CurlSek Security Blog

Expert insights on AI-powered penetration testing, offensive security, LLM vulnerabilities, and autonomous cybersecurity. Stay updated with the latest security intelligence, threat research, and best practices from CurlSek.

Beyond the OWASP Top 10: Engineering Logic Vulnerabilities in AI-Driven Architectures

For years, the OWASP Top 10 has served as a shared language between security teams, developers, auditors, and vendors. Injection flaws, broken authentication, access control issues remain relevant and continue to cause real-world breaches. But as application architectures evolve, an uncomfortable truth is becoming harder to ignore: Some of the most impactful vulnerabilities no longer map cleanly to OWASP categories at all. They live in logic, state, and assumptions; and increasingly, they emerge from AI-assisted and event-driven systems.

Detecting React2Shell at Scale: How CurlSek's Probe Agent Delivered Rapid, Validated Response Across Customer Assets

When the React2Shell vulnerability began circulating across security feeds, engineering and AppSec teams worldwide scrambled to understand three critical questions: Are we exposed? Where exactly is this vulnerable component used? Can we validate exploitability before triggering broad incident workflows? For teams running modern JavaScript stacks, especially React-based frontends and middleware; the clock started ticking the moment proof-of-concept exploits appeared online. Learn how CurlSek's Probe agent delivers rapid, validated response for continuous pentesting.

Building Autonomous Pentesting Pipelines with AI

Building Autonomous Pentesting Pipelines with AI: A Practical Guide for Modern Engineering Teams

Modern engineering pipelines move fast. Feature branches merge daily, microservices deploy independently, and cloud infrastructure evolves continuously. Yet, one part of the pipeline remains stuck in the past: security testing. Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) tools help, but they generate noise and rarely validate their findings. Manual pentesting is accurate but slow, expensive, and episodic. Discover how continuous AI-powered pentesting integrates into CI/CD workflows.

AI Agents Are Quietly Changing Offensive Security

AI Agents Are Quietly Changing Offensive Security - And We Need to Talk About It

Over the last year, we've seen a noticeable shift in how AI interacts with real systems. Not the hype around "AI writing exploits," but something far more practical: models that can plan, keep track of system state, interact with tools, and retry when the first attempt fails. For those of us who've spent years in engineering and security, this feels like the start of a very different era. Explore autonomous security agents in offensive security testing.

Beyond the Hype: Unmasking the Critical Vulnerabilities in Your LLM Supply Chain

Beyond the Hype: Unmasking the Critical Vulnerabilities in Your LLM Supply Chain

The age of AI is upon us, transforming industries and unlocking unprecedented capabilities. Large Language Models (LLMs) are at the heart of this revolution, driving innovation from enhanced customer service to advanced data analysis. Yet, beneath the surface of this powerful technology lies a complex and often overlooked vulnerability: the LLM supply chain. For many organizations, the question is no longer if they will embrace AI, but how they will secure it. The reality is stark: the components that fuel your LLMs—external datasets, third-party APIs, and pre-trained models—are not just building blocks; they are potential attack vectors. These interconnected elements form a digital supply chain, each link presenting an opportunity for malicious actors to compromise your AI systems, intellectual property, and ultimately, your business continuity.

Beyond Traditional Pentesting: Why AI-Driven Security is the Future

Beyond Traditional Pentesting: Why AI-Driven Security is the Future

The Shifting Landscape of Cyber Threats. Penetration testing has long been the go-to approach for identifying security weaknesses before attackers do. However, in today's dynamic, cloud-native, AI-driven attack landscape, traditional pentesting is starting to show serious limitations. Let's put things into perspective: Zero-day vulnerabilities are being exploited within hours of discovery. Traditional pentests often occur quarterly or annually, making them too slow to catch emerging threats. Dynamic cloud environments change daily, sometimes hourly, rendering one-time security assessments outdated before they are even completed. Attackers are automating reconnaissance and exploitation using AI, adversarial ML techniques, and large-scale fuzzing engines—while defenders are still relying on manual, human-heavy testing cycles. This raises a fundamental question: Can security testing evolve at the same speed as cyber threats? Learn how continuous pentesting addresses these challenges.

OpenAI's Operator Agents & The Future of AI-Driven Cybersecurity

OpenAI's Operator Agents & The Future of AI-Driven Cybersecurity

The Next Leap: Autonomous AI in Cybersecurity. AI isn't just assisting security teams anymore—it's operating independently. OpenAI's Deep Research & Operator Agents introduce a new paradigm: LLM-powered agents capable of executing complex, multi-step tasks with near-autonomy. This fundamentally alters how AI is integrated into security operations—both for defense and offense. Security teams are already leveraging AI for threat intelligence, pentesting automation, and SOC augmentation, but these new autonomous agents raise some critical questions: How do we secure AI systems that are making real-time security decisions? What happens when offensive AI leverages these agents for adversarial operations? Do we need security frameworks specifically designed for AI-driven automation?

The Rise of Offensive AI in Cybersecurity – Are We Already Behind?

The Rise of Offensive AI in Cybersecurity – Are We Already Behind?

The Cyber Arms Race: AI vs. AI. Cybersecurity is no longer a human-versus-human battlefield. Artificial intelligence is now actively shaping both defense and offense and organisations must adapt or risk being outpaced by AI-driven threats. Security teams are increasingly deploying AI-powered defensive solutions, but attackers are doing the same—except their models are unrestricted, unregulated and optimised for weaponised automation. The question is: Are security teams evolving fast enough to counter AI-driven cyberattacks?