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AI agents have become incredibly useful across many industries by their ability to reach inboxes, documents, and financial information, then search, summarize, or act on what they find. But that access creates a data-in-use problem: conventional encryption protects information in storage and transit, but an agent generally needs it decrypted in memory while processing it, where sensitive material can be exposed to application code, logs and debugging systems, infrastructure operators, or a compromised host. Conan Yu's work offers one practical response to that problem. He is co-founder of Rena Labs , which develops infrastructure for confidential AI training and inference using trusted execution environments (TEEs), hardware-isolated environments designed to limit the surrounding host's access while code and data are processed. Over roughly two years, Yu has worked across hardware and cloud TEE deployments, privacy-preserving financial-data analysis, and private AI inference. He a...

Check your expanding identity attack surface Identity has become the new perimeter, and attackers know it. According to new research from CrowdStrike, 80% of modern cyberattacks are identity-driven , leveraging compromised credentials.  This substantial volume is driven by the widespread use of well-known directories such as Active Directory, and the vulnerabilities associated with compromised privileged accounts that are overprivileged or unmanaged, not network intrusion.  The explosion of privileged credentials and lack of adequate visibility or oversight can be attributed to growth, whether due to migration to the cloud, mergers and acquisition, the increased use of contractors, or simple organic business growth. This growth outpaces the ability to adequately govern the environment, leaving exploitable vulnerabilities.

AI coding agents are already inside engineering organizations. The problem security teams need to solve is not only that AI-generated code might be vulnerable. You already have ways to catch that: code review, CI, SAST, dependency scanning, and production monitoring. The real problem is that tools such as Claude Code, OpenAI Codex, Claude Cowork, and GitHub Copilot are becoming extensible agent runtimes. Skills, plugins, hooks, repository instructions, and MCP servers can influence what the agent reads, which tools it selects, what commands it runs, and where enterprise data is sent. Most AI governance programs stop at approving the application. Very few can tell you everything that has been installed inside it. That is the supply-chain gap. What changed: Third-party components are no longer participating only at build or deploy. They are participating in the agent's decision loop. From coding assistant to agent runtime The first generation of coding assistants mainly...

Artificial intelligence is everywhere now. From automated code completion to autonomous infrastructure management, AI tools and AI agents help DevOps speed up deployment cycles and change how development teams operate in general. At the same time, this rapid adoption of AI has created a reality that is hard for security teams to ignore: as with the growth of AI capability within the software development life cycle, the attack surface also grows. In 2025, there were 68 AI-related incidents recorded across major DevOps platforms according to the 2026 DevOps Threats Unwrapped Report . In the first half of 2026, the number of AI-related incidents visibly grew — research from GitProtect Lab tracked 84 AI-related incidents in six months alone. Thus, comparing the first half of 2026 to the same period in 2025 shows that AI-related incidents in development environments have nearly tripled. What do DevOps and DevSecOps say about AI incidents in general? According to GitProtect Lab 's surve...

Identity is the attack surface now. Most identity governance and administration (IGA) programs still run on manual certifications, static role models, and quarterly reviews that go stale the day someone signs off on them. That's not a compliance inconvenience for a CISO. It's a structural gap. Attackers don't wait for the next recertification cycle, so identity risk detection can't either. Autonomous identity governance turns IGA from a periodic, human-driven exercise into something that runs continuously, watching real usage, learning what normal looks like, and acting on deviations before they turn into incidents. That autonomy applies across every identity and entitlement placed under governance, continuously reassessing access as usage, roles, and risk signals change. Three things are colliding to force this shift. Identity sprawl across cloud and SaaS environments has grown past what manual reviews can realistically handle, service accounts and non-human identi...

We had an enterprise customer tell us their entire AI footprint was Copilot. That was the whole answer. One tool, one line item, done. We ran the first scan. Copilot wasn't even close to number one. Claude was. OpenAI came in second. Copilot was third. Nobody on the security team knew because Claude doesn't show up the way a SaaS app used to show up. There's no single login screen, no single admin console, no one place to look. That's the part most security teams miss. Claude isn't one surface. It's six. The six places Claude actually runs Claude Enterprise and Connected Apps. This is the surface everyone pictures: employees typing into Claude, OAuth'd into Google Drive, GitHub, Slack, and Jira, asking Claude to act on what's inside. The audit log shows that a connection happened. It does not show what got pulled into the prompt or what came back out. A finance analyst can drop a quarter of board materials into a conversation in ten second...

Security is fundamentally about knowing what a system is supposed to do, then catching it when it does something else. For software with deterministic execution paths, that is a tractable problem. For AI agents, it is not. An agent does not follow a fixed code path. It reasons toward a goal, selects tools based on that reasoning, and adapts its next action based on what those tools return. The same input can produce a different sequence of actions depending on context, session history, and what an external tool happened to return. Behavior is the attack surface, and behavior changes. Traditional proxies and AI firewalls were built to inspect content: what a user sent, what a model returned. Intent security asks a different question: is this agent doing what it was built to do, in this context, for this user, right now? Answering that requires building a behavioral baseline for every agent and measuring deviation from it continuously. That is the problem Lasso was built to solve....

Attackers prefer the path of least resistance. Why break in when you can log in? That is what makes working credentials so valuable. A leaked password, token, or API key does more than reveal sensitive data; it offers a way in. No vulnerability or privilege escalation chain necessary. If the credential is valid, the attacker can simply use it, and the session will look like ordinary activity. This shifts the questions from "where can attackers break in?" to "where do usable keys tend to accumulate? Increasingly, the answer is the developer laptop: one of the most instrumented machines most companies own, and one of the easiest places for credentials to go unnoticed. The endpoint is watched for malware, behavior, posture, and configuration. But a valid plaintext credential is something else: a door an attacker may not need to force. A fully patched fleet can still have usable keys scattered across its devices, enough to turn one foothold into something much larger....

Why Authentication Context Matters Most people think logging in is a small act. Type your password, type your code, tap a screen, scan a face, and move on. But to the systems on the other side, the method behind that moment can matter just as much as the fact that it happened at all. That is where two strangely named but surprisingly important identity concepts enter the story: OIDC's AMR and SAML 2.0's AuthnContext. They sound like the kind of acronyms that only standards committees could love, yet both were created to answer a deeply human question in digital form: How sure a system has to be before it trusts someone? The backstory starts with the internet growing up. Early online services often treated authentication as a light switch: either the user was in, or the user was out. But as online systems began handling payroll, health records, taxes, academic data, contracts, and financial approvals, that simple model started to crack. A login backed by a reused password is not ...

Modern attacks are not primarily defeating infrastructure. They are inheriting trust. Identity Did Not Become Important. It Became Infrastructure. Security teams still talk about identity as though it is one security discipline among many, sitting beside endpoint protection, cloud security, network defense, and vulnerability management. That framing no longer reflects how modern enterprises actually operate. Modern business environments run on identity, delegated trust, cloud roles, automation pipelines, APIs, machine permissions, and continuously exchanged credentials. Users authenticate into SaaS platforms that the organization does not own. Workloads assume permissions that nobody provisions manually. Services trust other services built across years of acquisitions, migrations, technical debt, and operational compromise. The enterprise is no longer running on infrastructure alone. It is running on identity. Attackers recognized this shift before many defenders did. That i...

Identity sprawl, agentic AI risk, and the path to NHI governance maturity When security leaders talk about identity risk, the conversation almost always centers on humans: Privileged users, compromised accounts, insider threats. But for most enterprises, the greater risk has already shifted. And it has nothing to do with your employees. Non-human identities (NHIs) — service accounts, API keys, OAuth tokens, SSH keys, RPA bots, cloud workload credentials and AI agents — are the fastest-growing, least-governed attack surface in the modern enterprise. And the industry is beginning to reckon with what that means. $4.88M Global average cost of a data breach — IBM Cost of a Data Breach 2024 The scope of the problem The numbers are striking. Research from Rubrik Zero Labs puts the NHI-to-human identity ratio at 45:1 in the modern enterprise. For cloud-native and DevOps environments, Entro Labs H1 2025 research puts that figure at 144:1.  These identities are not passive: They au...

Most of the commentary on Anthropic's Claude Mythos Preview has gone in one of two directions: one camp treats it as the civilizational inflection point, the other as marketing dressed up as a research result. Neither read is particularly useful for a security leader who still has a program to run on Monday. The AISLE team's technical response to the Mythos announcement made a fair point worth sitting with: much of what was demonstrated is recoverable on smaller, open-weight models, particularly on the discovery side. Early testing results of OpenAI's GPT 5.5 show CTF performance close to or slightly superior to Mythos; the exclusivity framing is arguable, but the accelerated model improvement in offensive security is undisputable. The UK AI Security Institute found that Mythos can autonomously execute a complete corporate network takeover, succeeding in 30% of its attempts on a complex attack range — a task AISI estimates would require roughly 20 hours for a human e...

The event that didn't exist At 2:14 p.m. on a Tuesday, an employee clicks a link. If you reconstruct the moment from your security stack, nothing happened. A browser process opened an HTTPS connection. The certificate was valid. The destination wasn't flagged. Traffic volume was unremarkable. No detections fired. Inside the browser session, a different story was unfolding. The page that loaded looked like a routine CAPTCHA with "verify you're human" framing, a prompt to complete a quick check to continue. The instructions told the user to press Windows+R, paste what had already been copied to their clipboard, and hit Enter. In the middle of a busy work day, they did. What they pasted was a shell script. It executed in the user's own context, with the user's own permissions, as a deliberate action the user performed with their own hands. Nothing about the browser session looked unusual. The page rendered normal web content. The clipboard write happene...

For security leaders, the inbox remains the front door for attackers. Here's why the smartest teams are adding adaptive, AI-driven protection to their cloud email security, not replacing them. Email is still the number-one attack vector for enterprises, and it is not even close. The FBI's Internet Crime Complaint Center reported that business email compromise alone generated $3 billion in losses in 2024 , with AI-enabled attacks accelerating the trend ( FBI IC3 Report ). The attacks that succeed today don't carry obvious malicious payloads. They rely on trust, tone, and timing; a spoofed vendor sending a "routine" invoice update, or a convincing impersonation of a CEO with an urgent request. No malware. No suspicious links. Just words, carefully chosen. Microsoft 365 is the backbone of productivity for most organizations, and Microsoft Defender and Exchange Online Protection do solid work catching known spam, malware, and co...

How session cookie theft bypasses MFA — and what you can do about it When you check into a hotel, you show your ID at the front desk. The clerk verifies who you are, maybe checks a secondary piece of information, and hands you a key card. From that point on, that key card is what gets you into your room. It doesn't matter that you proved your identity at check-in. What matters is who has the key. Your applications work the same way. When a user logs into a web application — entering their password, completing an MFA challenge — the application issues them a session token, typically stored as a cookie in their browser. That token is their key card. Every subsequent request the user makes, the application checks for the token, not the credentials. If the token is valid, access is granted. And if someone steals that token? They get in, too. No username required. No password required. No MFA prompt. They simply ...

Vulnerability management is the continuous process of identifying, assessing, prioritizing, and addressing security weaknesses across systems, applications, and infrastructure. It extends beyond periodic scanning; it includes validating findings, understanding exposure in real-world environments, and tracking remediation over time. Effective vulnerability management combines asset visibility, vulnerability intelligence, and operational context to determine which flaws present actual risk rather than theoretical exposure. Modern IT environments further complicate the process of vulnerability management. Hybrid IT infrastructure, third-party dependencies, and internet-facing services increase the attack surface while generating large volumes of vulnerability data. Security teams must balance operational constraints, such as out-of-support legacy systems and uptime requirements, with the need to quickly reduce exposure. As a result, vulnerability management is no longer limited to coun...

Higher education institutions operate some of the most complex identity environments of any industry. Universities often struggle to balance open access for learning and research with strong security controls to protect students, faculty, and sensitive institutional data. This contrast creates unique identity security and management challenges that require specialized strategies and tools. A Highly Complex Identity Ecosystem Unlike corporate businesses, the ecosystem that is common at universities requires them to manage a variable and highly diverse population of users. Churn is a constant challenge, with students, faculty, alumni, researchers, contractors, and affiliate colleges and labs, and other contributors enrolling, changing roles or status, tracks or departments, and leaving frequently.  This dynamic ecosystem results in an identity lifecycle that is far more fluid than most corporate environments. "Joiners", or new identities, are created continuously, while "movers a...

When Shai-Hulud 2.0 hit in late 2025, it was a brutal, expensive wake-up call for DevSecOps teams. It showed that the industry's direction of shifting left, where teams pass security onto developers, wasn't the silver bullet everyone hoped for. Pushing that responsibility was fine in theory, but it crumbled quickly because the foundation it was built on was inherently flimsy. As we move further into 2026, we need a more definitive fix to the structural weakness in the pipelines in light of a potential Shai-Hulud 3.0. A major lesson from 2.0 was that internal CI/CD runners were easily hijacked and turned into attack botnets. Teams need to take that finding and come back with a truly proactive defense. A curated catalog is a way for security teams to control exactly what code and components enter their environment, while still giving engineering teams a fast, secure way to build - it is the key to creating a sustainable solution. More on a curated catalog later. The Anatomy o...

For decades, the firewall was the most trusted enforcement point in enterprise security. Every packet crossed it. Every policy lived on it. If you wanted to secure the network, you started there. Then work moved somewhere the firewall couldn't follow. Today, the average enterprise employee spends most of their day inside a browser — navigating SaaS applications, collaborating in cloud platforms, running queries through AI tools, and sharing files through web interfaces. All of it travels over HTTPS. All of it looks identical at the network layer: port 443, encrypted, and opaque. The firewall sees a connection. It doesn't see a ChatGPT prompt containing customer PII. It doesn't see a browser extension silently harvesting credentials. It doesn't see the SaaS file-sharing that just moved sensitive data outside the organization's control. This is the visibility gap that defines enterprise security in 2026. SSE Was the Right Answer — Deployed the Wrong Way Securi...