Malik Haidar is a veteran cybersecurity expert who has spent years at the front lines of defense for multinational corporations, specializing in the intersection of threat intelligence and business-centric security strategy. His deep understanding of how state-sponsored actors manipulate everyday administrative tools makes him a leading voice in the fight against advanced persistent threats. Recently, he has been closely monitoring “Operation MacroMaze,” a sophisticated campaign by APT28 that utilizes deceptive simplicity and legitimate cloud services to breach entities across Western and Central Europe. In this discussion, we explore the technical nuances of beaconing via XML fields, the evolution of browser-based evasion, and the challenges of securing environments where legitimate tools are turned into weapons.
Many recent spear-phishing campaigns utilize the “INCLUDEPICTURE” field in XML documents to trigger outbound requests to webhook services upon opening. How does this beaconing mechanism complicate the initial incident response process, and what specific metadata should security teams prioritize when analyzing these remote connections?
The use of the “INCLUDEPICTURE” field is particularly devious because it transforms a standard document preview into a silent intelligence-gathering tool. From an incident response perspective, this complicates things because the connection occurs at the very moment the file is accessed, often before any “traditional” malicious code like a macro has even been allowed to run. It effectively functions as a tracking pixel, giving the attacker immediate confirmation that they have reached a live target and that the user is active. When we analyze these connections, we must prioritize the source IP, the specific User-Agent string, and the timestamp of the request to correlate it with email delivery logs. By capturing this metadata from the webhook service, we can determine the exact geographic location and internal workstation that first “blinked,” allowing us to isolate the threat before the second-stage dropper even touches the disk.
Threat actors are increasingly moving away from custom backdoors toward legitimate services like webhook.site for both command delivery and data exfiltration. What are the primary challenges in distinguishing this malicious traffic from authorized developer activity, and how can organizations implement granular controls without disrupting legitimate workflows?
The primary challenge lies in the “reputation” of the service; many security tools are configured to trust well-known domains like webhook.site because they are frequently used by legitimate DevOps and engineering teams for testing API integrations. When APT28 hides their command-and-control traffic within these streams, it blends in perfectly with the daily “noise” of software development. To counter this, organizations need to move beyond simple domain whitelisting and instead implement deep packet inspection that looks for suspicious patterns, such as Base64-encoded strings or HTML forms being posted from non-developer machines. We recommend implementing egress filtering that restricts access to such tools to specific IP ranges or VLANs dedicated to development. This way, if a machine in the HR or finance department suddenly starts communicating with a webhook service, it triggers an immediate high-priority alert without breaking the workflow of the engineering staff.
The evolution from “headless” browser execution to using keyboard simulations like “SendKeys” suggests a shift in bypassing security prompts. Could you walk through the technical progression of these evasion techniques and explain how defenders can better detect scripts that manipulate browser windows or move them off-screen to hide activity?
We have observed a fascinating tactical shift where attackers move from purely automated “headless” modes—which are increasingly flagged by modern EDR solutions—to more “human-like” interactions. In the earlier versions of the Operation MacroMaze scripts, the malware relied on a hidden browser instance to fetch commands, but as security tools got better at spotting headless Edge processes, the actors pivoted to “SendKeys” to simulate actual user input. This allowed them to bypass prompts that require a physical-like interaction, essentially tricking the OS into believing a person is navigating the page. To detect this, defenders should look for browser processes that are launched with unusual coordinates, such as being positioned off-screen where the user cannot see them, or processes that aggressively terminate all other instances of the same browser to gain total control. Monitoring for the “SendKeys” API call within VBScript or PowerShell is also a critical telemetry point that often reveals these hidden orchestrations.
Droppers often establish persistence through scheduled tasks and then execute multi-stage scripts to render Base64-encoded HTML in local browsers. What are the key forensic artifacts left behind by this browser-based exfiltration technique, and what metrics can be used to gauge the effectiveness of automated sandboxing against such minimal disk footprints?
This technique is designed to be “fileless” and ephemeral, but it still leaves a trail if you know where to look. The key forensic artifacts are found in the Scheduled Tasks logs, where the initial persistence is anchored, and in the browser’s temporary cache or memory strings where the Base64-encoded HTML is decoded before execution. Because the exfiltration happens via a standard HTML form submission, the network logs will show a POST request to a remote endpoint, but the local disk remains relatively clean. To gauge sandboxing effectiveness, we look at the “dwell time” between the task execution and the first outbound POST request, as well as the sandbox’s ability to intercept the VBS-to-CMD-to-Batch execution chain. If your sandbox only looks for binary executions and ignores script-based browser manipulations, it will likely give a “benign” verdict, which is a metric of failure in this context.
Advanced persistent threats frequently use a combination of VBScripts, CMD files, and batch scripts to orchestrate a compromise. In environments where these tools are necessary for administration, what step-by-step strategies do you recommend for hardening systems against such “living-off-the-land” tactics while maintaining operational efficiency?
Hardening against “living-off-the-land” tactics requires a layered approach that focuses on visibility rather than outright prohibition. First, I recommend implementing Constrained Language Mode for PowerShell and strictly signing any administrative scripts to prevent unauthorized VBS or Batch files from running. Second, use Group Policy to disable the execution of scripts from common user-writable directories like “Downloads” or “Temp,” forcing legitimate admin tools to run from protected, read-only locations. Third, ensure that every script execution is logged with its full command-line arguments, as this allows you to see the actual Base64 payloads or “SendKeys” commands being used in real-time. Finally, you must train your SOC to recognize that “legitimate tool + unusual parent process” (like Word launching a CMD shell) is the most important indicator of a breach, regardless of how “clean” the actual script might appear.
What is your forecast for the future of legitimate-service exploitation in state-sponsored cyber operations?
I expect state-sponsored actors to double down on “infrastructure-as-a-service” abuse because it is cost-effective and provides them with built-in anonymity and high availability. We will likely see a surge in the use of legitimate cloud storage, collaboration platforms, and even social media APIs not just for exfiltration, but for the entire lifecycle of the attack to make it indistinguishable from daily cloud traffic. This “cloaking” within the white noise of the global digital economy will force a shift in our industry; we can no longer rely on blocking “bad” IPs or domains. Instead, the future of defense will be entirely behavior-centric, where the security of an organization depends on its ability to understand the specific intent behind every single digital interaction, no matter how “trusted” the service on the other end might be.
