An AI coding agent with the right permissions just accidentally deleted a production database. A marketing bot with a valid login is spamming users from a trusted account. These aren’t future hypotheticals; they are the new reality of automated systems. We’ve given AI agents the keys to our digital kingdoms but have forgotten to check who’s giving the orders. A successful login doesn’t prove a human is at the wheel, which raises a fundamental security challenge. How can a platform confirm a human approved an action, not just that the credentials were valid? It’s time to move beyond identity checks and start verifying real, in-the-moment human intent.
Key Takeaways
- Shift from Verifying Identity to Intent: A successful login no longer proves a real person is making decisions. To prevent fraud and misuse from bots or compromised accounts, you must confirm a human is consciously approving each high-stakes action.
- Treat Approval as a Security Event: Turn every “confirm” click into a verifiable checkpoint. Use a layered defense, including biometrics and behavioral analysis, to ensure a live human is present and create an auditable record of their consent.
- Link Every AI Action to Human Consent: Since AI agents can act independently with valid credentials, you must create a direct, auditable connection between their tasks and a specific moment of human approval, ensuring every automated action is tied to a verified human instruction.
Beyond the Login: Why Human Approval Is the New Security Standard
For decades, digital security has revolved around one central question: are you who you say you are? We’ve built complex systems of passwords, two-factor authentication, and biometrics, all designed to act as digital gatekeepers. The goal was to validate a user’s identity at the front door and trust that everything they did afterward was legitimate. But that model is breaking down. In a world filled with sophisticated bots, AI agents, and deepfakes, a successful login is no longer a reliable signal of human intent.
The new, more critical question is: did a real person actually approve this action, right now? An authenticated account can be used to power automated fraud, spread disinformation, or make unauthorized transactions, all without the real user’s knowledge or consent. Simply verifying identity at the point of entry is not enough to protect your platform or your users from these threats. We need to move beyond the login and embrace a new standard that confirms a real, live human is present and intentionally giving their approval for important interactions. This is the shift from identity verification to intent verification, and it’s essential for rebuilding trust online.
What Is Credential Validation?
At its core, credential validation is the process of checking a user’s identity before giving them access to a system. Think of it as the digital equivalent of a bouncer checking your ID at the door. This process, often called authentication, protects digital spaces by confirming that credentials like a password, fingerprint, or a one-time code are valid.
Its main job is to make sure the person or system trying to get in has the right key. Once the gate is open, traditional authentication steps back. It’s a crucial first line of defense, but its responsibility ends once access is granted. It confirms you have permission to enter the building, but it doesn’t watch what you do once you’re inside.
Why “Logged In” Doesn’t Mean “I Agree”
A successful login confirms that a set of credentials are valid, but it says nothing about who or what is actually using them. An employee’s stolen credentials could be used by a fraudster, or an automated script could be running on a user’s machine without their knowledge. A valid login is not a blank check for any and all activity that follows. This problem is becoming even more urgent with the rise of AI agents.
An AI assistant might have legitimate credentials to act on a person’s behalf, but that doesn’t mean the person approved a specific, high-stakes action. As experts point out, we need to verify that a human’s approval for an action is real and not faked. Without that proof, any action an AI takes cannot be trusted, even if the agent itself is legitimate. This is why human approval verification is becoming the new frontier of digital security.
Why Traditional Verification Methods Fall Short
For years, we’ve relied on passwords and two-factor authentication to guard our digital spaces. The logic was straightforward: if you have the right credentials, you must be the right person. But as bots and AI agents become more sophisticated, this assumption is proving to be dangerously outdated. These traditional methods were designed to check an identity, not the human intent behind an action. They can tell you who logged in, but not if that “who” is a person making a conscious choice or a bot running a script. This fundamental gap is where trust begins to break down, leaving systems exposed.
The old security playbook focused on building a strong perimeter. Once inside, a user, or an agent acting as one, was generally trusted. This model is no longer sufficient. Automated systems can now mimic human behavior with alarming accuracy, making it easy for them to slip past these outdated defenses. The challenge isn’t just about preventing unauthorized access anymore; it’s about ensuring that every authorized action is genuinely intended by a real person. Without this layer of confirmation, platforms are left vulnerable to everything from accidental data deletion to large-scale fraud, all carried out by entities with perfectly valid credentials.
How Stolen Credentials Bypass Old Systems
Think of a username and password as a digital key. Traditional security simply asks, “Does this key fit the lock?” If the answer is yes, the door opens. The problem is, the system never asks who is holding the key. This is why identity-based authorization is failing us. It’s no longer enough to know who an agent is; we need to know why it’s performing a specific action in that exact moment. A bot armed with stolen credentials looks identical to a legitimate user, giving it the ability to access sensitive systems or execute commands without any check on its actual intent. This is why a shift toward proof-based authorization is becoming critical.
When Bots and AI Beat the System
The consequences of this flaw are not just theoretical. In one alarming case, an AI coding agent with all the correct permissions accidentally deleted a production database with over 1,200 executive records. The system saw a valid, authorized user and approved the action, unable to distinguish a routine task from a catastrophic error. This is a perfect example of how automated agents can cause massive damage even with valid access. The traditional security model simply has no way to understand the context or the potential impact of a command once the initial identity check is passed. It approves the “what” without ever confirming the “why.”
The Danger of Too Much Access
Part of the problem is that we often give users, and the AI agents acting for them, far too much power. This is known as “standing privileges,” where an account holds broad permissions that it rarely, if ever, needs. For instance, an AI agent might be assigned a ‘developer’ role to perform one small task, but that role also gives it the power to delete critical infrastructure. It’s like giving a contractor the master key to an entire office building just so they can fix a leaky faucet in one room. This excessive, always-on access creates a massive and unnecessary security risk just waiting to be exploited.
Valid Credentials Aren’t Enough Anymore
Security organizations are starting to recognize this gap. Groups like the National Institute of Standards and Technology (NIST) are focusing on creating clear identities for AI agents to better track their actions. While this is a positive step, it doesn’t solve the whole problem. As security experts point out, when an AI agent acts on behalf of a person, we need to be sure that the person’s approval was real and not faked. The critical missing piece is the ability to verify human approval in real time. Without it, even a perfectly identified agent could be acting on fraudulent instructions, leaving systems vulnerable.
What Is True Human Approval?
True human approval moves beyond simply asking, “Is this the right user?” and instead asks, “Is a real person consciously and willingly approving this specific action right now?” It’s a fundamental shift from verifying a static credential, like a password, to confirming a dynamic, in-the-moment decision made by a living, breathing human. In a world where automated systems and AI can act on our behalf, this distinction is everything. It’s about ensuring there’s a clear, unbroken line between a person’s intent and a digital outcome.
Confirming Intent, Not Just Identity
Knowing a user is logged in isn’t enough. True human approval is about confirming the intent behind an action, not just verifying an identity. Think of it as the difference between someone having the keys to your house and you explicitly asking them to water your plants. When an AI agent acts on a person’s behalf, we have to be certain the approval was real and not coerced or faked. If the approval is compromised, any action that follows is invalid, even if the credentials used were legitimate. This is why we need to move beyond simple logins and toward verifying conscious, deliberate consent for important actions.
Treating Approval as a Key Security Step
We need to start thinking of human approval as a critical security event. Every time a user clicks “confirm,” “agree,” or “purchase,” it should be treated with the same seriousness as a password entry or a multi-factor authentication code. This means logging who gave the approval, how they gave it, and the context surrounding that decision. Effective consent management isn’t just a privacy checkbox; it’s a powerful security layer. By treating approval as a verifiable event, you empower users with genuine control over their actions and data while creating a clear, auditable trail that protects your systems from unauthorized activity.
How AI Agents Change the Game
The rise of AI agents completely changes the security landscape. An AI agent can have perfectly valid credentials and still cause massive problems, executing commands that are technically correct but entirely unintended by the human user. As one expert notes, an agent with valid access can still “delete production” without any malicious intent. Traditional methods like CAPTCHAs or simple login checks are no longer reliable. As another source puts it, AI has effectively broken every old proof of human, turning them into speed bumps that only slow down real users. The new challenge is distinguishing between an action initiated by a human and one executed by an autonomous agent.
How to Verify a Real Human Is Present
Once you accept that a simple login isn’t enough, the next question is: how do you actually confirm a real person is behind the screen, giving their approval? It’s not about a single magic bullet. Instead, a strong verification strategy combines different methods to check not just who someone is, but how they behave and what they’re trying to accomplish. These techniques work together to build a confident picture of human presence and intent, creating a system that’s both secure and user-friendly.
Biometrics and Anti-Spoofing Tech
Biometrics use unique physical traits, like your face or fingerprints, to confirm you are who you say you are. But in an age of deepfakes and digital manipulation, simply matching a face to a photo on file isn’t enough. That’s where anti-spoofing technology comes in. It’s designed to answer a critical question: is this a real, live person, or just a picture, video, or mask? By analyzing subtle cues like texture, depth, and micro-movements, these systems perform a liveness check to ensure the person is physically present during the verification process. This makes it much harder for bad actors to fool the system with a stolen image or a fabricated video.
Reading the Signs with Behavioral Biometrics
While physical biometrics look at what you are, behavioral biometrics focus on what you do. This technology analyzes the unique patterns in your digital behavior, such as your typing rhythm, mouse movements, or even the way you hold your phone. Think of it as a digital signature based on your habits. These patterns are incredibly difficult for bots or imposters to mimic accurately. Because it works by observing normal user activity, behavioral biometrics can continuously confirm a human presence in the background without ever interrupting the user, offering a powerful layer of security that’s completely seamless. It helps spot anomalies the moment they happen, like if a user’s typing speed suddenly changes dramatically.
Using Justification Proofs and Consensus
This method adds a layer of logic and accountability, especially for actions taken by AI agents or automated systems. Before a system performs a significant action, like deleting a database or transferring funds, it must generate a “justification proof.” As security expert Travis Lelle explains, this proof is a digital record that outlines what the agent wants to do, why it has permission, and what the potential risks are. This proof-based authorization can then be automatically checked against company policies or even require consensus from other systems before proceeding. It shifts the security focus from just identity to intent, ensuring that every critical action is deliberate and authorized.
Passive vs. Active Verification
Verification methods can be sorted into two main categories: passive and active. Active verification is what most of us are used to. It requires you to take a specific action, like entering a code from an app or solving a CAPTCHA. While effective, these interruptions can frustrate users. Passive verification, on the other hand, works silently in the background. It uses signals like behavioral biometrics to continuously confirm a human is present without requiring any extra steps. The most sophisticated security systems balance these two approaches. They rely on passive methods for a smooth experience but escalate to active verification only when they detect suspicious activity, striking the right balance between security and usability.
How to Secure the Approval Process
Once you accept that a login isn’t enough, the next step is to build a system that can reliably confirm human intent. Securing the approval process isn’t about finding a single perfect tool; it’s about creating a smart, flexible framework. A truly secure process is one that layers different methods to verify an action, spots unusual activity as it happens, and adapts to risk in real time. By limiting access and assessing trust dynamically, you can
Build a Multi-Layered Defense
Relying on a single point of verification, like a password or even a simple two-factor authentication code, leaves you vulnerable. A truly strong platform uses a combination of technologies to create a multi-layered defense. Think of it like securing a building; you don’t just lock the front door. You have cameras, motion sensors, and maybe even a security guard. Online, this means using tools like biometrics, liveness detection, and AI-powered analysis to stop threats accurately and in real time. The goal is to build a system that is incredibly difficult for a bot or fraudster to bypass but remains fast and simple for a legitimate user.
Spot Anomalies When They Happen
Your system should be able to recognize what’s normal and flag what isn’t. This means monitoring for behavioral anomalies that could signal a compromised account or a bot at work. For example, is a user who normally operates during business hours in New York suddenly approving a major financial transfer at 3 a.m. from a new device in another country? That’s a red flag. This is also where user consent becomes a security signal. A sudden, unexpected request for new data permissions can be an anomaly worth investigating. Effective consent management gives users control over their data, and it also creates a pattern of behavior that helps you spot when something is wrong.
Assess Trust Dynamically, Not Statically
Trust shouldn’t be a one-time event that happens at login. It needs to be a dynamic, ongoing assessment that adapts to the situation. The level of verification required should match the level of risk for any given action. Liking a post is low-risk and may not need any extra checks. Authorizing a six-figure wire transfer, on the other hand, demands a much higher level of certainty that a real, authorized human is giving the green light. When done well, this approach ensures your business can comply with regulations like GDPR and CCPA. More importantly, it builds a foundation of trust with your customers by showing you take their security seriously.
Limit Access to Reduce Risk
One of the most effective ways to reduce risk is to limit the potential for damage. This is the principle of least privilege: users and systems should only have the absolute minimum level of access required to do their jobs. If an account is compromised, a bad actor can only do so much harm if the account’s permissions are tightly restricted. This requires a mature process for managing permissions and consent. Having clear, transparent, and user-friendly procedures for obtaining and managing access is key. A well-documented consent management process isn’t just a legal requirement; it’s a fundamental part of a strong and sensible security posture.
How Do AI Agents Fit into Human Approval?
As AI agents become more common in our work lives, they add a new wrinkle to security. These agents are more than just tools; they are proxies that act on our behalf, scheduling meetings, making purchases, or even managing critical business systems. This brings up a big question: when an AI agent takes an action, how can you be sure a real human approved it? The old method of just checking an agent’s credentials isn’t enough anymore. We are past the point where a valid login equals true intent.
The challenge has two parts. First, you need to confirm that the person who supposedly authorized the AI is who they say they are and that they are physically present during the approval. Second, you need a clear, undeniable link between that human’s consent and the specific action the AI is about to perform. Without this, a compromised account could give a malicious actor free rein to use an AI agent for destructive purposes. To build trust in these automated systems, we must be able to tell the difference between a human-approved action and one started by a bot or a bad actor hiding behind a legitimate-looking AI.
When AI Acts for a Human
Think of an AI agent as a digital employee acting on instructions. For any business to trust that employee with sensitive tasks, it needs to know who gave the order. When an AI agent joins a call or accesses a database, it’s not enough to know the agent itself is authorized. You must also confirm the human who delegated the task is real, present, and legitimate. This is where human approval verification becomes so important.
The main issue is that an AI’s credentials can be valid, but the approval behind them might be fraudulent. For instance, a bad actor could use stolen credentials to authorize an AI to transfer funds or delete data. To prevent this, businesses need a way to verify both the AI agent’s identity and the human’s approval in real time. This means using technology that can confirm a living person is behind the screen at the moment of consent.
Connect AI Actions to Human Consent
Traditional identity-based authorization is showing its age. It’s no longer enough to know who an AI agent is; you need to know why it has permission to perform a specific task right now. An agent with valid credentials could accidentally or maliciously cause serious damage, and simply knowing its identity won’t stop it. This is why the security world is shifting toward a model of proof-based authorization.
In this model, an AI agent must generate a “Justification Proof” before it carries out a high-stakes action. This proof acts as a digital paper trail, outlining what the agent plans to do, the basis for its authorization, and the potential risks. This process creates a direct, auditable link between a specific human instruction and a specific AI action. It changes consent from a vague, one-time event into a continuous, action-specific verification, ensuring every important task is tied back to a clear moment of human approval.
Tell the Difference Between Bot and Human Actions
As AI becomes more advanced, the lines between human and machine behavior are blurring. Sophisticated AI agents can mimic human conversation, typing patterns, and other digital mannerisms so well that it’s getting incredibly hard to tell if you’re interacting with a person or a program. This ambiguity is a serious security threat, as it weakens the foundation of online trust. If you can’t be sure who or what is on the other side of the screen, you can’t trust the interaction.
This is why it’s so important to verify the person behind an AI agent. Knowing that a real human is accountable for an AI’s actions is key to preventing fraud and protecting your business. It’s about ensuring that every digital interaction, especially those involving automated agents, can be traced back to a verified human presence. Without this ability, your systems are open to manipulation by bots designed to exploit the assumption of human authenticity.
User Consent Is a Security Layer, Not Just a Legal Checkbox
When you hear “user consent,” your mind probably jumps to those cookie banners and lengthy privacy policies we all click through. For years, we’ve treated consent as a legal hurdle, a box to check for regulations like GDPR and CCPA. But it’s time to reframe that thinking. Treating consent as an active security measure is one of the most effective ways to confirm human intent and protect your platform from automated attacks and account takeovers. It transforms a passive legal requirement into an active, real-time verification of what a user actually wants to do.
Think about it: requiring a user to explicitly agree to a specific action creates a powerful checkpoint. It’s another signal that a real person is present and paying attention, not a bot running a script or a fraudster using stolen credentials. This approach moves beyond just verifying an identity at login and toward confirming intent at the moment of action. By making consent a core part of your security strategy, you not only strengthen your defenses but also build deeper trust with your users. A good consent management process puts power back into their hands, giving them control over their data and actions, which is exactly what people expect from platforms they rely on. This isn’t just about compliance; it’s about creating a more secure and transparent digital environment for everyone.
Get Explicit Consent for Each Action
A one-time “I agree” during signup is no longer enough. To truly verify intent, you need to ask for consent at the point of action. This means getting explicit permission before a user makes a purchase, shares data with a third-party app, or changes critical account settings. Each of these prompts serves as a small but significant security check, confirming that the person who logged in is the same person approving the action.
This strategy is all about putting power in the hands of your users. When you ask for explicit consent, you ensure they are fully aware of and agree to what’s happening. It’s a simple but profound shift. Instead of assuming a logged-in user approves of everything, you create a system that requires conscious, deliberate choices for important actions. This method makes it much harder for bots or bad actors with stolen credentials to cause damage, as they are less likely to navigate these context-specific approval steps.
Offer Granular and Easy-to-Withdraw Consent
Building trust isn’t a one-and-done deal; it requires transparency and flexibility. A mature consent management process gives users clear, specific options over what they agree to. Instead of a single, all-or-nothing choice, let them consent to individual actions. For example, a user might be happy to share their email for newsletters but not their phone number for marketing texts. Giving them this level of control shows respect for their privacy and preferences.
Just as important is making it easy for users to change their minds. A user should be able to withdraw their consent at any time without having to dig through confusing menus or contact support. A simple, accessible dashboard where they can review and manage their permissions is ideal. When you make the process user-friendly, you demonstrate that you see consent as an ongoing dialogue, not a one-time transaction.
Keep Clear Records for Accountability
Managing consent isn’t just about asking for permission; it’s also about documenting it. Keeping clear, organized records of who consented to what, when, and how is essential for both accountability and security. This audit trail is your proof that an action was legitimately approved by a human user, which is invaluable for resolving disputes or investigating suspicious activity.
Think of it as a security log for user intent. If a fraudulent transaction occurs, you can trace it back to the moment of consent (or lack thereof). This process of getting, storing, and applying user permission is fundamental to a trustworthy system. These records are not only crucial for complying with privacy laws but also serve as a critical dataset for understanding user behavior and identifying anomalies that could signal a security threat. A solid consent management strategy is your foundation for building a system that both users and your organization can trust.
How to Maintain Ongoing Trust
Verifying a user once is a good start, but it’s not the end of the story. True trust is built and maintained over time, through consistent and reliable interactions. In a digital world where threats are constantly changing, your approach to security has to be just as dynamic. It’s not about putting up a wall at the entrance; it’s about ensuring the right person is still in the room for every important decision. This means shifting from a one-time check to a continuous process of validation that protects both your platform and your users without getting in their way.
Monitor Continuously, Not Just Once
A single login or initial verification doesn’t guarantee future integrity. Think of trust as a living thing that needs to be nurtured. As security experts note, trust should adapt over time based on user actions and potential new risks. This means your security can’t be static. Instead of a single checkpoint, you need a system that re-evaluates trust at critical moments. Is a user suddenly trying to transfer a large sum of money? Is an AI agent accessing sensitive data for the first time? These are moments that call for a quick, frictionless check to confirm a real human is still present and has approved the action.
Adapt Your Security as Threats Evolve
The tools used by fraudsters are getting more sophisticated every day, from realistic deepfakes to advanced bots that mimic human behavior. Your defense system has to keep pace. A static security model is a sitting duck. A truly strong platform uses a flexible, multi-layered defense that combines different technologies to identify and stop threats as they happen. This might include biometrics to confirm a physical presence, liveness detection to thwart spoofing attempts, and behavioral analysis to spot unusual activity. The goal is to create a resilient security framework that can adapt to new attack vectors without slowing down legitimate users. It’s about being prepared for the threats of tomorrow, not just the ones from yesterday.
Stay Transparent with Audits and Communication
Security shouldn’t feel like a black box to your users. Building lasting trust requires transparency and giving users control. This is where clear communication and robust consent management come into play. When you ask for verification, explain why it’s necessary to protect their account. More importantly, give them granular control over their data and permissions. When users feel empowered and informed, they become active participants in their own security. Keeping clear, auditable records of consent and approval not only ensures accountability but also reinforces that you value their privacy and partnership.
Build a Scalable Human Approval Framework
Creating a system to confirm human approval isn’t just about adding another security check. It’s about building a framework that can grow with your platform, adapt to new threats, and earn user trust along the way. A scalable framework is one that works seamlessly behind the scenes, protecting your systems and your users without creating unnecessary roadblocks. It requires a thoughtful approach that considers the user experience, protects privacy, and integrates smoothly with your existing technology. When you get it right, you create a more secure environment where genuine human interactions can thrive, giving your business the confidence to trust the decisions and actions happening on your platform. This isn’t a one-time fix; it’s an ongoing commitment to maintaining the integrity of your digital community.
Find the Right Balance Between Security and User Experience
The strongest security system is useless if it drives your users away. If every action requires a frustrating, multi-step verification process, people will simply go elsewhere. The goal is to find the sweet spot where security is strong but nearly invisible. This starts with putting users in control. Modern consent management is a great model for this, as it empowers users by letting them decide what information is collected and how it’s used. By adopting a similar mindset for human approval, you can turn a security measure into a trust-building feature. When users feel respected and in control of their experience, they are more likely to engage with your platform and appreciate the protections you have in place.
Protect Privacy Without Sacrificing Security
Many people hear “biometrics” and immediately worry about their privacy. But confirming human presence doesn’t have to mean collecting and storing sensitive personal data. The most effective modern systems are designed to be privacy-first. They can verify that a real person is present and intentionally approving an action without needing to know who that person is. The key is to be transparent and obtain clear consent. A mature consent management process involves informing users about what data is being used and giving them control over their information. By focusing on verifying the act of approval rather than the identity of the user, you can implement robust security measures that respect personal privacy and build lasting trust.
Handle Integration and False Positives
A new security tool is only as good as its ability to work with your existing systems. When building your human approval framework, plan for a smooth integration that won’t disrupt your operations. Beyond the technical setup, you need a strategy for handling exceptions. No system is perfect, and you will occasionally encounter false positives, where a legitimate user is incorrectly flagged. A mature framework includes clear and user-friendly procedures for managing these instances. Having a simple process for users to resolve issues shows that you value their experience and are committed to fairness, turning a potential point of friction into another opportunity to reinforce trust.
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Frequently Asked questions
What’s the real difference between the authentication I already use and this idea of “human approval“? Think of it this way: traditional authentication, like a password or a two-factor code, is like a bouncer checking your ID at the door. It confirms you have permission to enter. Human approval is what happens inside; it’s like asking for your specific consent before you make a big decision, like signing a contract. It verifies your intent for a specific action, right now, which is something a simple login can’t do.
My users hate extra steps. How can I verify a human is present without frustrating them? This is a great question, and it’s a common concern. The key is to use passive verification methods that work silently in the background. Technologies like behavioral biometrics can analyze things like typing patterns or mouse movements to confirm a human is present without ever interrupting the user. You can then save the active checks, like a quick facial scan, for high-risk actions, such as changing account details or transferring a large sum of money.
How does this apply to AI agents? Aren’t they supposed to act on their own? AI agents are meant to act on our behalf, but that’s exactly why human approval is so critical. The goal isn’t to stop the AI from working; it’s to create a clear, unbreakable link between the AI’s action and a specific human’s consent. Before an AI agent performs a major task, it should be tied to a verifiable moment of approval from a real person, ensuring the agent is acting on legitimate instructions and not from a compromised account.
Isn’t asking for consent for every little thing just going to create “consent fatigue”? Absolutely, and it shouldn’t be for every little thing. A smart system assesses risk dynamically. Liking a photo is a low-risk action that doesn’t need extra verification. Authorizing a six-figure payment or deleting a database is high-risk and demands a higher level of certainty. The goal is to match the level of verification to the importance of the action, which protects users on critical tasks without annoying them on minor ones.
I’m worried about privacy. Does verifying a human mean I have to collect more sensitive user data? Not at all. In fact, modern human verification technology is designed with privacy at its core. These systems can confirm that a real, live person is present at their screen without needing to know or store who that person is. The technology focuses on confirming liveness and intent, not on collecting and storing sensitive identity data, which allows you to increase security while still respecting user privacy.