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Week in review: PoC for Splunk Enterprise RCE flaw released, scope of Okta breach widens
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10 most critical LLM vulnerabilities
OWASP updated its Top 10 LLM application vulnerabilities, ranking prompt injection first and elevating excessive agency to third amid agentic adoption.
OWASP refreshed its Top 10 list of critical vulnerabilities in LLM applications, for the first time incorporating real-world incident data alongside expert voting. Prompt injection and sensitive information disclosure remain first and second, while excessive agency jumped from sixth to third as agentic systems that call APIs and execute code proliferate. Unbounded consumption of AI resources rose in prominence, while improper output handling dropped to the bottom as output sanitization becomes widespread. The list includes remediation guidance such as strict output schemas, human-in-the-loop approvals, and least-privilege credentials held in application code.
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The OWASP Top 10 for LLM Applications 2026: From Model Risks to Agentic Security
Akamai analyzes the OWASP Top 10 for LLM Applications 2026, which shifts focus from model-level risks to agentic AI security.
The OWASP Top 10 for LLM Applications has been updated for 2026, and Akamai published an analysis of the revised list. Per the title, the 2026 edition shifts emphasis from model-level risks toward the security of agentic AI systems, framed as a realistic security model. No article body was available, so the specific ranked risk entries cannot be enumerated.
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GuardBreaker: Derailing AI-assisted malware analysis with a code comment
ESET names 'GuardBreaker': UAC-0099 embeds a nuclear-weapon question in VBScript comments to trip LLM scanner guardrails during analysis of its MATCHBOIL loader.
ESET researchers observed the Russia-aligned group UAC-0099 inserting a decoy prompt injection into a VBScript used to install its MATCHBOIL loader in an attack against a Ukrainian target, aiming to make LLM-based code scanners refuse and stop inspecting the file. The comment triggers safety guardrails with a request about building a nuclear weapons but has no runtime effect. Similar LLM-thwarting tricks have appeared in malicious PyPI and npm packages reported by Socket and StepSecurity. ESET recommends multi-model cross-validation of AI-assisted analysis and treating missing LLM output as requiring further checks.
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Week in review: cPanel vulnerability actively exploited, DigiCert breach, LinkedIn job scams
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Autonomous AI Agents Compromise Thousands of Credentials in Under Six Hours
Google's GTIG reports threat actors using autonomous AI agents, credential stealers, and LLMs to steal AI models, API credentials, and harvest thousands of credentials.
Google Threat Intelligence Group says attackers are targeting proprietary AI models across healthcare, government, and media, exfiltrating API credentials, and co-opting victim cloud environments to run unauthorized AI workloads. TeamPCP (Altered Spider/UNC6780) is conducting supply chain compromises of PyPI, npm, and Docker Hub, deploying the SANDCLOCK and DUSTMAKER credential stealers, with DUSTMAKER using AI workspace poisoning and prompt injection for defense evasion. One financially motivated actor used an autonomous multi-agent framework to compromise thousands of third-party credentials in under six hours without human intervention. China-nexus groups UNC6508 and Basin Castle (Mustang Panda) used local open-weight LLMs and commercial LLMs like Gemini, Claude, and Codex for espionage tasks and evading provider monitoring.
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Week in review: Patch Tuesday forecast, 9 free ransomware guides, Cybertech Europe 2023
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Google researchers uncover criminal zero-day exploit likely built with AI
Google links a likely LLM-built criminal zero-day for an open-source admin tool to planned mass exploitation and maps AI-assisted threats.
Google Threat Intelligence Group linked a zero-day exploit for a popular open-source web-based administration tool, enabling 2FA bypass with valid credentials via a semantic logic error, to a criminal group, citing educational docstrings, a hallucinated CVSS score, and textbook Python as signs of LLM authorship; the vendor was notified before a planned mass exploitation campaign. The report also details Russia-nexus malware families CANFAIL and LONGSTREAM using AI-generated decoy code, the PROMPTSPY Android backdoor driving the UI through the Gemini API, APT27 using Gemini to build relay tooling, and the TeamPCP (UNC6780) supply chain compromise of LiteLLM and Trivy repositories that planted the SANDCLOCK credential stealer.
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Hackers Use Autonomous AI Agents to Harvest Thousands of Credentials in Under 6 Hours
Google Cloud documents a financially motivated actor using autonomous AI agents on a compromised cloud tenant to harvest 23,800+ credentials in under six hours.
Google Cloud reports that an attacker compromised a victim's cloud environment and deployed a multi-agent framework driven by preconfigured Markdown playbooks to autonomously handle vulnerability scanning, credential collection, error troubleshooting, and IP rotation. An exposed command-and-control server hosted the 'Recon' framework with a live dashboard managing over 23,800 harvested secrets, including cloud and AI-service API keys. The report also ties DUSTMAKER to UNC6780/TeamPCP, targeting AI development tools and CI/CD systems via trojanized MCP packages such as tiktoken_mcp. Google has disabled linked assets and updated protections after the actors' operational security failures.
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Hackers Use Autonomous AI Agents to Launch Mass Credential Theft Attacks in Under 6 Hours
Google Cloud reports attackers used autonomous AI agents to steal thousands of credentials including 23,800 secrets in a sub-six-hour campaign.
Google Cloud threat intelligence observed financially motivated attackers compromising cloud infrastructure and using AI coding agents guided by written playbook files to scan, harvest and rotate credentials within six hours. An exposed C2 dashboard for a framework called Recon organized and validated more than 23,800 stolen secrets, including API keys for cloud and AI services. Related activity includes UNC6780 publishing the trojanized tiktoken_mcp package on PyPI to target CI/CD tokens and the DUSTMAKER stealer hiding in .claude, .vscode and .cursor workspace directories.
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Zscaler unveils a set of security solutions designed to leverage the full potential of generative AI
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