Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
733 detections
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Detects anomalous actions within the Coder registry, such as template creation, version updates, or dry-run/workspace builds with module caching disabled, that occurred during a known registry compromise window on August 31, 2026.
This rule detects the presence of specific file hashes known to be associated with backdoored software builds, specifically related to recent supply chain compromises affecting South Korean software vendors (e.g., HAProxy builds). It monitors device file events, process initiation, and identity logon events to identify systems that have deployed, executed, or been accessed by these malicious binaries.
Detects anomalous actions within the Coder registry, such as template creation, version updates, or dry-run/workspace builds with module caching disabled, that occurred during a known registry compromise window on August 31, 2026.
Detects high-velocity publication of Ruby packages by an account that uses naming conventions related to 'OAI' or a known-malicious contact email. This behavior is indicative of a supply chain attack involving the automated deployment of numerous malicious packages to the RubyGems ecosystem.
Detects high-velocity publication of Ruby packages by an account that uses naming conventions related to 'OAI' or a known-malicious contact email. This behavior is indicative of a supply chain attack involving the automated deployment of numerous malicious packages to the RubyGems ecosystem.
Matches known malicious dlp.sh/dlp-docker.sh Terraform module scripts used in Coder registry supply chain attack (common, aider, rstudio-server, windows-rdp, zed variants)
Detects cached malicious dlp.sh/dlp-docker.sh Terraform module artifacts served from the compromised registry.coder.com infrastructure
Detects network activity (TCP, DNS, and HTTP) directed towards a known rogue infrastructure IP identified in a supply chain compromise affecting the Coder registry. The rule alerts on attempts to resolve or communicate with this infrastructure to download backdoored Terraform modules or interact with malicious resources.
Detects network activity (TCP, DNS, and HTTP) directed towards a known rogue infrastructure IP identified in a supply chain compromise affecting the Coder registry. The rule alerts on attempts to resolve or communicate with this infrastructure to download backdoored Terraform modules or interact with malicious resources.
Detects anomalous actions within the Coder registry, such as template creation, version updates, or dry-run/workspace builds with module caching disabled, that occurred during a known registry compromise window on August 31, 2026.
Detects anomalous actions within the Coder registry, such as template creation, version updates, or dry-run/workspace builds with module caching disabled, that occurred during a known registry compromise window on August 31, 2026.
Matches known malicious dlp.sh/dlp-docker.sh Terraform module scripts used in Coder registry supply chain attack (common, aider, rstudio-server, windows-rdp, zed variants)
This rule detects the presence of specific file hashes known to be associated with backdoored software builds, specifically related to recent supply chain compromises affecting South Korean software vendors (e.g., HAProxy builds). It monitors device file events, process initiation, and identity logon events to identify systems that have deployed, executed, or been accessed by these malicious binaries.
Detects the installation of software packages in build or CI pipelines where the package was published to its registry between 30 and 90 days prior to being first used in the environment. This pattern is indicative of potential dependency confusion or typosquatting attacks, where adversaries use newly created packages to deliver malicious code.
Detects the installation of software packages in build or CI pipelines where the package was published to its registry between 30 and 90 days prior to being first used in the environment. This pattern is indicative of potential dependency confusion or typosquatting attacks, where adversaries use newly created packages to deliver malicious code.
Detects suspicious PowerShell execution spawned by common development tools or shell environments like node, npm, or WSL. The rule evaluates the process lineage and scores the command line arguments for characteristics commonly used by malicious payloads, such as hidden execution, bypass flags, network download activity, or temporary file access, which are indicative of software supply chain attacks or automated malicious script execution.
This rule detects the presence of specific file artifacts and directory paths associated with the 'Mini Shai-Hulud' malicious campaign, which involves the compromise of the 'openapi-react-query-codegen' npm package. It monitors for indicators of compromise (IOCs) such as specific malicious JavaScript and shell script filenames, as well as persistence artifacts like plist and service files.
Detects evidence of malicious file tampering on public CDNs (bootcdn.net, bootcss.com, staticfile.org) associated with the Funnull campaign. The rules identify specific malicious file hashes and anomalous oversized file sizes that indicate the presence of injected malicious loaders within common JavaScript libraries.
Detects evidence of malicious file tampering on public CDNs (bootcdn.net, bootcss.com, staticfile.org) associated with the Funnull campaign. The rules identify specific malicious file hashes and anomalous oversized file sizes that indicate the presence of injected malicious loaders within common JavaScript libraries.
The following analytic detects a Python process making an outbound network connection during package installation.
Adversaries can abuse `setup.py` build scripts by leveraging `distutils`/`setuptools` command classes to execute arbitrary code, including network beacons to third-party domains, the moment a malicious Python package is installed.
This activity is significant because it allows adversaries to establish a foothold or exfiltrate data without any direct interaction from the victim beyond running `pip install`.
If confirmed malicious, this could indicate a successful software supply chain compromise.
Adversaries can abuse `setup.py` build scripts by leveraging `distutils`/`setuptools` command classes to execute arbitrary code, including network beacons to third-party domains, the moment a malicious Python package is installed.
This activity is significant because it allows adversaries to establish a foothold or exfiltrate data without any direct interaction from the victim beyond running `pip install`.
If confirmed malicious, this could indicate a successful software supply chain compromise.
Detects package installation activities involving potentially compromised TanStack packages during the defined malicious publish window (2026-05-11 to 2026-05-12). The rule monitors common Node.js package managers (npm, pnpm, yarn, bun) and CLI tools for commands attempting to fetch identified affected versions of @tanstack/* libraries.
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