Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
3,865 detections
Filters
Last updated
All Time
Detection languages
2,524
525
299
218
131
Contributors
999
706
554
263
188
Categories
1,449
1,199
1,091
792
575
Platforms
39,932
7,263
6,535
3,865
3,643
Products / Services
1,755
1,449
1,121
438
406
MITRE Techniques
1,889
1,392
913
814
727
CVEs
12
5
4
3
2
IDS Classtypes
10
7
6
6
5
IDS Protocols
37
2
1
Detects an anomalous volume of artificial intelligence model inference API calls (e.g., AWS Bedrock, Azure OpenAI, Google Vertex AI) initiated by a single IAM principal or API key within a short time window. This activity is indicative of 'LLMjacking', where compromised cloud credentials are leveraged by threat actors to perform unauthorized, high-cost AI model inference tasks.
Detects a two-stage activity: first, the potential unauthorized reading or access of LLM provider API keys from files, environment variables, or command-line arguments; and second, the subsequent use of those same credentials to authenticate to LLM provider APIs (OpenAI, Anthropic, Azure, Bedrock) from a different, unrecognized source IP address, indicating potential credential theft and session hijacking.
Detects a two-stage activity: first, the potential unauthorized reading or access of LLM provider API keys from files, environment variables, or command-line arguments; and second, the subsequent use of those same credentials to authenticate to LLM provider APIs (OpenAI, Anthropic, Azure, Bedrock) from a different, unrecognized source IP address, indicating potential credential theft and session hijacking.
Single-source Sigma proxy for the authentication-persistence stage of the multi-stage device-code-phishing-to-Graph-collection chain (see the companion KQL correlation rule "Passkey Persistence: Device-Code Phishing to MFA Takeover and Graph Collection" for the full, threshold-gated, cross-table detection). Sigma has no join, temporal-windowing, or aggregation support, so this rule fires on the authentication-persistence event alone and does NOT enforce the device-code sign-in precursor or the subsequent Graph-activity burst - both required by the full correlation. Scoped to the two highest-signal operations only (new security-info registration, and any admin-initiated registration on another user's account) to cut noise from routine self-service profile edits.
Detects anomalous sign-in patterns indicative of real-time MFA relay attacks, where a user principal authenticates successfully from multiple distinct IP addresses and geographical locations within a short time window (15 minutes), suggesting the active interception of credentials and MFA challenges by a Phishing-as-a-Service platform.
Detects anomalous sign-in patterns indicative of real-time MFA relay attacks, where a user principal authenticates successfully from multiple distinct IP addresses and geographical locations within a short time window (15 minutes), suggesting the active interception of credentials and MFA challenges by a Phishing-as-a-Service platform.
Detects anomalous sign-in patterns indicative of real-time MFA relay attacks, where a user principal authenticates successfully from multiple distinct IP addresses and geographical locations within a short time window (15 minutes), suggesting the active interception of credentials and MFA challenges by a Phishing-as-a-Service platform.
This rule monitors for successful sign-in events that follow a threshold of failed authentication attempts within a one-hour window, specifically flagging cases where the successful login originated from a new location or a previously unseen device, which is often indicative of successful brute force or password spraying attacks.
Detects when a namespace-scoped identity creates, updates, or patches AWS or Azure IAM-related custom resources in Kubernetes. This pattern monitors for a 'confused deputy' scenario where a user might attempt to leverage high-privilege cloud operators (like ACK or ASO v2) that operate with a shared high-privilege identity to modify cloud IAM configurations.
Detects when a namespace-scoped identity creates, updates, or patches AWS or Azure IAM-related custom resources in Kubernetes. This pattern monitors for a 'confused deputy' scenario where a user might attempt to leverage high-privilege cloud operators (like ACK or ASO v2) that operate with a shared high-privilege identity to modify cloud IAM configurations.
Detects high-privileged Entra ID accounts successfully reaching the verification stage of the Self-Service Password Reset (SSPR) process. While SSPR is automatically enabled for administrative accounts, this activity is anomalous and potentially indicates an attacker focusing on discovered privileged accounts after performing broader enumeration.
Detects high-privileged Entra ID accounts successfully reaching the verification stage of the Self-Service Password Reset (SSPR) process. While SSPR is automatically enabled for administrative accounts, this activity is anomalous and potentially indicates an attacker focusing on discovered privileged accounts after performing broader enumeration.
Detects high-privileged Entra ID accounts successfully reaching the verification stage of the Self-Service Password Reset (SSPR) process. While SSPR is automatically enabled for administrative accounts, this activity is anomalous and potentially indicates an attacker focusing on discovered privileged accounts after performing broader enumeration.
Detects anomalous, high-volume account enumeration against the Microsoft Self-Service Password Reset (SSPR) endpoint from a single source IP. The rule identifies a pattern of mixed response codes, specifically interleaving '50034' (Account does not exist) with successful or other outcomes, which indicates the use of automated tools to validate the existence of corporate accounts via response differentiation.
Detects anomalous, high-volume account enumeration against the Microsoft Self-Service Password Reset (SSPR) endpoint from a single source IP. The rule identifies a pattern of mixed response codes, specifically interleaving '50034' (Account does not exist) with successful or other outcomes, which indicates the use of automated tools to validate the existence of corporate accounts via response differentiation.
Detects anomalous, high-frequency interaction with AI model endpoints characterized by a high volume of requests with a near 1:1 ratio of distinct inputs. This pattern is indicative of automated knowledge-distillation or model extraction attacks against AI services.
Detects the use of common command-line tools (curl, wget, python, etc.) to interact with known cloud provider metadata service IP addresses or URL paths, often performed by shell processes. This behavior is frequently associated with initial reconnaissance or attempts to steal identity tokens from cloud-based virtual machines.
Detects modifications or creations of Azure DevOps pipelines and service connections, as well as pipeline executions performed outside of standard business hours (6 AM to 8 PM on weekdays). This activity is intended to identify potential unauthorized infrastructure or pipeline configuration changes that could indicate persistence or lateral movement via CI/CD pipelines.
This rule detects a correlation between a successful user login from an IP address not previously seen for that specific user in the last 14 days, followed immediately (within 1 hour) by sensitive administrative operations performed by the same user, such as adding members to roles or modifying application permissions.
Detects modifications or creations of Azure DevOps pipelines and service connections, as well as pipeline executions performed outside of standard business hours (6 AM to 8 PM on weekdays). This activity is intended to identify potential unauthorized infrastructure or pipeline configuration changes that could indicate persistence or lateral movement via CI/CD pipelines.
Detects successful authentication attempts in Azure AD or Microsoft 365 logs originating from known proxy/VPN service providers or identified by suspicious Python-requests user agent strings. The rule specifically filters for events where MFA was not satisfied, indicating potentially bypassed or failed security controls from potentially malicious infrastructure.
Page 42 of 185