A maximum severity GitLab flaw could turn your CI/CD server into an attacker’s treasure trove
GitLab patched maximum-severity CVE-2026-85706, an unauthenticated path traversal enabling arbitrary file reads; CISA added it to KEV amid observed in-the-wild probes.
CVE-2026-85706 is a CVSS 10.0 path traversal in GitLab's repository commits API caused by improper confinement and missing authentication enforcement, allowing arbitrary file reads in a single unauthenticated HTTP request. It affects GitLab CE and EE versions 18.7 before 19.1.8, 19.2 before 19.2.6, and 19.3 before 19.3.2, and was reported via GitLab's HackerOne bug bounty. CISA added the flaw to its Known Exploited Vulnerabilities catalog, and watchTowr Intel reports already observing in-the-wild probes; GitLab is used by roughly 50% of the Fortune 100 with over 50 million registered users. Defenders are advised to patch immediately, rotate any exposed secrets, and hunt logs for HTTP POST requests to /api/v4/projects/{id}/repository/commits/ URIs containing file.path parameters.
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.
Hackers Use Passkey-Themed Phishing to Hijack Microsoft 365 Accounts and Steal Cloud Data
Microsoft reports passkey-themed phishing campaigns hijacking Microsoft 365 accounts via AiTM and device-code flows, then exfiltrating cloud data.
Microsoft researchers identified passkey-themed phishing across cloud intrusions observed since May 2026, where callers posing as IT support direct victims to lookalike sign-in pages. The flows include adversary-in-the-middle phishing and device-code authentication, letting attackers capture usable sessions even when MFA succeeds, followed by rogue MFA registration for persistence. Attackers enumerate tenants via Microsoft Graph and collect SharePoint, OneDrive, and Exchange data at rates below 1,000 items per hour; lure domains include passkeyhelpdesk.com and setupmypasskey.com.
Shai-Hulud's Reach Just Grew to 469 Credential Locations. Here's What That Means
GitGuardian found the Shai-Hulud infostealer worm now scans 469 credential locations, including CI/CD and AI tool configs, expanding supply-chain risk.
GitGuardian researchers found that a recent Shai-Hulud worm variant scans for credentials across 469 locations in developer environments, CI/CD tooling, cloud configurations, and AI tool configs, up from 189 paths in earlier variants. The worm reuses stolen credentials to pivot from developer workstations to source code, cloud infrastructure, and package publishing channels, turning credential theft into forward-propagating supply chain attacks. The analysis urges defenders to prioritize removing long-lived package publishing tokens in favor of short-lived OIDC-based trusted publishing, citing recent Docker and GitHub Actions improvements.
How hackers used Claude for missiles, drone swarms, and surveillance, while Chinese labs mined it for training data
Anthropic's threat report details eight months of Claude misuse: AI-assisted espionage against 20+ organizations, self-rewriting malware, and Chinese labs distilling Claude via fraudulent accounts.
Anthropic's threat intelligence report covering December 2025 through August 2026 documents Claude misuse across seven categories including cyber operations, surveillance, fraud, and unauthorized model distillation. A Russian-speaking espionage actor tracked as GTG-20006 used AI agents to rewrite and recompile malware evading antivirus detection, targeting more than 20 organizations in Ukraine and Europe and stealing a drone vision system SDK. Alibaba's Qwen lab ran the largest distillation campaign, with over 151 million exchanges between May and July 2026 peaking near 3 million per day to train Qwen 3.5, 3.6, and 3.7. DeepSeek, Moonshot AI, Xiaomi, and Zhipu also relayed customer or replayed traffic to Claude, including PLA-linked users analyzing CCTV footage and users with credentials tied to the Russian Ministry of Defense.
Malicious LiteLLM Releases Tied to Trivy Hack May Have Exposed 2,100+ Organizations
Malicious LiteLLM 1.82.7/1.82.8 PyPI releases tied to the Trivy TeamPCP campaign harvested cloud, SSH, and database credentials, potentially exposing 2,500+ organizations.
CloudSEK reported that two malicious LiteLLM releases on PyPI (versions 1.82.7 and 1.82.8, live about 40 minutes on March 24) harvested cloud keys, SSH keys, Kubernetes tokens, and database passwords, with captured loot files mapping potential exposure to more than 2,500 organizations including NVIDIA, Cisco, Deloitte, Volkswagen, FedEx, Siemens, and X Corp. The campaign is part of TeamPCP (tracked by Google as UNC6780), linked to the Aqua Security Trivy scanner compromise tracked as CVE-2026-33634 and added to CISA's Known Exploited Vulnerabilities catalog on March 26. The payload used a litellm_init.pth file executed at Python interpreter startup and exfiltrated secrets to models.litellm[.]cloud; the FBI's FLASH-20260702-01 advisory urged rotation of CI/CD, publishing, and cloud credentials.
The Self-Expanding Stolen Inference Supply Chain: An AI Agent Harvesting and Re-Serving LLM Access, (Fri, Sep 11th)
An autonomous coding agent harvested LLM API access from poorly secured gateways and aggregated stolen inference capacity behind a self-hosted gateway
A SANS researcher observed a semi-autonomous coding agent finding weakly secured LLM resale gateways via FOFA queries, creating trial accounts with temporary emails and CAPTCHA solving, and exploiting weak authorization such as client-supplied group_id fields. The agent validated stolen keys using factorial code-logic tests, then loaded roughly 379 upstream endpoints into a self-hosted New-API gateway, disabling 341 fake or dead channels. Five model names including claude-opus-5 and gpt-5.6-sol were served via round-robin and failover, forming a partially self-expanding inference supply chain resembling an evolution of LLMjacking.