In a May 21, 2025 episode of Dark Reading Confidential, security researchers describe two investigations that began with clues in unexpected places: a fake IP-scanning tool associated with FIN7 activity and a Cyrillic-language threat cluster that did not appear to target Ukraine. Their accounts show how threat hunters can find activity before ransomware is deployed, why missing logs matter, and why a familiar group name may conceal several actors working in sequence.
What the episode covers
Host Becky Bracken and Dark Reading editors Kelly Jackson Higgins and Jim Donahue speak with Ismael Valenzuela, identified in the episode as Arctic Wolf’s vice president of threat research, and Vitor Ventura, identified as a lead security researcher with Cisco Talos. The episode was released May 21, 2025. Its examples are the guests’ interview accounts, not independent technical verification of the incidents. Listen to the episode and read its transcript at Dark Reading.
How a fake IP-scanning tool revealed FIN7 activity
Valenzuela recounts an investigation around a US auto manufacturer in which his team found signs of ransomware activity before a late-stage payload appeared. The operators had cloned a website for an IP-scanning tool and used look-alike domains to attract targeted users to trojanized downloads. The episode names Anunak and PowerTrash as malicious binaries and describes command-and-control infrastructure as part of the investigation.
Rather than relying on one alert or artifact, the researchers combined network and endpoint signals with techniques such as machine learning and clustering, then considered infrastructure clues to attribute the activity to FIN7. The practical lesson is to look for behaviors and precursors that precede the disruptive payload: a convincing imitation site, a suspicious download, or connections to related infrastructure may matter before ransomware runs. Valenzuela frames this as a way to spot deviations from normal activity and act earlier, not as a guarantee that every attack can be stopped.
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Why an unexpected language or missing data can matter
Ventura describes looking for actors targeting Ukraine when he encountered a Cyrillic-language threat cluster. Its material and look-alike subdomains suggested one context, but the activity did not appear to target Ukraine. That mismatch prompted closer investigation, which identified targeting across countries in the surrounding region, including Turkey.
The investigation illustrates two complementary questions for threat hunting:
- What is present? Examine observed domains, language, endpoints, network connections, and other telemetry for patterns that do not fit expected behavior.
- What should be present but is not? Consider whether relevant events, devices, or systems have stopped reporting. Ventura’s advice was, “When we do want to do threat hunting, we need to look for what’s not there.”
A gap is not proof of an intrusion: logging can fail for routine reasons. But when an endpoint sensor stops reporting or an edge device stops sending syslog unexpectedly, investigators should establish why rather than treating the absence as reassurance. Valenzuela said such interruptions “should be something to investigate right away.”
Why one “APT group” label may hide several roles
Ventura cautions that the label attached to an operation can oversimplify who did what. One possible chain involves an initial-access broker obtaining entry, an affiliate using that access, and a ransomware-as-a-service operator deploying a payload. Their tools, objectives, and timelines may differ.
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In the example he describes, an initial compromise was followed days later by a separate ransomware deployment. The time gap and differing techniques helped reveal a handoff. This is a reason to distinguish evidence of initial access, later deployment, and infrastructure use where the evidence supports those separate roles—not to infer a multi-party operation from a delay alone. Ventura cautions against attribution based on a single clue.
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Build a joined-up view of activity
Endpoint, network, and cloud telemetry can each show only part of a sequence. Collecting and correlating these sources gives investigators a better chance to connect an unusual download, subsequent behavior, and infrastructure clues. The episode does not prescribe a particular product or architecture; the relevant question is whether your environment records the events needed to investigate the behaviors you care about.
Hunt for precursors, not only payloads
Use reports of adversary tactics and techniques to ask what those actions would look like in your own environment. Check whether your logging and sensors would capture suspicious downloads, unusual connections, or changes in account and system behavior. If the data is unavailable, treat that as a visibility gap to address rather than assuming the activity is absent.
Make response feasible with focused alerts
Monitoring is useful only if someone can investigate and respond. Ventura points to high-priority alerts for activity such as unexpected use of a domain administrator account as a way to keep response manageable. The episode does not provide a universal threshold or a complete alerting configuration; teams need to tune priorities to their environment and ensure that critical alerts reach a responder.
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