Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects the creation of Scalable Vector Graphics (SVG) files on a system, particularly those initiated by common applications like Outlook, web browsers, or archive utilities. It then correlates this file creation with subsequent network activity from a browser process within a 5-minute window. The network activity is further scrutinized for suspicious URLs, specifically those using Cloudflare Workers domains with a specific pattern or URLs containing an '@' symbol, which can indicate obfuscation or malicious redirection attempts. This behavior is indicative of SVG smuggling techniques used to deliver malicious payloads or redirect users to phishing sites.
This analytic detects the creation or modification of network interfaces on Cisco devices, which could indicate an attacker establishing persistence or preparing for lateral movement. After gaining initial access to network devices, threat actors like Static Tundra often create new interfaces (particularly loopback interfaces) to establish covert communication channels or maintain persistence. This detection specifically looks for the configuration of new interfaces, interface state changes, and the assignment of IP addresses to interfaces. These activities are particularly concerning when they involve unusual interface names or descriptions containing suspicious terms.
This analytic detects the creation of privileged user accounts or the elevation of existing accounts to privilege level 15 (the highest administrative privilege level) on Cisco IOS devices. This activity is suspicious as it could indicate an attacker establishing backdoor access or persistence after gaining initial access, potentially through vulnerabilities like CVE-2018-0171. The rule specifically looks for commands related to setting user privilege to 15, modifying user passwords in conjunction with user table modifications, or explicit privilege updates to level 15.
This KQL query is designed to enrich "Malicious URL Click" alerts by correlating them with user sign-in activity. It finds the affected accounts and then checks if they had a successful login from a new IP address around the time of the alert. The final output flags high-risk events where a user's URL click activity is immediately followed or preceded by a login from an IP they've never used before. This helps prioritize investigation into potentially compromised accounts.
This analytic provides comprehensive monitoring of configuration changes on Cisco devices by analyzing archive logs. Configuration archive logging captures all changes made to a device's configuration, providing a detailed audit trail that can be used to identify suspicious or malicious activities. This detection is particularly valuable for identifying patterns of malicious configuration changes that might indicate an attacker's presence, such as the creation of backdoor accounts, SNMP community string modifications, and TFTP server configurations for data exfiltration. By analyzing these logs, security teams can gain a holistic view of configuration changes across sessions and users, helping to detect sophisticated attack campaigns like those conducted by threat actors such as Static Tundra.
This analytic detects suspicious Python package installations where the package name resembles popular Python libraries but may be typosquatted or slightly altered. Typosquatting is a common technique used by attackers to trick users into installing malicious packages that mimic legitimate ones. This detection leverages Cisco NVM flow telemetry and checks for pip or poetry package managers with the "install" or "add" flags, making outbound connections to package repository such as `pypi.org` with known or suspected typo package names.
This analytic detects oversized Cisco Smart Install (SMI) protocol messages by inspecting traffic to TCP port 4786 within the Network_Traffic data model. Abnormally large SMI payloads have been associated with exploitation and protocol abuse (e.g., CVE-2018-0171; activity reported by the "Static Tundra" threat actor). Monitoring message sizes over time can help identify possible attempts at remote code execution, denial of service, or reconnaissance against Cisco devices exposing Smart Install.
This analytic detects network traffic to TCP port 4786, which is used by the Cisco Smart Install protocol. Smart Install is a plug-and-play configuration and image-management feature that helps customers to deploy Cisco switches. This protocol has been exploited via CVE-2018-0171, a vulnerability that allows unauthenticated remote attackers to execute arbitrary code or cause denial of service conditions. Recently, Cisco Talos reported that a Russian state-sponsored threat actor called "Static Tundra" has been actively exploiting this vulnerability to compromise unpatched and end-of-life network devices. Monitoring for traffic to this port can help identify potential exploitation attempts or unauthorized Smart Install activity.
Detects an exploit attempt against Sitecore vulnerability CVE-2025-53690. This rule correlates an HTTP POST request to '/sitecore/blocked.aspx' with a subsequent 'ViewState verification failed' Windows Event Log (EID 1316) from the same source IP and target host.
Detects the reconfiguration of a virtual machine where a virtual disk (.vmdk) from a different, often critical, VM is attached. This is a key tactic used by threat actors like UNC3944 to perform offline credential theft by mounting a Domain Controller's disk to a staging VM to access the NTDS.dit file.
Detects successful non-interactive sign-ins to Microsoft Graph using the Visual Studio Code (VSCode) application identity. This behavior was observed in a phishing campaign where threat actors tricked users into an OAuth flow to harvest tokens. These tokens were then used to access user data, such as emails, via the Graph API.
Detects incoming emails that contain suspicious attachment types (e.g., RAR, ZIP) or links to file-sharing services, combined with subject lines commonly used in phishing campaigns. This pattern is indicative of initial access attempts via spear-phishing.
This detection looks for emails which include URLs with ‘amp/s’. This is an indicator of Google AMP Phishing which uses legitimate Google domains to redirect to the malicious URLs. When detected this is a high confident sign of phishing.
An attacker knows a users login credentials for an account with MFA enabled. The attacker overloads the user with MFA requests hoping the user will accept one of them. This detection looks for a successful MFA completion that follows a stream of failed MFA requests within the past hour.
This alert indicates that a user has successfully passed MFA after a stream of login failures. This activity may indicate that an attacker has successfully brute forced an accounts credentials and has passed MFA.
Detects scenarios where an attacker would attempt to enumerate hosts resources and execute a payload with a compromised account. Vulnerability scanners, enumeration software or tool like SharepHound/CrackMapexec may generate such behavior.
The analytic detects the creation of a new Automation Runbook Webhook within an Azure tenant. It leverages Azure Audit events, specifically the "Create or Update an Azure Automation webhook" operation, to identify this activity. This behavior is significant because Webhooks can trigger Automation Runbooks via unauthenticated URLs exposed to the Internet, posing a security risk. If confirmed malicious, an attacker could use this to execute code, create users, or maintain persistence within the environment, potentially leading to unauthorized access and control over Azure resources.
Detects scenarios where an attacker attempts authenticate to the database using a disabled user accont
Detects scenarios where an attacker attempts to connect to a Windows host using the SSH protocol.
Detects scenarios where an attacker attempt to hide emails in order to perform phishing attacks by replacing, for example, financial information from the original email with another email containing attacker's financial information. This technique may also be used to avoid specific email notification to be received by end users in case, for example, of an ongoing breach.
Detects scenarios where a user of a predefined set of group(s) logs on a target machine.
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