I’m thrilled to sit down with Rupert Marais, our in-house security specialist with a wealth of experience in endpoint and device security, cybersecurity strategies, and network management. With a career dedicated to dissecting advanced persistent threats and fortifying digital defenses, Rupert has been at the forefront of analyzing sophisticated cyber-espionage campaigns. Today, we dive into the evolving tactics of the Russian-speaking Tomiris group, exploring their stealthy use of legitimate platforms for malicious operations, their multi-language malware approach, and the persistent targeting of high-value diplomatic entities in the CIS region. We’ll also unpack the challenges defenders face and the strategies needed to counter such insidious threats.
Can you explain how Tomiris leverages platforms like Telegram and Discord for command-and-control traffic, and why this makes their activities so hard to detect in a typical network environment?
Well, Tomiris is tapping into platforms like Telegram and Discord because these services are widely used for legitimate communication, which allows their malicious traffic to blend seamlessly into the noise of everyday network activity. These platforms are often whitelisted in corporate settings since employees rely on them for collaboration, so security tools might not flag the traffic as suspicious right away. I recall a case where a client’s security team was baffled by intermittent data exfiltration—they didn’t realize their own chat tools were being abused until we dug into the logs and spotted unusual API calls to Discord servers late at night, long after business hours. It’s a clever tactic because it exploits trust in familiar services. Defenders need to get granular with traffic inspection, looking for anomalies like odd data volumes or connections to unfamiliar servers, even if the platform itself seems benign. Behavioral analysis also helps—legitimate users don’t typically send repetitive, structured messages to external endpoints at 3 a.m.
What’s driving Tomiris to develop malware in multiple programming languages like Go, Rust, and Python, and how does this diversity complicate detection efforts for security teams?
The shift to multiple languages is really about adaptability and evasion. By using languages like Go, Rust, and Python, Tomiris can tailor their malware to different environments and bypass signature-based detection tools that rely on recognizing known patterns in code. Each language has unique compilation traits or runtime behaviors that make it harder for a single antivirus solution to catch everything—Rust binaries, for instance, are often leaner and less predictable than traditional C++ malware. I think of it like a chameleon changing colors to match its surroundings; just when you think you’ve spotted it, it shifts again. I’ve seen cases where security teams were tuned to detect Python-based scripts, only to miss a Go implant sneaking through because their tools weren’t calibrated for its specific memory usage patterns. This diversity forces defenders to adopt broader, behavior-focused detection methods rather than relying on static signatures, which is a resource-intensive pivot.
Tomiris seems laser-focused on diplomatic and political targets in CIS countries. What do you think motivates this specific targeting, and why does their persistence pose such a significant threat despite lacking high-end sophistication?
Their focus on diplomatic and political entities in the CIS region likely stems from a strategic interest in accessing sensitive geopolitical intelligence—think internal documents or communications that could influence regional power dynamics. These targets are goldmines for espionage, offering insights into foreign policy or negotiations that could be leveraged for political advantage. What makes Tomiris particularly dangerous is their dogged persistence; they’re not deterred by initial failures and will cycle through disposable malware until something sticks. I remember working on a case where a government entity kept getting hit with seemingly rudimentary phishing attempts, but over months, one slipped through due to sheer volume and timing, leading to a months-long breach. Their brute-force approach may lack the polish of other nation-state actors, but it’s effective because they exploit human error and overworked defenses. It’s a grinding war of attrition, and that’s what keeps them a serious threat.
Phishing emails with password-protected archives are a common entry point for Tomiris attacks. Can you walk us through how they design these lures and detail the infection chain that follows?
Tomiris crafts phishing emails with a deceptive simplicity that preys on curiosity or urgency. They often include password-protected archives with the password provided in the email itself, which bypasses some email scanners that can’t unpack encrypted files. The archive might be named something innocuous like “Budget_Report.doc” with a bunch of blank spaces hiding the real .exe extension, tricking users into thinking it’s a safe document. Once opened, the executable deploys an initial payload that establishes contact with a command-and-control server—often via a platform like Discord—and pulls down secondary malware like Havoc for deeper system control. I’ve seen stats from reports where over half of these lures are in Russian, tailored to specific cultural contexts, which boosts click-through rates significantly. I had a client once who fell for a similar ruse because the email mimicked an urgent memo from a known contact; it wasn’t until data started leaking that we traced it back to that single click. It’s a low-tech start, but it exploits trust and distraction with deadly precision.
How does Tomiris’ strategy of customizing attack content to languages and cultures of specific nations like Turkmenistan and Kyrgyzstan enhance their effectiveness?
Localization is a powerful tool for Tomiris because it builds familiarity and lowers psychological barriers for victims. When an email or document is in the native language of a target—say, Turkmen or Kyrgyz—and references local events or institutions, it feels authentic and urgent, increasing the likelihood of engagement. For instance, tailoring content to mention a specific regional policy or a well-known diplomatic figure can make a phishing lure seem like a legitimate internal communication. I’ve observed campaigns where attackers used localized slang or formatting that mirrored government correspondence, which made even cautious users second-guess their instincts. It’s like receiving a handwritten letter from a neighbor versus a generic flyer—you’re more likely to open the one that feels personal. This strategy significantly boosts their success rate by exploiting cultural trust, making it harder for standard phishing filters to flag based on generic keywords alone.
Tomiris often uses open-source frameworks like Havoc and AdaptixC2 for controlling infected systems. What benefits do these tools provide over custom-built malware, and how do they help maintain long-term access in a network?
Using open-source frameworks like Havoc and AdaptixC2 gives Tomiris a huge advantage in terms of flexibility and deniability. These tools are publicly available, well-documented, and often come with a community of users who inadvertently help debug or enhance features, saving attackers the effort of building from scratch. They can be customized quickly for specific targets, allowing hands-on control like file uploads or remote command execution without leaving a unique fingerprint that custom malware might. I recall a network breach where we struggled to attribute the attack because the C2 framework used was so common among various groups—it was like trying to trace a mass-produced car part back to a single driver. These tools also aid persistence by enabling attackers to pivot within a network, moving from one compromised system to another via proxy tools, often staying undetected for months. Their widespread use means defenders can’t easily block them without deep behavioral analysis, giving Tomiris a prolonged foothold.
The group uses tools in Rust and Python to harvest system data and documents. Can you break down how these tools operate to steal information, and why they’re effective for espionage?
The Rust-based tools Tomiris uses are particularly adept at system reconnaissance—they’re coded to scan for specific file types like .pdf or .jpg, gather system information, and quietly exfiltrate data to servers on platforms like Discord. Rust’s efficiency means these tools can run with minimal resource impact, avoiding the spikes in CPU usage that might alert a defender. On the Python side, they’ve got scripts that hunt for targeted files, bundle them into compressed archives, and upload them to C2 servers with stealthy, staggered timing to evade detection. These tools are effective for espionage because they prioritize high-value data—think diplomatic correspondence or strategic plans—and automate the collection process to minimize attacker interaction. I once dealt with a breach where a Python script sat dormant for weeks, only activating during off-hours to zip and send files, which went unnoticed until a routine audit caught an odd outbound transfer. The precision and low profile of these tools make them ideal for long-term data theft, especially in sensitive environments.
Using legitimate platforms like Telegram for C2 communications poses unique detection challenges. What makes this so tough for enterprise security teams, and how can they overcome it?
The challenge with platforms like Telegram for C2 is that they’re inherently trusted and often whitelisted in enterprise settings for legitimate use, so traditional firewalls or intrusion detection systems won’t raise alarms. Malicious traffic can look identical to an employee sending a quick message, especially if it’s encrypted or routed through API calls that mimic normal behavior. It’s like trying to spot a counterfeit bill in a stack of cash—you need a magnifying glass and a lot of patience. I remember a corporate client who nearly missed a breach because their security tools ignored Telegram traffic; it took a manual review of connection logs to spot recurring pings to an obscure channel. To counter this, teams need deep packet inspection to analyze payload patterns, even on trusted platforms, and behavioral tools to flag anomalies like unusual data transfer volumes. It’s also critical to train staff on spotting phishing attempts that might initiate these connections—prevention is often easier than cleanup.
There’s speculation about Tomiris sharing tools with Turla, yet they’re considered distinct groups. Can you elaborate on how their approaches or priorities differ, and why experts see them as separate entities?
While Tomiris and Turla overlap in some malware tools, their operational focus and methods set them apart significantly. Tomiris hones in on diplomatic and political targets in the CIS region with a relentless, almost industrial approach to persistence, cycling through disposable malware until they breach a system. Turla, on the other hand, often exhibits a broader scope tied to nation-state objectives, with more caution and sophistication in their stealth tactics. I’ve seen analyses where Tomiris would hammer a target with phishing for months, while Turla might spend that time crafting a single, near-invisible exploit. Experts distinguish them based on these targeting priorities and operational tempo—Tomiris feels more opportunistic, less polished. It’s like comparing a sledgehammer to a scalpel; both can do damage, but the intent and precision differ. This distinction, along with separate infrastructure in their C2 setups, convinces most researchers they’re not the same entity, even if some tools are shared.
Advanced detection methods like behavioral analysis are recommended to counter Tomiris’ stealthy tactics. How do these strategies work against their multi-language implants, and can you share an example of their impact in uncovering a hidden threat?
Behavioral analysis is a game-changer against multi-language implants because it focuses on what the malware does rather than what it looks like. Instead of matching code signatures—which vary across languages like Go or Rust—it monitors actions like unauthorized file access, abnormal network calls, or unexpected process behavior, flagging anomalies regardless of the programming language. For Tomiris, whose implants often pivot to secondary payloads like Havoc, this means catching the unusual activity of a system suddenly connecting to a Discord server, even if the initial executable evades traditional scans. I worked on a case where a government network had a hidden implant that our standard tools missed because it was written in an obscure language variant, but behavioral tools caught it when it tried to exfiltrate compressed archives at odd hours. We traced the activity back, isolated the infected endpoint, and prevented a major data loss. These methods require investment in real-time monitoring and skilled analysts, but they’re essential for spotting stealthy, evolving threats like Tomiris.
What’s your forecast for the future of cyber-espionage tactics like those used by Tomiris, especially regarding the use of legitimate platforms and multi-language malware?
I see groups like Tomiris pushing even harder into exploiting legitimate platforms, not just for C2 but also for malware distribution and social engineering, as these services continue to proliferate in workplaces. We might witness more sophisticated abuse of cloud services or collaboration tools, where malicious payloads hide in shared drives or meeting links, making detection an uphill battle. The multi-language trend will likely grow too, with attackers experimenting with niche or emerging languages to stay ahead of static detection tools, forcing defenders to lean on AI-driven behavioral analysis. I’m also concerned about automation—imagine scripts that adapt code on-the-fly based on the target environment. The cat-and-mouse game will intensify, and I think we’ll see more emphasis on zero-trust architectures to mitigate these evolving risks. It’s going to be a challenging few years, but staying proactive with layered defenses will be key.
