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10 most critical LLM vulnerabilities
OWASP updated its Top 10 LLM application vulnerabilities, ranking prompt injection first and elevating excessive agency to third amid agentic adoption.
OWASP refreshed its Top 10 list of critical vulnerabilities in LLM applications, for the first time incorporating real-world incident data alongside expert voting. Prompt injection and sensitive information disclosure remain first and second, while excessive agency jumped from sixth to third as agentic systems that call APIs and execute code proliferate. Unbounded consumption of AI resources rose in prominence, while improper output handling dropped to the bottom as output sanitization becomes widespread. The list includes remediation guidance such as strict output schemas, human-in-the-loop approvals, and least-privilege credentials held in application code.
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OWASP Flags Top AI Skill Risks in New Security Blueprint
OWASP released a new top 10 security list for AI skills and introduced a Universal Skill Format to standardize security of AI add-ons.
The Open Worldwide Application Security Project (OWASP) published a new top 10 risk list tailored to AI skills, the add-on capabilities extending AI agents. It also debuts a Universal Skill Format intended to add consistency and security to these AI add-ons. The blueprint gives defenders a structured way to assess risks introduced by third-party skills.
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The OWASP Top 10 for LLM Applications 2026: From Model Risks to Agentic Security
Akamai analyzes the OWASP Top 10 for LLM Applications 2026, which shifts focus from model-level risks to agentic AI security.
The OWASP Top 10 for LLM Applications has been updated for 2026, and Akamai published an analysis of the revised list. Per the title, the 2026 edition shifts emphasis from model-level risks toward the security of agentic AI systems, framed as a realistic security model. No article body was available, so the specific ranked risk entries cannot be enumerated.
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Rubrik MCP gives AI agents controlled access to security intelligence
Rubrik launched MCP support exposing Rubrik Security Cloud APIs to enterprise AI agents with RBAC, configurable permissions, and OWASP MCP Top 10 guardrails.
Rubrik announced Rubrik MCP (Model Context Protocol), giving organizations' AI agents a secure, programmable path to Rubrik's data, identity, and application intelligence via the Rubrik Security Cloud API schema. Teams can save multi-step recovery or compliance workflows as reusable, deterministic tools, with role-based access control parity and OWASP MCP Top 10 aligned guardrails. Rubrik engineered its agent architecture with Anthropic's teams for multi-step reasoning in incident response, and says Rubrik AI is now trusted by one-third of its global customers.
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When the prompt becomes the payload: A practical pen-testing guide for GenAI, LLM and RAG applications
CSO Online publishes a practical penetration-testing guide for GenAI, LLM, and RAG applications, covering prompt injection, retrieval poisoning, and tenant isolation testing.
The guide frames LLM applications as attack graphs spanning prompts, retrieval layers, vector stores, tools, identities, and downstream APIs, arguing that conventional web testing misses instruction-vs-data channel risks. It builds on OWASP prompt injection guidance (direct vs. indirect injection) and NIST's 2025 adversarial machine-learning taxonomy, noting that RAG and fine-tuning do not remove injection risk. Recommended practices include documenting trust transitions across components, using canaries and synthetic records to avoid test side effects, running multi-turn and obfuscated injection campaigns, and verifying chains from poisoned documents to observable state changes. It also details testing RAG pipelines via controlled document poisoning across metadata, OCR layers, and code comments, plus cross-tenant isolation checks on retrieved document IDs.
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AI Agents Are Here. So Are the Threats.
Unit 42 demonstrates nine framework-agnostic attack scenarios against AI agents built with CrewAI and AutoGen, causing data leakage, credential theft and remote code execution.
Palo Alto Networks Unit 42 investigated how attackers can target agentic applications, implementing two functionally identical apps with the open-source CrewAI and AutoGen frameworks and executing the same attacks on both. Nine attack scenarios produce outcomes including information leakage, credential theft, tool exploitation and remote code execution. Findings show most vulnerabilities are framework-agnostic, arising from insecure design patterns, misconfigurations and unsafe tool integrations rather than flaws in the frameworks themselves. The team published defense strategies per scenario and open-sourced the source code and datasets on GitHub.
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PuzzleMask: Abusing Plain Prose as a Covert AI Attack Vector
Check Point details PuzzleMask, a plain-prose technique that bypasses LLM gatekeeper policy checks, letting hidden payloads reach target models unreviewed.
Check Point Research describes PuzzleMask, a prompt-crafting technique that hides policy-violating payloads inside plain-English prose wrappers, bypassing quick LLM-based policy checks without emojis, Base64, or invisible formatting. The researchers tested 23 automated prompts against gatekeepers including GPT-4o-mini, GPT-OSS-Safeguard 20b, Claude 3 Haiku, and Llama Guard 3, and all were classified as safe despite policies that flagged the plain versions. When submitted to GPT-5 in thinking-high mode with a Python interpreter, the target model extracted and acted on the payload in over 90% of trials. The technique is not itself a jailbreak but can carry a jailbreak prompt as payload; mitigations include input paraphrasing, hardened gatekeeper policies, and output monitoring.
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Reflectiz Launches Agentic Pentesting for Websites: Up to 10x Coverage vs Conventional Pentests
Reflectiz launched a multi-agent AI penetration testing platform for websites, claiming up to 10x more coverage than conventional pentests.
Reflectiz, a continuous web exposure management vendor, launched a multi-agent penetration testing platform for websites under a new Offensive Hub. Four specialized agents crawl the site like a real user, fingerprint the stack, run attacks, and independently validate findings to remove false positives. The company claims up to 10x more coverage than conventional pentesting by starting from its pre-existing live model of each site. Findings integrate via REST API, CI/CD triggers and Slack, and the Atlas remediation agent guides fixes.
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Reflectiz Launches Agentic Pentesting for Websites: Up to 10x Coverage vs Conventional Pentests
Reflectiz launched a multi-agent AI penetration testing platform for websites, claiming up to 10x more coverage than conventional pentests by leveraging existing site context.
Reflectiz, a web exposure management vendor, announced an agentic penetration testing product within a new Offensive Hub. The platform uses specialized AI agents for crawling, stack fingerprinting, attack execution, and independent validation, claiming to cover the OWASP Top 10 and reduce false positives. Findings integrate with existing workflows via REST API, CI/CD triggers, and Slack, and an AI remediation agent named Atlas guides fixes. The announcement is a vendor press release with a planned September 15 webinar demo.
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Securing AI agents: Key controls and best practices
Security experts warn AI agents with employee-level privileges outpace human access controls and advise layered enforcement, sandboxing, and approval gates.
CSO reports that enterprises granting AI agents credentials, tools, and network access face risks that human-focused identity controls cannot contain, including machine-speed action chaining and sub-agent spawning. Experts from Strike Graph, Veracode, Delinea, and XBOW recommend treating agents as privileged insiders with hard technical boundaries: egress proxies with allowlists, short-lived brokered tokens, separated read/write rights, and approval for high-risk actions. XBOW describes a layered architecture with a guardian model reviewing agent actions and per-agent audit files. OWASP guidance on excessive agency urges limiting agent functions, permissions, and autonomy with authorization enforced downstream.
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Your AI agent's system prompt is not a security control
AWS and SANS guidance says system prompts are not security controls; enforce user permissions at retrieval time and default-deny every agent tool invocation.
AWS VP Gee Rittenhouse and SANS fellow Eric Johnson, with three AWS security specialists, published agentic AI security guidance for organizations with agents running or under development. They recommend scoping queries to user permissions inside existing RBAC/ABAC systems and filtering results before the model's context window, noting prompts can be bypassed, ignored, or overridden. The guidance warns risk concentrates when one agent holds sensitive data access, external communication, and exposure to untrusted content, the vector for prompt injection, which OWASP ranks as the top AI application threat. It cites IBM 2025 research that ungoverned shadow AI added $670,000 to average breach cost, and prescribes 30-day behavioral baselines, Cedar or Open Policy Agent for default-deny tool invocation, and four-layer containment with automatic circuit breakers.
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New CISO appointments 2026
Companies including Mistral AI, Trellix, Marriott, and ANZ appointed new CISOs in July-September 2026 amid high security-leadership turnover.
CSO Online's rolling column tracks senior security appointments, noting many companies are hiring a CSO/CISO for the first time. Notable moves include Thomas Coudray leaving Ledger to become Mistral AI's CISO, David Soto joining Trellix from Amazon, and Daniel Dubowski becoming Marriott International's SVP and CISO. Other appointments span ANZ, Gigamon, Axonius, Tricentis, Remitly, Allied Universal, and the State of California.
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BugBase Pentest Copilot Enterprise automates black-box pentesting
BugBase launched Pentest Copilot Enterprise, an autonomous AI black-box pentesting platform using parallel agents to attack 100 vulnerability classes with validated PoCs.
BugBase announced Pentest Copilot Enterprise, which performs black-box red teaming without source-code access while maintaining authenticated context. Parallel specialized agents map pages, APIs, accounts and business functions, then execute iterative attacks across 100 vulnerability types including authentication, injection and business-logic flaws. The tool uses real Chromium browsers to preserve cookies, tokens, CSRF state and multiple identities, and navigates WAFs, bot detection, CAPTCHA and T-OTP. BugBase claims full scope coverage on OWASP Juice Shop, Broken Crystals and GOAD, NHA, and DRACARYS Active Directory labs.
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What 90 days and a small budget can buy in AI agent security
Versa Field CISO details hidden costs of self-hosting open-weight models and a 90-day AI agent security plan of inventory, blast-radius reduction and testing.
In a Help Net Security interview, Prasad Tharippala, Field CISO at Versa, argues running open-weight models in-house improves control but shifts hardening, patching, access control, monitoring and incident response onto the buyer, with underestimated costs in GPU infrastructure, licensing review, EU AI Act compliance and scarce AI/ML security skills. On red-teaming AI agents, he recommends testing prompt injection, indirect injection, excessive permissions, data leakage, memory and RAG poisoning, malicious tool outputs, cross-agent trust abuse and infrastructure attack paths, mapped to OWASP agentic guidance and MITRE ATLAS. He highlights the handoff between chained agents as a major risk zone and stresses exercising human approval, shutdown and rollback controls under test conditions. For teams with 90 days and small budgets, he ranks inventory, blast radius reduction and ongoing testing as the priority order.
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One in four MCP servers opens AI agent security to code execution risk
Noma Security whitepaper finds most popular AI Skills and many MCP servers carry high-risk capabilities, with state changes most prevalent.
Noma Security analyzed hundreds of popular MCP servers and Skills across eight risk categories, finding most widely used Skills carry at least one risky characteristic and a typical enterprise runs well over a hundred high-risk agent tools, with arbitrary code execution common across MCP servers. The most prevalent risk is the ability to change state or data, and named toxic combinations include ContextCrush data leakage, ForcedLeak via poisoned Salesforce CRM records, DockerDash supply-chain compromise, the Replit production database deletion, and the hijacked Amazon Q VS Code extension. Building on OWASP LLM06:2025, the paper proposes the No Excessive CAP framework of capabilities, autonomy, and permissions, recommending allowlisting, MCP version pinning, approval gates on irreversible actions, and user-scoped expiring credentials.
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Prisma Cloud WAAS Archives
Unit 42 archive page for Prisma Cloud WAAS, Palo Alto's web application and API security module; contains no new findings.
This is a product category archive page from Unit 42 describing Prisma Cloud Web Application and API Security (WAAS). It advertises protection spanning the OWASP Top 10, API protection, risk profiling, file upload and geolocation controls for cloud-native architectures. No new research findings, incidents, or vulnerabilities are reported.
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