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LiteLLM Flaws Let Attackers Execute Code as Root and Steal Cloud Credentials
Wiz disclosed LiteLLM flaws including CVE-2026-59822 MCP auth bypass, now in CISA KEV, enabling root RCE and AWS credential theft from exposed gateways.
Wiz researchers disclosed weaknesses in the open-source LiteLLM AI gateway: CVE-2026-59821 allows authenticated administrators to execute code as root via the Custom Code Guardrails feature, while CVE-2026-59822 is an MCP authentication bypass where a meaningless Bearer token establishes a valid session. The MCP bypass was observed in the wild through Wiz honeypots and added to CISA's Known Exploited Vulnerabilities catalog on September 2. A scan of 3,074 internet-facing instances found 294 (9.6%) accepting the default master key sk-1234 or lacking authentication. Fixes shipped in LiteLLM 1.82.0 (guardrail hardening) and 1.84.0 (MCP bypass); exposed instances can leak provider API keys and temporary AWS IAM credentials via the pass-through feature and metadata service, with a related config-check issue tracked as CVE-2026-35029.
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CISA Red Team Fully Compromised Two Critical Infrastructure Orgs
CISA red teams achieved full domain and cloud compromise at two critical infrastructure orgs; one SOC never detected the intrusion.
CISA advisory AA26-237A documents two simultaneous red team assessments. Organization A (Government Services sector) missed the intrusion entirely, as default credentials on a web app, ADCS ESC1 abuse, and thousands of false-positive alerts let the red team reach sensitive business systems and read SOC email. Organization B (Water/Wastewater sector) detected, isolated, and reimaged hosts quickly, but both orgs lacked Conditional Access for workload identities, and B still exposed DCSync, Golden Ticket, and OT network attack paths.
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AI agents help compress ransomware intrusion to under 10 hours, raising stakes for CISOs
Unit 42 reports AI agents compressed a ransomware intrusion from weeks to under 10 hours, using 50+ MITRE ATT&CK techniques against an enterprise network.
Palo Alto Networks Unit 42 investigated a ransomware incident where AI agents moved through an enterprise network in under 10 hours, work that would have taken human operators roughly two weeks. The attacker entered via a public-facing API endpoint, used automated reconnaissance to map microservices, searched source-code repositories for credentials, and accessed a secrets-management system. They hijacked enterprise code workflows to exfiltrate cloud access keys, attempted Terraform backdoors (blocked by branch protections), and used stolen credentials to access the victim's own AI services as attack infrastructure. Over 50 MITRE ATT&CK techniques were observed; the actor confirmed using frontier AI models and agentic frameworks during negotiations.
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BigBear 2.0 phishing campaign hijacks Microsoft 365 sessions after MFA
CloudSEK uncovered BigBear 2.0, a PhaaS operation that captured 4,148 Microsoft 365 session cookies, hijacking authenticated sessions after MFA via AiTM proxy.
CloudSEK infiltrated the BigBear 2.0 phishing-as-a-service panel in June, finding 5,137 credential records tied to 461 organizations in over 40 countries, including 4,148 captured session cookies and 474 completed post-MFA logins. The operation, built on Evilginx2, uses an attacker-controlled reverse proxy to steal authenticated session cookies and residential proxies to defeat location-based Conditional Access checks, while custom code disables FIDO2/WebAuthn on phishing pages. At least five affiliates operated 42 VPS nodes, with IT services and managed service providers the most targeted sector.
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Hackers Deploy Agentic AI to Automate Exploitation and Mass Credential Harvesting
Google GTIG documents a financially motivated actor using a multi-agent AI framework to automate credential harvesting, compromising over 23,800 secrets within hours.
Google Threat Intelligence Group (GTIG) documented a financially motivated actor that compromised an unnamed organization's cloud infrastructure and used a multi-agent AI framework to automate vulnerability scanning, credential harvesting, troubleshooting, and IP rotation. The operation went from planning to mass credential compromise in under six hours, harvesting more than 23,800 secrets including cloud and AI-service API keys via an exposed C2 dashboard called 'Recon'. The actor directed specialized agents using an AI coding chatbot and Markdown instruction files such as AGENTS.KNOWLEDGE.md and agentic_vuln_research.md. Google has not observed fully autonomous zero-day exploitation; the shift automates labor-intensive tasks like reconnaissance, account validation, and infrastructure management, sharply shrinking detection windows.
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