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Identifies a burst of successful NFS write activity combined with destructive REMOVE or RENAME operations from a single client to one export server within a one-minute window. Ransomware and destructive actors often encrypt, delete, or rename large numbers of files on mounted NFS shares; this aggregation surfaces that behavior using NFS opcode telemetry when file paths are not available on the wire.
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Identifies the first source and destination IP pair observed in a five-day history window where an NFS client asserts AUTH_SYS (RPC UNIX) credentials with UID 0 (root). NFSv3 and NFSv4 clients can claim arbitrary UIDs through AUTH_SYS, and weak export controls may honor root-equivalent access from unexpected hosts. This is a common precursor to unauthorized mounts, sensitive file reads, and remote encryption of exported shares.
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Identifies the first successful or no-reply Memcached store command from a client to a server. Memcached commonly has no authentication, so an unauthorized writer can overwrite session tokens, poison cached application content, or alter security-sensitive state. This behavior can enable session hijacking such as the exposure described by CVE-2026-29093.
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Identifies the first client IP observed issuing MongoDB commands that can drop databases, collections, indexes, users, or roles within a five-day history window. Adversaries with access to an exposed or compromised MongoDB service may use these commands to destroy data, disrupt applications, or prepare a wipe-and-extort attack.
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Identifies MySQL statements that create a user-defined function backed by a shared library. Adversaries with sufficient database privileges can place a malicious library in the MySQL plugin directory and register it with "CREATE FUNCTION ... SONAME", establishing a database-resident primitive for operating-system command execution.
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Identifies PostgreSQL "COPY" statements that invoke an operating-system command through the "PROGRAM" option. A superuser or role with "pg_execute_server_program" can use this feature to execute arbitrary commands as the PostgreSQL service account, a technique used after credential compromise and by cryptomining campaigns.
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Identifies Cassandra Query Language statements that create a JavaScript user-defined function. On vulnerable and dangerously configured Cassandra servers, adversaries can abuse scripted UDF creation to escape the JavaScript sandbox and execute operating-system commands, including through CVE-2021-44521.
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Identifies the first decoded Apache Thrift RPC relationship from a public client address to a server. Thrift commonly connects trusted internal microservices and data platforms, and an externally originated method invocation can indicate an exposed service, unauthorized access, or exploitation of a public-facing Thrift endpoint.
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Identifies repeated SIP REGISTER authentication rejection responses for one or more extensions from a client to a VoIP server within five minutes. The rule distinguishes repeated failures from the single 401 or 407 challenge expected in a normal digest-authentication flow. Attackers brute-force extension credentials to register rogue endpoints for toll fraud, call interception, or registration hijacking.
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Identifies SIP OPTIONS requests targeting many distinct extension values from a single client within two minutes. Attackers and VoIP scanners use OPTIONS sweeps to discover valid users before REGISTER brute force, toll fraud, or registration hijacking attempts.
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Identifies multiple successful AMQP queue purge operations issued by the same client to the same broker within a short period. The AMQP queue.purge method removes all messages from a queue that are not awaiting acknowledgment. Purging several distinct queues can indicate deliberate message destruction or disruption after broker credentials are compromised.
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Looks for compiler activity by a user context which does not normally run compilers. This can be the result of ad-hoc software changes or unauthorized software deployment. This can also be due to local privilege elevation via locally run exploits or malware activity.
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Searches for rare processes running on multiple Linux hosts in an entire fleet or network. This reduces the detection of false positives since automated maintenance processes usually only run occasionally on a single machine but are common to all or many hosts in a fleet.
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A machine learning job detected unusually large numbers of DNS queries for a single top-level DNS domain, which is often used for DNS tunneling. DNS tunneling can be used for command-and-control, persistence, or data exfiltration activity. For example, dnscat tends to generate many DNS questions for a top-level domain as it uses the DNS protocol to tunnel data.
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A machine learning job detected a rare destination country name in the network logs. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from a server in a country which does not normally appear in network traffic or business work-flows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network.
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A machine learning job has detected data exfiltration to a particular destination port. Data transfer patterns that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.
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A machine learning job has detected data exfiltration to a particular geo-location (by IP address). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.
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A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.
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A machine learning job has detected data exfiltration to a particular geo-location (by region name). Data transfers to geo-locations that are outside the normal traffic patterns of an organization could indicate exfiltration over command and control channels.
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A population analysis machine learning job detected potential DGA (domain generation algorithm) activity. Such activity is often used by malware command and control (C2) channels. This machine learning job looks for a source IP address making DNS requests that have an aggregate high probability of being DGA activity.
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A machine learning job detected an unusually large spike in network traffic that was denied by network access control lists (ACLs) or firewall rules. Such a burst of denied traffic is usually caused by either 1) a mis-configured application or firewall or 2) suspicious or malicious activity. Unsuccessful attempts at network transit, in order to connect to command-and-control (C2), or engage in data exfiltration, may produce a burst of failed connections. This could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic.
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A machine learning job detected an unusually large spike in network traffic. Such a burst of traffic, if not caused by a surge in business activity, can be due to suspicious or malicious activity. Large-scale data exfiltration may produce a burst of network traffic; this could also be due to unusually large amounts of reconnaissance or enumeration traffic. Denial-of-service attacks or traffic floods may also produce such a surge in traffic.
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A machine learning job detected an unusually large spike in network activity to one destination country in the network logs. This could be due to unusually large amounts of reconnaissance or enumeration traffic. Data exfiltration activity may also produce such a surge in traffic to a destination country that does not normally appear in network traffic or business workflows. Malware instances and persistence mechanisms may communicate with command-and-control (C2) infrastructure in their country of origin, which may be an unusual destination country for the source network.
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A machine learning job detected a rare and unusual DNS query that indicate network activity with unusual DNS domains. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, when a user clicks on a link in a phishing email or opens a malicious document, a request may be sent to download and run a payload from an uncommon domain. When malware is already running, it may send requests to an uncommon DNS domain the malware uses for command-and-control communication.
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Identifies Linux processes that do not usually use the network but have unexpected network activity, which can indicate command-and-control, lateral movement, persistence, or data exfiltration activity. A process with unusual network activity can denote process exploitation or injection, where the process is used to run persistence mechanisms that allow a malicious actor remote access or control of the host, data exfiltration, and execution of unauthorized network applications.
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Identifies unusual destination port activity that can indicate command-and-control, persistence mechanism, or data exfiltration activity. Rarely used destination port activity is generally unusual in Linux fleets, and can indicate unauthorized access or threat actor activity.
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A machine learning job detected a rare and unusual URL that indicates unusual web browsing activity. This can be due to initial access, persistence, command-and-control, or exfiltration activity. For example, in a strategic web compromise or watering hole attack, when a trusted website is compromised to target a particular sector or organization, targeted users may receive emails with uncommon URLs for trusted websites. These URLs can be used to download and run a payload. When malware is already running, it may send requests to uncommon URLs on trusted websites the malware uses for command-and-control communication. When rare URLs are observed being requested for a local web server by a remote source, these can be due to web scanning, enumeration or attack traffic, or they can be due to bots and web scrapers which are part of common Internet background traffic.
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A machine learning job detected a rare and unusual user agent indicating web browsing activity by an unusual process other than a web browser. This can be due to persistence, command-and-control, or exfiltration activity. Uncommon user agents coming from remote sources to local destinations are often the result of scanners, bots, and web scrapers, which are part of common Internet background traffic. Much of this is noise, but more targeted attacks on websites using tools like Burp or SQLmap can sometimes be discovered by spotting uncommon user agents. Uncommon user agents in traffic from local sources to remote destinations can be any number of things, including harmless programs like weather monitoring or stock-trading programs. However, uncommon user agents from local sources can also be due to malware or scanning activity.
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Identifies the network signature of CVE-2026-41940, a pre-auth root-level authentication bypass in cPanel and WebHost Manager (WHM) caused by a CRLF injection in the session writer. The exploit-inherent shape on the wire is a "GET /" request to a cPanel/WHM admin port (typically TCP/2087, 2086, 2083, 2082, 2095, 2096) carrying an "Authorization: Basic" header whose base64-decoded value contains CRLF-injected session fields, which causes cpsrvd to respond with a 3xx redirect whose "Location" header leaks a "/cpsessNNNNNNNNNN" token granting the attacker a privileged session. This is the network-layer equivalent of the cPanel "access_log" artifact identified by Unfold and watchTowr as the first bulletproof detection for this CVE: a "GET /" recorded with "auth_method=b" (HTTP Basic). Legitimate access to "GET /" on a WHM admin port returns 200 with the login screen and never includes HTTP Basic credentials, so this combination is not produced by normal use.
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Detects a POST to the Splunk Enterprise PostgreSQL backup endpoint followed by a POST to the restore endpoint from the same client to the same host within a 15-minute window. This sequence is unusual and can align with the public CVE-2026-20253 pre-authentication RCE chain, where an attacker stages a database dump via the backup path and executes attacker-controlled SQL via the restore path.
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Splunk Enterprise PostgreSQL Recovery Endpoint Injection Artifacts
Jul 2, 2026 · Domain: Network Use Case: Threat Detection Use Case: Vulnerability Use Case: Network Security Monitoring Tactic: Initial Access Data Source: Azure Data Source: Elastic Defend Data Source: GCP Data Source: Google Cloud Platform Data Source: Network Packet Capture Data Source: Network Traffic Data Source: Zeek Data Source: Suricata Resources: Investigation Guide ·Detects CVE-2026-20253 exploit artifacts against the Splunk Enterprise PostgreSQL sidecar recovery endpoints via complementary signals. Where endpoint or Network Packet Capture request-body logging is available, the rule matches PostgreSQL connection-string injection keywords, suspicious
backupFiledestinations, and known filesystem artifacts used to pivot from backup/restore primitives to file write or RCE. It also detects vulnerable recovery endpoint probing and empty-password Basic auth credentials observed in public exploit tooling.
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This rule detects attempts to abuse Redis CONFIG SET commands to inject SSH authorized keys on Linux hosts. Attackers targeting unauthenticated Redis instances issue CONFIG SET dir to an SSH directory such as /root/.ssh, set the filename to authorized_keys via CONFIG SET dbfilename, write an attacker-controlled public key via SET, and call BGSAVE to flush it to disk, establishing persistent SSH access as root.
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This rule detects exploitation attempts targeting CVE-2025-49844 (RediShell), a CVSS 10.0 use-after-free vulnerability in the Redis Lua interpreter. An authenticated attacker sends an EVAL command containing a Lua script that calls string.rep() to create memory pressure and collectgarbage('collect') to force garbage collection, exploiting a use-after-free in the Lua parser to achieve remote code execution.
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This rule detects attempts to abuse Redis CONFIG SET commands to redirect the database save directory to a cron directory on Linux hosts. Attackers issue CONFIG SET dir to a cron path such as /etc/cron.d or /var/spool/cron, set a filename via CONFIG SET dbfilename, write a cron payload via SET, and then call BGSAVE to flush it to disk, establishing persistence for execution of an XMRig cryptominer.
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Detects HTTP GET requests to the link-local instance metadata service (169.254.169.254) for cloud credential or token paths on AWS, GCP, or Azure. Adversaries and vulnerable workloads use scripts, shells, or application runtimes to read IAM role credentials or OAuth tokens from the metadata API. Requires the Network Packet Capture integration with HTTP decoding on ports 80 and 443 and process enrichment enabled so "process.*" fields are present.
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This rule detects exploitation attempts targeting CVE-2025-55182, a critical remote code execution vulnerability in React Server Components (RSC) Flight protocol. The vulnerability allows attackers to execute arbitrary code on the server by sending specially crafted deserialization payloads that exploit prototype chain traversal to access the Function constructor. This rule focuses on high-fidelity indicators of active exploitation including successful command execution responses and prototype pollution attack patterns.
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