Blog & Resources

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.

Download Straiker's datasheet to see how our AI security, red teaming, and runtime guardrails protect agentic AI apps.

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.

Watch the video

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