Search: “Model Context Protocol (MCP)”

Your AI agents can now control your Google Home devices

Google launches early-access MCP server letting MCP-capable AI agents like Claude and ChatGPT control Google Home devices.

Google rolled out early access to a Model Context Protocol (MCP) server for Google Home, allowing agents such as Claude, ChatGPT, Hermes, OpenClaw, and Google Antigravity to control Nest devices, review camera summaries, monitor activity, and access event history. Setup requires a Google Cloud project configured for Home MCP plus user permission grants. Access begins this week for US Google Home Premium Advanced ($20/month) subscribers, with broader rollout timing unannounced.

TechCrunch · AI·17:00 UTC · 3h agoAI industry 2 sources

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.

Help Net Security·10:41 UTC · 9h agoTools1

How MCP Servers Can Expose Enterprise Secrets

MCP servers holding AI agent credentials risk secret exposure via plaintext configs, credential sprawl, prompt injection, and over-permissioning; mitigations include centralization and least privilege.

The article examines how Model Context Protocol servers, which hold API keys, tokens, and service-account credentials for AI agents, can leak enterprise secrets. Documented exposure paths include plaintext credentials in config files, ungoverned credential sprawl, prompt injection, over-permissioning, and untrusted third-party servers. It cites CVE-2025-6514 in mcp-remote (400,000+ downloads), where a malicious server triggered OS command injection leading to remote code execution. Recommended mitigations include centralized secret stores, short-lived auto-rotated credentials, least privilege, and human approval for sensitive actions.

The Hacker News·Aug 17, 11:58 UTC · Aug 17, 2026AI safety & securityCVE-2025-6514

How Cloudflare detects MCP traffic and helps secure it

Cloudflare Gateway now detects Model Context Protocol traffic via protocol-level heuristics to expose shadow MCP usage and enforce approved-server access.

Cloudflare Gateway identifies Model Context Protocol (MCP) requests using protocol-level heuristics. Security teams can use the signal to discover shadow MCP traffic on managed networks, enforce Portal-only access for approved MCP servers, and block direct connections. The updates extend standard gateway and zero-trust controls to AI agent traffic.

Cloudflare Blog·Aug 14, 13:12 UTC · Aug 14, 2026Tools

Meta now lets AI agents handle the boring parts of WhatsApp Business setup

Meta launched a WhatsApp Business Tools MCP server that lets AI agents like Claude or Cursor set up and manage WhatsApp Business messaging accounts.

Meta announced a WhatsApp Business Tools MCP server, a Model Context Protocol server that connects AI coding agents such as Claude, Cursor, Codex, or ChatGPT directly to the WhatsApp Business Platform. The agents can handle account creation, phone number verification, Cloud API registration, Terms of Service checks, messaging template creation/editing, and webhook testing. Meta's companion Social Technologies MCP can also discover API endpoints, search documentation, and troubleshoot errors. The launch extends Meta's existing MCP servers for ad management and app configuration monitoring.

TechCrunch · AI·Sep 15, 20:12 UTC · 1d agoAI tools & infra

Your enterprise AI footprint is about three times bigger than your model list

Help Net Security·Aug 5, 00:00 UTC · Aug 5, 2026AI safety & security

Fortinet expands AI security portfolio with Virtue AI acquisition

Fortinet acquired Virtue AI to add agent red-teaming, MCP scanning and runtime guardrails to its AI security portfolio.

Fortinet acquired Virtue AI to extend its Security for AI strategy beyond FortiAIGate, which protects LLMs from prompt injection, data leakage and model poisoning. Virtue AI brings automated agentic red-teaming across 50+ sandboxed environments and 14 domains, agent discovery and governance including MCP tool scanning, continuous AI validation, and real-time guardrails across text, images, video, audio and code. Financial terms were not disclosed and the consideration is immaterial to Fortinet; Gartner projects the AI security market to grow from $2.8B in 2026 to $16.4B by 2030.

Help Net Security·Aug 17, 00:00 UTC · Aug 17, 2026Industry

Opaque recurrence, and other AI terms that you should probably know

TechCrunch updates its plain-English glossary defining common AI terms from AGI and agents to chain-of-thought reasoning.

TechCrunch maintains a regularly updated glossary of AI terminology, defining terms such as AGI, AI agents, API endpoints, chain of thought, coding agents, compute, deep learning, and diffusion. It highlights 'opaque recurrence', the reasoning technique in OpenAI's new Astra model that has drawn attention from AI safety researchers. The piece is an educational living document rather than new research or a product announcement.

TechCrunch · AI·Sep 7, 19:24 UTC · 9d agoAI industry1

Agent Harness vs Agent Framework vs MCP: Which Layer Owns the Loop, State, Tools, Permissions, and Recovery

Architecture explainer separates agent harnesses, frameworks, and MCP by which layer owns the loop, state, permissions, and recovery.

The article distinguishes agent harnesses (OpenAI Codex, Claude Agent SDK), which own the execution loop, sandbox, permission model, and recovery; frameworks (LangGraph, OpenAI Agents SDK, Microsoft Agent Framework), which supply composable primitives; and MCP, a stateless JSON-RPC wire protocol governed by the Linux Foundation's Agentic AI Foundation since December 2025. An ownership matrix maps the execution loop, state, tool transport, permissions, recovery, sandboxing, and multi-agent orchestration to each layer. The 2026-07-28 MCP specification made the protocol fully stateless, retiring the initialize handshake and session headers.

MarkTechPost·Sep 14, 21:54 UTC · 1d agoAI research1

⚡ Weekly Recap: AI Goes Rogue, Metabase 0-Day, MCP Supply

The Hacker News·Aug 10, 15:03 UTC · Aug 10, 2026Ransomware in the wildCVE-2026-34348CVE-2026-18497CVE-2026-63508+43 CVEs1

Amazon Kiro Prompt Injection Can Exfiltrate Sensitive Data Through Kiro Powers

Mindgard found a prompt injection flaw in Amazon Kiro IDE letting attacker-controlled workspace files exfiltrate sensitive local data; fixed in version 0.8.140.

Mindgard disclosed a prompt injection flaw in Amazon Kiro, an agentic AI IDE, that lets attacker-controlled repository content steer the agent into exfiltrating sensitive workspace data through Kiro Powers, which bundles MCP server configurations, POWER.md steering files, hooks, and contextual knowledge. Exploitation requires the user to open a malicious project via a workspace file and send any message to the agent; difficulty is rated low and it works in both trusted and untrusted workspaces. Amazon fixed the issue in Kiro IDE 0.8.140; the flaw has no CVE identifier and follows earlier Kiro bugs including CVE-2026-10591, plus related prompt-injection and code-execution issues in Codex CLI, Cursor, Gemini CLI, Copilot CLI, and Claude Code.

The Hacker News·Aug 28, 18:35 UTC · 19d agoAI safety & securityCVE-2026-10591CVE-2026-35603CVE-2026-257251

[remote] mcp-server-kubernetes 3.8.x - Argument Injection

Argument injection in mcp-server-kubernetes 3.8.x MCP server could allow AI clients to execute unintended Kubernetes operations.

Exploit-DB entry 52638 documents an argument injection vulnerability in mcp-server-kubernetes version 3.8.x, a Model Context Protocol server that lets AI assistants interact with Kubernetes clusters. Crafted input can inject additional arguments into commands executed by the server, potentially enabling unauthorized operations or command execution against the cluster. This highlights growing security concerns around MCP servers bridging LLM agents and infrastructure.

Exploit-DB·Aug 11, 00:00 UTC · Aug 11, 2026Exploit / PoC

GTIG AI Threat Tracker: From Prompting to Autonomy – The Evolution of Adversarial AI

GTIG's Q2 2026 tracker shows adversaries adopting agentic AI workflows, including credential harvesting in under six hours and supply chain attacks by UNC6780.

Google Threat Intelligence Group's Q2 2026 report documents adversaries moving from basic prompting to agentic AI workflows and automation, including a cloud compromise followed by agent-enabled mass credential harvesting executed in under six hours. It tracks financially motivated actor UNC6780 (TeamPCP) conducting large-scale open source supply chain compromises across PyPI, npm, and Docker Hub since March 2026, deploying credential stealers. The report also highlights growing targeting of proprietary AI models, source code, prompts, and API credentials, plus LLMJacking practices where adversaries steal developer credentials or hijack cloud infrastructure to run unauthorized AI workloads.

Google Threat Intelligence·Sep 8, 14:00 UTC · 8d agoThreat actor in the wild1

ToolHive: The open-source way to run any MCP server securely

Stacklok's open-source ToolHive runs Model Context Protocol servers in isolated containers with per-request identity enforcement, audit logging and a signed registry.

ToolHive, shipped under Apache 2.0, containersizes MCP servers locally via Docker or Podman or in clusters through a Kubernetes operator, applying permissions, network filtering, and secrets management. The platform includes a Registry Server implementing the official MCP Registry API with signing and provenance verification, a Virtual MCP Server gateway with OIDC/OAuth single sign-on and OpenTelemetry traces, and a desktop Portal for one-click installs. The browser-based cloud UI is retired, so the desktop app and CLI are the supported rollout paths.

Help Net Security·Sep 7, 00:00 UTC · 9d agoAI tools & infra1

Off Guard: Breaking LiteLLM from authentication bypass to cloud compromise

Wiz found LiteLLM auth bypass (CVE-2026-59822) and post-auth RCE (CVE-2026-59821) chainable to cloud compromise; the bypass is in CISA KEV with in-the-wild exploitation.

Wiz scanned roughly 3,074 internet-facing LiteLLM deployments and found 9.6% accepted the default master key sk-1234 or required no authentication, making post-auth attacks effectively pre-auth. The MCP endpoint accepts any Bearer token and grants a valid session (CVE-2026-59822), confirmed exploited in the wild via honeypots and added to CISA's Known Exploited Vulnerabilities catalog. Custom code guardrails allow post-auth root-level RCE via exec(compile(...)) (CVE-2026-59821), while pass-through endpoints lack URL validation, enabling cloud credential theft in post-auth scenarios. All assigned vulnerabilities have been patched; the research was presented at DEF CON 34.

Wiz Blog·Sep 9, 16:06 UTC · 7d agoExploit / PoC in the wildCVE-2026-59822CVE-2026-598211

Akuity gives AI agents operational context to safely ship software

Akuity launches Agentic Control Plane and MCP Server to govern AI agent actions inside production software delivery pipelines.

Akuity introduced an Agentic Control Plane and MCP Server that lets AI agents such as Claude, Codex, and Cursor access deployment and cluster context under existing identity, permission, and audit controls. MLB reported the product identified over 100 degraded applications within hours. Akuity positions it against open-source MCP servers granting raw access with no identity inheritance or policy layer.

Help Net Security·Sep 15, 08:37 UTC · 1d agoAI tools & infra

When AI Agents Go Rogue: Agent Session Smuggling Attack in A2A Systems

Unit 42 unveils agent session smuggling, where a rogue AI agent hides covert instructions in established Agent2Agent (A2A) protocol sessions to manipulate victim agents.

Palo Alto Networks Unit 42 discovered agent session smuggling, a new attack technique in which a malicious AI agent exploits an established cross-agent session under the Agent2Agent (A2A) protocol to send covert instructions hidden among benign client requests and server responses. The technique leverages the implicit trust agents place in collaborating agents and the stateful, multi-turn nature of A2A sessions; the researchers stress it affects any stateful protocol, not an A2A flaw. Unlike one-shot data-based attacks, a rogue agent can converse, adapt and build false trust over multiple interactions. Proposed mitigations include human-in-the-loop enforcement, cryptographically signed AgentCards for remote agent verification, and context-grounding to detect injected instructions.

Palo Alto Unit 42·Aug 17, 12:32 UTC · Aug 17, 2026AI safety & security2

Authorization Architectures for Tool-Using AI Agents

Review paper proposes an authorization reference architecture for tool-using AI agents, identifying runtime enforcement and delegation bounds as unresolved gaps.

This review examines authorization models for tool-using AI agents that invoke APIs, databases, browsers, and protocols like MCP, arguing every consequential agent action must be traceable to a human principal, bounded by delegation, and contestable. It introduces a principal hierarchy spanning human user, operator/deployer, orchestrator agent, sub-agent, and tool endpoint, and analyzes five layers including credential lifecycle, delegation propagation, runtime enforcement, prompt injection as authorization bypass, and auditability. Drawing on 89 primary sources from 2023-2026, it proposes seven structural requirements, a four-layer reference architecture, and three deployable configurations.

arXiv cs.CR·Sep 14, 17:21 UTC · 2d agoAI safety & security

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.

Help Net Security·Aug 24, 04:21 UTC · 23d agoAI safety & security

ThreatsDay: 296K IoT Botnet, 100+ Water Systems Targeted, SharePoint RCE Chain + 27 New Stories

Weekly ThreatsDay bulletin details a ShinyHunters-style social engineering hit on ReliaQuest, the 296,000-device Dysphoria IoT botnet, and several new malware families.

ReliaQuest confirmed a social engineering attack on August 22, 2026, in which an attacker used a fake SSO page and MFA push approval to gain brief view-only access to an identity dashboard, with tactics matching ShinyHunters, which has since listed the firm on its leak portal. The Shadowserver Foundation reported the Dysphoria botnet has compromised nearly 296,000 IoT devices for DDoS attacks and recently added residential proxy capability. Cisco Talos documented JWR, an operator-driven phishing-as-a-service framework linked to The Outsider that harvests credentials, identity documents, and 2FA codes over an encrypted WebSocket. New malware coverage includes the Octagon Android fraud bot ($1,400/month), the C2Looper Rust backdoor delivered via ClickFix, and the Aeternum loader that moved C2 to the Polygon blockchain.

The Hacker News·Sep 1, 17:35 UTC · 15d agoMalware in the wild

Fresh-Challenge VDF Attestations for Model-Relative Response Latency

Fresh-Challenge VDF Attestations bind verifiable delay functions to unpredictable public challenges, yielding succinct evidence of model-relative response latency.

The paper specifies FCLA, a protocol composition that binds a VDF to an unpredictable public challenge, a message, and independently auditable release/receipt records. Under explicit assumptions about VDF sequentiality and a calibrated bound on an adversary's sequential evaluation rate, an accepted transcript is inconsistent with post-challenge generation. A benchmark of the public reference implementation confirms the expected evaluation-versus-verification separation on one documented machine. The contribution is a protocol design analysis, not a new VDF construction.

arXiv cs.CR·Sep 11, 11:25 UTC · 5d agoResearch

Nearly 1 in 10 Exposed LiteLLM Gateways Accepted the Example "sk-1234" Admin Key

Wiz found 294 of 3,074 internet-facing LiteLLM gateways accepted the documented default admin key sk-1234, exposing provider API keys and cloud IAM credentials.

Wiz Research's February Shodan scan found 3,074 LiteLLM gateways, 294 of which accepted the setup guide's sk-1234 admin key; 191 had no master key set and would accept any credential. The master key doubles as the authentication switch, and before 1.82.0-stable a gateway started without one granted every request full admin rights, exposing stored provider API keys, prompts, and MCP-connected tools. A documented pass-through endpoint lacks checks against private and cloud metadata addresses, letting an admin-key holder retrieve cloud IAM credentials, though no real-world abuse is reported. Related LiteLLM flaws include CVE-2026-59821 (disputed guardrail code execution), CVE-2026-59822 (CVSS 8.8, added to CISA KEV on September 2 and observed against Wiz honeypots), and CVE-2026-42271, used to install a cryptominer.

The Hacker News·updated Sep 10, 12:56 UTC · 6d ago·first Sep 10, 07:12 UTC · 6d agoVulnerability in the wild 3 sourcesCVE-2026-59821CVE-2026-59822CVE-2026-42271+2 CVEs

MicroHasTEE: Bare-Metal Haskell for Type-Level Peripheral Ownership on Armv8-M

MicroHasTEE expresses TrustZone secure and non-secure firmware as one typed Haskell program, catching peripheral-ownership inconsistencies at compile time.

MicroHasTEE is a multiparty Haskell framework that models both TrustZone firmware images as participants in a single typed program, using type-level capability ledgers to track peripheral acquisition, configuration, transfer, and finalization. MicroHs compiles the shared program twice to produce separate bare-metal Secure and Non-secure firmware images. The framework rejects inconsistent resource use, post-configuration attribution changes, wrong-domain callbacks, and calls to unregistered Secure services. A door-lock case study on an STM32U5 Nucleo board produced images of 232.7 KiB and 228.4 KiB of flash with roughly 220 KiB of SRAM per domain.

arXiv cs.CR·Sep 11, 08:34 UTC · 5d agoResearch1

AI supply chain risk is showing up in developer workflows first

Zentera Systems CEO says AI supply chain attacks currently hit developer workflows first, advising segmentation over tooling and citing the Phantom Raven campaign.

In an interview, Zentera Systems CEO Dr. Jaushin Lee argues that most active AI supply chain incidents target developer workflows and open-source package repositories, while poisoned model weights, compromised MCP servers, and poisoned vector stores remain largely in research and demos. He cites the active 'Phantom Raven' campaign, where attackers register AI-hallucinated package names in public repositories with malicious payloads that silently infect vibe-coding build pipelines. He recommends software-defined segmentation, semiconductor-style project enclaves with egress controls, and warns that self-hosting models without agent sandboxing leaves exposure unchanged.

Help Net Security·Aug 25, 00:00 UTC · 22d agoAI safety & security

Survey of filesystem MCP servers: how the "sandboxed filesystem" boundary is enforced (one breach, four defended-by-design)

Survey finds one filesystem MCP server vulnerable to a symlink-based sandbox escape while four others are defended by design.

A survey of five filesystem MCP servers assessed how each enforces its path-confinement boundary against symlink escapes in recursive directory walkers. The iceener/files-stdio-mcp-server is vulnerable to a read-side sandbox escape. The other four are defended by design or make no confinement claim. The author describes the vulnerability class as small but real.

oss-security·Sep 10, 01:14 UTC · 6d agoVulnerability

Infostealers Target Claude, Cursor, Codex and Other AI Agents to Steal Credentials and Sensitive Data

Gen Digital researchers report infostealer families Amatera, Remus and CallbackBeaver now harvest Claude, Cursor and Codex agent data, including tokens and MCP configs.

Gen Digital researchers found commodity infostealers extending their collection rules to local AI coding agent data from Claude, Cursor, Codex, Cline, Continue and OpenCode on Windows and macOS. Amatera targets Cline and Continue, Remus targets Claude, Cursor and OpenCode, and CallbackBeaver added Claude and Cursor with more than 5,000 samples observed in 30 days; Djinn Stealer hits Claude, Codex, Gemini, Cline, OpenCode and Kilo on macOS. Stolen data includes access and refresh tokens, prompt histories, conversation databases and MCP configurations holding API keys, potentially exposing connected source-control, cloud and ticketing systems. Remus is assessed as a Lumma Stealer variant using EtherHiding C2 resolution via Ethereum smart contracts.

GBHackers·Sep 9, 07:05 UTC · 7d agoMalware in the wild1

Evaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks

Context segmentation framework boosts memory-constrained gemma-4 agents on picoCTF, solving 18.52% of tasks standard execution fails, highlighting local SLM offensive risk.

The paper introduces context segmentation, a two-level agentic framework that divides long-horizon CTF exploitation tasks into contextually isolated sub-problems to counter context bloat and cognitive degradation from accumulated tool-call outputs. It evaluates memory-constrained gemma-4 models on the picoCTF dataset; the E4B model achieves competitive rewards with superior token efficiency compared to brute-force retries. It solves 18.52% of tasks that standard agentic execution fails to complete. The work frames locally deployed open-weight SLMs as an escalating risk since they bypass proprietary API guardrails; code is released on GitHub.

arXiv cs.CR·Sep 11, 13:34 UTC · 5d agoAI safety & security1

ENCP: Episode-Normalized Conformal Prediction for Vision-and-Language Navigation

ENCP calibrates conformal prediction per navigation episode, giving step-level coverage guarantees for vision-language navigation agents despite within-episode dependence.

Episode-Normalized Conformal Prediction (ENCP) rescales a nonconformity score by a VLN policy's residual confidence and calibrates one maximum score per episode, preserving step-level coverage of at least 1−α despite dependence among steps within an episode. Across four VLN policies and three nonconformity scores on R2R and REVERIE, ENCP meets all reported empirical step-coverage targets in seen-to-unseen evaluation. The model-agnostic uncertainty estimates can signal when an agent should defer to a stronger predictor or human assistance.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 17:42 UTC · 1d agoAI research

Marimo Notebook Flaw Could Run MCP Commands Before Cells Execute in Edit Mode

Marimo notebook flaw CVE-2026-75149 (CVSS 8.7) allows attacker-supplied MCP commands to run as local subprocesses before any cell executes in edit mode.

Marimo addressed CVE-2026-75149, a high-severity code injection flaw allowing attacker-supplied Model Context Protocol (MCP) commands to execute as local subprocesses when a crafted notebook is opened in edit mode, before any cell runs. The issue affects versions prior to 0.23.15, carries CVSS v4 of 8.7 and CVSS v3.1 of 8.8, and requires user interaction but no authentication. Marimo fixed it in version 0.23.15 (released July 23, 2026) via a PEP 723 hardening patch that treats notebook metadata as attacker-controlled and strips ai, mcp, completion, secrets, and server configuration sections. VulnCheck's CNA also disclosed CVE-2026-67618 (CVSS 7.1), involving an attacker-controlled AI base_url that exfiltrates operator API keys, and earlier CVE-2023-39987, a missing auth on /terminal/ws endpoint allowing full PTY shell access.

The Hacker News·Aug 25, 12:43 UTC · 22d agoVulnerabilityCVE-2026-75149CVE-2026-67618CVE-2026-39987

RMM Tools for MSPs: Features, Risks & How to Stay Secure

Threat actors continue abusing MSP remote monitoring and management tools to reach downstream customers, four years after the Kaseya supply chain attack.

Huntress examines how RMM platforms remain a favored gateway for attackers targeting managed service providers and their clients. A recent incident demonstrates that adversaries still successfully pivot from MSP RMM tooling into downstream customer environments. The piece also covers RMM features, associated risks, and hardening guidance for providers.

Huntress·Sep 1, 04:00 UTC · 15d agoThreat actor in the wild

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.

CSO Online·Sep 8, 08:25 UTC · 8d agoAI safety & security

Bitsight connects threat intelligence and exposure monitoring across the supply chain

Bitsight made Beacon generally available, combining supply-chain exposure monitoring with MCP support to feed threat intelligence into AI workflows.

Bitsight announced general availability of Beacon, which continuously monitors critical vendors for exposure, vulnerabilities, malicious activity, intrusion, stolen credentials and compromise. New Model Context Protocol (MCP) and agentic capabilities push Bitsight intelligence into AI-enabled workflows, with over 400 customers signing up for early access in one month. The company cites data that third parties now account for almost half of enterprise breaches, up over 60% year over year.

Help Net Security·Sep 14, 13:42 UTC · 2d agoTools

Microsoft AI Code of Conduct Sets Cyberattack Boundaries, Chain of Command, Safety Constraints

Microsoft AI's draft Humanist AI Code of Conduct blocks MAI models from producing exploit code and constrains autonomous agent behavior.

The draft code sets 'Absolute Constraints' preventing MAI models from generating working exploit code, attack tooling, or intrusion guidance, while permitting authorized defensive work such as vulnerability discovery and malware analysis. A 'Chain of Command' rule means tool outputs, file contents, and webpages carry no authority over model behavior, countering injected instructions. Microsoft opened a six-week public consultation; a revised version will guide 2027 model development, and current MAI Models were not trained on the document.

SecurityWeek·Sep 15, 09:40 UTC · 1d agoAI safety & security1

Context Engineering Inside the Harness: 4 Mechanisms That Beat Context Overflow and Goal Loss on Long-Horizon Tasks

Survey of four harness mechanisms—context budgeting, compaction, todo-state, and memory—that keep long-horizon LLM agents on task across 200+ tool calls.

The article details how agent harnesses, not larger context windows, solve context overflow and goal loss on long-horizon tasks, citing Chroma's Context Rot report showing 18 LLMs (GPT-4.1, Claude 4, Gemini 2.5, Qwen3) degrade on long inputs. Concrete implementations include LangChain Deep Agents offloading tool responses over 20,000 tokens to the filesystem and truncating old tool calls at 85% window usage, and Claude Code capping auto memory at 25KB while re-reading the 5 most recently modified files after compaction. OpenAI's Responses API now offers server-side compaction via context_management with a standalone /responses/compact endpoint, which Codex uses for long-running coding tasks. Manus reports a roughly 100:1 input-to-output token ratio per ~50-tool-call task, motivating todo.md state recitation to prevent goal drift.

MarkTechPost·Sep 13, 05:56 UTC · 3d agoAI research1

CISA Adds Seven Exploited Flaws as Attackers Deploy Reverse Shells and Crypto Miners

CISA added seven actively exploited vulnerabilities to its KEV catalog, including SonicWall SMA 1000 SSRF CVE-2026-83548, amid campaigns deploying reverse shells and crypto miners.

CISA's KEV additions cover flaws in SonicWall SMA 1000 (CVE-2026-83548, CVE-2026-83549), Sangoma Switchvox (CVE-2026-9586), JFrog Artifactory (CVE-2026-82329), Kludex Starlette (CVE-2026-48710), Kestra OSS (CVE-2026-49869) and Berri LiteLLM's MCP endpoint (CVE-2026-59822). SonicWall confirmed active exploitation of the SMA 1000 flaws, while Microsoft and Wiz reported attackers chaining LiteLLM flaws CVE-2026-42271 and CVE-2026-48710 to fingerprint hosts, steal provider API keys and deploy XMRig miners on AI infrastructure. Wiz linked exploitation of the LiteLLM chain to the Qilin ransomware group, and Microsoft detailed a Kestra compromise chain ending in cryptocurrency mining and data harvesting via exposed RAGFlow flaws.

The Hacker News·Sep 3, 05:19 UTC · 13d agoExploit / PoC in the wildCVE-2026-83548CVE-2026-83549CVE-2026-9586+10 CVEs1

Bring Licensed Threat Intelligence into Every Conversation with SOCRadar and ChatGPT

SOCRadar launched a Threat Intelligence MCP app connecting ChatGPT to its licensed threat intelligence via OAuth-authenticated MCP server.

SOCRadar announced a Threat Intelligence MCP app that connects ChatGPT to the SOCRadar MCP server over OAuth. The integration exposes the vendor's licensed intelligence models directly in ChatGPT conversations. The announcement is a vendor product launch with no incident or vulnerability content.

SOCRadar·Sep 7, 10:28 UTC · 9d agoTools

AI Coding Tools Now a Prime Target for Threat Actors, Google Warns

Google Threat Intelligence Group warns threat actors increasingly target AI coding tools and proprietary AI data, with UNC6780's Dustmaker enabling large-scale supply chain compromises.

Google Threat Intelligence Group's September 8 report says AI-assisted coding tools have become prime targets, contributing to large-scale software supply chain compromises in 2025 and early 2026. Financially motivated group UNC6780 used its Dustmaker credential stealer to extract tokens from GitHub Actions runner memory and compromise packages across PyPI, npm, and Docker Hub, then sold harvested AI tool credentials to other criminals. Chinese nation-state actor UNC6508 conducted espionage against proprietary AI research at North American academic, medical, and military institutions, while extortion gangs stole models, prompts, and source code in Q2 2026. GTIG also documented agentic attacker experimentation, including an autonomous multi-agent credential harvesting campaign built in under six hours and a 'Recon' C2 framework managing over 23,800 harvested secrets.

Infosecurity Magazine·Sep 8, 12:02 UTC · 8d agoThreat actor in the wild 2 sources1

Safety for Whom? Boundary-Aware Self-Distillation for Controlled LLM Safety Refusal

A self-distillation safety framework tunes narrow-boundary refusals in Qwen3-8B, raising target-domain refusal to 84.75% while cutting over-refusal from 15.20% to 5.20%.

The paper formulates narrow-boundary safety, where deployments need refusals within specific topics rather than whole subjects, and proposes an offline self-generated framework with controlled topic generation, escalating retries, and harmful-benign boundary pairs. On political persuasion with Qwen3-8B, the method raised target-domain refusal from 9.47% to 84.75% and cut the mean unsafe-response rate across three broader benchmarks from 26.26% to 0.14%. Verified target-model responses reduced over-refusal from 15.20% to 5.20%, and boundary-pair data cut comply-side over-refusal on held-out pairs from 32.94% to 4.16%. Results show data composition controls the safety-usability trade-off and alignment should be evaluated on both sides of the refusal boundary.

Hugging Face daily papers·Sep 2, 20:00 UTC · 14d agoAI safety & security1

Keepit AI Truth Cloud protects the data behind enterprise AI

Help Net Security·Aug 7, 00:00 UTC · Aug 7, 2026AI tools & infra

LLMs and Contextual Integrity

Bruce Schneier highlights two papers: the CIMemories benchmark shows frontier LLMs leak memory attributes up to 69%, and an RL method reduces inappropriate disclosures.

Bruce Schneier discusses contextual integrity in LLMs, referencing the CIMemories benchmark, which uses synthetic profiles with 100+ attributes per user to test whether models with persistent memory disclose sensitive information appropriately. Evaluation showed frontier models exhibit up to 69% attribute-level violations, with GPT-5's violation rate rising from 0.1% to 9.6% across 40 tasks and reaching 25.1% with repeated prompting, showing unstable leakage behavior. A second paper introduces a reinforcement learning framework trained on a synthetic 700-example dataset that substantially reduces inappropriate disclosure while maintaining task performance, with improvements transferring to the human-annotated PrivacyLens benchmark.

Schneier on Security·Aug 18, 10:40 UTC · 29d agoAI safety & security