Adversaries have always relied on legitimate tools to carry out their attacks. These tools are already trusted by security solutions, which allows them to blend in with normal activity, maintain a low footprint, and make detection much harder for defenders. By using these legitimate tools, adversaries can carry out a wide range of actions, such as moving laterally across networks, establishing C2 channels, or maintaining persistence, all without triggering any alerts.
Category: Detection Engineering
The Axios npm supply chain incident: fake dependency, real backdoor
On March 31, 2026, two malicious Axios versions (1.14.1 and 0.30.4) were briefly published to npm via a compromised maintainer account. The only change performed was the addition of a trojanized dependency, whose postinstall script deployed a crossโplatform RAT (for macOS, Windows, and Linux). Although the Axios packages were removed within hours, multiple hits were … Continue reading The Axios npm supply chain incident: fake dependency, real backdoor
Capture the Kerberos Flag: Detecting Kerberos Anomalies
Kerberos is one of the most common protocols in organizations that utilize Windows Active Directory, and an essential part of Windows authentication used to verify the identity of a user or a host [1]. As such, Kerberos is often a target for adversaries trying to either steal or forge Kerberos tickets [2]. In this blog … Continue reading Capture the Kerberos Flag: Detecting Kerberos Anomalies
ConsentFix (a.k.a. AuthCodeFix): Detecting OAuth2 Authorization Code Phishing
ConsentFix (a.k.a.AuthCodeFix) is the latest variant of the fix-type phishing attacks, initially identified by Push Security. In this technique, the adversary tricks the victim into generating an OAuth authorization code that is part of a localhost URL, by signing in to the Azure CLI instance (or other vulnerable applications). Then, the victim is instructed to copy that URL and paste it into a phishing website, essentially handing over the authorization code to the adversary, who is now able to exchange it for an access token. Using the access token, the adversary gets access to the victim's Microsoft account.
Detection Engineering: Practicing Detection-as-Code โ Tuning โ Part 8
In Part 7, we showcased how we can leverage automation to continuously monitor the performance and trigger rate of our deployed detections. In this part, we are going to investigate how we can introduce automation and utilize continuous deployment pipelines to streamline the tedious task of tuning our detections.
Detection Engineering: Practicing Detection-as-Code โ Monitoring โ Part 7
In this part, we are going to introduce automation to effectively monitor our deployed detections. By setting up automations at this phase we adopt a proactive approach towards maintenance, allowing our team to take action before a blowout of alerts or an untuned detection is escalated by the SOC.






