Sergio Albea
@Sergio_AlbeaTrusted contributorCompletionist
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TIFCE (Threat Intelligence Feed Content Evaluation) is a simple way to measure if a TI feed is actually useful based on four things — uniqueness, real matches, confirmed maliciousness, and activity.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
TIFCE (Threat Intelligence Feed Content Evaluation) is a simple way to measure if a TI feed is actually useful based on four things — uniqueness, real matches, confirmed maliciousness, and activity.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
🚨 TIFCE allows using one detection per IOC type (URLs, domains, file hashes) instead of dozens of rules per feed, keeping detections clean, centralized, and easy to maintain.
If you rely on threat intelligence for detection, it can be a good solution to how to evaluate current or new TI feeds.
This Query is oriented to identify Malicious URL sent via Microsoft Teams and detect possible hits based on online Malware sites reported by the TI Feed URL Haus.
This KQL Query helps to understand all the URL Redirections from URLs received by Email using the UrlChainId identifier on KQL that groups together all URLs that belong to the same “click/redirect chain”. When an message contains a URL, that URL may redirect through several intermediate URLs (trackers, shorteners, phishing, etc.) before land on the final site. KQL builds a URL chain from the original URL in the email through each redirect hop. All URLs that are part of a single chain share the same UrlChainId and for each hop. On the other hand, UrlChainPosition register the position of every URL, the original one = value 0 and the other redirections tagged with next numbers(1, 2, etc. ) The following query includes different options to classify the insights into four categories:
Tracking Domains
Redirecting to Different Countries
Redirecting to Different Domains
Number of Redirections
Tracking Domains
Redirecting to Different Countries
Redirecting to Different Domains
Number of Redirections
A Tor exit node is the last server in the Tor network that your traffic passes through before it reaches the public internet so it is the one that actually makes the connection to website.
In this particular query, I am getting the devices with connections to Tor Exit Nodes, to list to which node are connecting and possible suspicious URLs with connections to the mentioned servers.
In this particular query, I am getting the devices with connections to Tor Exit Nodes, to list to which node are connecting and possible suspicious URLs with connections to the mentioned servers.
When, for example, a printer, camera, IoT appliance, or other device suddenly makes outbound connections to countries such as China, Russia, or Iran, this may not be noise. The following detection helps identify connections from these specific device groups that we were not previously aware of and that could be exfiltrating information.
The query below correlates device inventory, IP assignment and network events to identify internal endpoints attempting to connect to routers — including whether they succeeded and via Web or Application access. Attack traffic often aligns with failed HTTP/HTTPS attempts or unknown device names.
Syncthing is a peer-to-peer file synchronization utility, designed to sync files between devices on a local network or between remote devices over the Internet.
This utility to exfiltrate data, has been already abused to exfiltrate data by Malicious actor.
The following KQL Query detect connections to external IPs via the mentioned software and the corresponding country.
This utility to exfiltrate data, has been already abused to exfiltrate data by Malicious actor.
The following KQL Query detect connections to external IPs via the mentioned software and the corresponding country.
This KQL Query helps to keep an eye on accounts that are being excluded from Conditional Access (CA) policies which they should be blocked by it and which specific field triggered the CA detection and got them excluded.
The aim of this case is to identify:
Spot CA policies with a high number of exclusions.
Find exclusions that don’t make sense, like skipping MFA when it’s mandatory for privileged accounts.
Catch new exclusions that might not have been approved.
Check how exclusions are actually working (e.g., excluding a device is fine, but if it’s connecting from risky countries or open networks, that’s a problem—hopefully, other CA policies cover this).
Identify unexpected exclusions, which could mean an attacker got in and excluded themselves to bypass CA controls
The aim of this case is to identify:
Spot CA policies with a high number of exclusions.
Find exclusions that don’t make sense, like skipping MFA when it’s mandatory for privileged accounts.
Catch new exclusions that might not have been approved.
Check how exclusions are actually working (e.g., excluding a device is fine, but if it’s connecting from risky countries or open networks, that’s a problem—hopefully, other CA policies cover this).
Identify unexpected exclusions, which could mean an attacker got in and excluded themselves to bypass CA controls
To detect sensitive or confidential information sent by email from our users, I discovered that DefenderXDR is registering events when some user or services is reading files tagged or marked as sensitive. Basically, it has a "SensitiveFileRead" ActionType in the DeviceFileEvents table which indicates that a process on the monitored device has accessed a file classified as sensitive. This could include files with personally identifiable information (PII), intellectual property, or other data deemed sensitive based on the organization’s data protection policies or Microsoft’s predefined rules. This event type is essential for tracking access to sensitive data, helping to identify potential data leakage or unauthorized access attempts.
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