Synthetic identity theft — where criminals combine real and fabricated data to create entirely new “people” — is one of the fastest-growing forms of digital fraud. Unlike traditional identity theft, which steals from real individuals, synthetic identity fraud manufactures fake identities that appear legitimate to verification systems.

This sophisticated type of fraud is costing organizations billions of dollars each year. As exposure of personal data expands across the surface, deep, and dark web, the challenge is no longer if a synthetic identity exists in your ecosystem — it’s whether you can detect it before it does damage.

At Constella.ai, we help organizations do exactly that. By analyzing billions of exposed identifiers and behavioral signals, Constella’s Identity Intelligence platform uncovers synthetic identities before they can be used to defraud financial systems or compromise customer trust.

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What Makes Synthetic Identity Theft So Dangerous

Synthetic identities are particularly insidious because they’re built from partial truths. Fraudsters merge authentic data — such as Social Security numbers, addresses, or phone numbers — with fictitious names or dates of birth. The resulting identity passes many traditional verification checks, making it extremely difficult to flag.

Once created, these “people” open bank accounts, apply for loans, and build legitimate-looking credit histories. Over months or even years, they operate like normal customers until one day they disappear — taking the financial institution’s money with them.

This long-game approach has made synthetic identity theft one of the most profitable and elusive types of fraud worldwide. According to the U.S. Federal Reserve, it remains the fastest-growing form of financial crime.

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How Synthetic Identities Are Created

The creation of synthetic identities typically involves three steps:

1. Collecting real data from breaches, phishing schemes, or dark-web marketplaces.
2. Blending authentic and fabricated details to form a plausible profile.
3. Cultivating credibility by opening small accounts and building up a transaction history over time.

What makes these identities so convincing is the scale and sophistication of available data. Fraudsters can now automate parts of this process using AI tools to generate consistent personal details and social media profiles — all of which appear genuine to surface-level screening.

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Why Traditional Fraud Detection Misses the Warning Signs

Legacy identity verification systems are designed to confirm that an identity exists, not to verify that it’s real. When a fraudster uses partial real data, those systems often validate the profile without recognizing the inconsistencies behind it.

Synthetic identities also don’t trigger alerts associated with stolen credentials — because no “victim” reports suspicious activity. The fraud remains invisible until the account defaults or an internal audit exposes discrepancies.

In today’s environment, organizations need a broader lens — one that goes beyond static identity checks and analyzes digital exposure and behavioral context.

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How Identity Intelligence Exposes Synthetic Identities

Constella’s approach goes beyond verification to deliver Identity Intelligence — connecting breached data, OSINT (open-source intelligence), and behavioral indicators to provide a holistic view of digital risk.

Through billions of correlated identity records, Constella detects patterns that traditional systems miss, such as:

• Reused credentials or identifiers appearing across unrelated identities.
• Synthetic profiles tied to known breach clusters or fraudulent domains.
• Data inconsistencies that suggest a fabricated or manipulated identity trail.

By continuously mapping identity exposure across the surface, deep, and dark web, Constella helps organizations identify and neutralize synthetic identities early — before they evolve into financial or reputational losses.

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Technology’s Role in Staying Ahead

AI is both the problem and the solution. Fraudsters now use generative AI to produce realistic personal data and digital personas. But at Constella, AI and machine learning are leveraged to counter these tactics — automatically analyzing vast data sets to uncover anomalies, correlations, and exposure trends that signal synthetic activity.

Our algorithms learn from emerging fraud behaviors, adapting detection logic in real time to stay ahead of evolving threats. Combined with Constella’s unmatched data coverage — over 180 billion compromised identities and growing — this intelligence provides organizations with actionable insights to protect their systems and customers.

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Strengthening Defense Through Collaboration and Proactive Monitoring

Preventing synthetic identity theft requires collaboration between financial institutions, technology providers, and identity-intelligence partners. The most effective strategies integrate:

• Comprehensive exposure monitoring across public, deep, and dark web sources
• Cross-system intelligence sharing to detect linked identities and fraud rings
• Continuous identity-risk scoring for early-warning visibility

By uniting data sources and technologies, organizations can move from reactive defense to proactive threat prevention.

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Conclusion: Detecting the Identities That Don’t Exist

Synthetic identity theft will continue to evolve — but so will our ability to detect it. With digital exposure increasing and fraud tactics growing more sophisticated, visibility across the entire identity landscape has never been more critical.

Constella’s Identity Fraud Detection and Identity Intelligence solutions empower organizations to identify fraudulent identities before they impact operations or customers.

See how Constella helps uncover synthetic identities before they strike.

Co-authored by Constella Intelligence and Kineviz

Most companies have no reliable way of knowing how corporate email accounts are being used, whether policies are being followed, or if critical data is being shared on unmonitored platforms. Malware does more than steal credentials. Infostealers’ bounty includes live sessions, saved credentials, browser configurations, and user interactions across infected devices throughout an organization. It reveals how employees behave, exposes how endpoints are configured, and highlights failing security policies. With such data in hand, bad actors can pinpoint an organization’s real-world weaknesses, beyond the perimeter monitored by logs or enforced by compliance checklists.  The good news is that organizations and defenders can use that same information to protect themselves and fight back.

In this third installment of the series, we explore policy violations, insecure practices, and endpoint weaknesses that silently expand the organizational attack surface. Drawing on findings from the Constella 2025 Identity Breach Report and given context by Kineviz’s visual analytics platform, we demonstrate how to use the intersection of behavioral and technical signals to expose systemic vulnerabilities before bad actors find them first.

Policy Violations: When Acceptable Use Becomes Unacceptable Risk

Acceptable Use Policies are designed to protect organizational assets by defining clear boundaries for how corporate accounts, devices, and identities should be used. But, the reality is that there is no such thing as a human firewall. Organizations can not enforce or monitor the intent or digital behavior of each employee in real time. The truth derived from infostealer data is that these boundaries are routinely ignored in day-to-day practice.

One frequently observed violation is the use of corporate email accounts to register on unauthorized platforms, whether they are social media sites, browser plugins, streaming services, or online marketplaces. In some cases, employees may be using their corporate email addresses on adult content platforms or online gambling services. Often times, these registrations are made from personal or unmanaged devices, which then become targets for malware infections. Once attackers exfiltrate credentials and session tokens, they gain access to potentially sensitive corporate resources as well as to those external services.

Whether intentional or accidental, these violations increase legal and operational risk. More importantly, they erode the boundary between internal systems and external exposure, creating opportunities for lateral compromise that security teams often cannot see until it is too late.

Password Reuse: Bridging External Infections with Internal Impact

Constella’s analysis shows that password reuse between personal and professional accounts remains one of the most common enablers of compromise. Employees frequently reuse passwords across unrelated services, often with minor variations, or use the same login combination for both internal systems and consumer applications. While this may be more convenient for the user, it opens the door to the organization if the password is compromised by a bad actor.

Organizations have no direct way to measure this behavior. Endpoint agents and IAM systems cannot detect whether a user is reusing the same password on a third-party site, nor can they prevent it unless password managers or strict vaulting practices are universally adopted and enforced. Even then, as mentioned, people find ways around them. This lack of visibility means that an employee’s compromised gaming account, shopping profile, or personal email account can silently open the door to a breach.

However, just as bad actors use the data they glean to pinpoint weaknesses for exploitation, organizations can use infostealer data to identify where and how they need to shore up their defenses. By analyzing infections at scale, companies can detect high-risk usage patterns that were invisible before.

Security teams who use Kineviz’ GraphXR can visualize data relationships, trace risk back to its origin, identify affected users and systems, and define clear priorities for containment and training.

By analyzing aggregated infections, security teams clearly see password reuse across domains and platforms. Infection analysis regularly finds credentials tied to cloud admin consoles, CI/CD tools, or customer databases side by side with consumer services or non-sanctioned applications.

Endpoint Exposure: A Reflection of Real-World Vulnerabilities

Infostealers not only extract credentials, they also capture detailed metadata about the infected environment. This includes browser versions, system configurations, running processes, antivirus products, and even clipboard contents or autofill settings. This technical context provides direct insight into which devices are most vulnerable and how malware is evading detection.

Among the findings surfaced in the 2025 report:

• Chrome, Firefox, and Edge are the most frequently targeted browsers due to their market share and extensive storage of session cookies and credentials.
• Antivirus evasion is widespread. Infostealer logs show infections on systems that report running up-to-date antivirus tools, suggesting misconfiguration, outdated signatures, or user-level bypasses.
• Infection hotspots vary significantly by geography, often correlating with weaker IT maturity or less frequent device patching and monitoring. These regions frequently include outsourced operations, contractors, or satellite offices where central control is limited.

Kineviz allows organizations to visualize these infections across office locations, endpoint types, and operating systems, enabling risk segmentation that aligns with actual exposure rather than policy assumptions.

From Static Policy to Adaptive Defense

The convergence of behavior and endpoint visibility allows organizations to shift from static security policies to contextual defense strategies. Diving into the data, gives teams the power to figure out where security policies are failing so they can focus their remediation efforts where the risk is highest.

Recommendations include:

1. Correlate identity data with device intelligence
   Combine credential exposure with endpoint metadata to understand infection conditions, identify vulnerable builds, and prioritize device-level hardening.
2. Visualize violations and usage drift
   Use graph-based analysis tools like GraphXR to group corporate identities misused on unapproved services or linked to high-risk behavioral patterns.
3. Deploy role-based awareness campaigns
   Train users on behavior as much as job function. For example, employees using the same password across services should receive targeted training and forced credential resets.
4. Monitor high-risk geographies and external partners
   Track infections across contractors, offshore teams, and unmanaged endpoints to detect weak links in distributed environments.
5. Implement policy validation with real data
   Replace static policy enforcement with continuous validation, driven by intelligence from real-world infections and endpoint activity.

Final Thoughts

Infostealers don’t just exfiltrate data. They dynamically sense policy violations, behavioral risks, and endpoint misconfigurations and can provide real benefits to the bad actors or to the organization attacked. If the information stays buried in disconnected logs, those benefits remain latent. However, if transformed into intelligence, then they can power adaptive, visual, and context-rich defense.

The absence of visibility into real employee behavior—how identities are used, where they appear, and which systems they access—creates blind spots that attackers actively exploit. No firewall can stop a user from making a poor security decision. But with deep infostealer intelligence from Constella and advanced visual analytics from Kineviz, organizations can finally see the risk for what it is, map it across users and endpoints, and act before it escalates.

Today, digital footprints are as significant as physical ones, which is why the importance of secure identity risk monitoring cannot be overstated. With the constant evolution of cyber threats, it’s crucial to implement robust strategies to protect not only personal but also professional identities from potential risks. As cybercriminals become more sophisticated, staying one step ahead requires diligence, awareness, and the right set of tools. This blog will dive into some of the best practices for ensuring effective identity risk monitoring, drawing insights from Constella Intelligence’s cutting-edge cybersecurity solutions.

Embrace Comprehensive Identity Monitoring

Comprehensive identity monitoring involves keeping a vigilant eye on various channels where personal information might be exposed, including the dark web, deep web, and more. It’s about understanding where your data could potentially be leaked or sold. Platforms like Constella Intelligence utilize AI-driven technology to scan these underground networks, providing real-time alerts and mitigating the risk of identity theft and impersonation.

Key Components of Effective Monitoring

A robust identity monitoring system should encompass the following:

• Real-Time Alerts: Immediate notifications about potential threats or breaches.
• Data Analysis: Advanced analytics to understand the nature and source of threats.
• Dark Web Surveillance: Regular scanning of hidden networks where data might be traded.

Leverage Deep OSINT Investigations

Open Source Intelligence (OSINT) is a critical component of identity risk monitoring. By leveraging deep OSINT investigations, organizations can uncover valuable insights about potential threats. Constella Intelligence excels in this area, using a vast dataset to track the activities of bad actors. This approach is particularly beneficial for fraud investigation teams, law enforcement, and national security agencies.

Benefits of OSINT Investigations

1. Uncover hidden threats that traditional monitoring might miss.
2. Gain insights into the modus operandi of cybercriminals.
3. Enhance understanding of the landscape of cyber threats.

Implement Advanced Fraud Detection Techniques

Fraud detection is at the heart of identity risk monitoring. Advanced techniques like Know Your Customer (KYC), Know Your Employee (KYE), and synthetic identity fraud detection are vital. These methods help verify identities and detect anomalies that could indicate fraudulent activities. Constella Intelligence’s capabilities in these areas are powered by a sophisticated data lake, encompassing over one trillion assets across 125 countries.

Fraud Detection Best Practices

• Regular Updates: Ensure fraud detection systems are regularly updated to tackle the latest threats.
• Cross-Verification: Validate identity information across multiple sources to confirm authenticity.
• Behavioral Analysis: Monitor for unusual patterns or behaviors that deviate from the norm.

Adopt a Proactive Security Culture

Last but not least, cultivating a proactive security culture within your organization can greatly enhance identity risk monitoring. This involves educating employees about the importance of cybersecurity, ensuring they understand their role in protecting sensitive information. Constella Intelligence champions this approach, emphasizing the need for continuous learning and adaptation to new threats.

In conclusion, secure identity risk monitoring is not just a technological challenge but a strategic imperative. By implementing comprehensive monitoring, leveraging advanced investigations, and adopting a proactive security culture, organizations and individuals alike can stay protected in an increasingly interconnected world. For more insights and resources on safeguarding your digital identity, explore Constella Intelligence’s extensive offerings in cybersecurity solutions.

Co-authored by Constella Intelligence and Kineviz

As infostealer malware continues to scale in reach, automation, and precision, organizations face an increasingly urgent challenge: a lack of comprehensive visibility across their identity exposure landscape. While credential leaks and cookie thefts are often detected in isolation, without centralized and time-aware analytics, security teams cannot understand the true extent and persistence of the threat.

This article outlines the critical elements required to close this visibility gap. Using data provided by Constella’s Identity Breach Report and delivered through Kineviz’s graph-powered analytics platform, we explore how organizations can use exposure segmentation, behavioral analysis, and temporal monitoring to turn infostealer intelligence into protective action.

Visualizing Strategic Exposure: From Fragmented Incidents to Global Awareness

Identity issues frame a variety of threats. They are critical when attempting to assess which geographies are under attack, whether certain countries are more targeted by threat actors, or whether there are internal deficiencies, such as low levels of security awareness or weaker hygiene practices that lead to password or credential sharing.

The larger the organization, the greater the hazard. Why? Because identity (however defined) is the key to access every subgroup, unit, division, and device. Without a consolidated view that links infections, credentials, and threat activity across countries and business units, security and risk leaders are forced to work with fragmented signals.

The challenge is to put all of this disparate information into a context that makes it possible to choose a plan of action. In a visual environment that explicitly shows connection between data, such as Kineviz’ GraphXR, organizations can, for example, transform raw infostealer logs into dynamic, interactive intelligence maps.

Such maps allow decision-makers to explore the identity threat surface across regions, teams, and technologies, making it possible to identify hotspots.

More specifically, using the information to track password patterns across regions, an organization might discover that offices in a specific country consistently use weak or reused credentials. Or, perhaps that local employees are registering corporate email addresses on high-risk consumer platforms. Such maps could reveal that regional exposure aligns with known adversary operations or geopolitical targeting patterns.

Such operational intelligence cannot be derived from isolated alerts or static dashboards. It requires the ability to explore and interact with relational data at scale, enabling organizations to go beyond detection towards true understanding.

Temporal Trends: Seeing Exposure Over Time

Timeline-based monitoring is another key element in closing the visibility gap. Security teams need to know:

• Is our phishing training actually reducing infections?
• Did the endpoint protection upgrade in Q2 reduce exposure?
• Are infections spiking after software rollouts or travel seasons?

Tracking infostealer telemetry across time reveals trends otherwise buried in static lists. By visualizing when credentials are exfiltrated, reused, or republished on dark web markets, organizations can assess whether their controls are working—or whether attackers are simply shifting vectors.

Kineviz’ GraphXR helps analysts slice infostealer intelligence by time, helping them detect waves of infections, correlate attacks with specific events (e.g., policy changes, layoffs, partner integrations), and measure the impact of remediation efforts.

Behavioral Weaknesses: The Hidden Patterns Behind Exposure

Besides geography and time, poor identity hygiene remains a critically underexplored root cause of infostealer impact. Constella’s analysis of 2024 data revealed multiple habitual behaviors driving exposure risk:

• Password reuse across personal and corporate services remains widespread.
  Infected users routinely store both business and consumer credentials in browser autofill.
• Shared credentials in production environments, particularly among DevOps and engineering teams, continue to appear across stealer logs, suggesting systemic violations of identity isolation policies.
• Weak passwords that clearly violate corporate policy appear not only in internal systems, but on third-party platforms where employees use work credentials for unapproved services.

These behaviors persist because they are difficult to detect in real time. However, the data forms clear patterns when infostealer logs are aggregated and visualized. Visual analytics reveal behavioral clusters, groups of employees using the same root passwords, storing credentials across unrelated services, or sharing privileged access. This behavioral context enables targeted interventions, not generic awareness campaigns. Now analysts can pivot from “this account was exposed” to “this role, region, or department has a recurring pattern of weak password usage.”

From Incident Response to Exposure Management

To close the visibility gap, organizations must elevate their infostealer response from tactical containment to strategic intelligence. This transformation depends on five key strategies:

• Centralize global telemetry
  Aggregate infostealer logs, credential leaks, and identity artifacts across all organizational domains, subsidiaries, and regions.
• Visualize exposure context
  Use platforms like Kineviz to connect identity elements, employee roles, geographic regions, and session data in real time, enabling meaningful exploration and segmentation.
• Track remediation over time
  Build timeline-based workflows that show how infection rates and exposure patterns evolve after security initiatives, training campaigns, or infrastructure changes.
• Detect patterns at the organizational level
  Move beyond individual detections to surface collective risk signals, such as password reuse clusters or role-based exposure profiles.
• Translate visibility into strategic policy
  Leverage this intelligence to inform acceptable use policies, endpoint configurations, access controls, and region-specific training efforts.

Final Thoughts

The volume of exposure is no longer the primary challenge. The real threat lies in the lack of insight. Without centralized, temporal, and behavioral visibility, organizations are forced to remain reactive, merely treating symptoms while systemic vulnerabilities persist beneath the surface.

By combining Constella’s deep infostealer intelligence with the advanced visual analytics provided by Kineviz’ GraphXR, organizations gain the ability to see their exposure, not just list it. This visibility enables faster response, more effective remediation, and ultimately, better decisions to promote enterprise security.

Passkeys Are Progress, But They’re Not Protection Against Everything

The cybersecurity community is embracing passkeys as a long-overdue replacement for passwords. These cryptographic credentials, bound to a user’s device, eliminate phishing and prevent credential reuse. Major players, like Google, Apple, Microsoft, GitHub, and Okta, have made passkey login widely available across consumer and enterprise services.

Adoption isn’t limited to tech platforms, either. In 2025 alone:

• The UK government approved passkeys for NHS and Whitehall services.
• Microsoft began defaulting to passwordless authentication for new users.
• Aflac, one of the largest U.S. insurers, enrolled over 500,000 users in its first passkey onboarding wave.
• The FIDO Alliance reported that 48% of the top 100 global websites now support passkeys, with more than 100 organizations signing public pledges to adopt them.

It’s a win on many fronts, but it doesn’t solve the identity problem. Authentication controls don’t matter if the device itself is already compromised, and that’s where infostealer malware continues to exploit a critical blind spot in the industry’s rush toward passwordless security.

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Infostealers Don’t Break In, They Log In After You Do

Infostealers are lightweight malware designed to extract sensitive data from infected endpoints — no exploit required. Once installed, they collect:

• Browser-stored credentials
• Authentication tokens and session cookies
• Auto-fill and personal data
• Crypto wallets, system info, and more

The attacker doesn’t need your passkey or password. If your device is infected, they can hijack your authenticated session and access systems without ever touching a login page.

This method for stealing and reusing session artifacts is growing because it works. And in a passkey-enabled world, it’s often invisible to traditional defenses.

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Real-World Data Shows the Risk Is Growing

In Constella’s 2025 Identity Breach Report, we tracked tens of millions of infostealer logs circulating across criminal markets in a single year. These logs often include session cookies and credentials tied to executive, developer, and admin accounts.

This isn’t speculative. These artifacts are actively traded, resold, and used to infiltrate corporate environments. And in many cases, organizations discover the breach only after the stolen data shows up for sale online.

Worse, the malware behind these logs is readily available as a service. Infostealers like Lumma, Raccoon v2, and RedLine are being deployed by low-skill attackers who no longer need phishing kits or password crackers. Just infect the device and extract what’s already there.

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Passkeys Solve One Problem, But Leave Others Unaddressed

To be clear, passkeys are a powerful and necessary evolution. They eliminate phishing vectors and reduce the burden on users. But they assume the endpoint is secure, and increasingly, that assumption doesn’t hold.

If malware has access to the browser’s local storage or the filesystem where session tokens live, passkeys offer no protection. The attacker simply reuses the session token and bypasses authentication entirely.

This is the new frontier of identity-based attacks. And as more organizations adopt passkeys, device compromise and session hijacking will become the primary identity threats.

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A Shift in Strategy: From Authentication to Identity Exposure

Organizations need to rethink their approach. Instead of focusing only on the login layer, security teams must assess whether the identities behind those logins have already been exposed. That starts with extending visibility beyond the perimeter.

1. Monitor for Identity Exposure in the Wild

Track stolen credentials, session cookies, and tokens showing up in infostealer logs and underground markets. These exposures are often the first sign of a compromise.

2. Harden Device Hygiene at the Edge

Endpoint protection and EDR tools remain critical, especially for remote users and unmanaged devices. Many infostealers are delivered through phishing attachments, malicious downloads, or cracked software.

3. Reduce Session Token Lifespan

Short-lived sessions limit attacker dwell time. Pair with device fingerprinting, geo-fencing, or re-authentication triggers to detect anomalous access patterns.

4. Link Exposure to Risk with Contextual Intelligence

The next step is understanding who is exposed, not just what credentials. This requires the ability to correlate disparate data points into a unified identity profile.

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Bringing Risk Into Focus with Identity Intelligence

Constella’s Identity Risk Intelligence solutions enable organizations to surface hidden connections across exposed credentials, session artifacts, and real-world users. By stitching together breach, malware, and dark web data, we help security teams:

• Enrich identity risk scoring with real-world exposure signals
• Link consumer and corporate identities
• Prioritize high-risk individuals based on context, not guesswork

This kind of visibility helps answer questions that authentication tools can’t. When a credential is exposed, is it tied to one of your developers? An executive? An unmanaged personal device accessing corporate systems?

That context makes the difference between an alert and an urgent response.

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Final Thought: Passkeys Are a Start, Not a Solution

We’re moving in the right direction. But the rise of passkeys shouldn’t create a false sense of security. Threat actors have already adapted. They no longer need to steal credentials; they’re quietly collecting access.

Device-level compromise, not credential theft, is becoming the dominant driver of identity risk.

And if your defenses stop at the login screen, you’re not securing the full picture.

Because in today’s threat landscape, it’s not about how strong your passkey is — it’s about whether your session is already in someone else’s hands.

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Want to assess your organization’s identity exposure?

Request a threat exposure report from Constella to see if your employees’ credentials or session tokens have been compromised — and learn how identity risk intelligence can close the gap.

Co-authored by Constella Intelligence and Kineviz

Infostealer malware dominates today’s cyber threat landscape. Designed to extract credentials, cookies, session tokens, autofill data, and other forms of digital identity, infostealers operate silently, persistently, and at industrial scale. They are no longer just a precursor to other attacks—infostealers are the breach.

There are two critical vectors of risk: employee-driven and user-driven infections. Yet many organizations treat these threats uniformly, without differentiating between them. Crucially, each introduces fundamentally different threat dynamics, requiring distinct detection strategies, containment protocols, and long-term mitigations.

This article, co-authored by Constella Intelligence and Kineviz, combines large-scale infostealer telemetry data with advanced visual analytics to demonstrate how organizations can understand and contextualize these evolving exposures. The foundation of this analysis is the Constella 2025 Identity Breach Report, which tracks over 219,000 breach events, 107 billion exposed records, and 30 million infected devices observed across deep and dark web sources. GraphXR, Kineviz’ graph data analytics and visualization platform, provided the means for the analysis and visualizations.

Employee Infections: A Gateway to Internal Compromise

Infostealers that target employees directly threaten enterprise systems. Why? Attackers exfiltrate credentials from devices used to access email, cloud services, production infrastructure, or collaboration platforms. With these credentials in hand, attackers win immediate access to the operational backbone of an organization. Constella’s data shows that infostealer logs included internal credentials in 78% of recently breached companies within an examined six-month window of compromise.

More than 30% of ransomware attacks in 2024 started with access acquired through infostealer infections. Attackers deployed infostealers like LummaC2, Redline, and Vidar to extract credentials which they either resold or reused. These infections also frequently evade detection on unmanaged or BYOD (bring your own) devices, especially in hybrid work environments.

Moreover, 95.29% of credentials exposed via infostealers in 2024 were found in plaintext, a dramatic increase from the previous year. The implications are clear: attackers don’t break in when they can simply log in.

User Infections: External, Yet Highly Impactful

While user-side infections may not directly affect enterprise systems, their impact is no less severe. What makes this type of exposure so dangerous is its latent pathway into internal systems. If an organization has federated authentication, shared credentials, or weak access controls in place, attackers may escalate privileges or move laterally using external identities. With 60% of 2024 breach datasets composed of recycled credentials, attackers often combine user- and employee-exposed data to uncover new attack paths.

Employees regularly use corporate devices to access personal accounts and vice versa. Constella’s telemetry has repeatedly shown cases where session cookies and credential pairs recovered from “user” infections include logins to administrative dashboards, internal cloud environments, or IT vendor platforms.

Attackers use credentials stolen from customers or partners to take over accounts (ATO), commit fraud, and abuse platforms. This increases the operational burden on support teams, drives up fraud losses, and even introduces brand-level risk when attackers use hijacked user sessions to phish or commit fraud.

The Critical Role of Visual Analytics in Deep Infostealer Intelligence

The dynamic nature of identity exposure—where a single infostealer infection may leak credentials across dozens of unrelated services—requires a different investigative model. Security teams must move away from static analysis of email domains or leaked passwords and begin treating infostealer datasets as high-context, interconnected threat maps.

The scale and relational complexity of Constella Intelligence’s infostealer data lakes demands a way to understand its significance beyond creating lists of actors and leaks. This is where Kineviz adds critical value. Through graph-powered visual analytics, teams can explore infostealer data in real time, connecting credentials, session artifacts, device metadata, and behavioral signals across internal and external entities. This gives analyst teams the insight they need to address the security issues as an interconnected ecosystem and to create plans to mitigate them.

Kineviz’ GraphXR enables security teams to visually distinguish and separate employee infections from user-based exposures, mapping each population independently while also exploring their intersections. This structured separation is fundamental when trying to tailor containment strategies or when reporting risk by department, geography, vendor, or user segment.

Furthermore, the ability to operate at scale across millions of credentials allows analysts to extract collective intelligence from affected populations. Instead of responding to threats one by one, teams can investigate clusters—such as all developers using a compromised plugin, or all employees sharing credentials with leaked user accounts. These insights help uncover shared infrastructure, behavioral patterns, or systemic security weaknesses that wouldn’t emerge from individual case analysis.

Kineviz’s visual engine also allows threat intelligence teams to:

• Group infostealer logs by attack vector or malware family (e.g., Redline vs. Lumma)
• Identify concentrations of exposure by business unit, role, or application
• Tag and monitor known vendors, executives, or contractors as high-risk nodes
• Segment remediation by use case: phishing risk, lateral movement, ATO, privileged access, etc.

The result is a shift from flat reporting to visual, contextual threat modeling, where security teams can rapidly see, segment, and prioritize threats by relevance and business impact. Visualization is no longer a reporting feature—it is an investigative tool and a decision accelerator.

Recommendations

1. Adopt a Dual-Lens Threat Model
   Separate internal and external exposures in your detection stack—but correlate them where identity overlap is suspected.
2. Leverage Visual Graph Analysis
   Use tools like those developed by Kineviz to visually explore infostealer logs and extract macro-level patterns across users, malware types, and threat actors.
3. Operationalize Infostealer Intelligence at Scale
   Treat infostealer data as the backbone of identity threat modeling. Avoid treating incidents in isolation—group them to detect systemic exposures.
4. Track Beyond Credentials
   Monitor for session tokens, authentication cookies, and configuration artifacts. These are increasingly used to bypass MFA and impersonate users.
5. Expand Awareness Across the Organization
   Train employees, fraud teams, and risk stakeholders to understand how infostealer risk impacts them—even outside the traditional security perimeter.

Final Considerations

Infostealers are not a niche threat. They are the operational mechanism behind today’s largest-scale identity attacks. According to the Constella 2025 Identity Breach Report, nearly every major breach now involves infostealer data, reused credentials, or session artifacts obtained via these infections.

Responding effectively requires more than threat feeds, it requires context, correlation, and visibility. Through the joint power of deep infostealer intelligence from Constella and real-time visual exploration from Kineviz, organizations gain the clarity needed to defend at the speed and complexity of modern threats.

Identity is the connective tissue of today’s enterprise. But with identity comes exposure. Credentials are being stolen, resold, and reused across the cybercriminal underground at a scale that far outpaces traditional defenses. Identity intelligence – the process of collecting, correlating, and acting on data tied to digital identities – has become a core pillar of risk management and threat detection.

This post explores how identity intelligence elevates security operations, the barriers to operationalizing it, and where we go next.

What Is Identity Intelligence?

Identity intelligence combines breach data, malware logs, and underground chatter to create a dynamic picture of identity exposure. When executed correctly, it empowers organizations to:

• Detect compromised credentials in use or circulation
• Attribute malicious activity to users or identities
• Proactively prevent account takeover, fraud, and privilege escalation

According to Gartner, identity intelligence supports both tactical response and strategic decision-making. But let’s be clear: this isn’t about theory. This is about arming teams with the right context at the right time to stop threats before they metastasize.

The Data: Where Identity Intelligence Comes From

Effective identity intelligence starts with expansive, diverse data. Critical sources include:

• Infostealer malware logs: Often overlooked, these data sets reveal credentials harvested from infected devices. They offer unfiltered insight into what adversaries see.
• Dark web forums and marketplaces: Threat actors use these platforms to sell, trade, or leak credentials. Monitoring these channels yields early-warning signals.
• Paste sites and breach repositories: Frequently used to dump credential sets, often anonymously.

The signal lies in the correlation. A breached email address by itself is noise. That same email, tied to an infostealer log, reused password, and recent dark web post? That’s actionable.

Operational Challenges and Hard Truths

Identity intelligence isn’t a plug-and-play solution. You’re dealing with:

• Data overload and false positives: Context is everything. Without it, alerts generate noise, not insights.
• Fragmented systems: Identity data is siloed across IAM tools, custom databases, Active Directory ecosystems, SIEMs, endpoint agents, and HR systems.
• Evolving threats: Infostealers are modular. TTPs shift. Credentials get reused across sectors and campaigns. Intelligence must evolve just as quickly.

The lesson? Organizations must move beyond static lists of leaked credentials. Contextual risk scoring, exposure timelines, and integration with identity providers and Threat Intelligence Platforms (TIPs) are non-negotiable.

From Monitoring to Mitigation: Automating Identity Threat Response

Knowing a credential is exposed is one thing. Acting on it is another.

Leading security teams are baking identity intelligence into their workflows by:

• Automating password resets and MFA enforcement when credential exposure is confirmed.
• Feeding alerts into SIEM/SOAR platforms for triage and incident correlation.
• Enriching IAM systems with risk-based signals to drive access decisions.

Take Texas A&M as an example. Using identity intelligence, they identified nearly 400,000 compromised credentials, reset affected passwords, and created automated alerts. That’s not theory – that’s operational resilience.

Where Identity Intelligence Fits in Modern Cyber Strategy

As zero trust architectures mature and perimeter-based defenses fade, identity becomes both the battleground and the opportunity. Identity intelligence strengthens:

• Continuous Threat Exposure Management (CTEM) by identifying high-risk users and accounts
• Insider risk programs by detecting anomalous behavior tied to compromised identities
• Fraud and trust platforms by surfacing risky logins and behavioral outliers

And it does so without requiring another agent or console. It operates upstream of the compromise.

The Road Ahead: Machine-Scale Identity Risk Management

Looking forward, the role of machine learning in identity intelligence will only grow. It’s already being used to:

• Detect patterns in credential reuse across environments
• Predict likelihood of credential exploitation
• Reduce false positives by enriching identity signals with behavioral data

With infostealer malware on the rise and over 53 million credentials compromised in 2024 alone, intelligence automation is the only way to keep up.

Final Thought

Cybersecurity teams don’t need more alerts. They need clarity. Identity intelligence provides that clarity – surfacing real risks buried in oceans of data and aligning security efforts to the digital realities of today’s enterprise.

If your strategy isn’t integrating identity exposure intelligence, you’re flying blind. It’s time to see.

FAQs

What is identity intelligence?
It’s the process of collecting, analyzing, and acting on data tied to user identities to detect compromised credentials and prevent threats.

What makes identity intelligence actionable?
Context. When data from malware logs, breach dumps, and underground forums is correlated, it provides a timeline and risk score that drive smarter decisions.

How is identity intelligence operationalized?
By integrating with IAM, SOAR, and SIEM systems to automate remediation steps like password resets, MFA enforcement, and access decisions.

What are common data sources?
Infostealer logs, dark web marketplaces, paste sites, breach repositories, and direct threat actor interactions.

What’s next in identity intelligence?
AI-driven risk scoring, real-time credential monitoring, and deeper integrations with zero trust and behavioral analytics platforms.

From Breach to Exploit: How Stolen Credentials Fuel the Underground Economy

In cybersecurity, breaches often make headlines. But what happens next – after usernames and passwords, or active session cookies, are stolen – is just as dangerous. The lifecycle of stolen credentials reveals a dark ecosystem of harvesting, trading, and exploitation. This post explores how attackers weaponize stolen logins and how defenders can disrupt the cycle with identity-centric intelligence.

Stolen Credentials: A Long Tail of Risk Most people think of stolen credentials as a one-time breach. But in reality, credentials have a life of their own. They are:

• Traded across Telegram channels and dark web forums
• Bundled into combo lists
• Sold by Initial Access Brokers (IABs)
• Used for credential stuffing, phishing, and ransomware

One high-profile example is the Colonial Pipeline breach. An attacker accessed the company’s network using a single compromised VPN credential – found in a prior breach dump, reused, and not protected by MFA. The fallout disrupted fuel supplies across the Eastern U.S.

The Stolen Credential Lifecycle in Action

1. Harvest – Phishing attacks, infostealer malware (e.g. RedLine, Raccoon), or exposed databases collect credentials at scale.
2. Distribute – Credentials are sold, leaked, or bundled into logs and combo lists on marketplaces like Genesis or Russian Market.
3. Exploit – Threat actors use stolen credentials for account takeover, initial access resale, or ransomware deployment.

The Flaw of Reactive Alerts

Browser alerts or breach notification services usually fire after credentials have already been traded or used. They rarely include:

• Origin of exposure (malware log vs. third-party breach)
• Whether the credential has been reused elsewhere
• The context for prioritization or response

Breaking the Cycle: What Proactive Looks Like

Identity-centric intelligence allows defenders to act before stolen credentials become incidents:

• Credential Pivoting: Search for reuse across other leaks and malware logs.
• Infostealer Correlation: Determine if credentials came from malware and link to infection vectors.
• Risk Scoring: Use context-aware scoring to flag risky credentials before they’re abused.

Example: Stopping an Infostealer Chain Reaction

Imagine a CISO receives an alert: the CFO’s corporate email and VPN password were found in a fresh infostealer log. Instead of waiting for signs of compromise, the security team can:

• Reset credentials immediately
• Investigate the endpoint for signs of infection
• Monitor for impersonation attempts on executive email and LinkedIn

From Reactive to Resilient

The credential lifecycle doesn’t stop at the breach. It ends when you stop it. By using proactive identity signals, security teams can:

• Shrink their credential attack surface
• Spot identity risk early
• Disrupt ransomware and fraud operations before access is used

Want to see how identity signals can disrupt the breach-to-breach cycle? Download The Identity Intelligence Playbook today.

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Executive Team’s Digital Footprint Exposure Is Real

Executives, board members, and other high-profile users carry more than just influence – they carry risk. With access to strategic assets, critical systems, and high-trust communications, these individuals are prime targets for threat actors. And in the age of oversharing, infostealers, and deepfakes, an executive’s digital footprint becomes a high-value entry point.

Why Are Executives Targeted So Aggressively?

These individuals have sprawling digital identities – corporate emails used across third-party sites, public speaking engagements, social media presence, travel announcements, and more. Attackers use this abundance of information to:

• Craft spear-phishing and impersonation campaigns
• Hijack personal and professional accounts
• Deploy infostealers to silently harvest credentials and cookies from executive devices

And unfortunately, even the most tech-savvy leaders fall into predictable patterns. Password reuse, lack of MFA, and device exemptions for frictionless access all make them vulnerable.

When Human Behavior Meets Cybercrime

Let’s get specific. Here’s how executive exposure has turned into real-world breaches:

• Mark Zuckerberg: His Twitter and Pinterest accounts were hijacked using a password (“dadada”) leaked in the 2012 LinkedIn breach. This wasn’t just about access—it was reputational damage.
• Colonial Pipeline: An inactive VPN account with a reused password—found in a breach—enabled one of the most high-profile ransomware attacks in U.S. history. MFA wasn’t enabled. The result? A fuel supply disruption across the Eastern U.S.
• Voice-Cloning Fraud: In 2019, cybercriminals used deepfake voice technology to impersonate a CEO’s voice, instructing a subordinate to wire $243K to a fraudulent account. The voice sounded real enough that no suspicion was raised—until it was too late.

The Deepfake Era Has Arrived

What used to be phishing emails has now evolved into:

• Deepfaked video and voice impersonations
• Fake Teams and Zoom meetings with AI-generated faces
• Spoofed WhatsApp messages that mimic executive tone and context

Security teams are facing not just technical exploits but psychological manipulation – crafted from breached data and AI tooling. And executives are the preferred channel for this high-leverage social engineering.

Infostealers Targeting Executive Endpoints

Threat actors know where the value lies. Infostealers like Raccoon, RedLine, and Vidar are mass-deployed to capture saved logins, cookies, and autofill data. Executive devices, often used across corporate and personal workflows, become low-friction, high-yield targets.

These logs are bundled and sold on dark web markets like Russian Market or Genesis, sometimes specifically filtered for domains like yours. One CISO’s nightmare? Seeing their CEO’s corporate login and session token available for $100 to the highest bidder.

How to Defend What Matters Most

Identity-centric digital risk intelligence provides visibility that traditional tools lack. Constella’s digital risk intelligence platform helps you:

• Continuously monitor executive credentials across breach dumps, infostealer logs, and dark web forums
• Detect impersonation attempts – email spoofing, social profile cloning, or deepfake media
• Apply identity risk scoring to high-privilege individuals to drive priority response

Final Thought
Executives won’t stop being high-value targets. But with the right visibility, proactive detection, and identity-centric alerts, you can stop their exposure from becoming your next breach.

Protect the people who protect your company. Download The Identity Intelligence Playbook today.

The Power of One: From Leaked Credential to Campaign Attribution

Attribution has always been the elusive prize in threat intelligence. The question every CISO wants answered after an attack: “Who did this?” Historically, attribution required heavy resources, deep visibility, and sometimes even luck. But in today’s world of digital risk intelligence, one leaked credential can be the thread that unravels an entire threat network.

In this blog, we explore how modern identity-centric intelligence, powered by breached data, infostealer logs, and automation, can link alias to alias, handle to hackers, and turn a compromised credential into a clear picture of adversary behavior.

The Human Flaw Behind the Keyboard

Cybercriminals may have sophisticated tools and anonymization methods—but they’re still human. And humans make mistakes. They reuse credentials across forums. They use the same Jabber ID or password for years. In the cat-and-mouse game of cyber defense, even one slip-up can be enough to expose an entire operation.

Let’s break down three real-world cases that illustrate this point:

Case 1: A Jabber ID Exposes a 15-Year Operation

The threat actor behind Golden Chickens malware-as-a-service—known as Jack, VENOM SPIDER, or LUCKY—operated in the shadows for over a decade. But Jack reused the same Jabber ID across multiple forums and channels. Investigators from eSentire connected this ID to 15 years of posts, private messages, and aliases. This single identifier allowed researchers to trace Jack’s tactics, infrastructure, and, ultimately, his real-world identity.

Case 2: The Hacker Who Infected Himself In a twist of irony, the actor known as La_Citrix infected his own machine with infostealer malware. That malware did what it was built to do: steal credentials, autofill data, browser cookies, and more. When that data showed up in an infostealer log dump, researchers realized what they were looking at. They used the recovered credentials and accounts to map La_Citrix’s criminal footprint across forums like Exploit.in. One misstep—one accidental infection—and his entire operation was exposed.

Case 3: A Reused Email Takes Down AlphaBay Alexandre Cazes, administrator of AlphaBay (once the largest dark web marketplace), used a personal email address—pimp_alex_91@hotmail.com—for system-generated emails. When a welcome message to new users contained that email in the header, investigators traced it to his real identity. One reused email address was enough to connect his online persona to his real-world self.

Pivoting to Attribution: From Clue to Confidence

These stories share a pattern: one piece of identity data exposed across breach datasets, forums, or malware logs becomes the jumping-off point for attribution. With modern tools and the right dataset, analysts can automate these pivots:

• Alias → Breach data → Forum handles
• Email → Info-stealer log → Saved accounts and behavior
• Password reuse → Cross-platform identity mapping

Why This Matters for CISOs and Threat Intel Teams

Attribution isn’t just about “naming and shaming.” It has a real security impact:

• Link incidents across time and infrastructure
• Predict future targets and attacker behavior
• Strengthen defenses against repeat offenders
• Aid law enforcement and intelligence-sharing

Modern identity-centric platforms like Constella make this practical. With one leaked credential, you can:

• Query a trillion-point breach data lake
• Automate pivots across leaked logs
• Visualize the identity graph that ties aliases together

Want to turn digital breadcrumbs into actionable attribution? Download The Identity Intelligence Playbook today.