Solutions for AI Identity Challenges

The Identity Theft Resource Center recently reported a 312% spike in victim notices, now reaching 1.7 billion for 2024. AI is transforming identity theft from something attackers did manually to full-scale industrialized operations. Look at what happened in Hong Kong: a clerk wired HK$200M to threat actors during a video call where every participant but one was an AI-generated deepfake. Only the victim was real. Here’s what you need to know 👇 1. Traditional authentication won’t stop these attacks. Get MFA on everything, prioritize high-value accounts. 2. Static identity checks aren't enough—switch to continuous validation. Ongoing monitoring of access patterns is essential after users log in. 3. Incident response plans have to address synthetic identity threats. Focus your response on critical assets. 4. Some organizations are using agentic AI to analyze identity settings in real time, catching out-of-place activity that basic rules miss. Passing a compliance audit doesn’t mean you’re protected against these attacks. The old “authenticate once” mindset needs to move to a model where verification is continuous and context-aware. If your organization is seeing similar threats, how are you adapting to push back against AI-driven identity attacks? #Cybersecurity #InfoSec #ThreatIntelligence

ChatGPT Created a Fake Passport That Passed a Real Identity Check A recent experiment by a tech entrepreneur revealed something that should concern every security leader. ChatGPT-4o was used to create a fake passport that successfully bypassed an online identity verification process. No advanced design software. No black-market tools. Just a prompt and a few minutes with an AI model. And it worked. This wasn't a lab demonstration. It was a real test against the same kind of ID verification platforms used by fintech companies and digital service providers across industries. The fake passport looked legitimate enough to fool systems that are currently trusted to validate customer identity. That should make anyone managing digital risk sit up and pay attention. The reality is that many identity verification processes are built on the assumption that making a convincing fake ID is difficult. It used to require graphic design skills, access to templates, and time. That assumption no longer holds. Generative AI has lowered the barrier to entry and changed the rules. Creating convincing fake documents has become fast, easy, and accessible to anyone with an internet connection. This shift has huge implications for fraud prevention and regulatory compliance. Know Your Customer processes that depend on photo ID uploads and selfies are no longer enough on their own. AI-generated forgeries can now bypass them with alarming ease. That means organizations must look closely at their current controls and ask if they are still fit for purpose. To keep pace with this new reality, identity verification must evolve. This means adopting more advanced and resilient methods like NFC-enabled document authentication, liveness detection to counter deepfakes, and identity solutions anchored to hardware or device-level integrity. It also requires a proactive mindset—pressing vendors and partners to demonstrate that their systems can withstand the growing sophistication of AI-driven threats. Passive trust in outdated processes is no longer an option. Generative AI is not just a tool for innovation. It is also becoming a tool for attackers. If security teams are not accounting for this, they are already behind. The landscape is shifting fast. The tools we trusted even a year ago may not be enough for what is already here. #Cybersecurity #CISO #AI #IdentityVerification #KYC #FraudPrevention #GenerativeAI #InfoSec https://lnkd.in/gkv56DbH

The Right Questions for AI Impersonation There’s intense focus right now on generative AI and the levels of impersonation it enables. We’ve already seen successful attacks impersonating individuals across email, text, live voice, and even live video. One thing is certain—the cost of these attacks will continue to drop, and the quality will continue to improve. As a knee-jerk reaction, the industry has jumped on the deepfake detection bandwagon. While there are valid use cases for deepfake detection, I’m highly skeptical of its broad-scale adoption. First, if we develop a highly effective deepfake detector, wouldn't we use it to train a better deepfake generator? Second, how do these detection systems differentiate between malicious deepfakes and legitimate AI-assisted content? I use LLMs to edit my writing. I use visual filters to hide the fact that I was kicked in the face by a horse. I use real-time AI voice translation to speak other languages. Should these uses trigger alarms? If we focus solely on detection, we risk suppressing beneficial use cases while failing to stop the actual threat. The Better Question: Who Created This Content? Instead of asking, “Is this a deepfake?” or “Was this produced by an LLM?”, a more meaningful question is: • Who created this content? • On what device was it produced? • What level of authentication assurance was present during its creation? • Was the content author’s identity backed by strong identity proofing? • Were the expected security controls enforced on the device? A secure-by-design identity solution makes it possible to integrate with the business applications people already use—real-time communication tools, email and text platforms, development environments, infrastructure-as-code workflows, and more—ensuring that you always know who authored what. At Beyond Identity, we call this capability Reality Check. We first demonstrated this use case years ago with a customer who needed to verify code authorship. We built integrations for Git, GitHub, and GitLab that answered key questions: • Who committed this code? • On what machine? • From what location? • With what security controls in place? This enabled the customer to establish clear governance, meet compliance requirements, and pass a complex audit—even with a mix of employees, contractors, and business partners working in the same infrastructure. At the time, we called this Secure DevOps. More recently, we introduced a plugin for Zoom and launched beta integrations for Microsoft Teams and Outlook, allowing organizations to verify the same questions of authenticity and origin. We will continue evolving to address AI-driven threats (Counter-AI), compliance and supply chain security, and advanced social engineering risks. A secure-by-design identity solution doesn’t just mitigate these problems—it eliminates them at the root. https://lnkd.in/eZ_YfWk5

Those of us in the cybersecurity industry understand AI has been behind much of the tooling used to protect systems and data for years (think adaptive firewalls). That said, some new AI security innovations are worth taking a closer look at when implementing. Take AI IAM (AI-driven Identity Authentication Management). While it can be a critical pillar of Zero Trust, deployment is rarely straightforward. Consider the following: - User Push back and Skepticism Behavior-based authentication and continuous verification can make workers feel distrusted, unnecessarily surveilled and ultimately resistant to adaptation. This is a human response that requires a human-based solution. Use behavior-based authentication as a precision tool, not a blanket solution. Employ step-up authentication only for high-risk access and roll out the new tool with a thoughtfully crafted change management approach. - Legacy Systems Integration Many legacy apps lack the ability to integrate well with many AI-driven tools. Use identity orchestration platforms to bridge modern and legacy IAM, figure out a prioritization metric for apps for refactoring or deprecation, and find places where a proxy-based solution makes more sense. - False Positives & Access Disruptions AI is a powerful tool…that still makes mistakes. Its risk scoring can generate excessive authentication challenges or access denials. The last thing you need is a company executive locked out of their email because they bought a new smartphone without telling the IT department. This is where the "learning" part of ML models come in. Instead of static rules, adjust risk guardrails based on sessions and incorporate real-world activities in model training. - Insider Threats & Privileged Access Risks As of this writing, traditional IAM has a spotty track record of detecting credential misuse. Often, a flood of false positives is the result of poorly tuned systems. Use your safety nets: Enforce continuous verification for sensitive roles and implement just-in-time access. - Compliance & AI Governance It can be difficult to clearly understand AI decisions and that makes audits and regulatory reporting difficult. Depending on the enterprise, simply having a "Reasoning" button won't cut it. This is where AI can solve its own problem by "chaining" AI platforms. Consider whether implementing explainable AI (XAI) for risk-based or highly sensitive access is a needed element. And, IAM policy enforcement can still be automated safely, as can assurance testing against established and predictable compliance baselines. But CISOs will need to take into account human behavior and be mindful of very specific organizational needs and use cases to implement it effectively.

As AI rapidly advances, an emerging critical challenge threatens to weaken the foundations of societal institutions: How can we maintain trust and accountability online when AI systems become indistinguishable from real people? I recently contributed to a paper with 20 prominent AI researchers, legal experts, and tech industry leaders from OpenAI, MIT, Microsoft Research, and the Partnership on AI proposing a novel solution: personhood credentials (PHCs). The implications of widespread AI-powered deception are profound. Our institutions rely on a social trust that individuals are engaging in authentic conversation and transactions. Anything that undermines that trust weakens the foundations for communication, commerce, and government interactions and threatens to erode the basic trust and shared understanding that enables societies to function. Key points: - AI-powered deception is scaling up, threatening societal trust. - PHCs offer optional, privacy-preserving online identity verification. - Users can prove their humanity without revealing personal information. - Trusted entities could issue PHCs, ensuring one-time verification. - This balances human verification needs with robust privacy protection. As AI continues to blur the lines between real and artificial, solutions like PHCs become crucial for maintaining the foundations of trust in our digital world. Blog post: https://lnkd.in/eywU_dpG Paper: https://lnkd.in/ekV4t8GS

IDENTITY FRAUD IS NOT JUST ESCALATING - IT'S EVOLVING. Just read a truly insightful piece from the team at IDVerse - A LexisNexis® Risk Solutions Company on how Agentic AI is redefining the identity verification landscape — and honestly, it’s one of the more intelligent contributions I’ve seen on the topic in a while. This isn’t a buzzword drop. It’s a clear-eyed look at what happens when identity, fraud, and AI intersect in a Zero Trust world — and what actually works to stay ahead of attackers who are evolving faster than the defenses that are supposed to stop them. 🔗 https://lnkd.in/eUaeNban 🔍 The piece explores something I’ve been thinking a lot about - how digital identity is no longer just a reflection of someone — it’s a construct that can be manipulated, faked, and industrialized. We’re not just dealing with bad actors. We’re dealing with entire ecosystems of "fraudsonas" — synthetic identities and AI-driven deception that can slip past so-called "innovative" verification tools. What IDVerse is doing with Agentic AI is pretty remarkable. Rather than replacing traditional tools which remain essential, they’re adding a new, adaptive layer — one that can learn, react, and detect in real time. It’s an evolution, not a rip-and-replace approach. 🤖 Agentic AI isn’t about automation — it’s about autonomy. It acts with context. It flags behaviors that aren’t just unusual, but intelligently inconsistent. It adapts verification flows to match the risk level. And it does this all without disrupting the user experience. And the timing couldn’t be more critical. 📈 Synthetic ID is now the fastest-growing type of financial crime 🎭 Deepfake-as-a-service is a real thing The idea of using intelligent, context-aware systems to bridge real-world data to digital behavior — and flag the dissonance between the two — is the future. It’s also one of the best paths forward for program integrity, especially across federal, state, and local government initiatives. This article didn’t just promote a platform. It reframed the way I think about how trust is earned — and maintained — in a high-risk, AI-enabled world. #IDVerse #AgenticAI #IdentityVerification #ZeroTrust #DigitalFraud #ProgramIntegrity #Cybersecurity #FraudPrevention #TrustAndSafety #GovTech LexisNexis Risk Solutions LexisNexis Risk Solutions Public Safety LexisNexis Risk Solutions Government

Every week, I am very fortunate to have the privilege to speak with CISOs and CIOs and CTOs and identity teams across industries. The most urgent need we hear is consistent: Securing identity permissions and entitlements as the most urgent perimeter. AI has the potential to redefine how organizations address identity and access debt. And with it, the need for a platform approach to next-generation identity use cases is becoming unavoidable. The feedback to us is clear: 1. Veza as the AI-powered next-generation identity platform, designed from the ground up with permissions and entitlements as the foundation to Veza Access Graph. Supporting identity visibility and intelligence (IVIP), modern IGA, next-gen PAM, and next-gen access across non-human identities, agentic AI, and more. 2. Veza for Agentic AI use cases: - What agents are in my environment? → Identity system of record for agents - What do agents have access to? → Least privilege across AI agents - What people have access to what agents? → Agent Access Policy Engine - What are AI agents doing? → Access Activity Monitoring Today, we’re launching a new resource hub that shares how Veza helps organizations govern identity and access in the age of AI: https://lnkd.in/gtDY8sv3 Topics include: 1. Identity security for AI Agents 2. AI governance 3. Securing access to LLMs (OpenAI, Anthropic, Amazon Web Services (AWS) Bedrock) 4. Securing access to AI-powered applications (GitHub Copilot and others) As agentic AI becomes operational across enterprises, identity security for AI is not a future problem. It is a right-now problem. #AgenticAI #IdentitySecurity #AIGovernance #CyberSecurity #Veza #IVIP

This is what identity chaos looks like in 2025: An AI agent executes a workflow across 5 APIs. Nobody provisioned it. It’s using a shared credential from six months ago. And it disappears before anyone notices. Multiply that by a thousand—and now you’re living in the agent era. That’s not innovation. That’s identity drift at machine speed. Most enterprise identity systems were built for people. Predictable, long-lived, manually onboarded humans. But agents? They spin up in seconds, act independently, and disappear. You can’t pre-provision for that. And you certainly can’t trust them with static credentials and hope for the best. This is where Just-in-Time (JIT) provisioning becomes essential. We’re not talking about tinkering at the edges. It's a foundational shift: 👉 Agent identities must be created, governed, and retired in real time 👉 Permissions must be scoped to task, intent, and delegation 👉 Every action must be traceable—even after the agent is gone You can’t scale Zero Trust with identity sprawl and over-permissioned service accounts. JIT turns identity into a runtime control plane—not a provisioning checklist. Just-in-Time provisioning isn’t an optimization. It's survival against what I'm seeing AI agents in real production systems do: → Moving money → Accessing critical infrastructure → Acting on behalf of humans—without real identity No scoped credentials. No delegation record. No audit trail. And it’s happening fast. Security teams know the AI wave is upon us—but most aren’t ready for how radically it breaks the identity model we’ve depended on for decades. Instead of pre-provisioning identities for every possible agent, JIT creates them at runtime: ✔️ Scoped to a task ✔️ Tied to a delegator ✔️ Expired automatically ✔️ Logged end-to-end You get Zero Trust by default—not by bolting on policy later. This shift is personal for me. I’ve spent my career helping secure digital transformation—but agentic AI is a whole new frontier. It demands identity infrastructure that’s fast, ephemeral, and built for autonomy. Find out how Maverics Identity for Agentic AI is built to orchestrate agent identity at runtime and get early access to the preview! https://lnkd.in/gi8Ujcnc

Sam Altman’s New AI Agent and his Bold Vision For Verifying Humans (OpenAI CEO Sam Altman is making big moves in AI again!) This week, Altman’s company OpenAI launched Operator, its first AI agent that can act independently on the internet. But that’s not the only project he’s working on. Altman is also leading another venture called World, a project that’s taking AI agents in a different direction. World’s big idea? To create tools that link AI agents to people’s online identities. This way, other users can verify that an AI is acting on behalf of a real person. The project believes this will be critical as it becomes harder to tell humans and AI apart online. Here’s how it works: ↳ Human Verification: World uses a system called “proof of human.” You scan your eyeball with a silver metal orb, and World gives you a unique digital ID stored on the blockchain. This proves you’re a human, not a bot. ↳ Linking AI Agents to People: World wants to expand this concept by letting AI agents act on your behalf, like handling tasks or interacting with others online. The tools would prove that the agent is connected to a real person versus a fake one. In Tiago Sada's words (World’s Chief Product Officer): “You could let an AI agent handle tasks for you, but others will know it’s connected to a real human. This kind of verification will be crucial in the future.” This idea builds on World’s original mission to verify humans online. But challenges remain. Tools like Cloudflare and Snowflake are already used by websites to block AI bots from accessing their platforms. Early users of OpenAI’s Operator report that some websites are blocking the new agent by default because they can detect it’s AI. Despite this, World believes their tools could play a huge role by 2025, helping people manage AI agents and ensure digital actions are tied to real identities. Sada sums it up well: “In some cases, it doesn’t matter if a person or an AI is acting. What matters is knowing there’s a real human behind it.” Would you let an AI agent act on your behalf online? _______________________ AI Consultant, Course Creator & Keynote Speaker Follow Ashley Gross for more content like this

AI agents will be performing functions on behalf of us very quickly. We have a critical need for establishing identity within AI agents as they transition from passive assistants to active decision-makers. Amit Sinha discusses the future of AI Identity Management must include the following: • Implement AI-specific PKI frameworks • Establish audit trails for AI decisions • Enable zero-trust architectures where every AI interaction is verified • Continuously monitor and revoke compromised AI identities "Implementing cryptographic identity management for AI ensures that we remain in control—empowering AI to act securely and transparently on our behalf." We have all seen how fast AI has advanced in the past year and it is continuing it's blazing advancements. To safely enable these emerging agents to act on our behalf, we must establish strong identity and trust frameworks. https://lnkd.in/gdwrwK5j