{"items":[{"id":"6de59db4e7e21b357c5368361659bd25deef6792","publicSlug":"control-room-a-central-system-to-track-and-stop-model-workloads-across-our-resea","incidentId":"1f9e73b11bae683d0790b854389383fa96038822","title":"Control Room: A central system to track and stop model workloads across our research infrastructure","summary":"OpenAI's Control Room is a deployed internal system that centrally tracks research inference workloads, including agentic training and evaluation, and can halt model output within 35 seconds of an intervention decision. Inference engines check job authorization with the service before fulfilling requests, and the system is designed to stop model output if Control Room itself goes down.","whyItMatters":"OpenAI's Control Room provides a concrete inference-layer containment design for stopping risky agentic workloads, including when supporting systems fail.","threatTypeTags":["ai-containment","model-misalignment"],"affectedTechTags":["ai-agents","llm","inference-infrastructure"],"threatActor":null,"relevanceScore":0.9,"severityScore":0.1,"sources":[{"sourceId":"openai","title":"Control Room: A central system to track and stop model workloads across our research infrastructure","link":"https://openai.com/index/control-room"}],"sourceItemIds":["4ee3d4e5f9092d74569ba9566dc270fa31ac5c88"],"publishedAt":"2026-11-09T13:00:00.000Z","firstReportedAt":"2026-11-09T13:00:00.000Z","curatedAt":"2026-11-10T00:31:01.666Z","itemType":"analysis","threatStatus":"unknown","contentClass":"news","toolPosture":null,"toolCategory":null,"references":[{"role":"original","url":"https://openai.com/index/control-room","domain":"openai.com","slug":"openai","tier":"known","title":"Control Room: A central system to track and stop model workloads across our research infrastructure","pageTitle":"Control Room: A central system to track and stop model workloads across our research infrastructure","isPrimary":true}],"freshness":{"version":1,"firstPublishedAt":"2026-11-09T13:00:00.000Z","latestPublishedAt":"2026-11-09T13:00:00.000Z","firstObservedAt":"2026-11-10T00:15:00.009Z","lastObservedAt":"2026-11-10T00:15:00.009Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T13:00:00.000Z","activityBasis":"publication","feedUpdatedAt":"2026-11-10T00:31:01.666Z","development":null}},{"id":"9afdfed58c3d94888fa63fd30f7317c42c7ef36f","publicSlug":"fireworks-ai-discloses-new-breach-after-cloud-provider-hack","incidentId":"2f055c7a268ce785207839ad5cfad753eddec2d7","title":"Fireworks AI discloses new breach after cloud provider hack","summary":"Fireworks AI disclosed that attackers breached a third-party cloud provider, reached its development machines, and ran an unauthorized workload. Attackers accessed customer resource metadata, billing information, and incomplete model weights and datasets for some customers. Fireworks isolated affected systems, rotated credentials, restricted network access, and reported no further evidence of successful unauthorized access to its customer platform as of October 25.","whyItMatters":"Fireworks AI's breach demonstrates how compromised cloud-provider infrastructure can expose customer data and AI model assets through development environments.","threatTypeTags":["supply-chain","data-exfiltration","cloud-compromise"],"affectedTechTags":["fireworks-ai","llm","ai-infrastructure","model-weights"],"threatActor":null,"relevanceScore":0.94,"severityScore":0.85,"sources":[{"sourceId":"bleepingcomputer","title":"Fireworks AI discloses new breach after cloud provider hack","link":"https://www.bleepingcomputer.com/news/security/fireworks-ai-discloses-new-breach-after-cloud-provider-hack/"}],"sourceItemIds":["2400cfa02c00993a337776f7300a073988f403e1"],"publishedAt":"2026-11-10T07:49:58.000Z","firstReportedAt":"2026-11-10T07:49:58.000Z","curatedAt":"2026-11-10T08:30:21.491Z","itemType":"incident","threatStatus":"in-the-wild","contentClass":"threat","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://www.bleepingcomputer.com/news/security/fireworks-ai-discloses-new-breach-after-cloud-provider-hack/","domain":"bleepingcomputer.com","slug":"bleepingcomputer","tier":"known","title":"Fireworks AI discloses new breach after cloud provider hack","pageTitle":"Fireworks AI discloses new breach after cloud provider hack"},{"role":"original","url":"https://fireworks.ai/security/bulletins/october-2026-security-incident-update","domain":"fireworks.ai","slug":null,"tier":"unknown","title":"Fireworks AI October 2026 security incident update","isPrimary":true}],"freshness":{"version":1,"firstPublishedAt":"2026-11-10T07:49:58.000Z","latestPublishedAt":"2026-11-10T07:49:58.000Z","firstObservedAt":"2026-11-10T08:15:00.025Z","lastObservedAt":"2026-11-10T08:15:00.025Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-10T07:49:58.000Z","activityBasis":"publication","feedUpdatedAt":"2026-11-10T08:30:21.491Z","development":null}},{"id":"e5a3f02f21c7f62c8ead1a3b79bccdbd6ac44bf6","publicSlug":"cisa-adds-four-known-exploited-vulnerabilities-to-catalog-cisa","incidentId":"2ca779b2c57368bb3431e754458636fc1f0d3f31","title":"CISA Adds Four Known Exploited Vulnerabilities to Catalog | CISA","summary":"CISA added vulnerabilities affecting GPUStack, OpenSSH, SignalWire FreeSWITCH, and IBM Aspera Faspex to its Known Exploited Vulnerabilities catalog, citing evidence of active exploitation. The supplied excerpt identifies GPUStack as affected but does not include its vulnerability details or exploitation mechanism.","whyItMatters":"GPUStack's inclusion in CISA's exploited-vulnerability catalog makes advisory review and remediation a priority for defenders operating the AI deployment platform.","threatTypeTags":["vulnerability-exploitation"],"affectedTechTags":["gpustack"],"threatActor":null,"relevanceScore":0.58,"severityScore":0.72,"sources":[{"sourceId":"thehackernews","title":"CISA Warns of Active Exploitation of OpenSSH, GPUStack, FreeSWITCH, and IBM Flaws","link":"https://thehackernews.com/2026/11/cisa-warns-of-active-exploitation-of.html"}],"sourceItemIds":["01879b9d63518c8990bb781b687fc4c8f37b4441"],"publishedAt":"2026-11-10T06:31:42.000Z","firstReportedAt":"2026-11-10T06:31:42.000Z","curatedAt":"2026-11-10T07:30:35.464Z","itemType":"advisory","threatStatus":"in-the-wild","contentClass":"threat","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://thehackernews.com/2026/11/cisa-warns-of-active-exploitation-of.html","domain":"thehackernews.com","slug":"thehackernews","tier":"known","title":"CISA Warns of Active Exploitation of OpenSSH, GPUStack, FreeSWITCH, and IBM Flaws","pageTitle":"CISA Warns of Active Exploitation of OpenSSH, GPUStack, FreeSWITCH, and IBM Flaws"},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-123218","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-123218","title":null},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-116779","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-116779","title":null},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-123158","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-123158","title":null},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-102895","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-102895","title":null},{"role":"original","url":"https://www.cisa.gov/news-events/alerts/2026/11/09/cisa-adds-four-known-exploited-vulnerabilities-catalog","domain":"cisa.gov","slug":"cisa","tier":"known","title":"CISA alert on four additions to the Known Exploited Vulnerabilities catalog","pageTitle":"CISA Adds Four Known Exploited Vulnerabilities to Catalog | CISA","isPrimary":true}],"freshness":{"version":1,"firstPublishedAt":"2026-11-10T06:31:42.000Z","latestPublishedAt":"2026-11-10T06:31:42.000Z","firstObservedAt":"2026-11-10T07:00:00.011Z","lastObservedAt":"2026-11-10T07:00:00.011Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-10T06:31:42.000Z","activityBasis":"publication","feedUpdatedAt":"2026-11-10T07:30:35.464Z","development":null}},{"id":"2a84f7d37c52e6886bcd7b2aa02ddb9a2cab9a73","publicSlug":"introducing-claude-fable-5-2-and-claude-mythos-5-2-anthropic","incidentId":"470bca18154a556fa6677403f37653a03084b42e","title":"Introducing Claude Fable 5.2 and Claude Mythos 5.2 \\ Anthropic","summary":"The Hacker News reports that Claude Fable 5.2 surpassed GPT-6 Cyber on a multi-stage cyberattack benchmark. Anthropic’s accompanying model announcement describes sandbox-escape evaluations, cyber-misuse safeguards and protections against distillation attacks, but the supplied excerpts omit the cyberattack benchmark’s methodology and detailed results.","whyItMatters":"Claude Fable 5.2’s reported cyberattack capabilities and safety evaluations warrant scrutiny by defenders assessing AI-enabled offensive capability and model containment.","threatTypeTags":["ai-enabled-cyberattacks","sandbox-escape","model-extraction"],"affectedTechTags":["llm","ai-agents","claude"],"threatActor":null,"relevanceScore":0.85,"severityScore":0.1,"sources":[{"sourceId":"theregister","title":"Anthropic's super bug-finding Mythos model is going into Cisco and IBM products","link":"https://www.theregister.com/ai-and-ml/2026/11/10/anthropics-super-bug-finding-mythos-model-is-going-into-cisco-and-ibm-products/5308616"},{"sourceId":"thehackernews","title":"Anthropic's Claude Fable 5.2 Beats GPT-6 Cyber in Multi-Stage Cyberattack Benchmark","link":"https://thehackernews.com/2026/11/anthropics-claude-fable-52-beats-gpt-6.html"}],"sourceItemIds":["90548f6dc52d93c91bf7ec92d17b1e38a9d5f048","1b793bb7474ee9a843675e7782c46db3b75fe6a2"],"publishedAt":"2026-11-10T08:16:14.000Z","firstReportedAt":"2026-11-10T00:00:20.000Z","curatedAt":"2026-11-10T00:31:01.585Z","itemType":"incident","threatStatus":"unknown","contentClass":"news","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://thehackernews.com/2026/11/anthropics-claude-fable-52-beats-gpt-6.html","domain":"thehackernews.com","slug":"thehackernews","tier":"known","title":"Anthropic's Claude Fable 5.2 Beats GPT-6 Cyber in Multi-Stage Cyberattack Benchmark","pageTitle":"Anthropic's Claude Fable 5.2 Beats GPT-6 Cyber in Multi-Stage Cyberattack Benchmark"},{"role":"aggregator","url":"https://www.theregister.com/ai-and-ml/2026/11/10/anthropics-super-bug-finding-mythos-model-is-going-into-cisco-and-ibm-products/5308616","domain":"theregister.com","slug":"theregister","tier":"known","title":"Anthropic's super bug-finding Mythos model is going into Cisco and IBM products","pageTitle":"Anthropic's super bug-finding Mythos model is going into Cisco and IBM products"},{"role":"original","url":"https://www.anthropic.com/claude-fable-and-mythos-5-2","domain":"anthropic.com","slug":"anthropic","tier":"known","title":"Claude Fable 5.2 and Mythos 5.2","pageTitle":"Introducing Claude Fable 5.2 and Claude Mythos 5.2 \\ Anthropic","isPrimary":true}],"freshness":{"version":1,"firstPublishedAt":"2026-11-10T00:00:20.000Z","latestPublishedAt":"2026-11-10T08:16:14.000Z","firstObservedAt":"2026-11-10T00:15:00.028Z","lastObservedAt":"2026-11-10T09:00:00.007Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-10T00:00:20.000Z","activityBasis":"publication","feedUpdatedAt":"2026-11-10T00:31:01.585Z","development":null}},{"id":"a20ca56fc02783479e94fb4a56847d1ac5a22e75","publicSlug":"cve-2026-82456-argo-cd-mcp-server-kubernetes-takeover-apiiro","incidentId":"6b149e097ead503a808f04da21c1fff4ef47e024","title":"CVE-2026-82456: Argo CD MCP Server Kubernetes Takeover | Apiiro","summary":"CVE-2026-82456 affects argocd-mcp 0.8.0, allowing unauthenticated network callers to invoke Argo CD operations using the server’s configured token. Apiiro demonstrated creating and syncing an application from an attacker-controlled repository using two MCP tool calls. The report identifies version 0.9.0 as fixed and recommends upgrading, rotating the server’s Argo CD token, and reviewing applications for unauthorized additions.","whyItMatters":"CVE-2026-82456 exposes an AI-agent integration as an unauthenticated path to deploy attacker-controlled workloads into Kubernetes using the MCP server’s Argo CD privileges.","threatTypeTags":["authentication-bypass","tool-abuse","privilege-escalation"],"affectedTechTags":["mcp","ai-agents","argo-cd","kubernetes"],"threatActor":null,"relevanceScore":0.99,"severityScore":0.96,"sources":[{"sourceId":"firecrawl-search","title":"CVE-2026-82456: Argo CD MCP Server Kubernetes Takeover | Apiiro","link":"https://apiiro.com/blog/cve-2026-82456-argo-cd-mcp-server-kubernetes-takeover/"}],"sourceItemIds":["a3510bda19d03c2f5615c99f505b10ddc2e73ca7"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:17.160Z","itemType":"research","threatStatus":"patched","contentClass":"threat","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://apiiro.com/blog/cve-2026-82456-argo-cd-mcp-server-kubernetes-takeover/","domain":"apiiro.com","slug":null,"tier":"unknown","title":"CVE-2026-82456: Argo CD MCP Server Kubernetes Takeover | Apiiro","pageTitle":"CVE-2026-82456: Argo CD MCP Server Kubernetes Takeover | Apiiro"},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-82456","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-82456","title":null},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2022-24348","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2022-24348","title":null},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2025-66414","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2025-66414","title":null}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:17.160Z","development":null}},{"id":"c06becd84be9dfe35c96a5a3634eac093f8c6d29","publicSlug":"github-copilot-cli-vulnerability-leaks-developer-secrets","incidentId":"cb92f6b31b15c573f63cf163ffce97a73c0278b2","title":"GitHub Copilot CLI vulnerability leaks developer secrets","summary":"Adversa AI demonstrated Cryptographic Context Injection against GitHub Copilot CLI in autopilot mode: an attacker-controlled page induces the agent to decrypt hidden instructions in its shell, read local files, and exfiltrate their contents. The demonstration stole a .env.prod file in about 28 seconds on one offered model, while two others rejected the identical payload. The researchers report that GitHub validated the finding but declined to classify it as a vulnerability.","whyItMatters":"Cryptographic Context Injection can turn a routine Copilot CLI page-reading task into secret exfiltration by laundering attacker instructions through decrypted shell output that the agent treats as trusted.","threatTypeTags":["prompt-injection","indirect-prompt-injection","data-exfiltration","tool-abuse","guardrail-bypass"],"affectedTechTags":["github-copilot-cli","copilot","ai-agents","llm"],"threatActor":null,"relevanceScore":1,"severityScore":0.83,"sources":[{"sourceId":"firecrawl-search","title":"Copilot CLI Prompt Injection Attack Chain | NeuralTrust","link":"https://neuraltrust.ai/blog/copilot-cli-prompt-injection"}],"sourceItemIds":["dbdac3083a4536986eceb8fa8b99dbb15f7924d5"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:40.271Z","itemType":"research","threatStatus":"poc","contentClass":"threat","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://neuraltrust.ai/blog/copilot-cli-prompt-injection","domain":"neuraltrust.ai","slug":null,"tier":"unknown","title":"Copilot CLI Prompt Injection Attack Chain | NeuralTrust","pageTitle":"Copilot CLI Prompt Injection Attack Chain | NeuralTrust"},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-29783","domain":"nvd.nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-29783","title":"NVD"},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-45033","domain":"nvd.nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-45033","title":"NVD"},{"role":"original","url":"https://adversa.ai/blog/cryptographic-context-injection-github-copilot/","domain":"adversa.ai","slug":"adversa","tier":"known","title":"GitHub Copilot CLI vulnerability: Cryptographic Context Injection steals developer secrets","pageTitle":"GitHub Copilot CLI vulnerability leaks developer secrets","isPrimary":true}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:40.271Z","development":null}},{"id":"e71041c6ffb2f7c0e8b4e2b2ddb17744b887643d","publicSlug":"nvd-cve-2026-102610","incidentId":"c949264cb76809fd10054ab33021cbaf27517db3","title":"NVD-CVE-2026-102610","summary":"CVE-2026-102610 affects fast-agent versions before 0.7.21: the serve command defaults to an unauthenticated HTTP service on 0.0.0.0:8000, allowing reachable clients to invoke the exposed agent through /mcp. With --shell enabled, clients can cause operating-system commands to execute as the server user; otherwise, they can still consume the operator's model and configured MCP tools. Version 0.7.21 fixes the issue.","whyItMatters":"The fast-agent vulnerability exposes agent capabilities—and potentially local command execution—to unauthenticated network clients, making upgrades to 0.7.21 and restrictions on endpoint access important for affected deployments.","threatTypeTags":["missing-authentication","tool-abuse","remote-code-execution"],"affectedTechTags":["fast-agent","ai-agents","mcp"],"threatActor":null,"relevanceScore":1,"severityScore":0.82,"sources":[{"sourceId":"firecrawl-search","title":"NVD-CVE-2026-102610","link":"https://nvd.nist.gov/vuln/detail/CVE-2026-102610"}],"sourceItemIds":["c3d4de14fee9acdfb757559316a6dda839b797f3"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:40.576Z","itemType":"advisory","threatStatus":"patched","contentClass":"threat","toolPosture":null,"toolCategory":null,"references":[{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-102610","domain":"nvd.nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-102610","title":"NVD-CVE-2026-102610","pageTitle":"NVD-CVE-2026-102610"}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:40.576Z","development":null}},{"id":"16981419fa0ba5dd8367913457a3cb0dd1bb7eb1","publicSlug":"nvd-cve-2026-57207","incidentId":"a8d2ddb3c490adb32d8a33467fd64358906c3e49","title":"NVD-CVE-2026-57207","summary":"CVE-2026-57207 affects NetBox MCP Server before version 1.2.1: deployments using TRANSPORT=http lack authentication on the HTTP endpoint, allowing any client that can reach the port to obtain an MCP session and access all four read-only NetBox tools without credentials. Version 1.2.1 fixes the vulnerability.","whyItMatters":"NetBox MCP Server deployments using the vulnerable HTTP transport expose NetBox tool access to unauthenticated clients, creating a confidentiality risk that defenders should address by upgrading to version 1.2.1.","threatTypeTags":["missing-authentication","tool-abuse","data-exposure","cve-2026-57207"],"affectedTechTags":["mcp","netbox-mcp-server","netbox"],"threatActor":null,"relevanceScore":0.98,"severityScore":0.59,"sources":[{"sourceId":"firecrawl-search","title":"NVD-CVE-2026-57207","link":"https://nvd.nist.gov/vuln/detail/CVE-2026-57207"}],"sourceItemIds":["edc16f321aec2be8d059c6ce599df7a6e25d7b07"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:40.559Z","itemType":"advisory","threatStatus":"patched","contentClass":"threat","toolPosture":null,"toolCategory":null,"references":[{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-57207","domain":"nvd.nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-57207","title":"NVD-CVE-2026-57207","pageTitle":"NVD-CVE-2026-57207"},{"role":"link","url":"https://github.com/netboxlabs/netbox-mcp-server/security/advisories/GHSA-5qg7-j8mr-9477","domain":"github.com","slug":"github","tier":"known","title":"NetBox MCP Server security advisory GHSA-5qg7-j8mr-9477"},{"role":"link","url":"https://github.com/netboxlabs/netbox-mcp-server/releases/tag/v1.2.1","domain":"github.com","slug":"github","tier":"known","title":"NetBox MCP Server v1.2.1 release"}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:40.559Z","development":null}},{"id":"755336cdc3fb8cfa86dcf6a5f6621750d073d7b9","publicSlug":"cve-2026-112380-missing-authorization-in-the-whatsapp-channel-in-kiro-crew","incidentId":"35c29fe7438c215fe13511bd49e95da7364368e6","title":"CVE-2026-112380 - Missing authorization in the WhatsApp channel in Kiro Crew","summary":"AWS bulletin 2026-140-AWS identifies CVE-2026-112380 as a missing-authorization vulnerability in Kiro Crew’s WhatsApp channel. The supplied excerpt ends before the technical description, leaving affected versions, exploitation requirements, impact, and remediation unconfirmed.","whyItMatters":"Kiro Crew deployments using the WhatsApp channel warrant review for an authorization weakness, although the supplied excerpt does not establish which capabilities an unauthorized user could access.","threatTypeTags":["missing-authorization","cve-2026-112380"],"affectedTechTags":["kiro-crew","whatsapp"],"threatActor":null,"relevanceScore":0.8,"severityScore":0.5,"sources":[{"sourceId":"firecrawl-search","title":"CVE-2026-112380 - Missing authorization in the WhatsApp channel in Kiro Crew","link":"https://aws.amazon.com/security/security-bulletins/2026-140-aws/"}],"sourceItemIds":["2e869a55e02edf3c4d95af65a74b7fe4ec352b77"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:17.353Z","itemType":"advisory","threatStatus":"unknown","contentClass":"threat","toolPosture":null,"toolCategory":null,"references":[{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-112380","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-112380","title":null},{"role":"vendor","url":"https://aws.amazon.com/security/security-bulletins/2026-140-aws/","domain":"aws.amazon.com","slug":"aws","tier":"known","title":"CVE-2026-112380 - Missing authorization in the WhatsApp channel in Kiro Crew","pageTitle":"CVE-2026-112380 - Missing authorization in the WhatsApp channel in Kiro Crew"}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:17.353Z","development":null}},{"id":"8a3b5fda8857866280861061c36134d1299c5235","publicSlug":"cve-tracking-for-ai-frameworks-langchain-ollama-vllm","incidentId":"df827b28a8036845b350dc657dbc6f4fbbc03b62","title":"CVE Tracking for AI Frameworks: LangChain, Ollama, vLLM","summary":"The CVE-tracking guide for LangChain, Ollama, and vLLM reviews recurring vulnerability patterns in tool execution, model-file handling, and inference-serving APIs, including a reference to Ollama's CVE-2024-37032. The guide provides secondary guidance on inventorying versions, assessing reachable attack surfaces, and applying compensating controls rather than disclosing a new vulnerability or demonstrating an exploit.","whyItMatters":"CVE tracking for LangChain, Ollama, and vLLM helps defenders prioritize vulnerabilities in privileged agent tools, model-management components, and inference endpoints while upgrades are tested.","threatTypeTags":["code-injection","unsafe-deserialization","path-traversal","remote-code-execution","denial-of-service","prompt-injection"],"affectedTechTags":["langchain","ollama","vllm","ai-agents","model-serving"],"threatActor":null,"relevanceScore":0.88,"severityScore":0.1,"sources":[{"sourceId":"firecrawl-search","title":"CVE Tracking for AI Frameworks: LangChain, Ollama, vLLM","link":"https://trussed.ai/resources/cve-tracking-for-ai-frameworks-langchain-ollama-vllm"}],"sourceItemIds":["e46c6782e2ecba618b01358a2878b31a2e21e411"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:17.079Z","itemType":"analysis","threatStatus":"unknown","contentClass":"analysis","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://trussed.ai/resources/cve-tracking-for-ai-frameworks-langchain-ollama-vllm","domain":"trussed.ai","slug":null,"tier":"unknown","title":"CVE Tracking for AI Frameworks: LangChain, Ollama, vLLM","pageTitle":"CVE Tracking for AI Frameworks: LangChain, Ollama, vLLM"},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2024-37032","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2024-37032","title":null}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:17.079Z","development":null}},{"id":"b8c904051aba0fed6fd332b4f449ab67280d080f","publicSlug":"2610-14453-secreason-vulnerability-detection-and-in-stream-self-repair-for-llm-c","incidentId":"0af9e2cb2cbe502f2b4556d5bde6ae18482f9834","title":"[2610.14453] SecReason: Vulnerability Detection and In-Stream Self-Repair for LLM Code Generation","summary":"SecReason scans code within an LLM’s streamed reasoning, checking individual statements and accumulated dataflows, then interrupts generation with warnings so the model can repair vulnerabilities before delivery. On evaluated tasks where unassisted generation introduces vulnerabilities, the authors report increasing secure, functionally correct outputs from below 15% to 72.8%–98.1% across CWEval and SecCodeBench, while consuming fewer tokens than post-hoc repair.","whyItMatters":"SecReason demonstrates a generation-time safeguard for AI coding workflows that could reduce vulnerable outputs without requiring full-response regeneration.","threatTypeTags":["insecure-code-generation"],"affectedTechTags":["llm","reasoning-models","ai-code-generation"],"threatActor":null,"relevanceScore":0.87,"severityScore":0.1,"sources":[{"sourceId":"firecrawl-search","title":"[2610.14453] SecReason: Vulnerability Detection and In-Stream Self-Repair for LLM Code Generation","link":"https://arxiv.org/abs/2610.14453"}],"sourceItemIds":["dd5d6c5bfee1bb97bc68b115f03d516584611c95"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:17.274Z","itemType":"research","threatStatus":"unknown","contentClass":"research","toolPosture":null,"toolCategory":null,"references":[{"role":"original","url":"https://arxiv.org/abs/2610.14453","domain":"arxiv.org","slug":"arxiv","tier":"known","title":"SecReason: Vulnerability Detection and In-Stream Self-Repair for LLM Code Generation","pageTitle":"[2610.14453] SecReason: Vulnerability Detection and In-Stream Self-Repair for LLM Code Generation","isPrimary":true}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:17.274Z","development":null}},{"id":"d6cda62584f3e5086c65eb2d25d6075218e66f1a","publicSlug":"vulnerability-disclosure-higgsfield-ai-vulnerability-disclosure-engagement-bugcr","incidentId":"fa5ff92bea74cca1beba2e602f85a1b3bbada878","title":"Vulnerability Disclosure: Higgsfield AI Vulnerability Disclosure Engagement - Bugcrowd","summary":"Higgsfield’s Bugcrowd vulnerability disclosure program covers its generative-AI platforms and MCP service, which allows authorized agents to generate media and access account information and generation history. The program highlights API-key exposure, authorization bypasses, cross-account data access, and unauthorized model execution as testing priorities, but discloses no specific vulnerability.","whyItMatters":"Higgsfield’s inclusion of MCP in its disclosure scope gives researchers an authorized route to investigate access-control and tool-execution risks in agent-connected creative workflows.","threatTypeTags":["access-control","credential-exposure","tool-abuse"],"affectedTechTags":["mcp","ai-agents","generative-ai"],"threatActor":null,"relevanceScore":0.76,"severityScore":0.1,"sources":[{"sourceId":"firecrawl-search","title":"Vulnerability Disclosure: Higgsfield AI Vulnerability Disclosure Engagement - Bugcrowd","link":"https://bugcrowd.com/engagements/higgsfield-ai-vdp-pro"}],"sourceItemIds":["7f1cbfef69e42e809b0dae510ef8d334b46adf4a"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:17.470Z","itemType":"advisory","threatStatus":"unknown","contentClass":"news","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://bugcrowd.com/engagements/higgsfield-ai-vdp-pro","domain":"bugcrowd.com","slug":null,"tier":"unknown","title":"Vulnerability Disclosure: Higgsfield AI Vulnerability Disclosure Engagement - Bugcrowd","pageTitle":"Vulnerability Disclosure: Higgsfield AI Vulnerability Disclosure Engagement - Bugcrowd"}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:17.470Z","development":null}},{"id":"fb0c976b70f0ed0299e618ed789756b38712cb7e","publicSlug":"prompt-injection-owasp-genai-security-project-security-glossary","incidentId":"90cc35f559de42b6b30adbe538bf6df2f59e904a","title":"Prompt Injection | OWASP GenAI Security Project Security Glossary","summary":"OWASP’s prompt-injection glossary entry explains direct and indirect injection, including how malicious instructions in retrieved content can induce agents to disclose information or perform unauthorized actions. The reference outlines mitigations such as least privilege, input/output validation, human approval, and prompt hardening; it does not disclose a new exploit or specific incident.","whyItMatters":"OWASP’s glossary helps defenders understand how untrusted content can influence agent behavior and why limiting permissions and requiring approval for consequential actions reduce exposure.","threatTypeTags":["prompt-injection","indirect-prompt-injection","data-exfiltration","tool-abuse"],"affectedTechTags":["llm","ai-agents"],"threatActor":null,"relevanceScore":1,"severityScore":0.1,"sources":[{"sourceId":"firecrawl-search","title":"Prompt Injection | OWASP GenAI Security Project Security Glossary","link":"https://genai.owasp.org/glossary/prompt-injection/"}],"sourceItemIds":["32dcf3cdf78d83ad8f04d532076b86428fb1ad69"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:40.421Z","itemType":"analysis","threatStatus":"unknown","contentClass":"analysis","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://genai.owasp.org/glossary/prompt-injection/","domain":"genai.owasp.org","slug":"owasp-genai","tier":"known","title":"Prompt Injection | OWASP GenAI Security Project Security Glossary","pageTitle":"Prompt Injection | OWASP GenAI Security Project Security Glossary"}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:40.421Z","development":null}},{"id":"9f2c3804122ae31bd6f05ae710d48f4ab5bd1d92","publicSlug":"bug-bounty-openai-bugcrowd","incidentId":"60041bac1209e2062792b178f66728bb61fd615e","title":"Bug Bounty: OpenAI - Bugcrowd","summary":"OpenAI's Bugcrowd security bounty policy advertises increased rewards, quality and loyalty bonuses, and exceptional payouts up to $172,000 with bonuses. Model-behavior findings such as jailbreaks, hallucinations, and prompt-based safety bypasses are excluded, but model-assisted attacks may qualify when they exploit a separate flaw in an in-scope OpenAI product or OpenAI-controlled integration.","whyItMatters":"OpenAI's bounty policy clarifies which AI-assisted security findings qualify for rewards and establishes authorization, safe-harbor, and data-protection boundaries for researchers.","threatTypeTags":["bug-bounty","vulnerability-disclosure"],"affectedTechTags":["llm","openai"],"threatActor":null,"relevanceScore":0.78,"severityScore":0,"sources":[{"sourceId":"firecrawl-search","title":"Bug Bounty: OpenAI - Bugcrowd","link":"https://bugcrowd.com/engagements/openai"}],"sourceItemIds":["acea545a516eb5e9f542e982557e9e56ab81d472"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:17.516Z","itemType":"advisory","threatStatus":"unknown","contentClass":"news","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://bugcrowd.com/engagements/openai","domain":"bugcrowd.com","slug":null,"tier":"unknown","title":"Bug Bounty: OpenAI - Bugcrowd","pageTitle":"Bug Bounty: OpenAI - Bugcrowd"}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:17.516Z","development":null}},{"id":"2c5e5f84faff919c5493193dbd59cecc8e0ea8b9","publicSlug":"prompt-injection-doesn-t-care-what-your-agent-does-for-a-living","incidentId":"1f35053377db1d7e54f8575673c026deab620c75","title":"Prompt injection doesn't care what your agent does for a living","summary":"Lambda reports findings from AgentBeats Security Arena, a prompt-injection competition run with UC Berkeley's RDI using attacker and defender agents on gpt-oss-20b. Clustering 1,433 winning attacks revealed recurring rhetorical strategies across application domains, while held-out testing exposed weaknesses in scenario-specific attacker designs.","whyItMatters":"AgentBeats' findings suggest defenders should test recurring prompt-injection strategies across applications rather than treat domain coverage alone as evidence of agent security.","threatTypeTags":["prompt-injection"],"affectedTechTags":["llm","ai-agents","gpt-oss-20b"],"threatActor":null,"relevanceScore":0.99,"severityScore":0.1,"sources":[{"sourceId":"firecrawl-search","title":"Prompt injection doesn't care what your agent does for a living","link":"https://lambda.com/blog/prompt-injection-doesnt-care-what-your-agent-does-for-a-living"}],"sourceItemIds":["0076a3a7a27a257a0a8a140091cdc71e37ea22cd"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:40.149Z","itemType":"research","threatStatus":"unknown","contentClass":"research","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://lambda.com/blog/prompt-injection-doesnt-care-what-your-agent-does-for-a-living","domain":"lambda.com","slug":null,"tier":"unknown","title":"Prompt injection doesn't care what your agent does for a living","pageTitle":"Prompt injection doesn't care what your agent does for a living"},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2025-32711","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2025-32711","title":null}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:40.149Z","development":null}},{"id":"15d682394c5e781e57ca638f8f098656e43d144d","publicSlug":"servicenow-research-study-warns-security-leaders-ungoverned-agentic-ai-exposure","incidentId":"78901d05338676ed0eabc621b6da148a1387d417","title":"ServiceNow Research Study Warns Security Leaders: Ungoverned Agentic AI Exposure Is Compounding Inside Enterprises - ServiceNow Newsroom","summary":"ServiceNow reports survey findings from more than 3,700 security leaders, stating that 90% of organizations experienced an agentic AI security incident in the past year and only 13% met its criteria for a defensible security posture. The study highlights incomplete agent inventories, unregistered production agents, and permissions and guardrails implemented reactively.","whyItMatters":"ServiceNow’s survey highlights inventory and governance gaps that can leave production AI agents operating without adequate security oversight.","threatTypeTags":["shadow-ai","agent-governance"],"affectedTechTags":["ai-agents"],"threatActor":null,"relevanceScore":0.92,"severityScore":0.1,"sources":[{"sourceId":"firecrawl-search","title":"ServiceNow Research Study Warns Security Leaders: Ungoverned Agentic AI Exposure Is Compounding Inside Enterprises - ServiceNow Newsroom","link":"https://newsroom.servicenow.com/press-releases/details/2026/ServiceNow-Research-Study-Warns-Security-Leaders-Ungoverned-Agentic-AI-Exposure-Is-Compounding-Inside-Enterprises/default.aspx"}],"sourceItemIds":["a1bcd6eadfe2cdb80146d50f4409f13d2bfc3b70"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:40.317Z","itemType":"research","threatStatus":"unknown","contentClass":"research","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://newsroom.servicenow.com/press-releases/details/2026/ServiceNow-Research-Study-Warns-Security-Leaders-Ungoverned-Agentic-AI-Exposure-Is-Compounding-Inside-Enterprises/default.aspx","domain":"newsroom.servicenow.com","slug":null,"tier":"unknown","title":"ServiceNow Research Study Warns Security Leaders: Ungoverned Agentic AI Exposure Is Compounding Inside Enterprises - ServiceNow Newsroom","pageTitle":"ServiceNow Research Study Warns Security Leaders: Ungoverned Agentic AI Exposure Is Compounding Inside Enterprises - ServiceNow Newsroom"}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:40.317Z","development":null}},{"id":"07de54aeab2f5b471ca16e222c61a2d1ef607cd0","publicSlug":"what-is-prompt-injection-direct-vs-indirect-attacks-explained","incidentId":"fcdff4ae3a82fb7337f46863b33c416257bf2f85","title":"What Is Prompt Injection? Direct vs. Indirect Attacks, Explained","summary":"Truvo Cyber explains direct prompt injection through user input and indirect injection embedded in documents, emails, or web pages. The overview describes how tool-enabled agents amplify the impact and recommends least privilege, approval gates, and egress controls to contain successful attacks.","whyItMatters":"Prompt injection can turn an AI agent’s access to sensitive data and tools into information disclosure or unauthorized actions, making containment important even when input filters are deployed.","threatTypeTags":["prompt-injection","indirect-prompt-injection","tool-abuse","data-exfiltration"],"affectedTechTags":["llm","ai-agents","copilot","rag"],"threatActor":null,"relevanceScore":0.97,"severityScore":0.1,"sources":[{"sourceId":"firecrawl-search","title":"What Is Prompt Injection? 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Direct vs. Indirect Attacks, Explained"},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-77521","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-77521","title":null}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:40.599Z","development":null}},{"id":"d7f052eefc7203363c46638f7eca0a64b3798c91","publicSlug":"new-report-from-ironscales-reveals-77-of-organizations-experienced-agentic-ai-re","incidentId":"5b38c60b5c7029a0db19cd1fac2868e1f1e48b31","title":"New Report From IRONSCALES Reveals 77% of Organizations Experienced Agentic AI-Related Security Incidents in the Past Year","summary":"IRONSCALES and Censuswide surveyed 501 U.S. IT and cybersecurity professionals: 77% said an AI agent or tool had acted on malicious, misleading, or unauthorized instructions or content in the past year, with 57% reporting a confirmed case. Reported incidents included agents summarizing or acting on malicious messages, while widespread agent access to internal systems increased potential exposure.","whyItMatters":"The IRONSCALES survey highlights the need to restrict agent permissions and monitor actions triggered by untrusted messages, particularly when agents can access internal files, inboxes, or payment systems.","threatTypeTags":["prompt-injection","tool-abuse","social-engineering"],"affectedTechTags":["ai-agents"],"threatActor":null,"relevanceScore":0.96,"severityScore":0.1,"sources":[{"sourceId":"firecrawl-search","title":"New Report From IRONSCALES Reveals 77% of Organizations Experienced Agentic AI-Related Security Incidents in the Past Year","link":"https://ironscales.com/news/new-report-from-ironscales-reveals-77-of-organizations-experienced-agentic-ai-related-security-incidents-in-the-past-year"}],"sourceItemIds":["f3df6217a664b341a42524c270ace376458ba1f2"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T20:00:33.299Z","itemType":"research","threatStatus":"unknown","contentClass":"research","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://ironscales.com/news/new-report-from-ironscales-reveals-77-of-organizations-experienced-agentic-ai-related-security-incidents-in-the-past-year","domain":"ironscales.com","slug":null,"tier":"unknown","title":"New Report From IRONSCALES Reveals 77% of Organizations Experienced Agentic AI-Related Security Incidents in the Past Year","pageTitle":"New Report From IRONSCALES Reveals 77% of Organizations Experienced Agentic AI-Related Security Incidents in the Past Year"}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T20:00:33.299Z","development":null}},{"id":"ccc93f4f19b20261e8b0038037f956005555bf77","publicSlug":"2601-10338-agent-skills-in-the-wild-an-empirical-study-of-security-vulnerabiliti","incidentId":"22c0050542216a5f32947c5673cdbfd5cc2e49f4","title":"[2601.10338] Agent Skills in the Wild: An Empirical Study of Security Vulnerabilities at Scale","summary":"MCP servers and agent skills introduce supply-chain risks because agents consume third-party instructions and may execute bundled code with their own credentials. The article recommends provenance checks, pinned versions, human review, scoped credentials, sandboxing, egress restrictions, and tool-call logging, citing research that found vulnerabilities in 26.1% of 31,132 analyzed skills.","whyItMatters":"MCP servers and agent skills can turn unvetted third-party content into privileged agent actions, making dependency review and runtime containment important defenses against injection and data theft.","threatTypeTags":["supply-chain","prompt-injection","data-exfiltration","privilege-escalation"],"affectedTechTags":["ai-agents","mcp","agent-skills"],"threatActor":null,"relevanceScore":0.98,"severityScore":0.1,"sources":[{"sourceId":"firecrawl-search","title":"MCP and Agent Skills Security: Security Considerations for MCP Servers and the Skills Your Agents Load","link":"https://truvocyber.com/blog/mcp-security-agent-skills"}],"sourceItemIds":["a1789fd19cd35137dc61080cfd804963323c52df"],"publishedAt":"2026-11-09T19:15:00.010Z","firstReportedAt":"2026-11-09T19:15:00.010Z","curatedAt":"2026-11-09T19:37:40.459Z","itemType":"analysis","threatStatus":"unknown","contentClass":"analysis","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://truvocyber.com/blog/mcp-security-agent-skills","domain":"truvocyber.com","slug":null,"tier":"unknown","title":"MCP and Agent Skills Security: Security Considerations for MCP Servers and the Skills Your Agents Load","pageTitle":"MCP and Agent Skills Security: Security Considerations for MCP Servers and the Skills Your Agents Load"},{"role":"cve","url":"https://nvd.nist.gov/vuln/detail/CVE-2026-77521","domain":"nist.gov","slug":"nvd","tier":"known","cveId":"CVE-2026-77521","title":null},{"role":"original","url":"https://www.arxiv.org/abs/2601.10338","domain":"arxiv.org","slug":"arxiv","tier":"known","title":"Agent Skills in the Wild: An Empirical Study of Security Vulnerabilities at Scale","pageTitle":"[2601.10338] Agent Skills in the Wild: An Empirical Study of Security Vulnerabilities at Scale","isPrimary":true}],"freshness":{"version":1,"firstPublishedAt":null,"latestPublishedAt":null,"firstObservedAt":"2026-11-09T19:15:00.010Z","lastObservedAt":"2026-11-09T19:15:00.010Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T19:15:00.010Z","activityBasis":"observation","feedUpdatedAt":"2026-11-09T19:37:40.459Z","development":null}},{"id":"ae5ca2874d81f3ee9bdc2d61df60c2f99b87c0c3","publicSlug":"attackers-crash-claude-s-office-party-flaw-to-run-malicious-code-on-linux","incidentId":"82f7cc13d61a7fb964c3e06dbf8421e9b37a6891","title":"Attackers Crash Claude's 'Office Party' Flaw to Run Malicious Code on Linux","summary":"AIR Security reported “Office Party,” a code-execution flaw in Anthropic's official DOCX, PPTX, and XLSX skills that can execute an attacker-created temporary file on Linux. The vulnerability involves the soffice.py document-conversion helper's fallback to loading a shared library through LD_PRELOAD when Unix-domain sockets are unavailable.","whyItMatters":"Office Party could turn Claude's trusted document-conversion workflow into a malicious-code execution path in Linux environments running the affected skills.","threatTypeTags":["code-execution","tool-abuse"],"affectedTechTags":["claude","ai-agents","linux","libreoffice"],"threatActor":null,"relevanceScore":0.98,"severityScore":0.78,"sources":[{"sourceId":"darkreading","title":"Attackers Crash Claude's 'Office Party' Flaw to Run Malicious Code on Linux","link":"https://www.darkreading.com/endpoint-security/attackers-claude-office-party-flaw-malicious-code-linux"}],"sourceItemIds":["6f5383f8d4c4547be427d4eb088a949c4dadfa9b"],"publishedAt":"2026-11-09T18:08:30.000Z","firstReportedAt":"2026-11-09T18:08:30.000Z","curatedAt":"2026-11-09T18:30:21.108Z","itemType":"incident","threatStatus":"disclosed","contentClass":"threat","toolPosture":null,"toolCategory":null,"references":[{"role":"aggregator","url":"https://www.darkreading.com/endpoint-security/attackers-claude-office-party-flaw-malicious-code-linux","domain":"darkreading.com","slug":"darkreading","tier":"known","title":"Attackers Crash Claude's 'Office Party' Flaw to Run Malicious Code on Linux","pageTitle":"Attackers Crash Claude's 'Office Party' Flaw to Run Malicious Code on Linux"}],"freshness":{"version":1,"firstPublishedAt":"2026-11-09T18:08:30.000Z","latestPublishedAt":"2026-11-09T18:08:30.000Z","firstObservedAt":"2026-11-09T18:15:00.131Z","lastObservedAt":"2026-11-09T18:15:00.131Z","meaningfulUpdatedAt":null,"activityAt":"2026-11-09T18:08:30.000Z","activityBasis":"publication","feedUpdatedAt":"2026-11-09T18:30:21.108Z","development":null}}],"total":2118,"limit":20,"offset":0}