We are joined today by Dominic Jainy, an IT professional whose extensive expertise in artificial intelligence and machine learning is providing new lenses through which to view cybersecurity. His recent work has focused on tracking the digital footprints of sophisticated state-sponsored groups, revealing the subtle infrastructural clues they leave behind. We’re here to discuss the recent discovery of new infrastructure clusters belonging to APT-C-35, a notorious espionage actor, and how a unique approach to threat hunting is changing the game.
The research identified APT-C-35 infrastructure using unique Apache HTTP response headers. Could you walk us through the discovery process and explain what specifically made the “Expires: Thu, 19 Nov 1981” header a reliable signature for this group’s command-and-control servers?
Of course. The discovery really began with a hunt for anomalies in the vast seas of internet data. We weren’t just looking for known malicious IP addresses, which are fleeting; we were searching for a persistent behavioral fingerprint. When my team started analyzing Apache server responses at scale, we noticed this peculiar and archaic pattern. The header “Expires: Thu, 19 Nov 1981” is an old, default value in some server configurations. Most modern, legitimately configured servers would have this updated or managed differently. Seeing it appear consistently, especially when paired with a “200 OK” status code, felt like finding a specific calling card left at a crime scene. It was so specific and out of place in today’s web traffic that it became a high-fidelity signature, allowing us to confidently attribute any server with this exact configuration to APT-C-35’s command-and-control network.
Your investigation combined HTTP analysis with a focus on ASN 399629, which narrowed the results to 36 unique IPs. Can you elaborate on the significance of this specific ASN and detail how this two-pronged approach helps analysts cut through the noise of internet-wide scanning?
ASN 399629 was the other crucial piece of the puzzle. You can think of an Autonomous System Number, or ASN, as a digital neighborhood—a specific block of internet real estate controlled by a single entity. While the unique HTTP header was our suspect’s calling card, the ASN was their known haunt. By combining these two distinct data points, we could filter out an immense amount of irrelevant noise. We were no longer just scanning the entire internet for that one obscure header; we were specifically looking for that header only within the digital territory we knew the group frequented. This two-pronged approach is what made the hunt so effective. It immediately cut down the possibilities, taking us from millions of potential servers to just 73 results and those 36 unique IPs. It’s the difference between looking for a needle in a global haystack and looking for it in a single, well-defined corner of the barn.
The primary server, gilbertfix.info, used “Cache-Control: no-store, no-cache” headers. What does this configuration reveal about APT-C-35’s operational security priorities, and how does this tactic help them protect their malware communications from being inspected or archived?
That “Cache-Control” configuration tells you everything about the group’s operational mindset: they prioritize stealth and ephemerality above all else. By instructing browsers and intermediary network devices with “no-store, no-cache, must-revalidate,” they are essentially ordering any data from their communications to self-destruct after being read. This prevents sensitive information from their malware—like new commands or exfiltrated data—from being stored in a temporary cache on a victim’s machine or a network proxy. For a forensic investigator, this is incredibly frustrating because it methodically erases potential evidence trails. It clearly shows a high level of operational security sophistication aimed at making their command-and-control channels as ghostly and untraceable as possible, ensuring their malicious traffic leaves minimal footprints.
This discovery enables proactive threat hunting. Can you provide a step-by-step example of how a security team could translate these findings—like the specific HTTP headers and status codes—into actionable detection rules or queries within their existing security tools like a SIEM or EDR?
Absolutely. This is the most important part—turning research into real-world defense. A security team can take these findings and immediately build a powerful, custom detection rule. For example, in their Security Information and Event Management (SIEM) platform, they could write a query that says, in essence: “Alert me in real-time whenever you see an outbound HTTP response from our network that contains the exact header Expires: Thu, 19 Nov 1981 08:52:00 GMT AND has the status code 200 OK.” To make it even more precise and reduce false positives, they could add a third condition to check if the destination IP address belongs to ASN 399629. When that rule triggers, it’s not just another random alert; it’s a high-confidence signal that one of your assets is communicating with a server tied to APT-C-35 infrastructure. This allows a security operations center to skip the initial, time-consuming triage and jump straight into their incident response playbook, knowing exactly where to look first.
Do you have any advice for our readers?
My main advice is to shift your security mindset from a purely reactive defense to proactive hunting. Don’t just wait for an alert based on a known malicious IP address or a file hash from a threat feed—those indicators have a very short shelf life and are easily changed by attackers. Instead, start hunting for the attackers’ methods and infrastructure patterns, like the unique server headers we discussed today. These are far more fundamental to an adversary’s operation and much more difficult for them to change without retooling their entire setup. Dedicate time to understanding the tactics, techniques, and procedures of threat groups that target your industry. By looking for these deeper behavioral and infrastructural indicators, you can detect threats before they become a full-blown incident and truly stay one step ahead of even the most persistent state-sponsored actors.