Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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Detects inbound network connections from known IP addresses associated with PHP2Shell exploitation attempts and malicious tooling infrastructure.
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
The following analytic detects outbound connections to commonly abused file sharing and pastebin-style hosting domains.
It leverages Cisco Secure Firewall Threat Defense logs and focuses on allowed connections (action=Allow) where the url field matches a list of known data hosting or temporary storage services.
While many of these platforms serve legitimate purposes, they are frequently leveraged by adversaries for malware delivery, data exfiltration, command and control (C2) beacons, or staging of encoded payloads.
This analytic is valuable for identifying potential abuse of legitimate infrastructure as part of an attacker's kill chain.
It leverages Cisco Secure Firewall Threat Defense logs and focuses on allowed connections (action=Allow) where the url field matches a list of known data hosting or temporary storage services.
While many of these platforms serve legitimate purposes, they are frequently leveraged by adversaries for malware delivery, data exfiltration, command and control (C2) beacons, or staging of encoded payloads.
This analytic is valuable for identifying potential abuse of legitimate infrastructure as part of an attacker's kill chain.
Detects devices reaching P7 DarkSword exploit-delivery hosts (cdn/js.gotoiphone.com, mzpo30.cam) and the agdx53.cc C2, with delivery-then-C2 chaining surfaced as the highest-confidence match. Matching is limited to the exact listed hosts and successful/attempted connection events.
Detects devices reaching P7 DarkSword exploit-delivery hosts (cdn/js.gotoiphone.com, mzpo30.cam) and the agdx53.cc C2, with delivery-then-C2 chaining surfaced as the highest-confidence match. Matching is limited to the exact listed hosts and successful/attempted connection events.
Detects devices reaching P7 DarkSword exploit-delivery hosts (cdn/js.gotoiphone.com, mzpo30.cam) and the agdx53.cc C2, with delivery-then-C2 chaining surfaced as the highest-confidence match. Matching is limited to the exact listed hosts and successful/attempted connection events.
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 devices reaching P7 DarkSword exploit-delivery hosts (cdn/js.gotoiphone.com, mzpo30.cam) and the agdx53.cc C2, with delivery-then-C2 chaining surfaced as the highest-confidence match. Matching is limited to the exact listed hosts and successful/attempted connection events.
Detects devices reaching P7 DarkSword exploit-delivery hosts (cdn/js.gotoiphone.com, mzpo30.cam) and the agdx53.cc C2, with delivery-then-C2 chaining surfaced as the highest-confidence match. Matching is limited to the exact listed hosts and successful/attempted connection events.
Detects a sequence of events where a user clicks a shared link to an AI chatbot conversation followed closely (within 15 minutes) by the execution of potentially malicious processes (mshta, powershell, cmd) that include suspicious command-line patterns indicative of ClickFix-style social engineering.
Detects a sequence of events where a user clicks a shared link to an AI chatbot conversation followed closely (within 15 minutes) by the execution of potentially malicious processes (mshta, powershell, cmd) that include suspicious command-line patterns indicative of ClickFix-style social engineering.
Detects a sequence of events where a user clicks a shared link to an AI chatbot conversation followed closely (within 15 minutes) by the execution of potentially malicious processes (mshta, powershell, cmd) that include suspicious command-line patterns indicative of ClickFix-style social engineering.
Detects a sequence of events where a user clicks a shared link to an AI chatbot conversation followed closely (within 15 minutes) by the execution of potentially malicious processes (mshta, powershell, cmd) that include suspicious command-line patterns indicative of ClickFix-style social engineering.
Detects a sequence of events where a user clicks a shared link to an AI chatbot conversation followed closely (within 15 minutes) by the execution of potentially malicious processes (mshta, powershell, cmd) that include suspicious command-line patterns indicative of ClickFix-style social engineering.
Detects network connections from common web browsers to domains associated with the BragJack threat actor infrastructure. This activity potentially indicates an end-user accessing malicious sites used for credential harvesting, malware delivery, or C2 communication.
Detects credential-phishing attempts originating from Proton Mail addresses that result in a user clicking on a link. The rule correlates email delivery from known Proton Mail domains with subsequent URL click events to identify potential Adversary-in-the-Middle (AiTM) activity, often associated with the Star Blizzard (COLDRIVER) threat group.
Detects potential lateral movement by identifying users who have recently had a confirmed infostealer malware infection on a source host and subsequently initiate RDP or WinRM connections from a different host to internal network resources.
Detects a multi-stage attack chain originating with a healthcare-themed phishing email (e.g., billing or patient coordination lures) that leads to a link click, followed by a subsequent suspicious user sign-in from a non-managed/non-compliant device for the same recipient. This correlates email threat data, URL click telemetry, and sign-in logs to identify potential credential harvesting.
Detects a multi-stage attack chain originating with a healthcare-themed phishing email (e.g., billing or patient coordination lures) that leads to a link click, followed by a subsequent suspicious user sign-in from a non-managed/non-compliant device for the same recipient. This correlates email threat data, URL click telemetry, and sign-in logs to identify potential credential harvesting.
Detects a multi-stage attack chain originating with a healthcare-themed phishing email (e.g., billing or patient coordination lures) that leads to a link click, followed by a subsequent suspicious user sign-in from a non-managed/non-compliant device for the same recipient. This correlates email threat data, URL click telemetry, and sign-in logs to identify potential credential harvesting.
Detects network traffic permitted from zones typically associated with NetScaler appliances (DMZ, perimeter, VPN, gateway) to sensitive internal zones (internal, trust, LAN, corp) using common administrative or lateral movement protocols (SMB, RDP, WinRM, RPC, LDAP). This behavior is indicative of potential lateral movement or exploitation originating from a compromised edge appliance.
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