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Introduction: Why Hacker Names Matter More Than Most People Realize
The cybersecurity industry has a strange problem that has existed for years: the same hacking group can have several different names depending on which security company is tracking it. One intelligence report might warn about “Sandworm,” another calls the same attackers “APT44,” while a third vendor assigns an entirely different codename. For security professionals, incident responders, and CISOs, this naming chaos wastes valuable time during critical investigations and creates unnecessary confusion.
Recognizing this long-standing issue, Google has announced a major overhaul of its threat intelligence naming system. Instead of maintaining multiple internal naming conventions inherited from different teams, the company is introducing a unified and memorable two-word naming structure designed to make cyber threat tracking more intuitive. While the cybersecurity community welcomes any attempt to reduce confusion, many experts wonder whether adding yet another naming system will truly simplify attribution—or simply become another translation layer that defenders must learn.
Google Unifies Its Internal Hacker Naming Systems
For years, Google operated two separate cyber threat intelligence teams with different methods of identifying threat actors.
Following Google’s acquisition of Mandiant in 2022, both organizations continued using their historical naming conventions. Mandiant had developed one set of identifiers, while Google’s own Threat Analysis Group (TAG) relied on another. As both teams expanded their research, overlapping names for identical threat actors became increasingly common.
Google now aims to eliminate that internal inconsistency by introducing a standardized naming framework across its entire threat intelligence operation.
According to Google, threat intelligence should focus on recognizing adversary behavior rather than forcing analysts to memorize dozens of unrelated aliases.
How
The new naming model assigns every tracked threat group a memorable two-word codename.
Each designation contains two separate components.
The first word is a unique identifier chosen specifically for memorability. Whenever possible, Google will reuse familiar terms that already appeared in previous reporting. If no suitable historical identifier exists, researchers will generate a completely new word before analysts review and approve it.
The second word categorizes the threat actor according to its origin or operational motivation.
Google’s current taxonomy includes categories such as:
CASTLE — China-linked threat groups
RELIC — Russia-linked threat actors
ION — Iranian operations
NEPTUNE — North Korean groups
COMET — Financially motivated cybercriminal organizations
This allows names like Sandworm Relic or entirely new combinations while preserving immediate contextual information about the suspected attribution.
A Familiar Concept Inspired by Existing Industry Standards
Although
CrowdStrike has successfully used a comparable naming structure for years.
Its system combines an identifying word with an animal associated with specific geopolitical or operational categories.
Examples include:
Panda for Chinese operations
Bear for Russian intelligence groups
Spider for financially motivated cybercriminals
Jackal for hacktivist organizations
Google replaces the animal theme with broader category labels such as CASTLE, RELIC, and COMET, but the underlying philosophy remains remarkably similar.
The objective is simple: provide names that are easier to remember while still conveying useful intelligence.
Microsoft’s Weather-Themed Experiment Changed the Conversation
Google is not the first technology giant to rethink cyber threat naming.
In April 2023, Microsoft completely redesigned its own classification system.
Instead of using chemical elements, trees, and volcanoes, Microsoft adopted weather-based terminology.
The mapping included:
Typhoon for Chinese actors
Blizzard for Russian operations
Sandstorm for Iranian groups
Tempest for financially motivated attackers
While technically functional, many of
Examples such as:
Strawberry Tempest
Pumpkin Sandstorm
Pistachio Tempest
became internet jokes almost immediately, with researchers arguing that they sounded more like seasonal beverages or dessert menus than sophisticated cyber espionage organizations.
Although memorable, critics questioned whether such names improved clarity or unintentionally reduced the seriousness of major cyber threats.
The Industry Has Been Struggling With Naming Chaos for Years
Cybersecurity has long suffered from fragmented attribution.
One hacker group can simultaneously carry names assigned by:
Microsoft
Mandiant
CrowdStrike
Palo Alto Networks Unit 42
MITRE ATT&CK
Government intelligence agencies
As a result, security teams frequently spend additional time translating names between vendor reports before they can even begin technical analysis.
This fragmentation becomes especially problematic during active cyber incidents, where speed and accuracy directly influence containment efforts.
The 2025 Industry Collaboration Attempt
Recognizing the growing problem, several cybersecurity leaders announced an unprecedented cooperation initiative during 2025.
Microsoft and CrowdStrike launched a joint mapping project designed to correlate their respective naming systems.
Rather than replacing existing names, the project aimed to build a translation layer that allows analysts to quickly determine whether different vendor reports actually describe the same threat actor.
Google, Mandiant, and Palo Alto Networks Unit 42 also agreed to contribute mappings into the shared ecosystem.
Importantly, none of the participating organizations attempted to establish a universal naming standard. Instead, they focused on making existing intelligence easier to correlate across multiple vendors.
Google’s latest announcement builds upon this broader industry effort.
Compatibility With Existing Threat Intelligence
Google understands that thousands of historical intelligence reports already reference older identifiers.
For that reason, legacy names will not disappear.
Instead,
Previous Google identifiers
Former Mandiant names
MITRE ATT&CK references
Other major vendor naming systems
This backward compatibility ensures that years of published threat research remain usable without forcing analysts to manually translate historical reports.
What About Unknown Threat Groups?
Not every cyber operation can immediately be attributed.
Google will continue using the familiar UNC (Uncategorized) designation whenever analysts lack sufficient evidence to confidently determine a group’s affiliation.
As investigations mature and intelligence improves, those UNC designations may eventually transition into Google’s standardized naming taxonomy.
This approach preserves analytical accuracy while avoiding premature attribution—a critical principle in professional threat intelligence.
Why Consistent Naming Matters for Cyber Defense
Threat actor names may seem like a cosmetic issue, but they directly affect operational efficiency.
When multiple vendors assign different identities to identical adversaries, organizations face several challenges:
Increased analyst workload
Delayed incident response
Confusion during intelligence sharing
Duplicate investigations
Complicated executive reporting
Higher training requirements for security teams
Standardized naming improves communication between researchers, government agencies, and enterprise security operations centers.
The easier threat intelligence becomes to understand, the faster defenders can react to evolving cyber campaigns.
Deep Analysis
Google’s announcement reflects a broader maturation of the cyber threat intelligence industry. Modern intelligence platforms now process millions of indicators of compromise (IOCs), malware samples, infrastructure relationships, and behavioral patterns every day. Human analysts cannot efficiently interpret that volume of information if every organization speaks a different “language.”
From a technical perspective, threat actor names are simply labels attached to clusters of infrastructure, malware families, tactics, techniques, and procedures (TTPs). The real intelligence lies beneath the name.
Security teams should therefore prioritize behavioral detection over memorizing branding terminology.
Useful MITRE ATT&CK-related investigation examples include:
Search ATT&CK techniques grep "T1059" attack_mapping.json
Review Sigma detection rules
grep -Ri "Sandworm" sigma/
Query threat intelligence feeds
curl https://threat-feed.example/api/groups
Search Indicators of Compromise
grep -Ri "IOC" intelligence_report.txt
YARA malware scan
yara malware_rules.yar suspicious_sample.bin
Sigma rule conversion
sigmac -t splunk ransomware.yml
ATT&CK Navigator layer validation
python attack_mapper.py --group RELIC
IOC enrichment
python enrich_ioc.py indicators.txt
From an intelligence correlation standpoint, future platforms are likely to depend less on human-readable names and more on machine-readable identifiers linked through STIX 2.1, TAXII servers, MITRE ATT&CK mappings, malware hashes, infrastructure fingerprints, behavioral signatures, and AI-assisted clustering. The visible codename may simply become a user-friendly label while automated systems perform the real attribution behind the scenes.
Artificial intelligence is also beginning to transform cyber threat intelligence by automatically correlating campaigns across multiple vendors, identifying overlapping infrastructure, predicting threat evolution, and reducing analyst workload. In such an environment, naming consistency becomes even more valuable because AI models perform better when historical data is normalized rather than fragmented across dozens of unrelated aliases.
Ultimately,
What Undercode Say:
Google is solving a genuine operational problem rather than introducing a cosmetic branding exercise.
The cybersecurity industry has accumulated nearly two decades of disconnected threat actor naming systems.
Every major vendor historically preferred its own internal taxonomy.
While each system made sense internally, cross-vendor intelligence became increasingly difficult.
Security analysts often spend valuable time translating names instead of analyzing attacks.
This creates friction during live incident response.
The problem becomes even worse during multinational investigations.
Government agencies frequently publish different names than private vendors.
Large enterprises subscribe to multiple intelligence providers simultaneously.
SOC analysts may see five different names describing one attacker.
Executive reports become unnecessarily complicated.
Training new analysts becomes harder every year.
Google’s two-word approach is logically structured.
Separating identity from attribution creates flexibility.
If attribution changes, only the category component may need updating.
That reduces disruption compared to renaming an entire actor.
Backward compatibility is another positive decision.
Keeping historical aliases searchable preserves years of accumulated intelligence.
The continuation of UNC designations also demonstrates analytical discipline.
Premature attribution remains one of cyber
Google avoids forcing certainty where evidence is still developing.
However, another naming system also introduces short-term complexity.
Organizations must now learn Google’s terminology alongside Microsoft’s and CrowdStrike’s.
Translation remains necessary.
Long-term success depends on industry adoption.
If major vendors gradually converge around interoperable mappings, analyst productivity should improve.
If everyone continues inventing independent labels, confusion will persist.
The future of threat intelligence likely belongs to structured data rather than names.
Machine-readable identifiers, ATT&CK techniques, STIX objects, malware families, and infrastructure graphs carry significantly more intelligence than any codename.
Names primarily exist for human communication.
AI-assisted intelligence platforms will increasingly automate cross-vendor correlation.
Eventually, analysts may rarely need to memorize threat actor names at all.
Google’s announcement therefore represents an important step toward standardization, but it is not the final solution.
True interoperability requires continued collaboration across the cybersecurity industry rather than isolated vendor initiatives.
✅ Fact: Google has introduced a unified two-word naming system to replace separate internal naming conventions used by Google Threat Intelligence Group and Mandiant. This aligns with Google’s official announcement and addresses internal duplication after the Mandiant acquisition.
✅ Fact: Microsoft’s weather-themed naming system and CrowdStrike’s animal-based taxonomy are accurately described. Both vendors publicly use these attribution models, and industry collaboration to map names across vendors has been announced.
✅ Fact: Google will continue supporting historical aliases, MITRE ATT&CK mappings, and UNC designations for uncategorized threat groups. This ensures backward compatibility while avoiding premature attribution of emerging cyber actors.
Prediction
(+1) Google’s new naming framework is likely to improve the readability of threat intelligence reports and reduce confusion inside organizations that rely heavily on Google’s security products. Over the next few years, AI-driven threat intelligence platforms will increasingly automate the translation between vendor naming systems, making human-friendly labels less important than standardized behavioral data, ATT&CK mappings, and machine-readable threat intelligence formats. If industry collaboration continues, cybersecurity professionals may eventually work within a far more unified ecosystem where threat actor identification is faster, more accurate, and significantly less confusing.
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References:
Reported By: cyberscoop.com
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