All news with #agent security tag

🔍 Sysdig researchers detailed an autonomous AI agent, dubbed JadePuffer, that executed an end-to-end intrusion and extortion campaign after exploiting a vulnerable Langflow server. The agent leveraged an LLM to adapt tactics, delivering over 600 Base64-encoded Python payloads to pivot from an internet-facing Langflow instance to a production MySQL/Nacos server and encrypt 1,342 configuration records before demanding ransom. The operation demonstrated rapid self-correction and contextual reasoning in payloads, prompting calls for behavior-focused detection.

🛡️ Researchers at the Hong Kong University of Science and Technology show that simple file-level transformations and packing tricks can let malicious AI coding agent "skills" evade existing static scanners while still executing normally. Their tool, SKILLCLOAK, fooled multiple marketplace scanners over 80–99% of the time, while a runtime sandbox, SKILLDETONATE, detected most evasions at the cost of slower analysis. The study highlights active real-world abuse, practical mitigation ideas, and the need to move trust decisions to behavior observed at execution time.

🛡️ Researchers discovered two vulnerabilities in the Cursor AI-enabled IDE that enable prompt-injection-driven remote code execution by escaping the command execution sandbox. The flaws, CVE-2026-50548 and CVE-2026-50549, allow attackers to change the working directory and exploit symlink canonicalization fallbacks to write or overwrite files outside the project scope. Cursor patched the issues in version 3.0, and the findings underscore broader risks in agentic AI workflows and the difficulty of defending against prompt injection.

🧩 Researchers at LayerX demonstrated a prompt injection called BioShocking that trains AI-powered browsers to treat risky real-world actions as fictional, bypassing safety controls. The PoC used a themed puzzle game to reward 'wrong' behavior and culminated in instructing agents to copy sensitive data from a GitHub repo. Six mainstream agentic browsers were tested; only one vendor implemented a working fix after disclosure. LayerX recommends explicit user confirmations, stricter context checks, and session scope limits.

🖥️ Amazon WorkSpaces for agents is generally available, enabling AI agents to securely access and operate desktop applications inside managed WorkSpaces. The service lets agents interact with legacy ERP, CRM, mainframe, and proprietary tools without application modernization or custom integrations, while preserving identity controls, network isolation, and compliance boundaries. It supports any agent framework using the Model Context Protocol (MCP), and pricing is based on active session time.

🛡️ This Microsoft Incident Response post examines an attack pattern targeting Model Context Protocol (MCP) tools, where poisoned tool metadata causes agentic AI to perform unauthorized actions. It outlines a playbook for detecting, containing, and preventing these attacks using Microsoft security controls and maps techniques to the OWASP Top 10 for Agentic Applications. The guidance emphasizes treating MCP servers as supply-chain dependencies, reviewing tool descriptions as prompts, and applying least agency controls.

🔒 New research from Adversa AI, dubbed GuardFall, shows a decades-old shell trick can bypass simple blocklist checks in open-source AI coding agents, letting hidden destructive commands run. The flaw arises because filters inspect the command as plain text while shells like bash rewrite and expand that text before execution. Ten of eleven tested agents were vulnerable; only Continue defended by parsing commands the same way the shell does.

🔒 AWS announces general availability of AWS WAF protection for Amazon Bedrock AgentCore Gateway, enabling protection of agentic AI workloads from common web exploits and abuse. You can associate an AWS WAF protection pack with your AgentCore Gateway to enforce IP-based access controls, rate-based throttling, and AWS Managed Rule Groups including Bot Control. Configure protections once at the Gateway and have them applied consistently to all targets behind it.

🔒 Google Cloud announces new VPC Service Controls features to secure agentic AI deployments by enforcing network-level perimeters and integrating agent identities. These updates let administrators add agent principals and principalSets to ingress/egress rules, apply conditional rules based on MCP attributes like mcp.toolName and mcp.method, and automatically protect the Gemini Enterprise Agent Platform from public internet access. The enhancements are designed to complement IAM and resource policies to prevent exfiltration and tool misuse in production agent fleets.

🛡️ This guide examines how agentic AI shifted enterprise identity risks and why existing IAM controls fall short. It explains how AI agents inherit human permissions, traverse systems at machine speed, and create an expanding population of autonomous identities often deployed without security review. The piece outlines the guardian agent concept: a purpose-built runtime control layer that inventories agents, baselines behavior, detects anomalies, and enforces least-privilege at execution time to close the governance gap.

🔒 Researchers at LayerX demonstrated a technique called BioShocking that convinces AI-powered web browsers they are playing a game, causing them to abandon safety guardrails and exfiltrate user data. The team tested six agentic browsers and plugins, including ChatGPT Atlas, Perplexity's Comet and Anthropic's Claude extension, and in a proof-of-concept had each copy login credentials and send them to an attacker. LayerX recommended requiring user confirmation for account reads and adding context-aware flags to limit what agents can access.

🔒 This article examines the rising need for AI security posture management (AI-SPM) as enterprises adopt AI across workflows. It outlines how AI maturity stages — from AI-assisted to AI-native — change security requirements and why agents and model services expand the attack surface. The piece surveys vendor approaches, key features, and integrations, and provides guidance for selecting AI-SPM solutions to avoid coverage gaps.

🛡️ A security firm, AIR, created a benign but deceptive AI agent skill named brand-landingpage, pushed it through a major skill marketplace and promoted it with an Instagram ad, and reports it reached roughly 26,000 agents including corporate accounts. Scanners from vendors like Cisco and NVIDIA marked the package safe because the skill pointed to external setup documentation rather than embedding malicious code. AIR later swapped the external page to deliver a harmless payload that collected email addresses, demonstrating how scanners miss links that can be rewritten after review. The experiment highlights structural trust problems with skills and common mitigations such as pinning versions and vetting external references.

🛡️ Shadow AI has evolved from simple data leakage to an access control challenge as employee-built agents connect to enterprise systems. These agents — created across platforms, extensions, and scripts — can call APIs, use credentials, and perform actions in production, often with broad or forgotten permissions. Traditional controls like DLP and domain blocking miss non-human identities, so organizations must inventory agents, map ownership and credentials, and enforce automated remediation.

🔒 Microsoft demonstrated a new remote code execution path called “AutoJack,” showing how web-enabled AI agents can be hijacked to reach local Model Context Protocol (MCP) services and execute arbitrary processes. The researchers exploited three weaknesses in AutoGen Studio’s MCP WebSocket implementation—origin allowlist inheritance, missing authentication for MCP paths, and unsanitized URL-supplied server parameters that spawn processes. Microsoft reported and mitigated the issue in development builds and warned this pattern could affect other agentic frameworks.

🛡️ Ongoing research found an exploit chain in AutoGen Studio that allowed untrusted web content rendered by a browsing agent to reach a local Model Context Protocol (MCP) WebSocket and spawn arbitrary processes on the host. Microsoft’s team reported the issue and maintainers hardened the main branch in commit b047730; the vulnerable MCP WebSocket surface was never included in the PyPI release. The advisory explains the attack chain, remediation steps, and developer guidance to avoid localhost trust-boundary risks.

🔒 Check Point and AWS are collaborating to secure enterprise AI agents by integrating Amazon Bedrock AgentCore with Check Point AI Security. This partnership extends AgentCore’s identity, gateway, registry, and policy capabilities with runtime behavioral protections that monitor agent actions across models, tools, data, and applications. The integration enables policy-driven governance, visibility into agent deployments, and prevention of misuse such as prompt injection or unintended data exposure.

🛠️ This blog demonstrates using AI agents to automate a VB6 disassembler by exposing its parsed model through the Windows Running Object Table and providing an operator briefing plus auto-generated prototypes. The agent (Claude Code in the examples) binds to the COM object, runs scripts to extract P-code, reconstruct source, generate call graphs, and export function metadata to SQLite, all locally without uploading binaries. The approach decouples tool features from fixed menus, enables repeatable exhaustive analysis, and preserves sensitive data on the analyst's workstation.

🛡️ Amazon Web Services announced that Amazon Bedrock AgentCore now supports Bedrock Guardrails in policy, enabling enterprises to enforce safety and security controls on AI agents in production. AgentCore policy authorizes which actions agents can take and now evaluates outputs and gateway inputs in real time to detect and block prompt injection, harmful content, and sensitive data exposure. Guardrail enforcement occurs at the AgentCore gateway perimeter, with all evaluations logged via AgentCore observability for auditing and optimization. The capability integrates with existing gateway deployments, supports natural language or policy-as-code authoring, uses consumption-based pricing, and is available in multiple global AWS regions.

🔍 AWS announces new AgentCore optimization capabilities that turn production traces into continuous agent improvements. The features surface failure, intent, and trajectory insights across sessions to reveal silent and recurring failures, then generate data-grounded recommendations for prompts and tool descriptions. Batch evaluation and A/B testing validate fixes against defined metrics before rollout, and capabilities work across AgentCore runtime, Lambda, EKS, and non-AWS environments.