Account Recovery Is Becoming the New Identity Attack Surface

As passkeys and phishing-resistant authentication reduce password risk, attackers will move pressure to the recovery plane.

The industry is moving in the right direction.

Passkeys, FIDO2/WebAuthn, hardware security keys, conditional access, better MFA policies, and risk-based sign-in controls are all meaningful improvements. They reduce entire classes of credential theft. They make phishing harder. They remove reusable passwords from many authentication ceremonies. They shift more of the security burden from user judgment to protocol design.

That is good.

But it is not the finish line.

In my recent passkeys article, I called out a point that deserves its own treatment: passkeys do not solve weak account recovery, help desk social engineering, stolen session tokens, OAuth consent abuse, unmanaged vendor access, or excessive privilege. They are a major step forward, but they do not remove the rest of the identity attack surface. 

That matters because attackers adapt.

If passwords become harder to steal, guess, spray, reuse, or phish, attackers will apply pressure somewhere else. They will go where the assurance is weaker, the workflows are more manual, the exceptions are more frequent, and the blast radius is still large.

Increasingly, that place is account recovery.

PassKey

The Inversion Test

A useful way to think about this is inversion.

Do not start with the defender’s roadmap. Start with the attacker’s question:

Once passwords disappear, where would I attack next?

The answer is usually not exotic.

I would attack the process that lets a user back into the account after they lose the device.

I would attack the support workflow that removes an authenticator.

I would attack the exception path that grants temporary access.

I would attack the SaaS admin who can approve OAuth grants.

I would attack the vendor portal that still uses email-based recovery.

I would steal a browser session instead of a password.

I would enroll a new device.

I would persuade the help desk to do for me what the authentication system will not.

That is the problem.

Authentication is getting stronger, but recovery is often still treated like customer service, not like privileged access.

The Recovery Plane Is Bigger Than Password Reset

When many teams hear “account recovery,” they think about password reset.

That definition is too narrow.

The recovery plane includes every path that can restore, replace, bypass, reset, re-enroll, approve, or extend access after normal authentication fails or becomes inconvenient.

That includes:

  • Password reset and account unlock workflows
  • MFA reset
  • Authenticator removal
  • Passkey re-enrollment
  • Lost phone and device replacement processes
  • Temporary access passes
  • Emergency access procedures
  • Help desk verification scripts
  • Vendor support portals
  • OAuth consent grants
  • Long-lived sessions
  • Break-glass accounts
  • Shared accounts
  • Offboarding workflows

That is a lot of surface area.

It is also where many organizations have the least visibility.

They can tell you how many users enrolled a passkey. They can tell you how many privileged users have hardware keys. They can show a nice adoption dashboard.

But ask how many privileged recovery events occurred last quarter, how many required human exception, how often callbacks used known-good numbers, how many OAuth grants have offline access, or how many vendor admins can recover access without the organization’s IdP, and the room gets quieter.

That is not because security teams do not care.

It is because the measurements have not caught up to the new risk.

Passkey Adoption Is Not the Same as Recovery Risk Reduction

Most passkey programs measure adoption.

That is understandable. Adoption matters. A phishing-resistant authenticator that nobody uses is not a control; it is a feature sitting idle.

But adoption alone can become a vanity metric.

A dashboard that says “82% of users have enrolled passkeys” may look good while the recovery plane remains weak. A privileged administrator may have a hardware key and still be vulnerable if a support agent can remove that key after a convincing phone call. A finance user may authenticate with a passkey and still have an OAuth grant that allows a third-party application to read mail and files. A SaaS admin may have phishing-resistant login and still carry a session token that can be replayed from an infected endpoint.

In other words, the front door can improve while the side doors remain unchanged.

The right question is not only:

How many users have passkeys?

The better question is:

Can an attacker still recover, re-enroll, delegate, or persist access without satisfying the same level of assurance we require at login?

That question changes the program.

Why Attackers Like Recovery Paths

Recovery paths are attractive because they are designed for failure.

Users lose phones. Laptops die. Executives travel. Hardware keys get left at home. Contractors change devices. Mergers bring strange identity histories. Help desks are measured on resolution time. Business units want access restored now. Support teams are asked to be helpful, empathetic, and fast.

Attackers understand this.

They do not need to defeat your strongest control if they can trigger a workflow that temporarily removes it. They do not need a zero-day if they can convince a support agent that the CFO is locked out before payroll closes. They do not need to phish a password if a malicious OAuth application can be granted the right permissions. They do not need to reauthenticate if a stolen session or refresh token remains valid.

This is second-order identity risk.

The first-order improvement is passwordless authentication.

The second-order attacker response is pressure on the lifecycle around authentication.

That is where many programs are underbuilt.

Help Desks Are Now Part of the Identity Control Plane

Help desk directors should be in the room for passkey planning.

Not after rollout.

Before rollout.

The support function is no longer just a service channel. In a passwordless environment, it becomes one of the places where identity assurance is either preserved or quietly downgraded.

When a support agent removes an authenticator, issues a temporary access pass, resets MFA, unlocks an account, updates a phone number, or approves device replacement, that agent may be changing the effective security posture of the identity.

For normal users, that can still matter.

For privileged users, it can be catastrophic.

Scattered Spider is a useful warning here. CISA has described the group’s use of social engineering to convince IT help desk personnel to reset passwords and MFA tokens, and CISA’s mitigation guidance emphasizes phishing-resistant MFA such as FIDO/WebAuthn. 

The broader lesson is that support and recovery workflows can become identity attack paths when attackers cannot easily defeat the primary login ceremony.

The lesson is simple: recovery for privileged users should not be a normal ticket.

It should be a controlled ceremony.

That means strong proofing, out-of-band verification using known-good contact information, two-person approval, time-bound access, explicit logging, alerting to security operations, and post-event review.

It also means the help desk needs permission to slow down when risk is high.

“Fast resolution” cannot be the only service metric when the request changes identity assurance.

Fallback Methods Are the Old Attack Surface Wearing a New Name

Fallback methods are often kept for good reasons.

They reduce lockouts. They make pilots easier. They help executives. They make support less painful. They allow legacy applications to keep working. They reduce friction for BYOD and remote users.

But they also preserve the attack surface that passkeys were meant to reduce.

SMS, voice OTP, email OTP, TOTP, push approval, security questions, personal email recovery, and “call the help desk” workflows can become the weakest link in an otherwise strong authentication program.

That does not mean every fallback disappears on day one.

It means fallback must be governed by risk tier, not convenience.

For privileged users, weak fallback should be removed first.

For high-risk business users, fallback should be limited, logged, and reviewed.

For standard users, fallback should be transitional and measured.

For vendors, fallback should be part of the access contract.

For break-glass accounts, fallback should be designed, vaulted, monitored, and tested.

Do not let fallback become the permanent exception nobody owns.

Device Replacement Is a Security Event

Passkeys change the device lifecycle.

If the authenticator is a phone, laptop, platform credential, password manager, sync fabric, or hardware key, then device loss and device replacement become security-sensitive workflows.

A new phone is not just a new phone.

It may be the path to a new authenticator.

A laptop rebuild is not just an endpoint ticket.

It may become a passkey re-enrollment event.

A password manager recovery is not just a user convenience problem.

It may restore access to synced credentials.

NIST’s current SP 800-63B language draws an important assurance distinction here: syncable authenticators are not allowed at AAL3 because syncing requires the private key to be exportable, while AAL3 requires stronger hardware-protected key handling. 

That distinction should shape enterprise recovery design.

The organization should know which authenticators are allowed for which risk tiers, whether credentials are synced or device-bound, how many authenticators each user must maintain, what happens when one is lost, and who can approve replacement.

For high-risk roles, device replacement should trigger stronger checks than normal sign-in.

If the attacker’s goal is to become the new device, then treating new-device enrollment as routine is a mistake.

OAuth Grants Are Recovery’s Cousin

OAuth consent is not account recovery in the traditional sense, but it belongs in the same risk conversation.

Why?

Because OAuth grants can create durable delegated access that survives the user’s normal login ceremony. In many attacks, the adversary does not need the password. The user is tricked into granting a malicious or compromised application access to mail, files, contacts, or other SaaS data. The attacker then operates through authorized application access rather than a classic interactive login.

Microsoft describes consent phishing as an attack where users are tricked into granting permissions to malicious cloud applications, allowing those applications to access legitimate cloud services and user data. Microsoft also recommends auditing applications and consented permissions, limiting user consent, and monitoring suspicious application behavior. 

Red Canary describes application access token theft as a technique adversaries use to gain unauthorized access to SaaS, cloud, and containerized resources, including through OAuth consent grant attacks. 

That is an identity bypass from a governance point of view.

If your passkey program does not include connected-app review, admin consent workflows, publisher verification, permission classification, and revocation procedures, then you have left a major identity path out of scope.

This is especially important in Microsoft 365, Google Workspace, Salesforce, GitHub, Slack, Box, Dropbox, and other SaaS-heavy environments where business productivity depends on integrations.

Security teams should ask:

  • Who can consent to applications?
  • Which grants include mail, files, directory, impersonation, or offline access?
  • Which applications are publisher verified?
  • Which grants are unused, stale, or excessive?
  • Which service principals have tenant-wide reach?
  • How quickly can suspicious consent be revoked?
  • Are OAuth changes visible in the SIEM?

Do not celebrate passwordless authentication while ignoring delegated access.

Sessions Are Where Authentication Becomes Authorization

Another uncomfortable point: authentication strength does not automatically protect the entire session.

After authentication succeeds, applications issue session tokens, cookies, and refresh tokens. Those artifacts often become the practical proof that the user is already trusted. If malware, a phishing proxy, browser compromise, or endpoint theft captures that token, the attacker may be able to bypass the login ceremony entirely.

Ping Identity describes session hijacking as reuse of a stolen session token to impersonate a logged-in user; because the attack occurs after login, MFA may already be satisfied. 

Microsoft has also published guidance on cloud token theft, including prevention, detection, and response considerations for token-based attacks. 

That is why session governance belongs in the passkey roadmap.

Shorter session lifetimes, device compliance, token binding where available, continuous access evaluation, impossible travel detection, user-agent and device mismatch analytics, rapid revocation, EDR coverage, browser hardening, and SaaS session visibility all matter.

Passkeys reduce credential theft.

They do not make stolen sessions harmless.

A Recovery-Plane Risk Score

Organizations need a way to score recovery paths the same way they score applications, data, vendors, and vulnerabilities.

Here is a practical model.

Factor Question High-Risk Signal
Proof strength How strongly does the process verify the person requesting recovery? Email access, caller ID, personal information, or manager approval alone.
Social-engineering exposure Can a human be pressured into overriding controls? Phone-only recovery, urgent executive exceptions, vague escalation rules.
Exception frequency How often is the standard process bypassed? Frequent temporary access, recurring VIP exceptions, non-expiring risk acceptances.
Blast radius What can the recovered account access? Admin roles, finance workflows, HR data, developer systems, mailboxes, cloud consoles.
Persistence Does recovery create long-lived access? Refresh tokens, remembered devices, OAuth grants, persistent sessions, new authenticators.
Visibility Can security see and investigate the event? No SIEM logging, no alerting, limited ticket context, SaaS-only logs.
Ownership Who governs the path? No control owner, no review cadence, split responsibility between IAM and support.

Score each recovery path from 1 to 5 on each factor.

Then multiply or weight by user tier.

A recovery path for a standard user with limited SaaS access is not the same as a recovery path for a global admin, payroll approver, domain admin, developer with production access, or vendor administrator.

Do not flatten the organization.

Risk is not evenly distributed. Recovery controls should not be either.

What Leaders Should Measure

CISOs and IAM leaders should add recovery-plane metrics to identity dashboards.

At minimum, track:

  • Recovery events by user tier
  • Authenticator resets and removals
  • New authenticator enrollments
  • Temporary access passes
  • Privileged recovery exceptions
  • Help desk recovery requests denied or escalated
  • Recovery events outside business hours
  • Users with fewer than two approved authenticators
  • Weak fallback still enabled by tier
  • OAuth grants by risk level
  • Long-lived session exceptions
  • Third-party accounts without phishing-resistant authentication
  • Vendor support paths that bypass the primary IdP
  • Open recovery exceptions by owner and expiration date

The executive dashboard should answer a plain question:

Can someone get back into a high-risk account through a process weaker than the process required to sign in?

If the answer is yes, the organization has work to do.

A Practical 90-Day Plan

Days 0–30: Inventory the Recovery Plane

Start with the systems that matter most:

  • IdP
  • Email
  • Endpoint management
  • PAM
  • Cloud consoles
  • Finance systems
  • HR systems
  • Developer platforms
  • Backup consoles
  • EDR
  • SIEM
  • Ticketing
  • Major SaaS applications

For each system, document:

  • Normal authentication method
  • Recovery method
  • Fallback methods
  • Approval path
  • Required proof
  • Generated logs
  • Alerts
  • Temporary access lifetime
  • Post-recovery review process

Do not start by buying another tool.

Start by finding the paths.

Days 31–60: Harden High-Risk Recovery

Prioritize administrators, executives, finance, HR, developers, help desk staff, security staff, and third parties with privileged or sensitive access.

For those users:

  • Require at least two approved authenticators before enforcement.
  • Remove weak fallback where feasible.
  • Require device-bound passkeys or hardware keys for privileged access.
  • Implement two-person approval for privileged authenticator reset.
  • Use known-good callback procedures.
  • Alert on authenticator removal and re-enrollment.
  • Require post-recovery review for high-risk accounts.

This is also the time to train the help desk on adversarial recovery scenarios.

Not generic security awareness.

Specific scripts.

Specific red flags.

Specific escalation authority.

The help desk needs to know when a request is no longer just a request.

It is a security event.

Days 61–90: Govern Tokens, Grants, Vendors, and Exceptions

Once the human recovery paths are under control, expand to adjacent identity persistence.

Review OAuth grants and connected applications.

Restrict user consent for higher-risk permissions.

Implement admin consent workflows.

Review refresh token and session lifetime policies.

Test rapid session revocation.

Identify vendor-controlled recovery paths.

Require phishing-resistant MFA for vendors with privileged access.

Publish an exception register with owners and expiration dates.

Run a tabletop exercise against recovery abuse.

The tabletop should be blunt:

An attacker has convinced the help desk to remove MFA from a finance administrator. What alerts fire? Who knows? How fast can we revoke sessions, disable OAuth grants, suspend the account, preserve evidence, and determine blast radius?

If that exercise feels uncomfortable, good.

That is the point.

Policy Baseline Language

Here is practical language to adapt:

Account recovery, authenticator reset, passkey registration, passkey removal, device replacement, temporary access issuance, OAuth consent approval, and session revocation are security-sensitive identity lifecycle events. These events must be governed by risk tier, verified using approved proofing methods, logged centrally, monitored for abuse, and reviewed for privileged or high-impact users. Recovery processes must not allow access to be restored through a weaker assurance path than the access being recovered without documented, time-bound risk acceptance.

That last sentence is the core principle.

Do not let recovery be weaker than login.

Where Compliance and Risk Teams Fit

Compliance teams should pay attention because recovery-plane risk creates evidence problems.

When auditors ask whether privileged access is controlled, the answer cannot stop at:

We require MFA.

The next questions are predictable:

  • How is MFA reset?
  • Who can approve a reset?
  • Are approvals logged?
  • Can support staff bypass the policy?
  • Are exceptions time-bound?
  • Are recovery events reviewed?
  • Are vendor recovery paths included?
  • Are OAuth grants reviewed?
  • Can sessions be revoked?

Those are not theoretical questions.

They are control design questions.

They are also incident response questions.

A mature identity program should be able to produce evidence for recovery events the same way it produces evidence for access reviews, privileged access approvals, and policy exceptions.

The Bottom Line

Passkeys are a real improvement.

Phishing-resistant authentication is worth doing.

Hardware keys for privileged users are worth the operational effort.

Conditional access, MFA cleanup, passkey rollout roadmaps, and fallback reduction all matter.

But the next identity fight is not only at login.

It is in recovery.

It is in help desk workflows.

It is in device replacement.

It is in OAuth consent.

It is in session persistence.

It is in vendor support paths.

It is in the exception process.

Attackers follow pressure. As the password attack surface shrinks, the recovery attack surface becomes more valuable.

So build for that reality now.

Measure recovery-plane risk.

Score recovery paths by proof strength, social-engineering exposure, exception frequency, persistence, visibility, ownership, and blast radius.

Harden the workflows that can restore high-impact access.

Give the help desk better procedures and the authority to use them.

Govern OAuth and sessions as part of identity, not as unrelated SaaS hygiene.

Treat vendor access and support recovery as part of the enterprise control plane.

The goal is not to make recovery impossible.

People will lose devices. Executives will travel. Hardware will fail. Business will need continuity.

The goal is to make recovery trustworthy.

Because in a passwordless world, the attacker does not need your password if they can become your recovery event.

More Information and Assistance

At MicroSolved, Inc., we help organizations move from security intentions to operational reality. If you are rolling out passkeys, hardening MFA, modernizing IAM, or trying to understand whether your recovery plane is becoming your weakest identity control, we can help.

MicroSolved can assist with:

  • Identity architecture assessments
  • Passkey and phishing-resistant authentication roadmaps
  • Account recovery and help desk workflow hardening
  • OAuth grant and SaaS identity reviews
  • Privileged access and vendor access risk reduction
  • Identity logging and SIEM use-case development
  • Tabletop exercises and adversarial simulations focused on recovery abuse
  • Executive dashboards for identity risk reduction

Contact MicroSolved at +1.614.351.1237 or info@microsolved.com.

Relax. We’re on watch.

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

Recalibrating Cyber Risk in a Geopolitical Era: A Bayesian Wake‑Up Call

The cyber landscape doesn’t evolve. It pivots. In recent months, shifting signals have upended our baseline assumptions around geopolitical cyber risk, OT/edge security, and the influence of AI. What we believed to be emerging threats are now pressing realities.

ChatGPT Image Jun 19 2025 at 11 28 16 AM

The Bayesian Recalibration

New data forces sharper estimates:

  • Geopolitical Spillover: Revised from ~40% to 70% – increasingly precise cyberattacks targeting U.S. infrastructure.
  • AI‑Driven Attack Dominance: Revised from ~50% to 85% – fueled by deepfakes, polymorphic malware, and autonomous offensive tools.
  • Hardware & Edge Exploits: Revised from ~30% to 60% – threats embedded deep in physical systems going unnoticed.

Strategic Imperatives

To align with this recalibrated threat model, organizations must:

  1. Integrate Geopolitical Intelligence: Tie cyber defenses to global conflict zones and state-level actor capabilities.
  2. Invest in Autonomous AI Defenses: Move beyond static signatures—deploy systems that learn, adapt, and respond in real time.
  3. Defend at the OT/Edge Level: Extend controls to IoT, industrial systems, medical devices, and field hardware.
  4. Fortify Supply‑Chain Resilience: Assume compromise—implement firmware scanning, provenance checks, and strong vendor assurance.
  5. Join Threat‑Sharing Communities: Engage with ISACs and sector groups—collective defense can mean early detection.

The Path Ahead

This Bayesian lens widens our aperture. We must adopt multi‑domain vigilance—digital, physical, and AI—even as adaptation becomes our constant. Organizations that decode subtle signals, recalibrate rapidly, and deploy anticipatory defense will not only survive—they’ll lead.

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

AI in Cyberattacks: A Closer Look at Emerging Threats for 2025

 

The complex interplay between technological advancement and cyber threats is reaching unprecedented heights. As artificial intelligence (AI) evolves, it presents both transformative opportunities and significant perils in the realm of cyberattacks. Cybercriminals are leveraging AI to devise more sophisticated and cunning threats, shifting the paradigm of how these dangers are understood and countered.

RedHacker3

AI’s influence on cyberattacks is multifaceted and growing in complexity. AI-powered tools are now utilized to develop advanced malware and ransomware, enhance phishing tactics, and even create convincing deepfakes. These advancements foreshadow a challenging landscape by 2025, as cybercriminals sharpen their techniques to exploit vulnerabilities in ubiquitous technologies—from cloud computing to 5G networks.

In response to the evolving threat landscape, our methods of defense must adapt accordingly. The integration of AI into cybersecurity strategies offers powerful countermeasures, providing innovative ways to detect, deter, and respond decisively to these high-tech threats. This article explores the emerging tactics employed by cybercriminals, the countermeasures under development, and the future prospects of AI in cybersecurity.

The Role of AI in Cyberattacks

As we approach 2025, the landscape of cyber threats is increasingly shaped by advancements in artificial intelligence. AI is revolutionizing the way cyberattacks are conducted, allowing for a level of sophistication and adaptability that traditional methods struggle to compete with. Unlike conventional cyber threats, which often follow predictable patterns, AI-driven attacks are dynamic and capable of learning from their environment to evade detection. These sophisticated threats are not only more difficult to identify but also require real-time responses that traditional security measures are ill-equipped to provide. As AI continues to evolve, its role in cyberattacks becomes more pronounced, highlighting the urgent need for integrating AI-driven defenses to proactively combat these threats.

AI as a Tool for Cybercriminals

AI has significantly lowered the barrier to entry for individuals looking to engage in cybercrime, democratizing access to sophisticated tools. Even those with minimal technical expertise can now launch advanced phishing campaigns or develop malicious code, thanks to AI’s ability to automate complex processes. This technology also allows cybercriminals to launch adaptive attacks that grow more effective over time, challenging traditional cybersecurity defenses. AI plays a critical role in the emergence of Cybercrime-as-a-Service, where even unskilled hackers can rent AI-enhanced tools to execute complex attacks. Additionally, machine learning models enable faster and more efficient password cracking, giving cybercriminals an edge in breaking into secure systems.

AI-Driven Malware and Ransomware

AI-driven malware is reshaping the threat landscape by making attacks more efficient and harder to counter. Ransomware, enhanced by AI, automates the process of identifying data and optimizing encryption, which poses significant challenges for mitigation efforts. Malicious GPTs, or modified AI models, can generate complex malware and create supportive materials like fake emails, enhancing the efficacy of cyberattacks. The rise of AI-driven Cybercrime-as-a-Service in 2025 allows less experienced hackers to wield powerful tools, such as ransomware-as-a-service, to launch effective attacks. Self-learning malware further complicates security efforts, adapting seamlessly to environments and altering its behavior to bypass traditional defenses, while AI-driven malware utilizes automated DDoS campaigns and sophisticated credential-theft techniques to maximize impact.

Enhancing Phishing with AI

Phishing attacks, a longstanding cyber threat, have become more sophisticated with the integration of AI. This technology enables the creation of highly personalized and convincing phishing emails with minimal manual effort, elevating the threat to new heights. AI’s ability to process large datasets allows it to craft messages that are tailored to individual targets, increasing the likelihood of successful infiltration. As these attacks become more advanced, traditional email filters and user detection methods face significant challenges. Preparing for these AI-enhanced threats necessitates a shift towards more proactive and intelligent security systems that can detect and neutralize adaptive phishing attacks in real-time.

The Threat of Deepfakes

Deepfakes represent a growing challenge in the cybersecurity domain, harnessing AI to create realistic impersonations that can deceive users and systems alike. As AI technology advances, these synthetic audio and video productions become increasingly difficult to distinguish from authentic content. Cybercriminals exploit deepfakes for purposes such as misinformation, identity theft, and reputational damage, thereby eroding trust in digital platforms. Organizations must use AI-based detection tools and educate employees on identifying these sophisticated threats to maintain their digital integrity. Furthermore, the rise of AI-powered impersonation techniques complicates identity verification processes, necessitating the development of new strategies to validate authenticity in online interactions.

Emerging Tactics in AI-Driven Attacks

In 2025, AI-driven cyberattacks are poised to escalate significantly in both scale and sophistication, presenting formidable challenges for detection and mitigation. Malicious actors are capitalizing on advanced algorithms to launch attacks that are not only more efficient but also difficult to counteract. Their adaptability enables these attacks to dynamically adjust to the defenses deployed by their targets, thus enhancing their effectiveness. AI systems can analyze vast quantities of data in real-time, allowing them to identify potential threats before they fully materialize. Consequently, the cybersecurity industry is intensifying efforts to integrate AI into security measures to predict and counter these threats proactively, ensuring that security teams are equipped to manage the rapidly evolving threat landscape.

Understanding AI Phishing

AI phishing attacks have transformed the cyber threat landscape by leveraging generative AI to create communications that appear exceedingly personalized and realistic. These communications can take the form of emails, SMS messages, phone calls, or social media interactions, often mimicking the style and tone of trusted sources to deceive recipients. Machine learning empowers these attacks by allowing them to evade traditional security measures, making them more challenging to detect. AI-driven phishing schemes can automate the entire process, providing outcomes similar to human-crafted attacks but at a significantly reduced cost. As a result, a notable increase in sophisticated phishing incidents has been observed, impacting numerous organizations globally in recent years.

Transition to Vishing (Voice Phishing)

Emerging as a novel threat, vishing or voice phishing employs AI to enhance the traditional scams, enabling wider and more efficient campaigns with minimal manual input. This method intensifies the effectiveness and sophistication of attacks, as AI-driven vishing can dynamically adjust to the defenses of targets. Unlike traditional, static cyber attacks, AI-enhanced vishing scams modify their tactics on-the-fly by monitoring defenses in real-time, making them harder to identify and mitigate. As this threat continues to evolve, businesses must employ proactive AI-driven defenses that can anticipate and neutralize potential vishing threats before they inflict damage. The incorporation of AI-driven security systems becomes vital in predicting and countering these evolving cyber threats.

Exploiting Zero-Day Vulnerabilities

AI-enabled tools are revolutionizing vulnerability detection by quickly scanning extensive codebases to identify zero-day vulnerabilities, which pose significant risks due to their unpatched nature. These vulnerabilities provide an open door for exploit that threat actors can use, often generating automated exploits to take advantage of these weaknesses rapidly. Concerns are growing that the progression of AI technologies will allow malicious actors to discover zero-day vulnerabilities with the same proficiency as cybersecurity professionals. This development underscores the importance of programs like Microsoft’s Zero Day Quest bug bounty, aiming to resolve high-impact vulnerabilities in cloud and AI environments. The rapid escalation of AI-driven zero-day phishing attacks means that defenders have a narrower window to react, necessitating robust response systems to address cybersecurity challenges effectively.

Targeting Cloud Environments

Cloud environments are becoming increasingly susceptible to AI-driven cyberattacks, which employ machine learning to circumvent standard protections and breach cloud systems. The sophistication of AI-powered impersonation necessitates enhanced identity verification to safeguard digital identities. Organizations must therefore integrate AI-driven defenses capable of identifying and neutralizing malicious activities in real-time. AI-assisted detection and threat hunting are instrumental in recognizing AI-generated threats targeting these environments, such as synthetic phishing and deepfake threats. With cloud infrastructures being integral to modern operations, adopting proactive AI-aware cybersecurity frameworks becomes essential to anticipate and thwart potential AI-driven intrusions before they cause irreparable harm.

Threats in 5G Networks

The expansion of IoT devices within 5G networks significantly enlarges the attack surface, presenting numerous unsecured entry points for cyber threats. Unauthorized AI usage could exploit these new attack vectors, compromising vital data security. In this context, AI-powered systems will play a crucial role in 2025 by utilizing predictive analytics to identify and preempt potential threats in real-time within 5G infrastructures. Agentic AI technologies offer tremendous potential for improving threat detection and neutralization, securing 5G networks against increasingly sophisticated cyber threats. As the threat landscape continues to evolve, targeting these networks could result in a global cost burden potentially reaching $13.82 trillion by 2032, necessitating vigilant and innovative cybersecurity measures.

Countermeasuring AI Threats with AI

As the cyber threat landscape evolves, organizations need a robust defense mechanism to safeguard against increasingly sophisticated AI-driven threats. With malicious actors utilizing artificial intelligence to launch more complex and targeted cyberattacks, traditional security measures are becoming less effective. To counter these AI-driven threats, organizations must leverage AI-enabled tools to automate security-related tasks, including monitoring, analysis, and patching. The use of such advanced technologies is paramount in identifying and remediating AI-generated threats. The weaponization of AI models, evident in dark web creations like FraudGPT and WormGPT, underscores the necessity for AI-aware cybersecurity frameworks. These frameworks, combined with AI-native solutions, are crucial for dissecting vast datasets and enhancing threat detection capabilities. By adopting AI-assisted detection and threat-hunting tools, businesses can better handle synthesized phishing content, deepfakes, and other AI-generated risks. The integration of AI-powered identity verification tools also plays a vital role in maintaining trust in digital identities amidst AI-driven impersonation threats.

AI in Cyber Defense

AI is revolutionizing the cybersecurity industry by enabling real-time threat detection and automated responses to evolving threats. By analyzing large volumes of data, AI-powered systems can identify anomalies and potential threats, providing a significant advantage over traditional methods. Malicious actors may exploit vulnerabilities in existing threat detection frameworks by using AI agents, but the same AI technologies can also strengthen defense systems. Agentic AI enhances cybersecurity operations by automating threat detection and response processes while retaining necessary human oversight. Moreover, implementing advanced identity verification that includes multi-layered checks is crucial to counter AI-powered impersonation, ensuring the authenticity of digital communications.

Biometric Encryption Innovations

Biometric encryption is emerging as a formidable asset in enhancing user authentication, particularly as cyber threats become more sophisticated. This technology leverages unique physical characteristics—such as fingerprints, facial recognition, and iris scans—to provide an alternative to traditional password-based authentication. By reducing reliance on static passwords, biometric encryption not only strengthens user authentication protocols but also mitigates the risk of identity theft and impersonation. As a result, businesses are increasingly integrating biometric encryption into their cybersecurity frameworks to safeguard against the dynamic landscape of cyber threats, minimizing potential vulnerabilities and ensuring more secure interactions.

Advances in Machine Learning for Cybersecurity

Machine learning, a subset of AI, is instrumental in transforming cybersecurity strategies, enabling rapid threat detection and predictive analytics. Advanced machine learning algorithms simulate attack scenarios to improve incident response strategies, providing cybersecurity professionals with enhanced tools to face AI-driven threats. While AI holds the potential to exploit vulnerabilities in threat detection models, it also enhances the efficacy of security teams by automating operations and reducing the attack surface. Investments in AI-enhanced cybersecurity solutions reflect a strong demand for robust, machine-learning-driven techniques, empowering organizations to detect threats efficiently and respond effectively in real time.

Identity and Access Management (IAM) Improvements

The integration of AI-powered security tools into Identity and Access Management (IAM) systems significantly bolsters authentication risk visibility and threat identification. These systems, critical in a digitized security landscape, enhance the foundation of cyber resilience by tackling authentication and access control issues. Modern IAM approaches include multilayered identity checks to combat AI-driven impersonations across text, voice, and video—recognizing traditional digital identity trust as increasingly unreliable. Role-based access controls and dynamic policy enforcement are pivotal in ensuring users only have essential access, preserving the integrity and security of sensitive systems. As AI-driven threats continue to advance, embracing AI capabilities within IAM systems remains vital to maintaining cybersecurity.

Implementing Zero-Trust Architectures

Zero-Trust Architecture represents a paradigm shift in cybersecurity by emphasizing least-privilege access and continuous verification. This model operates on the principle of never trusting, always verifying, where users and devices’ identities and integrity are continually assessed before access is granted. Such a dynamic approach ensures real-time security policy adaptation based on emerging threats and user behaviors. Transitioning to Zero-Trust minimizes the impact of breaches by compartmentalizing network resources, ensuring that access is granted only as necessary. This proactive strategy stresses the importance of continuous monitoring and data-driven analytics, effectively moving the focus from reactive measures to a more preemptive security posture, in anticipation of future AI-driven threats.

Preparing for AI-Enabled Cyber Threats

As we near 2025, the landscape of cyber threats is becoming increasingly complex, driven by advances in artificial intelligence. AI-enabled threats have the sophisticated ability to identify system vulnerabilities, deploy widespread campaigns, and establish undetected backdoors within infrastructures, posing a significant risk to data integrity and security. Cybersecurity professionals are finding these AI-driven threats challenging, as threat actors can exploit weaknesses in AI models, leading to novel forms of cybercrime. The critical need for real-time AI-driven defenses becomes apparent as businesses strive to recognize and neutralize malicious activities as they occur. Organizations must prioritize preparing for AI-powered cyberattacks to maintain resilience against these evolving threats. Traditional security measures are becoming outdated in the face of AI-powered cyberattacks, thus compelling security teams to adopt advanced technologies that focus on early threat detection and response.

Developing AI Resilience Strategies

The development of AI resilience strategies is essential as organizations prepare to counter AI-driven cyber threats. Robust data management practices, including data validation and sanitization, play a crucial role in maintaining data integrity and security. By leveraging AI’s power to monitor networks continuously, security teams gain enhanced visibility, allowing for the early detection of potential cyber threats. Preparing AI models by exposing them to various attack scenarios during training significantly increases their resilience against real-world adversarial threats. In this evolving threat landscape, integrating AI into cybersecurity strategies provides a notable advantage, enabling preemptive counteraction against emerging risks. AI-enabled agentic cybersecurity holds the promise of automating threat detection and response, thus reducing response time and alleviating the workload on security analysts.

Importance of Cross-Sector Collaborations

Cross-sector collaborations have become vital in adapting to the rapidly evolving AI-driven cyber threat landscape. Public-private partnerships and regional interventions provide a foundation for effective intelligence sharing and identifying new threats. These collaborations between tech companies, cybersecurity vendors, universities, and government agencies enhance cyber resilience and develop best practices. The collective efforts extend beyond individual organizational capabilities, leveraging a diverse expertise pool to tackle systemic cybersecurity challenges strategically. By fostering strong public-private cooperation, sectors can combat cybercrime through unified action, demonstrating the importance of cybersecurity as a strategic priority. Initiatives like the Centres’ collaboration with over 50 partners exemplify the power of alliances in combating AI-driven threats and fortifying cyber defenses.

Upgrading Security Infrastructures

The evolution of AI-driven threats necessitates a comprehensive upgrade of security infrastructures. Organizations must align their IT, security, procurement, and compliance teams to ensure effective modernization of their security measures. Strengthening identity security is paramount and involves deploying centralized Identity and Access Management (IAM), adaptive multi-factor authentication (MFA), and real-time behavioral monitoring. Implementing AI-powered solutions is essential for automating critical security tasks, such as monitoring, analysis, patching, prevention, and remediation. AI-native cybersecurity systems excel in leveraging vast datasets to identify patterns and automate responses, enhancing an organization’s defensive capabilities. As communication modes become more complex, multi-layered identity checks must account for AI-powered impersonation to ensure that verification processes remain secure and robust.

The Role of Continuous Monitoring and Response

Continuous monitoring and response are core components of modern cybersecurity strategies, particularly in the face of sophisticated AI-powered cyberattacks. AI-driven security systems significantly enhance this process by analyzing behavioral patterns to detect anomalies in real time. Automated incident response systems, using AI, can contain breaches much quicker than traditional human-led responses, allowing for more efficient mitigation of threats. The AI algorithms in these systems are designed to learn and evolve, adapting their strategies to effectively bypass static security defenses. As the complexity of attack vectors increases, the need for continuous monitoring becomes critical in adapting quickly to new threats. Advanced AI tools automate vulnerability scanning and exploitation, identifying zero-day and n-day vulnerabilities rapidly, thereby bolstering an organization’s ability to preempt and respond to cyber risks proactively.

The Future of AI in Cybersecurity

Artificial Intelligence (AI) is revolutionizing the field of cybersecurity, playing a pivotal role in enabling real-time threat detection, providing predictive analytics, and automating responses to the ever-evolving landscape of cyber threats. By 2025, the sophistication and scale of AI-driven cyberattacks are anticipated to significantly escalate, pressing organizations to deploy robust, AI-powered defense systems. The global market for AI in cybersecurity is on a path of remarkable growth, expanding from $15 billion in 2021 to a projected $135 billion by 2030. AI technologies are transforming the cybersecurity industry by allowing businesses to pinpoint vulnerabilities far more efficiently than traditional security measures. In this battleground of cybersecurity, AI is not only a tool for defenders but also a weapon for attackers, as both sides leverage AI to enhance their strategies and respond to emerging threats.

Predictions for 2025 and Beyond

The integration of AI into cybersecurity is predicted to greatly enhance threat detection and mitigation abilities by processing extensive data in real-time, enabling swift responses to potential threats. The financial burden of global cybercrime is expected to rise drastically, from an estimated $8.15 trillion in 2023 to $11.45 trillion by 2026, potentially reaching $13.82 trillion by 2027. The increasing impact of AI-powered cyber threats is acknowledged by 78% of Chief Information Security Officers, who report its significant influence on their organizations. To counteract these threats, it’s critical for organizations to cultivate a security-first culture by 2025, incorporating AI-specific cybersecurity training and incident response drills. The accelerating sophistication of AI-driven cyberattacks is reshaping the cybersecurity landscape, creating an imperative for proactive, AI-driven defense strategies. This evolution demands that cybersecurity professionals remain vigilant and adaptive to stay ahead of malicious actors who are constantly innovating their attack methods.

Ethical Implications and Challenges

As AI becomes broadly available, it presents both exciting opportunities and significant risks within the cybersecurity domain. The potential for AI-driven methods to be manipulated by threat actors introduces new vulnerabilities that must be meticulously managed. Balancing the implementation of AI-driven security measures with the ethical necessity for human oversight is crucial in preventing the unauthorized exploitation of AI capabilities. As these technologies advance, ethical challenges emerge, particularly in the context of detecting zero-day vulnerabilities, which can be used exploitatively by both defenders and attackers. Effective mitigation of AI-driven cyberattacks requires an equilibrium between technological innovation and ethical policy development, ensuring that AI is not misused in cybersecurity operations. The expanding application of AI in this field underscores the ethical obligation to pursue continuous monitoring and secure system development, acknowledging that AI’s powerful capabilities can serve both defensive purposes and malicious ends.

More Info and Help from MicroSolved

For organizations looking to fortify their defenses against AI-driven cyber threats, MicroSolved offers expert assistance in AI threat modeling and integrating AI into information security and risk management processes. With the growing complexity of cyber threats, especially those leveraging artificial intelligence, traditional security measures often prove inadequate.

MicroSolved’s team can help your business stay ahead of the threat landscape by providing comprehensive solutions tailored to your needs. Whether you’re dealing with ransomware attacks, phishing emails, or AI-driven attacks on critical infrastructures, they are equipped to handle the modern challenges faced by security teams.

Key Services Offered by MicroSolved:

  • AI Threat Modeling
  • Integration of AI in Cybersecurity Practices
  • Comprehensive Risk Management

For expert guidance or to initiate a consultation, contact MicroSolved at:

By partnering with MicroSolved, you can enhance your organization’s ability to detect and respond to AI-powered cyberattacks in real time, ultimately protecting your digital assets and ensuring cybersecurity resilience in 2025 and beyond.

 

 

* AI tools were used as a research assistant for this content, but human moderation and writing are also included. The included images are AI-generated.

 

 

The Biggest Challenges to Firms using Cyber Threat Intelligence

Cyber threat intelligence is one of the hottest topics in cybersecurity today. Many firms are investing heavily in developing and deploying solutions to identify and respond to cyber threats. But despite the hype surrounding cyber threat intelligence, many firms still struggle to make sense of the data they collect.

Why are firms struggling to make sense of their data, and how they can overcome this challenge? We asked around. It looks like three key challenges emerged, and here they are:

1. Data quality – How do we know if our data is accurate?

2. Data volume – How much data do we need to store?

3. Data integration – How do we combine multiple sources of data?

We’re working on ideas around these 3 most common problems. We’re working with firms of all sizes to help solve them. When we get to firm, across-the-board answers, we’ll post them. In the meantime, knowing the most common issues firms are facing in the threat intelligence arena gives us all a good place to start.

Got workarounds or solutions to these issues? Drop me a line on Twitter (@lbhuston) and let me know how you’re doing it. We’ll share the great ideas as they are proven out.

3 Threats We Are Modeling for Clients These Days

Just a quick post today to discuss three threat scenarios we are modeling frequently with clients these days. #ThreatModeling

1) Ransomeware or other malware infection sourced from managed service providers – this scenario is become a very common issue, so common that DHS and several other organizations have released advisories. Attacker campaigns against managed services providers have been identified and many have yielded some high value breaches. The most common threat is spear phishing into a MSP, with the attackers eventually gaining access to the capability to push software to the clients. They then push a command and control malware or a ransomware infection down the pipe. Often, it is quite some time before the source of the event is traced back to the MSP. The defenses here are somewhat limited, but the scenario definitely should be practiced at the tabletop level. Often, these MSPs have successfully passed a SOC audit, but have very little security maturity beyond the baselines.

2) Successful credential stuffing attacks against Office 365 implementations leading to wire/ACH/AP fraud – This is another very common scenario, not just for banks and credit unions, but a lot of small and mid-size organizations have fallen victim to it as well via account payable attacks. In the scenario, either a user is phished into giving up credentials, or a leaked set of credentials is leveraged to gain access to the Office 365 mail and chat system. The attackers then leverage this capability to perform their fraud, appearing to come from internal email accounts and chats. They often make use of stored forms and phish their way to other internal users in the approval chain to get the money to actually move. Once they have their cash, they often use these email accounts to spread malware and ransomware to other victims inside the organization or in business partners – continuing the chain over and over again. The defenses here are to MFA, limited access to the O365 environment to require VPN or other IP-specifc filtering, hardening the O365 environment and enabling many of the detection and prevention controls that are off by default. 

3) Voicemail hacking and dial-system fraud – I know, I know, it’s 2020… But, this remains an incredibly impactful attack, especially against key management employees or employees who traffic in highly confidential data. Often this is accessed and then either used for profit via trading (think M&A info) or as ransom/blackmail types of social engineering. Just like above, the attackers often hack one account and then use social engineering to get other users to follow instructions around fraud or change their voicemail password to a given number, etc. Larger corporations where social familiarity of employees and management is low are a common attack target. Dial system fraud for outbound long distance remains pretty common, especially over long weekends and holidays. Basically, the attackers hack an account and use call forwarding to send calls to a foreign number – then sell access to the hacked voicemail line, changing the destination number for each caller. Outbound dial tone is also highly regarded here and quite valuable on the underground markets. Often the fraud goes undetected for 60-90 days until the audit process kicks in, leaving the victim several thousand dollars in debt from the illicit activity. The defenses here are voicemail and phone system auditing, configuration reviews, hardening and lowering lockout thresholds on password attempts. 

We can help with all of these issues and defenses, but we love to help organizations with threat scenario generation, threat modeling and attack surface mapping. If you need some insights into outside the box attacks and fraud potential, give us a call. Our engagements in this space are informative, useful and affordable.

Thanks for reading, and until next time, stay safe out there! 

Are You Seeing This? Join a Threat Sharing Group!

Just a quick note today about threat sharing groups. 

I am talking to more and more companies and organizations that are putting together local, regional or vertical market threat sharing groups. These are often adhoc and usually driven by security practitioners, who are helping each other with cooperative defenses and sharing of new tactics and threat patterns (think TTPs (tactics, techniques & procedures)) or indicators of compromise (IOCs). Many times, these are informal email lists or RSS feeds that the technicians subscribe to and share what they are seeing in the trenches. 

A few folks have tried to commercialize them, but in most cases, these days, the sharing is simply free and open. 

If you get a chance to participate in one or more of these open source networks, you might want to check it out. Many of our clients are saying great things about the data they get via the networks and often they have helped contain incidents and breaches in a rapid fashion.

If you want to discuss your network, or if you have one that you’d like me to help promote, hit me up on Twitter (@lbhuston). If you are looking for one to join, check Twitter and I’ll share as folks allow, or I’ll make private connections as possible. 

As always, thanks for reading, and until next time, stay safe out there! 

Where Does Trouble Come From?

One of the most common questions I get is, “Where does attack traffic come from?”. I want to present a quick and dirty answer, just to show you how diverse illicit traffic sources are. 

To give you a glimpse into that, here is a list of the top 20 ISPs, based on the number of unique malicious source IP addresses who touched one of my HoneyPoint deployments in a single 24 hour period.

The list:

9 korea telecom
7 hinet
6 dynamic distribution ip’s for broadband services ojsc rosteleom, regional branch “urals”
5 sl-reverse
5 sfr
5 rr
5 chinanet jiangsu province network china telecom no.31,jingrong street beijing 100032
5 china mobile communications corporation mobile communications network operator in china internet service provider in china
4 turknet-dsl
4 superonline
4 sbcglobal
4 chinanet jiangsu province network china telecom 260 zhongyang road,nanjing 210037
3 zenlayer inc
3 virginm
3 verizon
3 totbb
3 jsc rostelecom regional branch “siberia”
3 intercable
3 comcastbusiness
3 comcast
3 charter
3 broadband multiplay project, o/o dgm bb, noc bsnl bangalore
3 as13285

As you can see by the above, the list is pretty diverse. It covers sources in many countries and across both domestic and foreign ISPs. In my experience, the list is also pretty dynamic, at least in terms of the top 10-20 ISPs. They tend to spike and fall like waves throughout different time periods. One of these days, maybe I will get around to visualizing some of that data to get a better view of the entropy around it. But, for now, I hope this gives you an idea of the diversity in sources of attacks.

The diversity also makes it very difficult to baseline log activity and such. As such, there may be some effective risk reduction in blocking ISPs by netblock, if your organization can tolerate the risk associated with doing so. But, more on that in another post. Hit me up on Twitter (@lbhuston) and let me know what your firm’s experience with that type blocking has been; if you’ve tried it or are doing it today. I’d love to hear if it reduced log noise, made traffic modeling easier or led to any specific risk reductions.

Thanks for reading! 

Petya/PetyaWrap Threat Info

As we speak, there is a global ransomware outbreak spreading. The infosec community is working together, in the open, on Twitter and mailing lists sharing information with each other and the world about the threat. 

The infector is called “Petya”/“PetyaWrap” and it appears to use psexec to execute the EternalBlue exploits from the NSA.

The current infector has the following list of target file extensions in the current (as of an hour ago) release. https://twitter.com/bry_campbell/status/879702644394270720/photo/1

Those with robust networks will likely find containment a usual activity, while those who haven’t implement defense in depth and a holistic enclaving strategy are likely in trouble.

Here are the exploits it is using: CVE-2017-0199 and MS17-010, so make sure you have these patched on all systems. Make sure you find anything that is outside the usual patch cycle, like HVAC, elevators, network cameras, ATMs, IoT devices, printers and copiers, ICS components, etc. Note that this a combination of a client-side attack and a network attack, so likely very capable of spreading to internal systems… Client side likely to yield access to internals pretty easily.

May only be affecting the MBR, so check that to see if it is true for you. Some chatter about multiple variants. If you can open a command prompt, bootrec may help. Booting from a CD/USB or using a drive rescue tool may be of use. Restore/rebuild the MBR seems to be successful for some victims. >>  “bootrec /RebuildBcd bootrec /fixMbr bootrec /fixboot” (untested)

New Petrwrap/Petya ransomware has a fake Microsoft digital signature appended. Copied from Sysinternals Utils. – https://t.co/JooBu8lb9e

Lastline indicated this hash as an IOC: 027cc450ef5f8c5f653329641ec1fed91f694e0d229928963b30f6b0d7d3a745 – They also found these activities: https://pbs.twimg.com/media/DDVj-llVYAAHqk4.jpg

Eternal Blue detection rules are firing in several detection products, ET Rules firing on that Petya 71b6a493388e7d0b40c83ce903bc6b04  (drops 7e37ab34ecdcc3e77e24522ddfd4852d ) – https://twitter.com/kafeine/status/879711519038210048

Make sure Office updates are applied, in addition to OS updates for Windows. <<Office updates needed to be immune to CVE-2017-0199.

Now is a great time to ensure you have backups that work for critical systems and that your restore processes are functional.

Chatter about wide scale spread to POS systems across europe. Many industries impacted so far.

Bitdefender initial analysis – https://labs.bitdefender.com/2017/06/massive-goldeneye-ransomware-campaign-slams-worldwide-users/?utm_source=SMGlobal&utm_medium=Twitter&utm_campaign=labs

Stay safe out there! 

 

3:48pm Eastern

Update: Lots of great info on detection, response, spread and prevention can be found here: https://securelist.com/schroedingers-petya/78870/

Also, this is the last update to this post unless something significant changes. Follow me on Twitter for more info: @lbhuston 

Pay Attention to Egress Anomalies on Weekends

Just a quick note to pay careful attention to egress anomalies when the majority of your employees are not likely to be using the network. Most organizations, even those that are 24/7, experience reduced network egress to the Internet during nights and weekends. This is the perfect time to look for anomalies and to take advantage of the reduced traffic levels to perform deeper analysis such as a traffic level monitoring, average session/connection sizes, anomalies in levels of blocked egress ports, new and never before seen DNS resolutions, etc. 

If you can baseline traffic, even using something abstract like net flow, you may find some amazing stuff. Check it out! 

Password Breach Mining is a Major Threat on the Horizon

Just a quick note today to get you thinking about a very big issue that is just over the security horizon.

As machine learning capabilities grow rapidly and mass storage pricing drops to close to zero, we will see a collision that will easily benefit common criminals. That is, they will begin to apply machine learning correlation and prediction capabilities to breach data – particularly passwords, in my opinion.

Millions of passwords are often breached at a time these days. Compiling these stolen password is quite easy, and with each added set, the idea of tracking and tracing individual users and their password selection patterns becomes trivial. Learning systems could be used to turn that raw data into insights about particular user patterns. For example, if a user continually creates passwords based on a season and a number (ex: Summer16) and several breaches show that same pattern as being associated with that particular user (ex: Summer16 on one site, Autumn12 on another and so on…) then the criminals can use prediction algorithms to create a custom dictionary to target that user. The dictionary set will be concise and is likely to be highly effective.

Hopefully, we have been teaching users not to use the same password in multiple locations – but a quick review of breach data sets show that these patterns are common. I believe they may well become the next evolution of bad password choices.

Now might be the time to add this to your awareness programs. Talk to users about password randomization, password vaults and the impacts that machine learning and AI are likely to have on crime. If we can change user behavior today, we may be able to prevent the breaches of tomorrow!