State-sponsored actors, better known as the friends you don’t want

  • State-sponsored actors don’t break in. They log in, and they use your own tools to stay invisible for months.
  • Responding to a state-sponsored threat is nothing like responding to ransomware, and the differences can make or break the outcome. 
  • From logging and baselines to OT segmentation and supply chain readiness, the work that matters happens long before the first alert.

State-sponsored actors, better known as the friends you don’t want

Most organizations operate under the assumption that anything residing within their trust boundary is trustworthy. Software arrives from vetted vendors, employees pass background checks, cloud providers hold compliance certifications, and build pipelines produce signed artifacts. 

In practice, these assumptions are rarely scrutinized, and state-sponsored actors have constructed their operational methodology around exploiting precisely this gap. They operate inside the trust boundary, using trusted tools, holding valid credentials, and performing actions that appear entirely authorized. Conventional security architecture is not designed to identify this, and that limitation warrants acknowledgment before turning to what incident response looks like when the adversary is a state-sponsored.

Responding to a state-sponsored intrusion is fundamentally different from responding to a criminal one. The adversary is better resourced, more patient, operationally disciplined, and often in pursuit of objectives that do not trigger any alarms, such as espionage or long-term data extraction. Standard incident response playbooks, typically built around malware containment and ransomware recovery, are not adequate for this category of threat. The tooling, decision-making, legal coordination, and even the definition of what constitutes a successful response all need to be reconsidered.  

This is also the context in which zero trust architecture becomes essential. This is a fundamental reorientation from a model in which trust is assumed to one in which it is continuously verified, and in which systems are architected to handle the case where verification fails. The operative principle is not “trust nothing,” which no organization can realistically operationalize, but rather “verify continuously and plan for failure.” 

The following sections cover how state-sponsored actors operate across the Cyber Kill Chain, why their techniques demand different detection and response approaches, and what organizations need to have in place before, during, and after an intrusion to mount an effective response.

Same Kill Chain, different objective 

Every cyber attack, from commodity ransomware to state-sponsored espionage, follows the same fundamental sequence as the Cyber Kill Chain developed by Lockheed Martin: reconnaissance, weaponization, delivery, exploitation, installation, command and control (C2), and action on objectives. State-sponsored actors do not deviate from this sequence. They execute each phase with greater patience, greater precision, and a fundamentally different objective. 

A financially motivated attacker requires the target to know it has been compromised. The ransomware note, the leak site, and the negotiation channel are all components of the business model. A state-sponsored actor requires the opposite. Whether the objective is espionage, intellectual property theft, or pre-positioning for future disruption, success depends on the target remaining unaware. That requirement for covertness shapes every technical decision the actor makes and determines what defenders need to look for at each phase. The following are common trends that change the dimensions of defense:

  • Reconnaissance: This stage tends to be deeper and more prolonged. Where a financially motivated actor might scan for exposed Remote Desktop Protocol (RDP) and move on, a state-sponsored adversary may spend weeks or months mapping an organization’s personnel, technology stack, vendor relationships, and communication patterns, often entirely outside the target’s perimeter through open-source intelligence (OSINT) and social engineering of adjacent organizations. This phase frequently leaves no artifacts in defender logs. State-sponsored actors also have lawful access laws in their respective countries that allow them to obtain some of this data without the target being aware that any reconnaissance is taking place.
  • Initial access: State-sponsored adversaries can afford to expend significant capabilities against a single target, including zero-days or supply chain vectors that signature-based detection will not identify. More commonly, however, they use legitimate credentials obtained through spear phishing or supply chain compromise, which produce no exploit signature at all. 
  • Lateral movement: This is where the covert imperative becomes most technically consequential. Rather than deploying custom malware, state-sponsored actors increasingly operate using tools already present on the target’s systems, such as PowerShell, WMI, and PsExec, or they take time to observe what tools are used in the environment. If the environment uses SCCM or Puppet to manage infrastructure, the state-sponsored actor will aim to gain access to these systems and use legitimate deployment methods to compromise additional hosts. When Active Directory is queried through PowerShell, the security stack registers a routine administrative task, because it is indistinguishable from one. Extended dwell times result not from slow operational tempo, but from deliberate use of trusted tools to minimize the detection surface. 
  • Persistence: State-sponsored actors operate on the assumption that any single access method may be discovered and therefore establish multiple mechanisms across different parts of the infrastructure. Think aboutscheduled tasks, modified service configurations, dormant accounts, and firmware-level implants. These footholds may remain inactive for extended periods, activating only when an intelligence requirement or geopolitical trigger demands it. 
  • Action on objectives: This stage may not resemble what most teams would identify as an incident. If the objective is long-term data collection, exfiltration is structured to blend into normal traffic patterns. If the objective is pre-positioned disruption, as CISA assessed with Volt Typhoon in U.S. critical infrastructure, the actor may take no visible action during peacetime. Salt Typhoon’s access to lawful intercept systems required no disruptive action to deliver intelligence value. The access itself was the operation. When that access gets used is a separate question. 
  • Anti-forensics: Advanced actors clear event logs, manipulate file timestamps, operate in memory where possible, and use encrypted channels that leave minimal artifacts. Attribution may be further complicated by the deliberate planting of indicators associated with a different threat actor. 

Detection methodology does not require reinvention. The Kill Chain remains the same. It does, however, need to be calibrated for an adversary that treats every phase as an exercise in remaining invisible, that can operate using the target’s own tooling, and that measures success in months of undetected access.

Attribution 

Attribution in the context of incident response deserves a straightforward treatment, because it is frequently misunderstood and its operational relevance is often overstated at the tactical level. Technical attribution, associating an intrusion with a known threat actor based on tactics, techniques, and procedures (TTPs); infrastructure; and malware characteristics is possible with varying degrees of confidence and is useful primarily for informing the threat model and anticipating likely next steps. An organization that can assess with reasonable confidence that Volt Typhoon is responsible for an intrusion can make better-informed decisions about what systems to prioritize, what persistence mechanisms to hunt for, and what the likely objectives are. Political attribution, the public or legal assignment of responsibility to a state-sponsored actor, is a government function -not a security team function – and attempting it without the intelligence resources to support it creates more risk than it resolves. 

The practical implication for incident response teams is that TTPs and infrastructure indicators should be shared with national authorities and relevant Information Sharing and Analysis Centers (ISACs), who are better positioned to place them in a broader intelligence context. Internal response should focus on containment, scope determination, and recovery regardless of whether attribution is ever formally established. 

Preparing for the long game 

Encountering a state-sponsored actor during incident response is not the time to discover logging gaps, missing baselines, or that the legal team has never discussed intelligence sharing with government agencies. The following sections cover the areas where preparation most directly determines whether detection and response are feasible. 

Logging and visibility 

Default logging configurations are not sufficient for detecting the techniques described above. 

  • Windows process creation (Event ID 4688): Enable full command-line argument logging to track exact parameters used during process execution. 
  • PowerShell script block logging (Event ID 4104): Capture the actual code being executed, not just the fact that PowerShell was launched. 
  • Sysmon: Deploy with a configuration tuned to detect suspicious parent-child process relationships, flagging legitimate binaries used as proxies for malicious activity, both on Windows and Linux environments. 
  • Strategic prioritization: If a full Sysmon rollout is impractical, prioritize critical servers, externally facing web applications, and cloud environments. Deploying Sysmon everywhere is sometimes not feasible due to very extensive and noisy logging. Prioritization is important here. 
  • Centralized log aggregation: Forward all logs to a write-once, centralized location, as sophisticated actors routinely clear local event logs, permanently destroying evidence left on compromised hosts 

More broadly, visibility needs to extend across identity systems, endpoints, network infrastructure, and cloud environments. 

Endpoint telemetry alone is insufficient. State-sponsored actors operating through legitimate tools will generate process events that are difficult to distinguish from normal administrative activity, and network-layer visibility provides an independent detection plane that host-based logging cannot replace. 

  • NetFlow analysis: Connection metadata without payload content is sufficient to identify unusual communication patterns, including beaconing behavior characteristic of C2 channels and lateral movement between systems that have no operational reason to communicate. 
  • DNS logging: Many C2 frameworks rely on DNS for command delivery and exfiltration. A host suddenly querying domains it has never previously resolved, or generating abnormal DNS query volumes, warrantsinvestigation. 
  • Encrypted traffic analysis: Machine learning models can identify C2 communication patterns in TLS sessions without breaking encryption, based on session timing, packet size distributions, and connection frequency. These capabilities do not require deep packet inspection and remain viable where privacy or compliance constraints limit payload visibility. 

Behavioral baselines 

CISA’s joint advisory on living-off-the-land techniques recommends maintaining continuous baselines across network traffic, user behavior, administrative tool usage, and application activity. The emphasis on “continuously” is not incidental. A baseline established once and left unattended can generate more problems than it resolves, creating false confidence that normal has been adequately defined, when in reality theorganization has moved on. Baselines need to reflect seasonal patterns, organizational changes, infrastructure updates, and role transitions. When an administrator changes teams, their access patterns shift. When a new application is deployed, new NetFlow patterns emerge. If the baseline fails to keep pace, genuine threats blend into an outdated picture of normal, and anomaly detection becomes a source of noise rather than signal.

Statistical anomaly detection can surface the low-and-slow deviations characteristic of state-sponsored lateral movement, but tuning is an ongoing commitment, and false positive management carries a real operational cost that should not be underestimated. 

State-sponsored actors do not typically maintain access through malware alone. Once inside, they move through identity infrastructure. Privileged access management deserves explicit treatment: administrative accounts should operate on a tiered model that prevents domain administrator credentials from being exposed on workstations, and service accounts should be scoped to the minimum access their function requires. Detection logic needs to account for credential abuse patterns that do not involve any malicious tooling. Pass-the-hash and pass-the-ticket attacks use legitimate authentication protocols and will not trigger antivirus. Kerberoasting, where an attacker requests service tickets for offline cracking, is visible in Kerberos event logs but only if those logs are collected and someone is looking. Anomalous authentication patterns, such as accounts authenticating at unusual hours, from unusual sources, or against systems they have never previously accessed, are among the more reliable behavioral signals available, provided the baseline exists to contextualize them. 

Operational security (OPSEC) 

If a state-sponsored breach is confirmed, the response needs to assume the adversary can see internal communications. If they have domain admin access, they can likely read email. If they have compromised a collaboration platform, they may be able to see the incident response channel. Here are some of the common aspects that should be considered:  

  • Out-of-band communications: Use encrypted channels on separate, unconnected devices to ensure investigative communications remain outside the compromised infrastructure. 
  • Compartmentalization: Limit knowledge of the investigation to essential personnel only, as each additional person aware of the response is a potential vector for the adversary to detect the investigation. 
  • Pre-established authority contacts: Maintain established relationships with national authorities, CERTs, and intelligence agencies before a crisis occurs, rather than identifying the right contacts during an active incident. 

Organizations should also have a pre-established relationship with national authorities, including the relevant contacts at national CERTs or intelligence agencies, rather than trying to find the right person during a crisis. 

OT and Industrial Control System (ICS) readiness 

For organizations with OT environments, the threat model extends beyond what most IT-centric IR plans address. 

The IT-OT boundary that appears on network diagrams is a logical construct, and state-sponsored actors treat it as a lateral movement path rather than a barrier. Volt Typhoon demonstrated this in concrete terms by moving from compromised IT infrastructure toward OT-adjacent systems, including those controlling water treatment plants and electrical substations. Through 2025, the group progressed from IT reconnaissance to directly interacting with OT network-connected devices and extracting sensor and operational data, representing a transition from passive espionage to what amounts to a sabotage-ready foothold, maintained quietly and positioned for activation when circumstances require it. Important aspects are:  

  • Availability as a safety constraint: OT systems often cannot be taken offline for forensic imaging, as production shutdowns in energy, water, or manufacturing carry significant safety and economic consequences.Investigations must work around live systems. 
  • Patching constraints: Many OT systems run legacy software that cannot be updated without vendor involvement, making virtual patching through IDS/IPS rules the only viable near-term remediation option. 
  • Insufficient software-defined segmentation: IT/OT boundaries relying solely on software-defined controls are inadequate, as a compromised account with sufficient privileges can reconfigure them. 
  • Hardware-enforced unidirectional gateways: Data diodes provide a physical, deterministic guarantee of network separation that cannot be overridden by a compromised account or software misconfiguration. 
  • Regulatory alignment: Both CISA and the UK’s NCSC recommend engineering-based, deterministic protections for OT boundaries as the baseline standard. 

Supply chain readiness 

Vendors, software dependencies, and network infrastructure are all extensions of the trust boundary, and preparing for supply chain compromise means understanding those dependencies and having response procedures ready before one of them is exploited. Some critical measures are as follows: 

  • Software Bill of Materials (SBOM): Maintain an SBOM for all applications and monitor it against vulnerability databases using automated tooling, connected directly to infrastructure. 
  • Vendor access inventory: Map which systems each third party can access, through what mechanisms, and at what privilege level. 
  • Contractual incident notification: Enforce 24-hour disclosure clauses in vendor contracts to ensure timely notification of compromise, preventing containment windows from closing before the organization is aware. 
  • Pre-authorized IR procedures: Define in advance what gets revoked, what gets isolated, and who makes the call for each vendor integration, eliminating delays while an adversary continues to operate. 
  • Firmware inventory: Maintain a firmware inventory with patch status for every network device, including firewalls, routers, switches, and VPN concentrators. 
  • Legacy and end-of-life (EOL) devices: Apply compensating controls such as network isolation, enhanced monitoring, and virtual patching to devices that can no longer receive patches, as they represent supply chain risk sitting inside the perimeter. 

Insider threat readiness 

In the state-sponsored context, the insider threat is not about a disgruntled employee stealing files. It is a structured intelligence operation that uses the hiring process itself as an attack vector, and preparation requires a cross-functional program spanning security, HR, legal, and finance because the indicators span all four domains. 

For planted insiders, the DPRK IT worker scheme being the most documented example, hiring verification needs to go beyond standard background checks. This includes live, multi-stage video interviews with liveness verification that current deepfake technology cannot reliably defeat (for now), digital footprint validation across independent data sources, detection of VoIP phone numbers and shared credentials across applications, and cross-referencing candidate information for the kinds of inconsistencies a fabricated identity cannot fully conceal. 

For all insider categories, behavioral baselines and data loss prevention policies should be in place before an incident occurs. Legal pre-authorization for employee monitoring is also important to establish ahead of time. Trying to build that legal framework during an active investigation will either delay the response or create legal exposure. 

Why your IR plan needs revisiting 

If your current IR plan covers malware and ransomware but typically it does not address supply chain compromise, insider threats, or living-off-the-land techniques. Most IR plans simply reflect a threat landscape that has already shifted. These gaps should be addressed through distinct playbooks, each with its own containment decision trees, evidence collection procedures, legal coordination requirements, and recovery verification steps. Each playbook should be tested through tabletop exercises built around realistic scenarios. 

One aspect of state-sponsored incident response sets it apart from criminal incident response is that the adversary may be observing the response in real time, will likely attempt to regain access after eviction, and the diplomatic, legal, and intelligence dimensions of the incident extend well beyond the security operations center. 

The containment decision in a state-sponsored incident is rarely straightforward. Treating it as a binary choice between immediate isolation and inaction understates the complexity involved. In a criminal incident, early containment is almost always the correct approach. In a state-sponsored incident, premature containment can eliminate the opportunity to understand the full scope of the adversary’s access, forfeit the ability to collect intelligence on their infrastructure, and signal to the adversary that they have been detected. That signal may trigger accelerated action on their objectives before defenses are fully in place. 

The deliberate choice to monitor silently while the adversary operates introduces its own legal, ethical, and operational risks. That decision should never be made unilaterally by the SOC. It requires input from legal counsel and senior leadership, and in many cases a conversation with national authorities before it is exercised. 

The incident response plan should define in advance who holds decision authority over containment timing, what criteria govern the transition from silent monitoring to active containment, and what evidence collection must be completed before containment begins. Tabletop exercises that do not incorporate this decision point are not adequately preparing teams for the reality of state-sponsored incident response. 

Post-incident 

After containment and recovery, the work is not finished. The intelligence collected during the incident has value beyond the organization that was targeted, and sharing it through ISACs and government channels contributes to a broader defensive picture that benefits the entire sector. Internally, the after-action review should map findings to MITRE ATT&CK, not as a compliance exercise but as a structured way to identify where detection failed, where response was too slow, and where controls need to be strengthened. That review should feed directly into updated detection logic, revised access controls, and adjusted monitoring priorities. 

Threat hunting should not stop when the incident is closed. A state-sponsored actor that has been evicted will often attempt to regain access using different infrastructure or modified techniques, and sustained hunting focused on the specific actor’s TTPs is the most reliable way to catch that early. Tabletop exercises should also be updated to reflect what was learned, so the next time a similar scenario plays out, the team is not relearning the same lessons under pressure. 

None of this is new guidance, but in the context of state-sponsored threats, where the adversary is persistent, well-resourced, and likely to return, these activities stop being procedural housekeeping and become direct preparation for the next intrusion. 

Where to start when you have low budget, minimal staff, and competing priorities 

Everything covered above assumes an organization can invest in logging, baselines, segmentation, supply chain controls, and dedicated IR planning in parallel. In reality, most security teams are operating under hiring freezes, flat budgets, and competing priorities, and the guidance to “do all of this” is not actionable without a sense of sequencing. The following is a pragmatic order of operations for teams that need to make meaningful progress without a step-change in resourcing. 

Start with visibility, because you cannot defend what you cannot see. Before buying new tooling, turn on what you already own. Enabling Windows command-line logging (Event ID 4688), PowerShell script block logging (Event ID 4104), and centralized log forwarding costs nothing in licensing and addresses the single largest gap most organizations have. If logs are not being collected and retained centrally, no amount of downstream investment will compensate. 

After this, prioritize identity over endpoints. State-sponsored actors move through credentials, not malware that can be easily fingerprinted, blocked, and made public through sandboxes. Enforcing multi-factor authentication (MFA) on all administrative accounts, implementing tiered admin models, and reviewing service account privileges typically delivers more risk reduction per hour invested than any endpoint initiative. These are configuration changes, not procurement cycles. 

Next, focus monitoring where the adversary has to go. If Sysmon everywhere is not feasible, then deploy it on domain controllers, identity infrastructure, externally facing systems, and critical servers. An adversary pursuing meaningful objectives will eventually touch these systems, and concentrated visibility on them is more valuable than thin visibility everywhere. 

The underlying principle is that state-sponsored readiness is not a single large investment. It is a sequence of smaller decisions where the early ones disproportionately determine whether the later ones are ever useful. Visibility and identity come first. Everything else builds on them.

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The Evolution of Kaspersky SIEM | Kaspersky official blog

To put it simply, the classic logic of a SIEM system works as follows: if event A occurs, followed by event B, this may be a sign of an attack, and an information security specialist should be notified. But in today’s environment, this simple scenario is increasingly failing. Just recently, our experts analyzed a high-profile incident: attackers compromised the update infrastructure of the popular Notepad++ software, and distributed malware via the update mechanism. It’s simply impossible to have rules in place in advance that are specifically designed to counter such scenarios.

The attacks themselves have become more sophisticated: attackers use legitimate tools, they attack through the supply chain by compromising software outside the corporate perimeter, stretch out their scenarios over time, and disguise their actions as normal activity. In other words, they do not “break into” the infrastructure; more often than not, they log in and use legitimate software. As a result, the classic fixed rules of the past either fail to trigger, or generate too many false alerts. This is what prompted the shift toward more flexible correlation scenarios.

Dynamically updated SIEM content

Correlation content today isn’t a static set of rules, but a process: it’s constantly evolving and adapting to current threats. In 2025 alone, we released 55 rule-package updates for different versions and languages of our Kaspersky SIEM system. In just one year, we added 10 new rule packs, as well as 250 detection rules and numerous improvements to existing content. This year, we’ve already added 43 new rules and refined another 63. In total, this amounts to over 850 rules covering a significant portion of the MITRE ATT&CK framework.

Kaspersky SIEM rules are written based on insights from our experts who analyze real-world, recent attacks: we primarily draw on the findings of our managed detection and response (MDR) service and our threat research. As a result, our rules cover scenarios — from reconnaissance to privilege escalation — that involve the latest approaches used by attackers. For example, we detect the use of new attack techniques such as ToolShell.

In addition to scheduled updates, the team regularly releases so-called emergency content — rule sets for rapid response to new and unexpected attack techniques. In February, for example, detection rules were released for authentication bypass in Fortinet products via the SSO mechanism: attackers used specially crafted SAML requests to gain access to systems without credentials.

From events to attack chains

Moreover, modern SIEM rules no longer describe individual events, but rather sequences of actions. Scenarios are built around the stages of an attack: from initial access, to privilege escalation and persistence. Kaspersky SIEM’s effectiveness is enhanced through integration with Kaspersky EDR and dedicated rule sets for Active Directory, which implement dozens of attack detection scenarios at various stages. This approach allows us to see not just individual signals, but the full picture.

Integration and internal visibility

Another way to improve the effectiveness of an SIEM system is to expand data sources. A classic SIEM aggregates events from different levels of the infrastructure: from logs to telemetry from endpoints and internal systems. In addition to this, our SIEM system includes specialized rule sets for our other solutions (Kaspersky Security Center, Kaspersky Security for Mail Groups, K Anti-Targeted Attack platform), which allow monitoring of administrator actions, authentication, and service status. As a result, the system becomes a tool not only for detecting attacks, but also for monitoring internal activity.

 

Overall, SIEM is no longer just a set of rules, but has evolved into a continuously updated detection system. Its effectiveness is determined not by the number of detections, but by their relevance, coherence, and how accurately they reflect the actual actions of attackers. Stay up to date regarding our Kaspersky Unified Monitoring and Analysis Platform (SIEM) on its official product page.

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Unplug your way to better code

Unplug your way to better code

Welcome to this week’s edition of the Threat Source newsletter.

Hey, you. Yeah, you! The person endlessly scrolling or typing away at their computer. Did you touch grass today? It’s just an expression, but if nature’s your thing, that works just fine.

What I do mean is that due to the nature of the field, cybersecurity is incredibly intangible. You can’t reach out and touch your logs, or the packets traversing your network, or the concept of DNS exfiltration… and if you tried, you’d just feel the smooth surface of your computer screen. (What a boring texture.) Spending all our time in the abstract can create some serious mental fatigue.

My point is that there’s something powerful to be said about engaging with the physical world. When we engage in a tactile hobby, we give our brains a hard reset. By moving from the abstract to the physical, our brains get the time and space to process the complex problems we’ve been staring at, often leading to the “aha!” moment that never comes when you’re trying to force it.

The other week, I was working in the Talos office with the Creative team. It was a quiet afternoon, people’s energy sapped by stomachs full of Mediterranean food. That was swiftly interrupted (in the best way) when Joe Marshall came over into our work area with his miniature painting kit, broke it open, and started teaching us how to drybrush 3D-printed figurines. Everyone immediately came alive. While I didn’t partake (I know, “Do as I say, not as I do”), it reminded me of how revitalized I feel when I get outside for a walk during lunch or spend 10 minutes knitting in silence between meetings. There’s nothing to focus on but the feel of the yarn between your fingers, the clacking of the needles, and the repetitive motions that result in a physical object you can wear and fish for compliments about.

Speaking of, do you think the vest I knit is cool? All compliments can be sent to me on LinkedIn, and I refuse to accept any negative comments. (Critiques are fine.)

Unplug your way to better code

Ahem… anyway. Go on a walk without your earbuds, listen to the wind through the leaves, ask a stranger to pet their dog, watch a pigeon bop its head around, and reach out to touch a cool-looking rock or the lichen on a tree. I hear you saying, “That’s some tree-hugging bullshit,” and counter you with, “Just humor me, okay? What’s the worst that could happen?”

If you’re more of an inside person, the goal might be to find a physical anchor for your technical interest. Maybe it’s building a mechanical keyboard from scratch — feeling the weight of the switches and hearing the click of the keycaps. Maybe it’s a complicated LEGO set. Even something as simple as making espresso or organizing your bookshelf can provide that sensory feedback your brain is craving.

If you’re not currently facing a life-altering deadline, take 10 minutes and try it now. The rest of the newsletter isn’t going anywhere, I promise.

When you pay attention to the noises you hear, the colors you see, and the textures under your fingertips, you might come back to your laptop refreshed, focused, and ready to solve the next problem.

The one big thing 

Cisco Talos has recently expanded our threat intelligence capabilities to track phone numbers as critical indicators of compromise (IOCs) in scam emails. Our latest research reveals that attackers heavily favor API-driven VoIP numbers to execute high-volume, cost-effective Telephone-Oriented Attack Delivery (TOAD) campaigns. To evade detection, these threat actors rotate through sequential blocks of numbers, use strategic cool-down periods, and recycle the exact same digits across completely unrelated lures and impersonated brands. 

Why do I care? 

Tracking ephemeral sender email addresses is a losing game, but phone numbers are the true operational anchors for these organized scam call centers. Because attackers reuse these numbers across multiple document types and brand impersonations, defenders who cluster this telephony infrastructure can expose the broader network of malicious activity. Understanding these reuse patterns gives defenders a much-needed edge in mapping out and dismantling these operations before users are manipulated into handing over sensitive data. 

So now what? 

Security teams should shift their focus toward clustering scam lures based on shared phone numbers and prioritize real-time reputation monitoring to flag high-risk infrastructure. Deploying an AI-powered email security solution like Cisco Secure Email Threat Defense can also help evaluate different portions of incoming emails to catch these targeted threats. A full list of indicators of compromise (IOCs) associated with these campaigns can be found in the blog.

Top security headlines of the week 

DigiCert revokes certificates after support portal hack 
The attack, the company said in a detailed report, occurred on April 2, when a threat actor targeted DigiCert’s support team with a malicious payload delivered via a customer chat channel, disguised as a screenshot. (SecurityWeek

Ubuntu services hit by outages after DDoS attack 
The DDoS-for-hire service in this case claims to power attacks in excess of 3.5 Tbps, which is about half of the bandwidth of a cyberattack that Cloudflare last year called the “largest DDoS attack ever recorded.” (TechCrunch

Canvas maker Instructure reveals data breach 
Instructure said the actors accessed “certain identifying information of users” at affected institutions, including names, email addresses, student ID numbers, and user communications. (Tech Radar

Exploitation of “Copy Fail” Linux vulnerability begins 
Threat actors are exploiting a recently disclosed Linux kernel vulnerability leading to root shell access, the US cybersecurity agency CISA warns. Dubbed Copy Fail, the security defect impacts all Linux distributions since 2017. (SecurityWeek

Student hacked Taiwan high-speed rail to trigger emergency brakes 
According to local reports, the student halted four trains for 48 minutes by using software-defined radio (SDR) communications and handheld radios to transmit a high-priority “General Alarm” signal, triggering emergency braking procedures. (BleepingComputer

Can’t get enough Talos? 

Tales from the Frontlines 
In this briefing, we’ll share behind-the-scenes insights from the most critical and high-impact incidents we responded to in the last quarter. This isn’t a report walkthrough; it’s a look at what really happened, how we handled it, and what it means for your organization. 

UAT-8302 and its box full of malware 
Cisco Talos is disclosing UAT-8302, a sophisticated, China-nexus APT group targeting government entities in South America since at least late 2024 and government agencies in southeastern Europe in 2025. 

CloudZ RAT potentially steals OTP messages using Pheno plugin 
Cisco Talos discovered an intrusion, active since at least January 2026, where an unknown attacker implanted a CloudZ remote access tool (RAT) and a previously undocumented plugin called “Pheno.” 

The trust paradox: How attackers weaponize legitimate SaaS platforms 
In this episode of Talos Takes, Amy Ciminnisi sits down with researcher Diana Brown to discuss the rise of “platform-as-a-proxy” (PAP) attacks. 

Upcoming events where you can find Talos 

Most prevalent malware files from Talos telemetry over the past week 

SHA256: 9f1f11a708d393e0a4109ae189bc64f1f3e312653dcf317a2bd406f18ffcc507  
MD5: 2915b3f8b703eb744fc54c81f4a9c67f  
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=9f1f11a708d393e0a4109ae189bc64f1f3e312653dcf317a2bd406f18ffcc507  
Example Filename: VID001.exe  
Detection Name: Win.Worm.Coinminer::1201** 

SHA256: 96fa6a7714670823c83099ea01d24d6d3ae8fef027f01a4ddac14f123b1c9974  
MD5: aac3165ece2959f39ff98334618d10d9  
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=96fa6a7714670823c83099ea01d24d6d3ae8fef027f01a4ddac14f123b1c9974  
Example Filename: d4aa3e7010220ad1b458fac17039c274_63_Exe.exe  
Detection Name: W32.Injector:Gen.21ie.1201 

SHA256: 90b1456cdbe6bc2779ea0b4736ed9a998a71ae37390331b6ba87e389a49d3d59  
MD5: c2efb2dcacba6d3ccc175b6ce1b7ed0a  
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=90b1456cdbe6bc2779ea0b4736ed9a998a71ae37390331b6ba87e389a49d3d59  
Example Filename: APQ9305.dll  
Detection Name: Auto.90B145.282358.in02 

SHA256: e60ab99da105ee27ee09ea64ed8eb46d8edc92ee37f039dbc3e2bb9f587a33ba  
MD5: dbd8dbecaa80795c135137d69921fdba  
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=e60ab99da105ee27ee09ea64ed8eb46d8edc92ee37f039dbc3e2bb9f587a33ba  
Example Filename: u112417.dat  
Detection Name: W32.Variant:MalwareXgenMisc.29d4.1201 

SHA256: a31f222fc283227f5e7988d1ad9c0aecd66d58bb7b4d8518ae23e110308dbf91 
MD5: 7bdbd180c081fa63ca94f9c22c457376  
Talos Rep: https://talosintelligence.com/talos_file_reputation?s=a31f222fc283227f5e7988d1ad9c0aecd66d58bb7b4d8518ae23e110308dbf91  
Example Filename: d4aa3e7010220ad1b458fac17039c274_62_Exe.exe  
Detection Name: Win.Dropper.Miner::95.sbx.tg** 

Cisco Talos Blog – ​Read More

Nearly half of the world’s passwords can be cracked in under a minute | Kaspersky official blog

Every year, hundreds of millions of real user passwords leak onto the dark web. We analyzed 231 million unique passwords from dark-web leaks between 2023 and 2026, and the conclusions are bleak: the vast majority are extremely weak. To crack 60% of these passwords, a hacker needs only an hour and a few dollars in their pocket. Furthermore, password cracking is accelerating by the year; in our similar 2024 study, the percentage of vulnerable passwords was lower.

Today we’re looking at just how reliable the average password is (spoiler: not really), and how you can secure your data and accounts using more robust methods. At the same time, we’ll highlight the patterns most commonly found in actual user passwords.

How passwords are cracked

In our previous study, we detailed the methods for storing and cracking passwords, but here’s a quick refresher on the essentials.

These days, passwords are almost never stored in plain text. For instance, if you create an account with the password “Password123!”, the server won’t store it as-is. Instead, the password is hashed using specific algorithms, turning it into a fixed-length string of letters and numbers (a hash) which is what actually stays on the server. For example, here’s what the MD5 hash for “Password123!” looks like:

2c103f2c4ed1e59c0b4e2e01821770fa.

Every time the user enters their password, it’s converted into a hash and compared against the one stored on the server; if the hashes match, the password is correct. If an attacker gets their hands on this hash, they have to decrypt it to recover the original password — this is what’s known as “password cracking”. This is typically done using owned or rented GPUs, and several methods can be employed for the crack:

  • Exhaustive enumeration (brute force). The computer tries every possible combination of characters, calculating the hash for each one. This method is the easiest way to crack short passwords, or those consisting of a single character set (such as digits only).
  • Rainbow tables. A total nightmare for anyone with a simple password, this is essentially a “phone book” for passwords whose hashes have already been cracked via brute force or smart algorithms. All an attacker has to do is find a matching hash and see which password corresponds to it.
  • Smart cracking. These algorithms are trained on databases of leaked passwords. They understand the frequency of different character combinations, and run their checks from the most likely to the least popular sequences. They account for dictionary words, character substitutions (a → @ or s → $), and consider common password structures like “dictionary word + number + special character”, while checking hashes against rainbow tables. Combining these methods significantly accelerates the cracking process.

Beyond that, attackers can also intercept passwords in plain text. There are numerous ways to do this, ranging from phishing (where a victim is lured to a fake web page and enters their password voluntarily) and keyloggers that capture keystrokes, to stealers or Trojans that swipe documents, cookies, clipboard data, and more. Unfortunately, many users keep their passwords as plain text in notes, messaging apps, and documents, or save them in browsers where attackers can extract them in seconds.

Every year, we track around a hundred million plain-text password leaks. We use these databases to warn Kaspersky Password Manager users if their data has been compromised. To address the most frequent question we get on this: no, we don’t know our users’ passwords. We’ve explained in non-techie language exactly how we compare your passwords to leaked ones without actually knowing them — and why neither your passwords stored in Kaspersky Password Managernor even their hashes ever leave your device — in our overviews of our leak analysis technology and our password manager’s internal architecture. Give them a read; you’ll be surprised by just how elegant the design is.

60% of passwords are cracked in under an hour

We expanded the database from our previous study by an additional 38 million real passwords posted by attackers on dark-web forums and compared the results. Testing was conducted using a single RTX 5090 GPU for passwords hashed with the MD5 algorithm. The data for the analysis was obtained from our Digital Footprint Intelligence service. You can review the algorithm we used to assess password strength in our article on Securelist.

Unfortunately, passwords remain as weak as ever, while cracking them becomes faster and easier with every year. Today, 60% of passwords can be cracked in less than an hour; two years ago, that figure was 59%. But the truly frightening part is something else: nearly half of all passwords (48%) are cracked in less than a minute!

Cracking time Percentage of passwords crackable within this time in 2024 Percentage of passwords crackable within this time today
Less than a minute 45% 48%
Less than an hour 59% (+14%) 60% (+12%)
Less than 24 hours 67% (+8%) 68% (+8%)
Less than a month 73% (+6%) 74% (+6%)
Less than a year 77% (+4%) 77% (+3%)
More than a year 23% 23%

Password cracking time: two years ago and today

Attackers owe this boost in speed to graphics processors, which grow more powerful every year. While an RTX 4090 in 2024 could brute-force MD5 hashes at a rate of 164 gigahashes (billion hashes) per second, the new RTX 5090 has increased that speed by 34% — reaching 220 gigahashes per second.

And although a high-end video card like that currently retails for several thousand dollars, the price tag isn’t much of a barrier: there are plenty of cheap cloud services available for renting GPU computing power. Depending on the configuration and the model, rental costs range from a few cents to a few dollars per hour. As we’ve seen, one hour is all an attacker needs to crack three out of every five passwords they’ve found in a leak. Plus, depending on the scale of the task, they can always rent ten or even a hundred GPUs instead of just one…

It’s worth noting that cracking every password in a dataset doesn’t take much longer than cracking a single one. During each iteration, once the attacker calculates a hash for a specific character combination, they check if that same hash exists anywhere in the dataset — and the larger the dataset, the easier it is to find a match. If a match is found, the corresponding password is flagged as “cracked”, and the algorithm moves along to the next one.

Which passwords are vulnerable?

The strength of any password depends on its length, content variety, and the randomness of that content. Passwords created by humans turn out to be the least resilient — unfortunately, humans are quite predictable. We use dictionary words and character combinations that smart algorithms have long since mastered, we avoid long random strings, and patterns can be found even in keystrokes we believe are random. Interestingly enough, passwords generated by AI still carry the fingerprints of a human approach; we covered this in a separate post on how to create a strong yet memorable password.

Password length is the primary factor affecting cracking time. As you can see from the table below, it takes less than 24 hours to crack almost any eight-character password.

Percentage of varying password lengths crackable within a given timeframe

Percentage of varying password lengths crackable within a given timeframe

But the predictability of your password is just as important. Think you’re boosting security by adding a number or a special character to a memorable word? You are, but only slightly. The patterns people use to create passwords are easily predictable and, at times, pretty amusing — though this is no laughing matter.

What we learned about password patterns

Analysis of over 200 million passwords revealed characteristic patterns that allow smart algorithms to crack user passwords with ease.

Pick a number

More than half of all passwords (53%) end with one or more digits, while nearly one in six (17%) starts with a number. Every eighth password (12%) contains sequences that look a lot like years — ranging from 1950 to 2030 — and one in ten (10%) specifically falls between 1990 and 2026. This most likely happens because folks add their birth year (or that of someone close), some other significant year, or the year they created the password or account. Fun fact: based on the distribution of these dates, it suggests that the most active internet users were born between 2000 and 2012.

However, among all numeric combinations, the most popular turned out to be… you guessed it: “1234”. Overall, patterns involving sequential keyboard presses (“qwerty, ,”ytrewq”, and the like) appear in 3% of passwords.

Special characters aren’t a silver bullet

Most password policies in recent years require at least one special character. The absolute winner in this category is the @ symbol: it appears in one out of every 10 passwords. The period (.) comes in second, followed by the exclamation point (!) in third.

Love rules the world… and Skibidi Toilet does too

Emotionally charged words often form the foundation of a password, and despite everything, positive words are more common. Frequently occurring examples include “love”, “angel”, “team”, “mate”, “life”, and “star”. That said, negativity pops up too — mostly in the form of common English swear words.

Interestingly, viral memes are reflected in passwords as well. Between 2023 and 2026, the use of the word Skibidi in passwords skyrocketed 36-fold! Naturally (see the link if it doesn’t seem natural), “toilet” saw a boost too, though to a lesser extent.

Users tend to keep their passwords unchanged for years

More than half of the passwords (54%) we identified in recent leaks have surfaced before. Part of this can be explained by the same data migrating from one dataset to another. However, there’s a much more troubling reason too: many users simply haven’t changed their passwords in years.

Analyzing the dates found within passwords shows that combinations containing the years from 2020 through 2024 remain popular. It seems people add the current year to their password when they create it — and then forget about it for several years. This actually allows us to calculate the average lifespan of a password: about three to five years.

This is a dangerous trend. For one, smart algorithms can crack much more complex passwords over that kind of timeframe. Secondly, the longer your password remains unchanged, the higher the probability it will leak — whether through a breach, malware infection, or a phishing attack.

The situation gets even worse when the same password is used across multiple accounts. In this case, attackers don’t even need to crack anything; they just need to find your password in a single leak and plug it into other sites.

How to protect your passwords and accounts

If you’ve realized while reading this post that your own passwords are among those easily crackable — don’t panic. We’ve put together a list of simple but essential tips for you.

Use a password manager

The weakest passwords are the ones people come up with themselves. Creating and memorizing hundreds of sequences of 16–20 random characters (since every site requires a unique, long password) is a daunting, unrealistic task.

That’s why you should delegate password generation and storage to our password manager. It doesn’t just create and store complex, randomized passwords in an encrypted format; it also syncs them across all your devices. To decrypt your vault, you only need to remember one main password that no one knows but you — our guide on mnemonic passwords can help you with that.

Don’t store passwords as plain text

Whatever you do, never write down passwords in files, messages, or documents. They lack the robust encryption provided by a password manager. Furthermore, these kinds of notes fall into the hands of attackers instantly if you happen to pick up a Trojan or an infostealer.

Don’t store passwords in your browser

Many users save their passwords in their browsers — especially since they conveniently offer to do it automatically. Unfortunately, research shows that malware has evolved to extract these passwords from all popular browsers almost instantly. Kaspersky Password Manager can help you import saved passwords from your favorite browser — just follow our simple, three-step guide. Most importantly, don’t forget to clear the browser’s password storage once the import is complete.

Switch to passkeys

Wherever possible, use passkeys — a cryptographic replacement for passwords. In this setup, the service stores a public key, while the private key remains on your device and is never transmitted. During login, the device simply signs a one-time request. Additionally, passkeys are tied to a specific domain, meaning phishing attacks using spoofed addresses won’t work. Kaspersky Password Manager allows you to store both passwords and passkeys, solving the problem of syncing them across different ecosystems, including Windows, Android, macOS, and iOS.

Set up two-factor authentication

Enable two-factor authentication wherever possible. Even if your password is compromised, a properly configured 2FA setup makes it extremely difficult for the attacker to access your account. For maximum security, skip the one-time codes sent via SMS and use authenticator apps instead — and yes, Kaspersky Password Manager comes in handy here, too.

Practice good digital hygiene

Remember, storing your passwords correctly is only half the battle. It’s crucial to follow the rules of digital hygiene: avoid downloading unverified files, pirated software, cheats, or cracks, and don’t click on random links. The number of infostealer attacks has been steadily rising in recent years, which means you need a robust security solution for full protection. We recommend Kaspersky Premium — it protects all your devices from Trojans, phishing, and other threats. Besides, the subscription includes our password manager.

For those serious about account security, check out our collection of posts on passwords, passkeys, and two-factor authentication:

Kaspersky official blog – ​Read More

How VoidStealer bypasses Chrome’s protections to hijack sessions and steal data | Kaspersky official blog

Malicious actors have developed a new way to steal data stored by Chrome for Windows. Researchers discovered the technique while analyzing a fresh build of an infostealer known as VoidStealer. The new method allows the malware to bypass Chrome’s Application-Bound (App-Bound) Encryption (ABE), a mechanism intended to protect session cookies and other valuable information stored in the browser.

Google hoped this mechanism would secure the master key Chrome uses to encrypt all sensitive data. Unfortunately, this isn’t the first time malware authors have found a workaround for this defense — leaving secrets stored in Chrome vulnerable once again.

How App-Bound Encryption works in Chrome

Google introduced App-Bound Encryption in July 2024 with the release of Chrome version 127. The company’s announcement mentioned infostealers snatching cookies from Chrome users on Windows as the primary problem ABE was intended to solve. We’ve already covered in detail what these files are and the consequences of their theft, so we’ll only briefly recap the main facts here.

Cookies are small files that the browser saves to the user’s device at a website’s request to remember various site settings. Of particular value to attackers are session cookies, which are used for automatic authentication on websites. It’s thanks to these files that we don’t have to enter a username and password every time we revisit a site.

But this convenience carries a risk: stealing these files allows an attacker to use an already-authenticated session without entering a username or password. This allows them to impersonate the user, which can lead to account hijacking, theft of personal or financial data, and other adverse consequences.

Infostealer Trojans are particularly dangerous for Chrome users on Windows. This is because, on this OS, Chrome previously relied solely on the standard built-in Data Protection API (DPAPI). With this system encryption mechanism, applications don’t need to create and store encryption keys to protect data.

The limitation of DPAPI is that it doesn’t protect data from malware that’s already successfully compromised the system and is capable of executing code on behalf of the logged-in user. This is exactly what stealers exploit: since they typically run with the user’s privileges, they can simply request DPAPI to decrypt the browser’s protected data.

The ABE mechanism was designed to solve that specific problem. The core idea is right in the name: App-Bound Encryption means the encryption is tied to a specific application. To achieve this, a separate service running with system privileges is responsible for protecting the key used to encrypt Chrome’s data. It verifies which application is requesting access to the key, and denies the request if it doesn’t originate from Chrome.

How Chrome's App-Bound Encryption (ABE) works

Chrome’s App-Bound Encryption (ABE) was designed so that only Chrome itself could retrieve the master key needed to decrypt the browser’s stored data. Source

As a result, the architects of this feature assumed that to access ABE-protected browser data, an infostealer would either need to escalate its privileges to system-level, or inject malicious code directly into Chrome. In theory, this should have made attacking Chrome significantly harder and reduced the effectiveness of mass-market infostealers. As you might have guessed, things didn’t go quite that smoothly in practice.

Previous successful bypasses of Chrome’s ABE

Just a couple of months after Google announced the implementation of App-Bound Encryption in Chrome, many infostealer developers claimed they’d already bypassed the protection. Among them were the creators of Meduza Stealer, Whitesnake, Lumma Stealer, and Lumar (also known as PovertyStealer).

Announcement of a new version of the Lumma stealer

Lumma stealer developers announce a bypass for Chrome’s App-Bound Encryption in a new version of the malware

Of course, you shouldn’t take malware developers at their word, but legitimate security researchers were able to confirm at least some of the claims. Bypasses for Google Chrome’s new data protection feature did become available almost immediately after its release.

A month later, in October 2024, tech enthusiast Alex Hagenah published a tool on GitHub called Chrome-App-Bound-Encryption-Decryption to bypass Google’s new security mechanism. Analysis of the tool’s code revealed that its author used roughly the same methods that attackers were already heavily exploiting.

What followed was a game of cat and mouse: security researchers and stealer developers came up with new tricks to circumvent App-Bound Encryption, while Google patched the newly discovered loopholes with varying degrees of success.

VoidStealer — a new data-nabbing menace

This brings us to recent events: in March 2026, news broke about a stealer named VoidStealer, which utilizes a brand-new and, by all accounts, highly effective method for bypassing ABE.

Announcement of a new VoidStealer version

VoidStealer developers advertising a new method for bypassing ABE. Source

The malware authors developed an attack technique that targets the brief moment when the master key sits in the browser’s memory in plaintext. This occurs because, at a certain point, the browser inevitably has to decrypt its data to actually use it — for instance, to automatically sign in to a website with the relevant session cookie or to access saved credentials.

To exploit this window of opportunity, the malware attaches itself to the Chrome process as a debugger — a tool that allows one to control a program’s execution, pause it, and inspect its memory. In legitimate scenarios, these tools are used by developers to find and fix bugs, analyze application behavior, and test performance.

The malware identifies the specific section of code where data decryption takes place. It then sets a breakpoint at that location; when the program’s execution reaches that point, the browser effectively freezes. This is how the malware catches the exact moment the master key is sitting in RAM in plaintext; it then reads the key directly from memory.

It’s worth noting that everything mentioned above also applies to other Chromium-based browsers that use ABE, including Microsoft Edge, Brave, Opera, Vivaldi, and others.

How to avoid falling victim to infostealers

The scale of VoidStealer’s reach could be significant, as its developers operate under the malware-as-a-service (MaaS) model. This means they rent out the ready-made tool to other attackers, so they don’t need to develop custom malware from scratch.

This situation demonstrates that relying solely on built-in security mechanisms isn’t enough. Unfortunately, stealer developers are coming up with new workarounds faster than browser and operating system developers can roll out patches.

Here’s what users can do about it:

  • Avoid installing programs from suspicious sources. This will minimize the chances of malware infiltrating your system.
  • Learn how ClickFix attacks Lately, stealers have frequently been distributed using this specific malicious tactic.
  • Keep your OS and software updated on all devices. Timely updates help patch many of the vulnerabilities that malware exploits.
  • Install a robust security solution on all your devices. It’ll block suspicious activity in real time and alert you to potential threats.

As an added precaution, avoid storing passwords and bank card info in Google Chrome or your Notes app, as these are the first places any self-respecting stealer looks. Instead, use a secure password manager.

Stealers are hunting for your data, finding ways to infiltrate both computers and smartphones alike. To protect yourself from theft, check out our other related posts:

Kaspersky official blog – ​Read More

How CISOs Reduce Cyber Risk with MITRE ATT&CK 

Nowadays CISOs face escalating threats that outpace traditional defenses. The strategy is evolving from compliance-driven checklists to a threat-informed approach. MITRE ATT&CK provides a globally accessible knowledge base of real-world adversary tactics, techniques, and procedures (TTPs), enabling organizations to understand, prioritize, and counter actual attacker behaviors rather than abstract controls. 
 
This shift helps align security efforts with business realities: minimizing downtime, protecting revenue streams, safeguarding customer trust, and potentially lowering cyber insurance premiums through demonstrated proactive risk management. 

Executive Summary 

  • Compliance-driven security measures control maturity, not adversary readiness. Threat-informed defense anchors risk management in real attack behaviors, which is where actual risk lives. 
  • MITRE ATT&CK provides the taxonomy, not the intelligence. The framework names and structures adversary techniques; organizations need curated, real-world threat data to make those techniques actionable. 
  • SOC workflow integration is non-negotiable. MITRE ATT&CK delivers risk reduction only when embedded into monitoring rules, triage processes, IR playbooks, and hunt methodologies. 
  • Speed of context determines security outcomes. Whether in triage or incident response, the time it takes to understand what a threat is doing directly determines how much damage it can cause. ANY.RUN’s Threat Intelligence Lookup and Sandbox compress that context-gathering from hours to seconds.
  • Threat hunting requires real attack patterns, not just technique categories. Generic ATT&CK-based hunt queries produce noise; high-fidelity feeds of current attacker behavior produce findings. 
  • Risk reduction is measurable. MTTD, MTTR, MTTC, hunt yield rate, and false positive ratios are the business-level metrics that translate MITRE ATT&CK investment into language boards and insurers understand. 

Two Lenses, One Risk: Compliance vs. Adversary-Centered Approach 

Traditional risk management often relies on vulnerability scanning, compliance audits (e.g., NIST, ISO), and static controls. It focuses on known weaknesses and regulatory requirements but frequently misses how attackers chain behaviors in live environments. 

MITRE ATT&CK is adversary-centric and behavior-focused. It maps real-world TTPs across tactics like Initial Access, Execution, Persistence, and Impact. This enables gap analysis, threat modeling, and measurable improvements in detection and response. 

Dimension  Traditional Risk Management  MITRE ATT&CK Approach 
Risk Basis  Regulatory requirements & audit findings  Real-world adversary techniques & behaviors 
Threat Model  Generic, category-level threats  Specific ATT&CK tactics, techniques, sub-techniques 
Detection Focus  Signature-based, perimeter controls  Behavioral analytics across the kill chain 
Measurement  Control maturity, audit pass/fail  Detection coverage mapped to ATT&CK matrix 
Response Approach  Incident → remediation → compliance update  Continuous detection, hunt, iterate 
Business Language  Risk scores, audit gaps  Mapped MITRE techniques tied to business impact 
Tooling  GRC platforms, scanners  SIEM + EDR + Sandbox + TI Feeds 

The most important takeaway from this comparison is not that compliance is worthless. It isn’t. Regulatory requirements create accountability, force documentation, and establish minimum hygiene floors that matter for smaller organizations with limited resources. The problem arises when compliance becomes the ceiling rather than the floor. 

Where Strategy Meets Reality: Making MITRE ATT&CK Operational 

MITRE ATT&CK is not a product. It does not detect threats. It does not alert your analysts, contain attackers, or generate threat intelligence. The organizations that extract real risk reduction from MITRE ATT&CK are those that connect the framework’s taxonomy directly to how their SOC actually operates: the tools analysts use, the data they see, the workflows they follow under pressure.

SOC Workflow  What MITRE Provides  What SOC Actually Needs  How ANY.RUN Bridges the Gap 
Monitoring  Identify techniques to watch  Alerts linked to ATT&CK IDs  TI Feeds: live IOC & technique feeds; Sandbox: real-time detonation signals 
Triage  Explain technique & impact  Fast analyst context on behavior  TI Lookup: instant technique context + related samples; Sandbox: behavioral report 
Incident Response  Provide structural framework  Full execution context to contain  Sandbox: full process tree, network, registry; TI Lookup: lateral movement history 
Threat Hunting  Suggest what to search for  Real attack patterns as hypotheses  TI Feeds: emerging technique clusters; TI Lookup: hunt pivot on IOCs & TTPs 

1. Eyes Wide Open: Enhancing Monitoring for Early Threat Detection 

MITRE ATT&CK is a powerful compass for monitoring strategy. It tells defenders which techniques adversaries use during specific phases of an attack. T1566 (Phishing) for initial access, T1055 (Process Injection) for defense evasion, T1021 (Remote Services) for lateral movement, etc. Security teams can use the framework to build detection hypotheses, design SIEM rules, and prioritize which telemetry sources to collect. 

What the SOC Actually Needs 

The value of monitoring emerges from early visibility to enable swift action, reducing dwell time and limiting blast radius. Analysts need alerts with sufficient fidelity and timeliness to intervene while the attack is still in progress. That requires not just knowing which techniques exist, but understanding the current threat landscape: which groups are active, which malware families are being deployed this week, and which detection signatures are already stale. 

Solution: Stay Current with Live Threat Feeds to Cut Detection Lag 

Threat Intelligence Feeds provide continuously updated, machine-readable threat intelligence stream of IOCs (indicators of compromise) with malware family tags derived from real detonations in ANY.RUN’s Interactive Sandbox. Security teams can pipe these feeds directly into their SIEM or EDR, ensuring that MITRE-mapped detection rules stay current with actual adversary activity. 

Business objective: Cut MTTD for novel threats. Increase the ratio of high-fidelity alerts to total alerts, lowering analyst alert fatigue and improving coverage of emerging attack vectors. 

Reduce breach impact, not just detect threats.
Fuel MITRE ATT&CK with real-time intelligence and full attack visibility.



Try ANY.RUN


2. Speed Matters: Accelerating Triage with Behavioral Context 

MITRE maps alerts to techniques, but analysts need rapid understanding of intent, impact, and validity to avoid alert fatigue. An alert tagged T1059.001 (PowerShell) tells an analyst that the technique involves command and scripting interpreter abuse. T1112 (Modify Registry) points to potential persistence or defense evasion. This context is valuable. But it is the starting point, not the destination. 

What the SOC Actually Needs 

Analysts dealing with hundreds of alerts per shift cannot afford multi-minute pivot chains to understand whether a flagged PowerShell execution is a legitimate IT automation script or the first stage of a ransomware deployment. They need behavior and impact context fast: What did this process actually do? Has this file hash or domain been seen in confirmed malicious activity?  

Solution: Reduce MTTD with Full Attack Visibility inside a Sandbox 

Threat Intelligence Lookup is a searchable threat data repository built on ANY.RUN’s analysis history. Analysts can query file hashes, IPs, domains, URLs, and process names and instantly surface related sandbox reports with MITRE ATT&CK mappings, malware family attributions, and associated threat actor context.  

During triage, analysts can answer the key questions before escalating: Is this a known threat? What does it do? Which ATT&CK techniques are involved? What is the likely impact?  

ANY.RUN Intelligence linking ATT&CK techniques to malware samples and behaviors

Interactive Sandbox complements TI Lookup for unknown samples. If an URL yields no TI Lookup match, analysts can submit it to the sandbox and receive a full behavioral report (process tree, network activity, file system changes, and ATT&CK technique tags) in minutes.  

Unlike automated sandboxes that process samples silently, ANY.RUN lets analysts interact with the execution — clicking through prompts, observing network connections, and watching process trees unfold — while the sandbox maps every observed behavior to MITRE ATT&CK techniques in real time.   

Attack techniques detected in ANY.RUN sandbox detonation

Business objective: Reduce mean triage time per alert. Decrease false positive escalations. Increase analyst capacity without headcount growth, enabling the SOC to handle greater alert volume at the same staffing level. 

3. Incident Response: From Labels to Action 

MITRE ATT&CK gives incident responders a structured model for understanding what an adversary may have done across the kill chain. It offers a common language and playbooks for containment, full visibility into attacker actions for precise, minimal-disruption response. This is genuinely valuable for architecting investigations and communicating findings to stakeholders. 

What the SOC Actually Needs 

During an active incident, responders need execution context. Which processes ran? In which order? What registry keys were modified? Which files were dropped and where? Which internal hosts did the malware beacon to? Without this granular execution responders end up remediating visible symptoms while the attacker maintains persistence through overlooked footholds. 

Turn MITRE ATT&CK into measurable risk reduction.
Use ANY.RUN to detect threats earlier and respond faster.



Start now


Solution: Compress Containment Time with Complete Execution Context 

Interactive Sandbox generates a complete execution timeline for any submitted sample: full process trees (parent/child relationships, command-line arguments), all network connections (DNS queries, HTTP/S requests, C2 communication patterns), file system changes (created, modified, deleted files), and registry modifications.  

Every action is timestamped and tagged with the corresponding MITRE ATT&CK technique. Responders don’t need to reconstruct what malware did from endpoint telemetry alone. They have a ground-truth behavioral record from a controlled detonation. 

Processes mapped to MITRE ATT&CK techniques in a sandbox detonation

TI Lookup accelerates the lateral movement investigation. If an incident involves a suspicious IP or domain used for C2, TI Lookup surfaces all previous ANY.RUN analyses involving that indicator. It helps reveal which malware families have used it, when, and in what context.  

Business objective: Reduce mean time to contain (MTTC) by giving responders complete execution context at the start of an investigation. Decrease re-infection rates by ensuring all persistence mechanisms are documented and remediated. Reduce incident response costs by compressing investigation timelines. 

4. Proactive Defense: Supercharging Threat Hunting with Real Patterns 

Threat hunting (proactively searching for adversary presence that evaded automated defenses) is where MITRE ATT&CK suggests hypotheses: if you are in a financial services organization, groups like FIN7 or Carbanak are relevant threats; their documented techniques (T1059, T1027, T1547) suggest where to look in your telemetry. This starting point is invaluable. 

What the SOC Actually Needs 

A successful hunt requires more than “look for PowerShell abuse”. It requires the specific parent-child process relationships, the exact command-line patterns, the particular registry keys, the network destinations that real-world attackers targeting your industry have actually used recently. Generic ATT&CK-based hunt queries produce excessive noise and burn hunter time on false leads. Real attack patterns are the fuel that makes hunts productive. 

Solution: Turn Hunt Hypotheses into High-Yield Findings with Real Attacker Patterns 

Threat Intelligence Lookup enables hunt pivoting at scale. A hunter who identifies a suspicious process name can query TI Lookup to find all samples that share that process, discover related IOCs, identify the malware family, and extract the precise command-line patterns that family uses. This turns a single hunt lead into a comprehensive behavioral profile needed to write high-confidence hunt queries. 

MITRE ATT&CK matrix in ANY.RUN’s TI Lookup

The combination of TI Feeds and TI Lookup transforms threat hunting from a creative exercise into an evidence-based discipline grounded in real adversary behavior. 

Business objective: Increase the yield rate of threat hunts (confirmed findings per hunt hour). Identify attacker dwell time earlier, reducing the average time an adversary operates undetected inside the network. Demonstrate proactive risk reduction to board and audit stakeholders. 

Conclusion: From Framework to Force Multiplier 

MITRE ATT&CK has fundamentally changed how the security industry thinks about risk: from abstract control gaps to concrete adversary behaviors. For CISOs, this shift represents an opportunity to speak a language that resonates equally in the boardroom and the SOC: the language of what attackers actually do, and how prepared your organization is to detect, contain, and recover. 

Make every SOC workflow count toward business protection.
Connect MITRE ATT&CK with live actionable threat data.



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But the framework’s potential is only realized when it is connected to operational reality. MITRE ATT&CK without actionable threat intelligence is a map without territory. The SOC workflows that matter (monitoring, triage, incident response, and threat hunting) all require real-world adversary data to function at the speed and fidelity modern threats demand. 

ANY.RUN’s threat analysis and intelligence products are purpose-built to close this gap. Together, they transform MITRE ATT&CK from a conceptual framework into an operational engine that drives measurable risk reduction across every phase of the security operations cycle. 

About ANY.RUN 

ANY.RUN, a leading provider of interactive malware analysis and threat intelligence solutions, helps security teams detect, investigate, and respond to threats faster.

ANY.RUN solutions include Interactive Sandbox, Threat Intelligence Lookup, Threat Intelligence Feeds, and integrations for SOC workflows across SIEM, SOAR, EDR, and other security tools. Together, they help teams safely analyze suspicious links, files, and scripts, uncover phishing behavior, trace credential theft and remote access activity, and enrich investigations with real-world threat context.

Built for security-conscious organizations, ANY.RUN is SOC 2 Type II attested and supports enterprise-ready controls such as SSO, MFA, granular privacy settings, and AES-256-CBC encryption.

Trusted by more than 15,000 organizations and 600,000 security professionals worldwide, ANY.RUN gives SOC teams the visibility they need to move from uncertain alerts to evidence-based decisions.

FAQ 

Can MITRE ATT&CK help me reduce cyber insurance premiums? 

Yes. Demonstrating ATT&CK-mapped controls, gap closures, and proactive testing provides evidence of mature risk management, which insurers often reward with lower premiums.

What is the difference between MITRE ATT&CK detection coverage and risk reduction? 

Detection coverage measures visibility into techniques; risk reduction quantifies business impact mitigation (e.g., prevented data loss or downtime) through layered defenses, response speed, and proactive measures.

How often should I reassess risk using MITRE ATT&CK? 

Quarterly at minimum, or after major incidents, new threat actor campaigns, or significant environment changes. Continuous integration via feeds and hunting yields ongoing insights.

How does MITRE ATT&CK integrate with existing frameworks like NIST? 

It complements them by adding adversary behavior details to NIST’s risk management processes, enabling more targeted control implementation and effectiveness measurement.

What role do ANY.RUN’s solutions play in operationalizing ATT&CK? 

They provide real-world context, fresh IOCs/IOAs, and behavioral examples that make abstract TTPs immediately actionable in monitoring, triage, and hunting.

How can small teams start using MITRE ATT&CK effectively? 

Begin with high-priority tactics relevant to your industry, map existing tools, use free ATT&CK Navigator, and incorporate accessible behavioral intelligence sources for quick wins in triage and response. 

 

The post How CISOs Reduce Cyber Risk with MITRE ATT&CK  appeared first on ANY.RUN’s Cybersecurity Blog.

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Insights into the clustering and reuse of phone numbers in scam emails

  • Cisco Talos has recently started to collect and gather intelligence around phone numbers within emails as an additional indicator of compromise (IOC). In this blog, we discuss new insights into in-the-wild phone number reuse in scam emails.  
  • According to Talos’ observations, the ease of API-driven provisioning makes a few VoIP providers the preferred tool for attackers, allowing for high-volume, cost-effective scam operations that are difficult to trace. 
  • Attackers maintain operational continuity by rotating through sequential blocks of phone numbers and utilizing strategic cool-down periods, with a median phone number lifespan of 14 days, to effectively evade reputation-based security filters. 
  • Threat actors try to maximize their reach by recycling the same phone numbers across diverse, seemingly unrelated lures – including varied subject lines and different attachment formats like HEIC and PDF – to impersonate multiple brands simultaneously. 
  • Security researchers can expose the hidden infrastructure of organized scam call centers by shifting focus from ephemeral email addresses to phone numbers, using clustering techniques to connect disparate campaigns and strengthen overall defensive postures.

Insights into the clustering and reuse of phone numbers in scam emails

Telephone-oriented attack delivery (TOAD) continues to be a prevalent tactic in modern email threats. By shifting the communication channel from email to a real-time conversation, attackers manipulate victims into disclosing sensitive information or installing malicious software. 

Cisco Talos has expanded its threat intelligence capabilities to include phone numbers as a critical IOC. Our analysis covers a wide spectrum of line types, including wireless (cellular), landline, and Voice over Internet Protocol (VoIP). While scammers leverage all three, VoIP numbers are particularly prevalent due to their ease of acquisition and the difficulty of tracing them back to their origin. In fact, six of the ten largest campaigns we detected between February 26 and March 31, 2026 relied on VoIP infrastructure.

To better understand how these numbers are weaponized, this blog first explains the technical structure of VoIP numbers and the role of service providers in this ecosystem. We then broaden the scope to analyze reuse patterns, lifespan, and campaign characteristics across all line types. By sharing these insights, Talos aimsto strengthen our collective defensive posture against these evolving threats.

The structure of VoIP phone numbers 

Most VoIP numbers follow the E.164 international public telecommunication numbering plan. This format ensures that every number is globally unique and can be routed correctly across the Public Switched Telephone Network (PSTN). 

An E.164 number is limited to 15 digits and consists of: 

  1. International Prefix (+): Indicates the number is in international format 
  2. Country Code (CC): 1 to 3 digits (e.g., 1 for the US/Canada, 44 for the UK) 
  3. Area Code/National Destination Code (NDC): Often referred to as the area code 
  4. Subscriber Number (SN): The specific number assigned to the user or device 

The above components are shown in the example phone number below:

Insights into the clustering and reuse of phone numbers in scam emails
Figure 1. The structure of an example VoIP phone number.

The VoIP ecosystem 

Voice over Internet Protocol (VoIP) has become the primary medium for scam campaigns due to its cost effectiveness, ease of deployment, and API-driven automation. Within this ecosystem, we identify two primary operational models: wholesalers and retailers. VoIP wholesalers (e.g., Virtue, Twilio, and Bandwidth) operate in a business-to-business (B2B) capacity, sitting between Tier 1 carriers (e.g., AT&T, Verizon) and smaller service providers, selling high volumes of numbers in bulk. Conversely, VoIP retailers (e.g., RingCentral) sell finished business calling and collaboration solutions directly to organizations and end users. 

VoIP providers are further categorized into communications platform as a service (CPaaS) and unified communications as a service (UCaaS). CPaaS providers offer programmable APIs that allow developers to integrate voice and messaging directly into applications. Because these platforms are designed for automation and high-volume traffic, they are frequently exploited by threat actors for rapid, API-driven number provisioning. In contrast, UCaaS providers offer comprehensive, end-user-facing communication suites. UCaaS platforms are typically designed for legitimate enterprise collaboration, and that makes them less attractive for scamemail campaigns. Talos has found Sinch (primarily a leader in CPaaS) as the most commonly abused VoIP provider, and Verizon and NUSO as the least abused providers in the studied time window.

Insights into the clustering and reuse of phone numbers in scam emails
Figure 2. The distribution of phone line types in scam emails.

While VoIP line types dominate the scam landscape (see Figure 2), Talos has observed that threat actors utilize wireless (cellular) and landline numbers as well. Cellular numbers are harder to provision at scale, as they typically require physical SIM cards and stricter customer verification, making them more expensive and less disposable than VoIP numbers. Nevertheless, they are still widely adopted by scammers. Figure 3 shows the distribution of wireless carriers that are used byscammers in the studied time window. Landline numbers, on the other hand, are used to project a sense of local presence or established business legitimacy. By using a landline with a specific local area code, scammers can effectively impersonate local businesses (e.g., banks, utility companies, or government offices).

Insights into the clustering and reuse of phone numbers in scam emails
Figure 3. The distribution of carrier names in wireless phone numbers found in scam emails.

Phone number reuse and lifespan in scam campaigns 

In this section, we provide insights into the lifecycle of phone numbers used in scam emails, examining how often they are reused, their typical lifespan, and how they appear across seemingly unrelated lures. Our analysis focuses on scam campaigns impersonating popular brands, including PayPal, Geek Squad (Best Buy), McAfee, and Norton LifeLock. 

Phone number reuse patterns 

Talos identified 1,652 unique phone numbers across these campaigns during the studied time window (February 26 to March 31). Of these, 57 numbers (approximately 3.4%) were reused across multiple consecutive days. The longest period of reuse observed for a single phone number was four consecutive days. 

As discussed in a previous blog post, phone numbers are reused for several strategic reasons. First, intelligence regarding phone numbers is often distributed more slowly than that of URLs or file hashes; many numbers remain under the radar of third-party reputation services for several days. Second, reuse offers logistical advantages for scam call centers, allowing them to maintain a consistent brand presence for multi-stage social engineering, callback scheduling, and persistent victim engagement. Finally, reuse minimizes operational costs, particularly for paid VoIP services. While we observed some phone numbers reused for up to four consecutive days, the most common reuse period was two consecutive days.

Lifespan analysis and cool-down periods 

Scammers do not always reuse phone numbers on consecutive days. Often, they implement a cool-down period — pausing the use of a number for a few days to evade detection — before reintroducing it into a campaign. 

Our investigation into the lifespan of these numbers revealed that 108 phone numbers (~6.5%) remained active for more than one day. As shown in Figure 4, most phone numbers have a lifespan of two to six days, though a handful remained active for nearly a month. During the study window, the median lifespan was approximately 14 days. Notably, infrastructure longevity often correlates with the impersonated brand; as illustrated in Figure 5, PayPal-themed scam campaigns utilized significantly more persistent phone numbers than those impersonating Norton LifeLock.

Insights into the clustering and reuse of phone numbers in scam emails
Figure 4. The distribution of phone number lifespans (in days) in scam emails impersonating the above four brands.
Insights into the clustering and reuse of phone numbers in scam emails
Figure 5. The lifespan of phone numbers in scam emails for the top two impersonated brands.

Phone numbers across unrelated lures 

A scam or phishing lure is typically a combination of a business context, a psychological trigger, a call-to-action, and an impersonated brand (see Table 1 for a few examples). These lures appear across various email layers, including subject lines, body content, and attachments.

Claimed business context

Psychological trigger

Call-to-action

Impersonated brand

Subscription renewal

Invoice or billing statement

Account security alert

Order confirmation/shipping issue

Technical support case

Refund or overpayment notice

Service cancelation confirmation

Financial transaction verification

Urgency

Fear/Loss aversion

Confusion

Relief opportunity

Curiosity

Call a phone number

Click a link

Reply with personal details 

Download/open attachment 

Provide payment/banking information

PayPal 

Geek Squad (Best Buy) 

McAfee 

Norton LifeLock

 

Table 1. Examples of lures that most commonly appear in scam or phishing emails.

We observed phone numbers being recycled across diverse, seemingly unrelated lures: 

  • Using the same phone number across multiple lures in the subject line: In one campaign, a single phone number appeared across multiple business contexts, such as “order confirmation” and “financial transaction verification.” Figure 6 demonstrates how these subject lines differ, despite the emails containing the same phone number and impersonating the same brand.
  • Using the same phone number across multiple document-based lures: In a second campaign, a single phone number was embedded in PDF attachments used for both “subscription renewal” and “financial transaction verification.”Interestingly, this campaign utilized two different brands — PayPal and Norton LifeLock — to redirect recipients to the same call center, leveraging urgency as a psychological trigger.
  • Using the same phone number across multiple attachment file formats: In a third campaign, a single phone number was embedded in two different attachment formats: HEIC and JPEG. The use of HEIC (High Efficiency Image Container) — a format often used for iPhone/iPad photos — demonstrates the attackers’ efforts to bypass traditional file-based detection while maintaining high image quality. Talos has observed campaigns utilizing even more attachment types, confirming that threat actors frequently distribute a single phone number across multiple attack vectors to maximize their reach.

Phone block-level clustering 

In the context of scam emails and related smishing or callback scams, attackers utilize specific VoIP grouping and clustering techniques to bypass security filters, appear legitimate, and maintain high-volume operations. One of the most common tactics is sequential number grouping. Scammers often obtain large ranges of sequential phone numbers by purchasing Direct Inward Dialing (DID) blocks. Consequently, if a specific number is flagged as spam and blocked by a carrier, the attackers simply rotate to the next number in the block. 

The figure below shows how a block of numbers — differing only in the last four digits — is used in various scam emails impersonating PayPal between March 3 and March 6, 2026. It is also clear that certain numbers are used in larger campaigns than others; for instance, “+1 804[-]713[-]4598” was used in 117 scam emails in a single day.

Insights into the clustering and reuse of phone numbers in scam emails
Figure 9. Example of sequential phone numbers used in scam emails impersonating one specific brand.

In large-scale scam campaigns, phone numbers within a single sequential block are reused across multiple brand lures. The figure below shows how a range of numbers in a sequential block is deployed across three different brand lures. As with the previous case, some phone numbers are utilized in significantly larger campaign volumes than others.

Insights into the clustering and reuse of phone numbers in scam emails
Figure 10. Example of sequential phone numbers used in scam emails impersonating multiple brands.

Conclusion and protection 

When tracking scam campaigns, it is essential to look beyond individual sender email addresses, which are often ephemeral. Instead, it is more strategic to focus on phone numbers, which serve as the true anchors of the operation. By clustering scam lures based on shared phone numbers, security researchers can effectively map connections between seemingly unrelated campaigns, ultimately exposing the infrastructure of organized criminal call centers. 

Service providers and security teams should prioritize the implementation of real-time reputation monitoring for different communication channels to proactively mitigate these threats. For example, establishing centralized databases that track and flag high-risk phone numbers across multiple platforms allows for rapid cross-campaign correlation. Collaboration between telecommunications and VoIP providers is also vital, as sharing threat intelligence regarding malicious telephony infrastructure enables an industry-wide defense against the persistent threat of social engineering and fraud. 

Cisco Secure Email Threat Defense 

Protecting against these sophisticated and devious threats requires a comprehensive email security solution that harnesses AI-powered detections. Cisco Secure Email Threat Defense utilizes unique deep and machine learning models, including Natural Language Processing, in its advanced threat detection systems that leverage multiple engines. These simultaneously evaluate different portions of an incoming email to uncover known, emerging, and targeted threats.

Secure Email Threat Defense identifies malicious techniques used in attacks targeting your organization, derives unparalleled context for specific business risks, provides searchable threat telemetry, and categorizes threats to understand which parts of your organization are most vulnerable to attack. You can sign up for a free trial of Email Threat Defense today. 

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