Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
13 detections
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Detects PNG image files containing an 'iTXt' metadata chunk and a specific byte marker (FF 89 AD 4A). This signature is characteristic of LausivLoader, which hides an encrypted payload within the image using steganographic techniques, intended for subsequent extraction via XOR decryption and DEFLATE decompression.
Detects the presence of PNG image files containing a specific steganographic marker embedded within the iTXt metadata chunk, often used by the LausivLoader malware for C2 communication or payload delivery. The rule looks for the specific marker 0xFF89AD4A or known C2 indicators (yapw.life, stego_zrgaixkku8.png) within PNG files.
Detects the presence of PNG image files containing a specific steganographic marker embedded within the iTXt metadata chunk, often used by the LausivLoader malware for C2 communication or payload delivery. The rule looks for the specific marker 0xFF89AD4A or known C2 indicators (yapw.life, stego_zrgaixkku8.png) within PNG files.
Detects endpoint security scanner hits indicating the presence of msaRAT malware, specifically identifying its characteristic double-layer encryption scheme (DTLS transport paired with application-layer ChaCha-Poly1305 encryption) triggered by a 0xFE handshake frame.
Detects potential use of steganography to hide C2 commands in image files
This rule detects potential command and control (C2) communication where data is hidden within image files using steganography. It specifically looks for HTTP responses (flow:to_client) containing JPEG image headers ('FF D8 FF') within the first 3 bytes, with a file size greater than 500,000 bytes. A threshold is applied to trigger an alert if 5 such events occur from the same destination within 60 seconds, indicating a potential high volume of large steganographic image transfers.
This rule detects potential command and control (C2) activity where commands are hidden within PNG image files. It specifically looks for HTTP traffic flowing from the server to the client (to_client) that contains the PNG file signature (89 50 4E 47) within the first 4 bytes of the file data, and where the file size is greater than 100,000 bytes. A threshold is applied to trigger an alert if 10 such events occur within 60 seconds from the same destination IP address, indicating a potential high volume of C2 communication disguised as image downloads.
This rule hunts for various artifacts and behaviors associated with the APT28 campaign "Phantom Net Voxel", which leverages COM hijacking, steganography, and cloud services for C2. This version is specifically tailored for Azure Sentinel using only DeviceProcessEvents, DeviceFileEvents, and DeviceNetworkEvents. It detects known malicious file hashes, regsvr32 execution of a specific DLL, Office applications dropping malicious DLLs or steganographic PNGs, C2 communications to known cloud storage domains, creation of SlimAgent log files, and explorer.exe accessing steganographic PNG files indicating successful COM hijacking.
Detects PowerShell commands used by Katz Stealer to download an image file containing a steganographically hidden payload, which is then decoded and executed in memory.
This query checks for network connection failures to Microsoft Defender for Endpoint URLs.
The output includes any device with 1+ connectivity failures, a list of the domains they
failed to connect to (including the number of failures), as well as the overall number of
failures in the time period. Results are sorted by the total number of connection failures
by the device.
The output includes any device with 1+ connectivity failures, a list of the domains they
failed to connect to (including the number of failures), as well as the overall number of
failures in the time period. Results are sorted by the total number of connection failures
by the device.
This query can be used to detect instances of malicious users who attempt to create steganographic images and then immediately browse to a webmail URL. This query would require additional investigation to determine whether the co-occurrance of generating a steganographic image and browsing to a webmail URL is an indication of a malicious event.
'Threat actors can use JPEG files to hide malware, or other malicious code from inspection. This query looks for the downloading of abnormally large JPEG files from a source where large JPEG files have not been downloaded.
Ref: https://www.microsoft.com/security/blog/2022/07/27/untangling-knotweed-european-private-sector-offensive-actor-using-0-day-exploits/'
Ref: https://www.microsoft.com/security/blog/2022/07/27/untangling-knotweed-european-private-sector-offensive-actor-using-0-day-exploits/'
Intent:
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.
- Use MTP capability to look for insider threat potential risk indicators
- Indicators would then serve as the building block for insider threat risk modeling in subsequent tools
Definition of Insider Threat:
"The potential for an individual who has or had authorized access to an organization's assets to use their access, either maliciously or unintentionally, to act in a way that could negatively affect the organization."
This collection of queries describes the different indicators that could be used to model and look for patterns suggesting an increased risk of an individual becoming a potential insider threat.
Note: no single indicator should be used as a lone determinant of insider threat activity, but should be part of an overall program to understand the increased risk to your organization's critical assets. This in turn is used to feed an investigation by a formal insider threat program to look at the context associated with the whole person to understand the implication of a set of indicators.