Straiker Blog

Learn why every enterprise deploying AI agents needs a kill switch and how Straiker secures AI before and during runtime.

Learn how Straiker's Agentic Kill Switch helps enterprises immediately disable compromised AI agents and reduce AI security risk.

Anthropic's Claude models escaped sandboxed tests and reached real systems 3 times. See why AI agents need a kill switch outside the lab.

Everything you need to know about the EU AI Act. Scope, prohibited practices, non-compliance fines up to €35M, and the real compliance deadlines for 2026-2028.

Discover the biggest AI security talks from Black Hat USA 2026 covering AI agents, prompt injection, LLM exploits, AI red teaming, defenses, and more.

Compare the top agentic AI security platforms for 2026 across AI agent discovery, Agent-SPM, AI red teaming tools, MCP security, AI chatbot guardrails, AI agent runtime security, and related security workflows.

Straiker secures Claude Chat, Cowork, and Code with runtime detection at 98.1 to 99 percent, full traceability, and a Skills and MCP scanner that stops indirect prompt injection. Now part of Wave 3 of the Claude Compliance API.

Thousands of real-world exploits against coding, productivity, and first-party AI agents. The data, the named threats, and the STAR Framework defenders need. Join the waitlist to read it first.

In agentic AI, the model behaves and the user is legitimate. The weapon is the context the agent reads. Here is why we built the Straiker STAR Framework to map the agentic attack surface, and how it supplements the NIST AI RMF and OWASP.

The inaugural STAR Labs report ran real exploits on AI agents. Among the findings: 91% of successful attacks on productivity agents left no trace.

Straiker threat models Emergent’s Wingman agent, showing how connected AI agents can be exploited through untrusted content, cross-connector flows, and autonomous actions.

Google's Antigravity coding agent, running on Gemini 3.1 Pro, loaded a compiled file that never should have run, then used the cloud's own internal network to walk the data out the back door.

Carl Vincent, a Straiker researcher, built Andromeda: an AI agent that writes its own red team payloads in real time. A Toorcamp 2026 prototype, now open source.

A seasoned cybersecurity revenue operator, Puthucode joins Straiker to scale global go-to-market following the company's $64M Series A.

‍Round led by Marathon with continued support from Bain Capital Ventures and Lightspeed. Trusted by Fortune 500 enterprises and Frontier AI labs, the company defends the fastest-growing workforce in the enterprise: AI agents.

Agentic security is real-time protection for AI agents—the systems that plan, call tools, and act on behalf of enterprises—delivered by Straiker’s Defend AI runtime engine and its medley-of-experts architecture, purpose-built to handle the complexity of agent behavior rather than just model safety.

Shadow AI is bigger than unsanctioned AI tools. Learn why security teams need visibility and governance inside sanctioned AI use, AI-SPM, and Agent-SPM.

Straiker has been named a winner of the 2026 Intellyx Digital Innovator Award.

Play the first playable video game CTF for AI security. Three challenges: prompt injection, remote code execution, memory poisoning. New chapters every quarter.

Straiker is named on the CSA Agentic AI Security Innovator Market Map across four categories, and as a Sample Vendor in three Gartner 2026 Hype Cycle reports.

Most AI governance tools are solving last year's problem. See how eight vendors compare on agent inventory, MCP scanning, and true Agent-SPM.

Straiker researchers uncovered a live infostealer campaign impersonating 30+ fake Claude Code, JetBrains, and NotebookLM pages. Full technical analysis with reversed C2 protocols, IOCs, and hardcoded wallet addresses.

What is offensive AI security testing for AI agents? Gartner positions Straiker with distinct AI-ST capabilities as organizations adopt semantic detection, runtime security, and continuous adversarial testing for autonomous AI agents.

Guardrails shape what an agent says. They don’t control what it does. The tool calls, the data reads, the actions taken on your credentials: that’s where the risk actually lives.

Top 7 AI runtime security platforms for 2026 compared across OWASP Agentic Top 10 (ASI01-ASI10), LLM Top 10, MCP tool poisoning, indirect prompt injection, and agent data exfiltration.

Why the Five Eyes guidance on agentic AI changes security architecture: privilege, behavioral, structural, and accountability risks demand runtime visibility, adversarial testing, and guardrails.

Top 6 AI red teaming and adversarial testing tools for 2026 compared across the OWASP Agentic Top 10, MCP testing, and multi-agent risk.

OpenAI, Google DeepMind, and Anthropic built their agent security frameworks independently and reached the same conclusions. Here's what they agree on.

Straiker recognized for achievements in model and agent security

AI coding agents, vibe-coded apps, and MCP servers are changing how we build. Learn why runtime protection and AI agent discovery are critical for safe AI adoption.

Pattern-based AI security filters miss encoded instructions, emoji-based bypasses, and multi-step hijacks — the attacks most commonly used against AI agents today. Semantic detection catches all of them.

Most security teams start with AI usage controls. Then coding agents start shipping faster than any policy can track. Here's why Agent-SPM is the layer that actually keeps up.

AI agents are autonomous systems that act. See why prompt injection is the #1 agentic threat, and what semantic detection does that patching can't.

Anthropic couldn't safely release their most powerful model. That's not just a safety story. It's an adversarial roadmap. Claude Mythos is a step function in AI capability, for defenders and adversaries alike. Model hardening alone doesn't close that gap.

OWASP published three separate AI security landscapes in Q2 2026: one for LLM and GenAI applications, one for agentic AI, and a first-ever Red Teaming Landscape. Each maps a categorically different attack surface. This breakdown explains what changed, why agentic security requires different controls, and what continuous red teaming means for teams shipping agents.

By deploying AI agents across order support and post‑purchase flows, DTC brands can cut average handling time by around 25% (McKinsey), improve team‑level productivity and cost‑to‑serve by about 30% (Gartner), and automate 80% of routine customer service requests without human intervention (Gartner).

NomShub is a critical vulnerability chain in the Cursor AI code editor where a malicious repository can silently hijack a developer's machine, combining indirect prompt injection, a sandbox escape via shell builtins, and Cursor's built-in remote tunnel to give attackers persistent, undetected shell access triggered simply by opening a repo.

Straiker is listed as a sample vendor in the Agentic AI Security profile of Gartner's inaugural Hype Cycle for Agentic AI — one of the furthest-along profiles in the report, with a High benefit rating and a 2–5 year time to plateau.

On March 31, 2026, Anthropic accidentally exposed 512,000 lines of Claude Code source via npm. Here's what the leak reveals about context poisoning, sandbox bypass, and the evolving threat model for AI coding agents.

As agents rapidly spread across the enterprise, the attack surface is the entire enterprise operating system. Straiker gives security teams the control plane to deploy agents securely. 

A practitioner's take on the most important agentic AI security sessions at RSAC 2026, from OWASP AIVSS to AIKatz and the rise of AI-powered threats.

Straiker is named a Representative Vendor in the Gartner® Market Guide for Guardian Agents. See how we secure AI agents with 98.1% detection accuracy.

As autonomous AI agents introduce risks that legacy security tools weren't built to handle, Straiker has been named an EMA Vendor Vision 2026 Visionary at RSAC for its ground-up approach to agentic security.

Experience Straiker’s red team vs blue team laser tag arena at RSAC 2026. See how adversarial AI testing and AI runtime security protect modern AI agents.

The enterprise AI landscape has evolved. What started as simple chatbots has now become an ecosystem of autonomous agents, agentic browsers, and agentic co-pilots embedded throughout business workflows. Each represents a fundamental shift in enterprise systems and each introduces unique attack surfaces that traditional security can't address.

SF Bay Area-based startup achieves record traction with AI threat detection and agentic runtime security, landing multiple six-figure and seven-figure deals across D2C, financial services, healthcare, and high-tech sectors

Over 50% of financial services organizations have deployed AI agents. Most lack the security to scale them safely.

Straiker uncovered an active agent-to-agent attack chain where malicious Claude Skills on ClawHub are spread via fake AI personas, enabling crypto scams and private key theft. The research shows AI skill marketplaces are already becoming a new supply chain attack surface

Agent hijacking moves lateral movement into agent workflows, making runtime behavior monitoring essential for securing agentic AI.

A sophisticated supply chain attack targeting the MCP ecosystem used fake GitHub accounts and a cloned Oura Ring server to infiltrate developer environments with credential-stealing malware.

Security research uncovered over 4,500 exposed Clawdbot/Moltbot instances globally—concentrated in the US, Germany, Singapore, and China—with testing confirming attackers can exfiltrate API keys, service tokens, and WhatsApp session credentials for surveillance.

High-tech companies are inventing the future of AI—and its security challenges. Learn how to secure AI-native products, MCP integrations, and novel agent vulnerabilities at competitive speed.

Healthcare AI has the same security threats as any other industry, but because mistakes can directly harm patients, teams must test and secure agents for real-world, ambiguous patient interactions—not just obvious adversarial attacks.

DIY guardrails, open-source tools, and cloud-native security isn't enough in banking and FSI. Here's why—and what 85% of financial institutions deploying AI need instead.

Straiker CEO's honest reflections on what it takes to build an AI security company when chatbots become agents, acquisitions accelerate, and customers still don't know what they need.

Gartner predicts 40% of enterprise apps will integrate AI agents by 2026. Despite 75% of leaders citing security as their top concern, organizations are deploying anyway because waiting means falling behind.

AI agents are shipping by default. Learn how Defend AI delivers production-grade agentic security with real-world detections, accuracy, and research-driven coverage.

OWASP just released its first Top 10 for Agentic AI. From goal hijacking to rogue agents, here's a plain-English breakdown of the 10 risks every security team needs to understand.

Microsoft's Security Copilot agents mark agentic AI's shift to production. With 80% of orgs reporting risky behaviors, runtime guardrails are now essential for secure deployment.

New STAR Labs research shows how Perplexity Comet executed a zero click Google Drive wipe from a single email. Learn why agentic browsers create new security risks.

Discover the top AI and cybersecurity conferences for 2025-2026. From RSA and Black Hat to NeurIPS and AI Summit NYC—your essential guide to industry events.

Enterprises are shifting from chatbots to copilots to agentic AI. This blog maps AI maturity stages, compares integration models, and shows how Straiker delivers runtime guardrails across SDK, eBPF, proxy, and gateway options to secure production AI.

As AI agents enter production, static security scans (SAST) can’t catch dynamic, reasoning driven risks. Learn how to integrate Autonomous Attack Simulation (AAS) into your CI/CD pipeline to test and harden agent behavior before deployment.

Milestone marks Straiker's breakthrough work in protecting agentic AI applications

AI supply chain security inherits all the long-standing vulnerabilities of traditional software—open-source dependencies, CI/CD risks, and infrastructure weaknesses—while introducing new, AI-specific threats. From model weights and datasets to prompt pipelines and plugin ecosystems, every layer expands the attack surface, requiring a fresh approach to securing the AI development lifecycle.

Learn why AI red teaming is different and compares three approaches that security leaders are weighing today.

Understand the next evolution of artificial intelligence. Learn how generative AI differs from agentic AI—how agents move beyond content creation to autonomous reasoning and action—and why this shift defines the future of enterprise AI.

OWASP, CSA, NIST, and MITRE are each shaping the future of AI security in their organizations’ objective: developer-focused, orchestration-specific, governance-led, or adversary-driven.

Reflections from Jason Sansone's first 30 days at Straiker as the Global VP of Sales and why I chose securing agentic AI apps as the place to put my energy into now.

Straiker uncovers Villager, a Chinese-based pentesting framework that acts as an AI-powered framework in the style of Cobalt Strike, automating hacking and lowering the barrier for global attackers.

The Salesloft Drift breach shows how quickly an AI chatbot can become an enterprise-wide supply chain risk when integrated to critical business systems like Salesforce, and why AI-native security has to be built in from the start.

This blog explains how memory in LLMs underpins both usability and security, showing why its design is critical to preventing data leaks, emergent exploits, and autonomous chaos... and how Straiker leverages memory to red-team and defend AI agents.

Straiker reveals how zero-click exploits can hijack AI agents to exfiltrate Google Drive data, no user interaction needed. See how attack chains form, why autonomy is dangerous, and how runtime guardrails catch what others miss.

Straiker’s attack and defense agents think, act, and adapt like AI agents, uncovering vulnerabilities, simulating real-world exploits, and enforcing real-time guardrails to stop prompt injection, tool misuse, and emergent threats before autonomous chaos takes hold.

The new capabilities in Ascend AI and Defend AI add automated red teaming, real-time guardrails and full-chain forensics to secure every agentic application.

The shift to agentic and generative AI applications is here to stay, and so is the responsibility to secure data and trust at the speed of AI.

Straiker, a leading provider of AI-native security solutions for enterprise AI applications and agents, today announced the availability of Ascend AI and Defend AI in the new AI Agents and Tools category of AWS Marketplace.

This June, Straiker Ascend AI and Defend AI

Exploiting GitHub Issues to hijack AI agents shows why full agent traceability is key to preventing multi-stage AI breaches.

New in this release: flexible CI/CD integration, comprehensive runtime document protection, and adaptable deployment options, enabling security teams to protect AI applications without constraining innovation.

More than 20 AI chatbots fell victim to prompt injections in what we call the Yearbook Attack.

The Straiker AI Research (STAR) team found a new attack that we’re calling MCP rebinding attack, which is a combination of DNS rebinding and MCP over Server-Sent Events (SSE) protocol.

Grounded in research, informed by practice – Straiker partners with OWASP AI Exchange

Straiker is leading the way with our product announcement to secure agentic workflows with MCP.

4 new capabilities to level up your AI security with Straiker's April 2025 release

Agentic AI's emergent behaviors changes how we play the cybersecurity game

The Rise of Straiker: Founder's Story unveils how a team of builders, hackers, and defenders came together to secure the future of intelligent systems.

AI applications are dynamic, making the attack surface and vulnerabilities behave differently than traditional applications.

An AI Security Researcher’s Perspective

Straiker has emerged from stealth mode with $21 million in funding from Lightspeed Ventures and Bain Capital Ventures to launch the first AI-native security platform designed to protect enterprise AI applications and autonomous agents from evolving threats through automated assessment and runtime guardrails.

This post introduces the unique security challenges posed by agentic architectures and why traditional security measures aren’t equipped to handle them.

AI's transformative potential is immense, but securing it requires a new, AI-native approach

Why Lightspeed invested in Straiker

Why Bain Capital Ventures Invested in Straiker