MCP Security
× Running MCP servers in production? 40 plus CVEs in 2026 · Are you exposed? Schedule a Meeting → QUICK ANSWER · MCP SECURITY 40 PLUS CVES · 2026 The Model Context Protocol (MCP), released by Anthropic in November 2024, lets AI agents call external tools, APIs, files, and services through a standardised interface. Between
EU AI Act Compliance
× August 2026 high risk AI deadline? Article 9 security testing · Ready? Schedule a Meeting → QUICK ANSWER · EU AI ACT AUG 2 2026 DEADLINE EU AI Act Regulation 2024/1689 Article 9 requires providers of high risk AI systems to establish, implement, document, and maintain a risk management system throughout the
AI Security
× SW Saudi AI compliance help? SDAIA · PDPL · NCA · 30 min scoping call Talk to Our Team → QUICK ANSWER · SAUDI ARABIA FIRST MOVER · 2026 An Arabic LLM security audit tests four risk surfaces that English-only evaluations miss: Arabizi (Arabic chatspeak) and transliteration jailbreaks that bypass refusals working in standard Arabic, dialectal
AI Security
When my team runs an AI security audit in 2026 whether it is a usual chatbot, a RAG pipeline, an agent, or a multi-agent system/application we find critical issues in the first hour of testing nine times out of ten. Not in week one. Not in day one. In
LLM Security
If you are budgeting for an LLM security audit or AI red teaming engagement in 2026, the honest market range is $6,000 to $45,000 or more depending on what you are actually buying. The bottom of that range covers a single chatbot, no tools, no compliance attachment. The
Prompt Injection
On 11 June 2025, Microsoft disclosed CVE-2025-32711 code-named EchoLeak, CVSS 9.3 a zero-click indirect prompt injection in Microsoft 365 Copilot. By sending a single crafted email with no user interaction required, an attacker could cause Copilot to access internal files and exfiltrate them to an attacker-controlled server. The chain
LLM Red Teaming
LLM applications shipped fast, mostly without a security review, and the attack surface has been catching up ever since. Prompt injection now sits at the top of OWASP's LLM Top 10 for the second consecutive year. Agentic systems with the ability to call functions, browse the web, and
LLM Security
Most organisations securing AI applications are doing it wrong not because they're careless, but because they're applying web application security thinking to a fundamentally different attack surface. A standard pentest doesn't test prompt injection. It doesn't test whether your RAG system leaks
LLM Security
Large Language Model (LLM) security has become a critical concern as organizations deploy AI systems into production environments that handle sensitive data, internal workflows, and user-facing logic. While many teams rely on prompt filtering, content moderation, or policy-based guardrails, these approaches often fail against real threats. Modern LLM attacks are
LLM Security
Large Language Models (LLMs) have become central to next-generation applications, powering everything from customer service chatbots to complex decision support tools. But with increased use comes increased risk. Adversaries are not just exploiting single prompt bugs; they are actively probing, manipulating, and breaking models using systematic adversarial techniques. This article
LLM Security
× Only tested with one prompt? Multi-turn jailbreak testing · Ready? Schedule a Meeting → QUICK ANSWER · LLM JAILBREAKING MULTI-TURN RISK Jailbreaking a production LLM is no longer about finding one clever prompt. Black-box models are stochastic systems accessed through unlimited, repeatable interaction — which turns the exchange into a repeated game where retries