Enterprise security teams are increasingly adopting intelligence-driven defense. This is good, but cyber criminals have since recognized that their underground reputations can easily become their greatest liabilities. The reason? When security analysts are able to turn diverse datasets into comprehensive threat actor profiles, cyber criminals find it harder to operate undetected.
It makes sense that the most sophisticated cyber criminals would actively take steps to evade profiling efforts. Understanding how they try to obfuscate their operational identities proves that passive intelligence gathering is no longer enough.
How Cyber Criminals Attempt to Evade Profiling
Successful threat actor profiling relies heavily on correct attribution. Therefore, cyber criminals leverage anti-attribution techniques designed to complicate endless investigations. When they succeed, they manage to muddy threat actor profiling data. Here are four ways DarkOwl says they do it:
1. Alias Fragmentation and Persona Cycling
It used to be that threat actors maintained a single high-reputation persona across the dark web. They no longer do that. Instead, they frequently rotate pseudonyms. They use separate identities for recruiting, negotiating ransom payments, purchasing exploits, and even participating in chat channels. Doing so makes it harder for analysts to link isolated activities back to a single person or entity.
2. Active Infrastructure Obfuscation
Threat actors get around network-based correlation by avoiding command-and-control servers and storing breach data directly on their infrastructure. They also chain bulletproof hosting providers and use decentralized domain systems. They even route communications through encrypted networks and residential proxy swarms to make their physical locations hard to discover.
3. Deliberately Generating Noise and False Flags
The most sophisticated threat actors routinely deploy false flags designed to confuse threat analysts. A favorite tactic is reusing a known open-source malware routine. Other strategies include planting non-native language strings in code comments or mimicking the TTPs of their competitors to deflect blame.
4. Leveraging Code Polymorphism and Shared Tooling
Some threat actors are now doing away with custom code in favor of off-the-shelf tools. In general, run-of-the-mill software doesn’t generate the same recognizable file signatures that custom code does. When dozens of individuals and groups share identical frameworks, it’s nearly impossible to attribute a specific attack based solely on the technical artifacts an investigator finds.
Why a Single Indicator Rarely Proves Identity
A malware sample, an IP address, or a forum username can provide an investigative lead, but none establishes who controls an operation. Criminal groups share infrastructure, purchase access from brokers, and reuse publicly available tools. Even a cryptocurrency wallet can change hands or represent a service used by several customers.
Analysts therefore look for independent evidence that points in the same direction. A consistent sequence of intrusion methods, overlapping communication habits, and repeated interactions with known associates can strengthen a connection.
Conversely, conflicting evidence should keep an attribution judgment tentative. Treating a technical match as proof risks merging unrelated actors into one profile and sending defenders after the wrong threat.
Anti-profiling Tactics Fall Short
Anti-profiling techniques can be effective in terms of preventing analysts from fully understanding hard data. For instance, threat actors can easily change IP addresses and forum handles. What they have a harder time changing is their own behaviors. Humans are creatures of habit, and changing entrenched habits is really difficult.
The realities of human nature explain why anti-profiling tactics fall short. Over time, persistent operational habits inevitably betray the cyber criminal:
- Communication Patterns – Proper stylometric analysis can reveal distinct phrasing and technical jargon. It can help analysts uncover linguistic habits that persist across multiple aliases and communication channels.
- Economic Footprints – Tracking how cryptocurrency flows across dark web markets often exposes connected wallet clusters and lists that can link seemingly separate personas to a single financial node.
- Target Consistency – Both individuals and crews tend to specialize in specific industries or target sets. Analysts can respond by designing playbooks based on threat actor specialty.
Reconstructing Activity Across Multiple Identities
When an actor abandons one alias, investigators may still find continuity in the activity surrounding it. Forum posts, marketplace listings, breach announcements, and infrastructure observations provide separate timelines that can be compared for unusual overlaps.
The timing of account creation, the services offered, and changes in advertised capabilities may help establish a working hypothesis.
A stronger link emerges when several observations align, rather than when two usernames merely sound alike. Analysts also need to document where each observation came from and when it was collected.
Deleted posts, fabricated screenshots, and recycled breach claims can otherwise distort the record. Preserving source context makes subsequent reviews possible as new information arrives.
Attribution Requires Clear Confidence Levels
Threat actor profiles become less reliable when assessments are presented as settled facts. Analysts can distinguish confirmed observations from plausible interpretations and explicitly assign confidence levels to major conclusions.
For example, evidence may strongly connect two campaigns through shared infrastructure while offering little basis for identifying the people directing either one.
Confidence should also change as the evidence changes. A newly discovered connection can strengthen a hypothesis, while signs of compromised accounts or rented infrastructure can weaken it.
Recording alternative explanations helps prevent confirmation bias, particularly when a familiar alias appears in a new investigation. The objective is a defensible assessment, not an impressive-looking list of names.
Making Threat Profiles Useful to Defenders
Knowing that two incidents might involve the same actor is valuable only when the connection informs security decisions. A useful profile should identify observed intrusion methods, likely targets, the tools involved, and the indicators that remain relevant.
Analysts can then compare those findings with their own organization’s exposure and existing detection coverage.
For example, if a group repeatedly gains initial access through stolen credentials, defenders can prioritize monitoring suspicious sign-ins and reviewing account protections. If an operation favors particular software vulnerabilities, patching and asset inventories become immediate concerns.
Profiles also need timestamps and revision histories so analysts can separate current behavior from activity that no longer reflects the threat. Attribution is most useful when it leads to better preparation.
Threat actor profiling can be either static or ongoing. Unfortunately, static threat actor profiles compiled in annual reports ultimately become obsolete. They become the victims of adversary obfuscation.
The workaround is fairly simple: continuous intelligence that aggregates historical data and compares it with the freshest intelligence gathered from across dark web and traditional internet sources. The cyber threat intelligence data can be continuously compiled into threat actor profiles that are as recent as the threat intelligence that produced them.
