Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
379 detections
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Detects a sequence where a device runs a staging/archiving utility (such as WinRAR, 7-Zip, or a copy script) followed within 4 hours by a file transfer or synchronization tool (such as rclone or FileZilla), which is indicative of data staging prior to exfiltration.
Detects permitted transfers from a user who was recently blocked. Repeated blocks
followed by a success means a channel was found that the policy does not cover —
the user, or the attacker operating as them, worked out what gets through.
Onboarding: TRELLIX-DLP is ingested via Syslog (XML) (Bloo extractor 805).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=firewall where sourcename='TRELLIX-DLP' and action='PACKET_ALLOWED'
| duration 1h
| groupby srcip, dstip, dstport, app
followed by a success means a channel was found that the policy does not cover —
the user, or the attacker operating as them, worked out what gets through.
Onboarding: TRELLIX-DLP is ingested via Syslog (XML) (Bloo extractor 805).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=firewall where sourcename='TRELLIX-DLP' and action='PACKET_ALLOWED'
| duration 1h
| groupby srcip, dstip, dstport, app
Detects a substantial outbound transfer from a Meraki-protected site. Branch
locations have predictable, modest traffic profiles, which makes a sustained upload
unusually visible against that baseline compared with the same transfer leaving a
datacentre.
Onboarding: CISCO-MERAKI is ingested via Syslog (Bloo extractor 300).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=firewall where sourcename='CISCO-MERAKI' and action='SESSION_ESTABLISHED'
| duration 1h
| groupby srcip, dstip, dstport, app, txlen
locations have predictable, modest traffic profiles, which makes a sustained upload
unusually visible against that baseline compared with the same transfer leaving a
datacentre.
Onboarding: CISCO-MERAKI is ingested via Syslog (Bloo extractor 300).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=firewall where sourcename='CISCO-MERAKI' and action='SESSION_ESTABLISHED'
| duration 1h
| groupby srcip, dstip, dstport, app, txlen
Detects an unusual volume of externally directed mail from one sender. Mail is a
high-capacity exfiltration channel that is permitted by default, and a compromised
mailbox sending outward in bulk is both data loss and, where the content is phishing,
damage to the organisation's sending reputation.
Onboarding: MS-EXCHANGE is ingested via Syslog (Bloo extractor 142).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=email-gateway where sourcename='MS-EXCHANGE'
and action='EMAIL_SENT_EXTERNAL'
| duration 1h
| groupby sender
| select sender, count(*) as cnt
| having cnt > 100
high-capacity exfiltration channel that is permitted by default, and a compromised
mailbox sending outward in bulk is both data loss and, where the content is phishing,
damage to the organisation's sending reputation.
Onboarding: MS-EXCHANGE is ingested via Syslog (Bloo extractor 142).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=email-gateway where sourcename='MS-EXCHANGE'
and action='EMAIL_SENT_EXTERNAL'
| duration 1h
| groupby sender
| select sender, count(*) as cnt
| having cnt > 100
Detects data staging and exfiltration preceding Play double extortion: WinRAR/RAR adding files to an archive (recursive or password-protected) followed within 4 hours by a WinSCP transfer from the same host and user.
Detects a large outbound transfer measured at the Versa edge. Branch sites typically
send modest volumes, so a sustained upload from one is either a backup nobody
documented or data leaving a location with the least security coverage in the
estate.
Onboarding: VERSA-NETWORKS is ingested via Syslog (KV) (Bloo extractor 806).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=firewall where sourcename='VERSA-NETWORKS'
and action='SESSION_ESTABLISHED'
| duration 1h
| groupby srcip, dstip, dstport, app, txlen
send modest volumes, so a sustained upload from one is either a backup nobody
documented or data leaving a location with the least security coverage in the
estate.
Onboarding: VERSA-NETWORKS is ingested via Syslog (KV) (Bloo extractor 806).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=firewall where sourcename='VERSA-NETWORKS'
and action='SESSION_ESTABLISHED'
| duration 1h
| groupby srcip, dstip, dstport, app, txlen
Detects DNS tunnelling, where data is encoded into queries and answers against a
domain the attacker controls. TXT records carry the most payload per query, so a
high volume of TXT lookups beneath one parent domain is the characteristic shape.
Tunnelling is slow, which means it is usually evidence of a long-running compromise
rather than a recent one.
Onboarding: INFOBLOX is ingested via Syslog (CEF) (Bloo extractor 155).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=dns where sourcename='INFOBLOX' and action='DNS_QUERIED'
and lower(recordtype) = 'txt'
| duration 1h
| groupby srcip
| select srcip, count(*) as cnt
| having cnt > 100
domain the attacker controls. TXT records carry the most payload per query, so a
high volume of TXT lookups beneath one parent domain is the characteristic shape.
Tunnelling is slow, which means it is usually evidence of a long-running compromise
rather than a recent one.
Onboarding: INFOBLOX is ingested via Syslog (CEF) (Bloo extractor 155).
Integration guide: https://bloo.io/docs/hypercloud/syslog-connector
BQL (Bloo Query Language):
stream=dns where sourcename='INFOBLOX' and action='DNS_QUERIED'
and lower(recordtype) = 'txt'
| duration 1h
| groupby srcip
| select srcip, count(*) as cnt
| having cnt > 100
Detects the use of curl or wget commands targeting the Cloud Instance Metadata Service (IMDS) at 169.254.169.254 for credential theft, or performing file uploads and data exfiltration patterns.
The following analytic detects instances where network traffic, identified by port and transport layer protocol as prohibited in the "lookup_interesting_ports" table, is allowed.
It uses the Network_Traffic data model to cross-reference traffic data against predefined security policies.
This activity is significant for a SOC as it highlights potential misconfigurations or policy violations that could lead to unauthorized access or data exfiltration.
If confirmed malicious, this could allow attackers to bypass network defenses, leading to potential data breaches and compromising the organization's security posture.
It uses the Network_Traffic data model to cross-reference traffic data against predefined security policies.
This activity is significant for a SOC as it highlights potential misconfigurations or policy violations that could lead to unauthorized access or data exfiltration.
If confirmed malicious, this could allow attackers to bypass network defenses, leading to potential data breaches and compromising the organization's security posture.
Detects data leakage and exfiltration attempts targeting Ollama model metadata and configuration endpoints. Adversaries repeatedly query /api/show, /api/tags, and /api/v1/models to systematically extract sensitive model information including architecture details, fine-tuning parameters, system paths, Modelfile configurations, and proprietary customizations. Multiple inspection attempts within a 15-minute window indicate automated exfiltration of valuable intellectual property such as custom model configurations, system prompts, and internal model specifications. This activity represents unauthorized data disclosure that could enable competitive intelligence gathering, model replication, or preparation for advanced attacks against the AI infrastructure.
Detects unauthorized process activity that reads, copies, archives, or transmits the NetScaler ns.conf configuration file. This file contains highly sensitive information, including AAA/LDAP bind credentials and certificates. Adversaries may stage or exfiltrate this file following the exploitation of vulnerabilities (such as CVE-2026-88771 or CVE-2026-88772) on NetScaler appliances to facilitate further network compromise.
This analytic detects the use of `curl.exe` with insecure flags such as `-k`, `--insecure`, `--proxy-insecure`, or `--doh-insecure`
which disable TLS certificate validation.
It leverages Cisco Network Visibility Module (NVM) flow data and process arguments
to identify outbound connections initiated by curl where TLS checks were explicitly disabled.
This behavior may indicate an attempt to bypass certificate validation to connect to potentially untrusted or malicious endpoints,
a common tactic in red team operations, malware staging, or data exfiltration over HTTPS.
which disable TLS certificate validation.
It leverages Cisco Network Visibility Module (NVM) flow data and process arguments
to identify outbound connections initiated by curl where TLS checks were explicitly disabled.
This behavior may indicate an attempt to bypass certificate validation to connect to potentially untrusted or malicious endpoints,
a common tactic in red team operations, malware staging, or data exfiltration over HTTPS.
Detects network connections or DNS resolutions to known anonymous file-sharing, cloud storage, and messaging-bot API endpoints (e.g., transfer.sh, Telegram Bot API, Discord CDN) commonly abused by adversaries for data staging and exfiltration. This rule specifically targets non-browser processes that attempt to communicate with these endpoints, helping identify potentially malicious exfiltration activities.
Detects network connection attempts by known AI agent or development-related runtime processes (python, node, etc.) to external endpoints that are not contained within a defined allowlist of LLM and infrastructure providers. This is intended to identify potential data exfiltration or unauthorized command and control communication originating from LLM-powered applications.
Detects the execution of known cloud synchronization utilities like rclone, megasync, or megacmd, which are frequently leveraged by ransomware operators to exfiltrate data to public cloud storage providers. The rule monitors both local process execution with typical command-line arguments and subsequent outbound network connections to common cloud storage domains.
Detects high-risk GitHub events indicating data or asset exposure, such as creating public repositories with specific naming conventions, changing private repositories to public, or creating new gists, which could indicate exfiltration of sensitive assets or information.
Detects high-risk GitHub events indicating data or asset exposure, such as creating public repositories with specific naming conventions, changing private repositories to public, or creating new gists, which could indicate exfiltration of sensitive assets or information.
Detects the creation or exposure of public repositories, releases, or gists under a personal GitHub account that utilize naming conventions associated with the 'PixelLeak' workaround. This technique allows adversaries to make previously private screenshots, recordings, or internal assets publicly accessible by hosting them in public personal repositories or releases.
Detects a suspicious sequence of events where a host performs multiple reconnaissance-style probes (health checks, documentation, or OpenAPI definitions) followed within 10 minutes by access to sensitive artifact-related URLs on the same remote host. This pattern is indicative of an attacker profiling a target server for metadata and then proceeding to exfiltrate files or sensitive artifacts.
Detects anomalous network behavior where a source host initiates a high volume of DNS TXT record queries to an external domain within a short timeframe. Such patterns are indicative of data exfiltration or C2 communication tunneling through DNS protocol.
Detects high-risk GitHub events indicating data or asset exposure, such as creating public repositories with specific naming conventions, changing private repositories to public, or creating new gists, which could indicate exfiltration of sensitive assets or information.
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