct_count(user)
| having distinct_count_col1 > 5
Detects a burst of failed authentications against Zimbra. Internet-facing webmail is
among the most consistently attacked surfaces in any estate, and Zimbra deployments
frequently sit outside the identity controls applied to the rest of the organisation.
Onboarding: ZIMBRA is ingested via Syslog (Bloo extractor 123).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=authentication where sourcename='ZIMBRA' and action='LOGIN'
| duration 15m
| groupby srcip, reason
| select srcip, reason, distinct_count(user)
| having distinct_count_col1 > 10
among the most consistently attacked surfaces in any estate, and Zimbra deployments
frequently sit outside the identity controls applied to the rest of the organisation.
Onboarding: ZIMBRA is ingested via Syslog (Bloo extractor 123).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=authentication where sourcename='ZIMBRA' and action='LOGIN'
| duration 15m
| groupby srcip, reason
| select srcip, reason, distinct_count(user)
| having distinct_count_col1 > 10
Detects anomalous Kerberos ticket requests observed by ADAudit Plus. Service ticket
harvesting — one account requesting tickets for many services in quick succession —
is the precursor to offline cracking of service account credentials, and it is quiet
at the domain controller unless something is watching for the pattern.
Onboarding: MANAGE-ENGINE-ADAUDIT-PLUS is ingested via Syslog (KV) (Bloo extractor 830).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=win-audit where sourcename='MANAGE-ENGINE-ADAUDIT-PLUS'
and action='KERBEROS_AUTHENTICATION_TICKET_REQUESTED'
| duration 1h
| groupby user, domain
| select user, domain, count(*) as cnt
| having cnt > 20
harvesting — one account requesting tickets for many services in quick succession —
is the precursor to offline cracking of service account credentials, and it is quiet
at the domain controller unless something is watching for the pattern.
Onboarding: MANAGE-ENGINE-ADAUDIT-PLUS is ingested via Syslog (KV) (Bloo extractor 830).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=win-audit where sourcename='MANAGE-ENGINE-ADAUDIT-PLUS'
and action='KERBEROS_AUTHENTICATION_TICKET_REQUESTED'
| duration 1h
| groupby user, domain
| select user, domain, count(*) as cnt
| having cnt > 20
Detects a privileged password change shortly after failed authentication attempts
against the vault. An attacker who gains vault access frequently rotates the
credential to lock out the legitimate owner and secure their own hold on it.
The sequence matters more than either event alone: failures followed by a successful
change is the pattern, and a change on its own is routine.
Onboarding: CYBERARK is ingested via Syslog (CEF) (Bloo extractor 279).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='CYBERARK' and action='PASSWORD_CHANGED'
| groupby user, targetuser, srcip, reason
against the vault. An attacker who gains vault access frequently rotates the
credential to lock out the legitimate owner and secure their own hold on it.
The sequence matters more than either event alone: failures followed by a successful
change is the pattern, and a change on its own is routine.
Onboarding: CYBERARK is ingested via Syslog (CEF) (Bloo extractor 279).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='CYBERARK' and action='PASSWORD_CHANGED'
| groupby user, targetuser, srcip, reason
Detects when Node.js or NPM processes access sensitive credential files such as .npmrc, SSH private keys, or AWS credentials, followed by an outbound public network connection from the same device within a 15-minute window.
Detects endpoint execution of specific known brute-force scripts and tools (such as ssh_brute.py, brute3.py, auto_login.py, etc.) using Python or shell interpreters, correlated with a high outbound network connection fan-out (50 or more distinct target IPs) from the same process.
Detects endpoint execution of specific known brute-force scripts and tools (such as ssh_brute.py, brute3.py, auto_login.py, etc.) using Python or shell interpreters, correlated with a high outbound network connection fan-out (50 or more distinct target IPs) from the same process.
Detects one account viewing many secrets in a short period. Normal privileged work
touches one or two; sweeping the vault is harvesting, and it is the single most
valuable action available to an attacker who reaches a PAM platform.
Onboarding: SECRET-SERVER is ingested via Syslog (CEF) (Bloo extractor 844).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=secretserver-secret where sourcename='SECRET-SERVER' and action='VIEWED'
| duration 1h
| groupby user, srcip
| select user, srcip, distinct_count(file)
| having distinct_count_col1 > 10
touches one or two; sweeping the vault is harvesting, and it is the single most
valuable action available to an attacker who reaches a PAM platform.
Onboarding: SECRET-SERVER is ingested via Syslog (CEF) (Bloo extractor 844).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=secretserver-secret where sourcename='SECRET-SERVER' and action='VIEWED'
| duration 1h
| groupby user, srcip
| select user, srcip, distinct_count(file)
| having distinct_count_col1 > 10
Detects one account retrieving an unusually high number of distinct privileged
credentials in a short window. Legitimate privileged work involves one or two
checkouts for a specific task; sweeping the vault is what an attacker does after
compromising a PAM operator account, to harvest as much as possible before the
access is noticed.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='PAM360' and action='PASSWORD_RETRIEVED'
| duration 1h
| groupby user
| select user, distinct_count(targetuser)
| having distinct_count_col1 > 10
credentials in a short window. Legitimate privileged work involves one or two
checkouts for a specific task; sweeping the vault is what an attacker does after
compromising a PAM operator account, to harvest as much as possible before the
access is noticed.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='PAM360' and action='PASSWORD_RETRIEVED'
| duration 1h
| groupby user
| select user, distinct_count(targetuser)
| having distinct_count_col1 > 10
Detects a privileged credential retrieved from the vault with no session following it.
Legitimate checkout is followed by work. Retrieval without use suggests the credential
was taken to be kept — staged for later, or exfiltrated for use outside the platform
where the vault cannot see it.
This is a slow-burn detection and deliberately so: it surfaces preparation rather
than action, which is where the response window is widest.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='PAM360' and action='PASSWORD_RETRIEVED'
| duration 24h
| groupby user, targetuser
Legitimate checkout is followed by work. Retrieval without use suggests the credential
was taken to be kept — staged for later, or exfiltrated for use outside the platform
where the vault cannot see it.
This is a slow-burn detection and deliberately so: it surfaces preparation rather
than action, which is where the response window is widest.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='PAM360' and action='PASSWORD_RETRIEVED'
| duration 24h
| groupby user, targetuser
Detects use of a vaulted privileged credential from a source address with no prior
history for that account. Privileged accounts operate from a narrow and stable set of
jump hosts; a new origin means either an undocumented access path or an attacker
operating the credential from their own foothold.
Onboarding: CYBERARK is ingested via Syslog (CEF) (Bloo extractor 279).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='CYBERARK' and action='PASSWORD_USED'
| groupby user, targetuser, srcip, role
history for that account. Privileged accounts operate from a narrow and stable set of
jump hosts; a new origin means either an undocumented access path or an attacker
operating the credential from their own foothold.
Onboarding: CYBERARK is ingested via Syslog (CEF) (Bloo extractor 279).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='CYBERARK' and action='PASSWORD_USED'
| groupby user, targetuser, srcip, role
Detects a privileged credential retrieved from the vault with no session following it.
Legitimate checkout is followed by work. Retrieval without use suggests the credential
was taken to be kept — staged for later, or exfiltrated for use outside the platform
where the vault cannot see it.
This is a slow-burn detection and deliberately so: it surfaces preparation rather
than action, which is where the response window is widest.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='PAM360' and action='PASSWORD_RETRIEVED'
| duration 24h
| groupby user, targetuser
Legitimate checkout is followed by work. Retrieval without use suggests the credential
was taken to be kept — staged for later, or exfiltrated for use outside the platform
where the vault cannot see it.
This is a slow-burn detection and deliberately so: it surfaces preparation rather
than action, which is where the response window is widest.
Onboarding: PAM360 is ingested via Syslog (Bloo extractor 879).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=iam where sourcename='PAM360' and action='PASSWORD_RETRIEVED'
| duration 24h
| groupby user, targetuser
Detects endpoint execution of specific known brute-force scripts and tools (such as ssh_brute.py, brute3.py, auto_login.py, etc.) using Python or shell interpreters, correlated with a high outbound network connection fan-out (50 or more distinct target IPs) from the same process.
Identifies brute force attacks on SAP systems using RFC logons. Detects a single IP attempting to sign in to several systems or clients within a 1-hour interval, indicating potential credential stuffing or internal lateral movement.
Detects the Shai-Hulud tensorlake payload pattern of fetching a platform-specific HackBrowserData binary and then executing it on the same host to dump browser-stored credentials. Anchored on tool behavior (download then execution on one host) rather than a single sample hash or the rotating C2 domain.
Detects post-exploitation activity against Ivanti ICS / Connect Secure
appliances on Windows hosts, where a script host (cmd.exe, powershell.exe, w3wp.exe)
drops a web shell (.aspx/.ashx/.asmx) into the appliance WebRoot or reaches into the
CredentialStore / system binaries. These behaviors are the hallmark of attackers
converting an authenticated file-write or SSRF into persistent remote code execution
and credential theft on edge devices.
appliances on Windows hosts, where a script host (cmd.exe, powershell.exe, w3wp.exe)
drops a web shell (.aspx/.ashx/.asmx) into the appliance WebRoot or reaches into the
CredentialStore / system binaries. These behaviors are the hallmark of attackers
converting an authenticated file-write or SSRF into persistent remote code execution
and credential theft on edge devices.
Detects the execution of known credential theft tools such as Mimikatz, SharpDecryptPwd, and WebBrowserPassView via EDR process creation telemetry.
Detects processes accessing sensitive files and configurations associated with multiple AI coding assistants (such as Claude, Codex, Grok, and Cursor) within a short time window, potentially indicating unauthorized access or credential theft from AI tools.
Detects non-browser processes accessing multiple sensitive browser credential/cookie files or cryptocurrency wallet files within a 24-hour window, which is a common indicator of credential theft or information stealer activity.
The following analytic identifies processes with command-line parameters associated with web browser credential dumping tools, specifically targeting behaviors used by Remcos RAT malware. It leverages data from Endpoint Detection and Response (EDR) agents, focusing on command-line executions and specific file paths. This activity is significant as it indicates potential credential theft, a common tactic in broader cyber-espionage campaigns. If confirmed malicious, attackers could gain unauthorized access to sensitive web credentials, leading to further system compromise and data breaches.
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