Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
771 detections
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This rule detects attempts to exploit the LiteLLM proxy pass-through endpoint to interact with the cloud Instance Metadata Service (IMDS). Specifically, it identifies configuration attempts to route traffic to the IMDS IP (169.254.169.254) and subsequent requests to retrieve IAM security credentials, which is indicative of a Server-Side Request Forgery (SSRF) attack to steal cloud identity tokens.
Detects OAuth2 JWT bearer-grant token requests to Google's OAuth endpoint using the attacker-controlled service-account identity and Sheets API scope observed in the fake GlobalProtect campaign
Detects network connections to known JeetBot infrastructure domains and IP addresses. The rule specifically identifies potential exfiltration of Twitch OAuth tokens via URL parameters or interaction with known token-collection proxy endpoints, which are associated with the JeetBot/Twitch Enhanced Viewer credential harvesting campaign.
Detects network connections to command-and-control infrastructure associated with the JeetBot/Twitch Enhanced Viewer malicious browser extension. The rule triggers on connections to known malicious domains or IPs, as well as specific API endpoints on ambiguous domains that are used for exfiltrating Twitch OAuth tokens.
Detects network connections to JeetBot/Twitch Enhanced Viewer malicious browser extension infrastructure exfiltrating Twitch OAuth tokens. Apex domains (jeetbot.cc, api.jeetbot.cc) are gated on a token-forwarding indicator to avoid false positives.
Detects a GitLab personal access token used from multiple distinct source IPs or from IPs associated with the leaked gitlab-triage token, inconsistent with expected CI runner infrastructure.
This rule detects potentially unauthorized access to cloud resources or OAuth applications by identifying sign-ins or API calls originating from IP addresses or locations not previously observed for the user in the 30 days prior to a documented Coder registry compromise exposure window.
Detects anomalous sign-in behavior where a device code authentication flow is initiated from one location, but the resulting session is replayed from a different IP address in a different country within a one-hour window. This behavior is indicative of an adversary capturing an authentication token via a device code phishing or relay attack and attempting to use it from their own infrastructure to bypass conditional access policies and MFA.
This rule detects attempts to exploit the LiteLLM proxy pass-through endpoint to interact with the cloud Instance Metadata Service (IMDS). Specifically, it identifies configuration attempts to route traffic to the IMDS IP (169.254.169.254) and subsequent requests to retrieve IAM security credentials, which is indicative of a Server-Side Request Forgery (SSRF) attack to steal cloud identity tokens.
Detects non-interactive sign-ins, such as those using refresh or session tokens, originating from an IP address, ASN, device, or country that does not match the user's recent interactive sign-in history. The absence of an MFA challenge for these new contexts is characteristic of session token replay attacks, often associated with AiTM phishing campaigns.
This rule detects potentially unauthorized access to cloud resources or OAuth applications by identifying sign-ins or API calls originating from IP addresses or locations not previously observed for the user in the 30 days prior to a documented Coder registry compromise exposure window.
Detects a GitLab personal access token used from multiple distinct source IPs or from IPs associated with the leaked gitlab-triage token, inconsistent with expected CI runner infrastructure.
Detects a GitLab personal access token used from multiple distinct source IPs or from IPs associated with the leaked gitlab-triage token, inconsistent with expected CI runner infrastructure.
This rule detects potentially unauthorized access to cloud resources or OAuth applications by identifying sign-ins or API calls originating from IP addresses or locations not previously observed for the user in the 30 days prior to a documented Coder registry compromise exposure window.
This rule detects potentially unauthorized access to cloud resources or OAuth applications by identifying sign-ins or API calls originating from IP addresses or locations not previously observed for the user in the 30 days prior to a documented Coder registry compromise exposure window.
Detects high-risk account modifications, such as adding MFA methods or OAuth consent grants, occurring shortly after a user sign-in. This pattern is indicative of post-AiTM session theft (e.g., NovaCookies) where an adversary uses a stolen session token to modify account settings for persistence or MFA bypass.
Detects non-interactive sign-ins, such as those using refresh or session tokens, originating from an IP address, ASN, device, or country that does not match the user's recent interactive sign-in history. The absence of an MFA challenge for these new contexts is characteristic of session token replay attacks, often associated with AiTM phishing campaigns.
Detects a sequence of events starting with a device code OAuth sign-in, followed within two hours by the creation or modification of inbox rules and high-frequency enumeration of email items (contacts, folders, messages, threads, people) via Microsoft Graph API. This behavior is indicative of post-compromise activity where an adversary uses OAuth device code grants to maintain access and subsequently automates inbox analysis or data harvesting.
This rule detects file-based activity associated with a tool named 'gh-token-monitor', which is likely used for the monitoring or exfiltration of GitHub access tokens from a compromised host. The rule monitors for the creation or presence of specific scripts, configuration files, and directory paths associated with this activity, including files related to a 'claude' configuration.
Detects newly granted or consented Microsoft Entra ID application permissions exceeding baseline, a weakness CISA's red team exploited to escalate privileges and reach cloud resources.
Detects successful authentication to Microsoft Teams or Slack where MFA was successfully completed, but the device is reported as unmanaged or non-compliant and is accompanied by sign-in risk signals. This behavior is consistent with Adversary-in-the-Middle (AitM) proxy attacks where an attacker captures credentials and session tokens, bypassing MFA, and using the hijacked session from an unrecognized device or location.
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